Cambridge Environmental

Cambridge Environmental Inc58 Charles Street Cambridge, Massachusetts 02141617-225-0810 FAX: 617-225-0813 www.CambridgeEnvironmental.com

Risk Assessment for the Evaluation ofDirect and Multi-pathway Impacts ofEmissions from the Maine EnergyRecovery Company Facility,Biddeford, Maine

Prepared for:

Maine Energy Recovery Corporation

by:

Michael R. Ames, Sc.D.,

Stephen G. Zemba, Ph.D., P.E.,

Kyle Satterstrom, and

Laura C. Green, Ph.D., D.A.B.T.

June 2006


ii

ContentsExecutive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES–1

1 Introduction and Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–11.1 Basic facility information and site description . . . . . . . . . . . . . . . . . . . . . . . . . 1–11.2 Risk assessment methods and study area characteristics . . . . . . . . . . . . . . . . . . 1–51.3 The concept of a ‘most exposed individual’ . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–81.4 Uncertainty and conservatism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–91.5 The meaning of risk estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–101.6 Risk assessment basis and organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–11

2 Facility emissions characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–12.1 Facility process information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–12.2 Compounds of Potential Concern (COPCs) . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–22.3 COPC emission rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–4

2.3.1 Procedures for estimating stack COPC emission . . . . . . . . . . . . . . . . . 2–52.3.2 Procedures for estimating odor scrubber system COPC emission rates 2–62.3.3 Data and procedures for estimating stack COPC emission rates under

process upset conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–82.3.3.1 Combustion control upsets . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–102.3.3.2 Spray dryer absorber upsets . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–102.3.3.3 Baghouse/fabric filter upsets . . . . . . . . . . . . . . . . . . . . . . . . . . 2–112.3.3.4 Combustion startup/shutdown conditions . . . . . . . . . . . . . . . . 2–112.3.3.5 Effects of upset emissions on long-term average . . . . . . . . . . 2–12

2.3.4 Procedures for non-detected compounds . . . . . . . . . . . . . . . . . . . . . . . 2–132.3.5 Chromium speciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–142.3.6 Mercury speciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–152.3.7 Summary of COPC emission rates used in Maine Energy Risk

Assessment modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–182.3.8 Recent variations and long-term trends in COPC emissions . . . . . . . . 2–22

3 Air dispersion and deposition modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–13.1 Background and general air modeling description . . . . . . . . . . . . . . . . . . . . . . 3–43.2 General modeling options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–53.3 Receptor locations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–63.4 Meteorological data processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–113.5 COPC deposition estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–193.5.1 Plume depletion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–20

3.5.2 Particulate-phase COPC deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–203.5.3 Vapor-phase COPC wet deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–21


iii

3.5.4 Vapor-phase COPC dry deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–283.6 Modeling of startup and shutdown emissions . . . . . . . . . . . . . . . . . . . . . . . . . 3–303.7 Summary of atmospheric dispersion and deposition modeling results . . . . . . 3–30

4 Exposure scenario selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4–1

5 Estimation of media concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–15.1 COPC concentrations in soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–45.2 COPC concentrations in produce, grain, and vegetation . . . . . . . . . . . . . . . . . . 5–85.3 COPC concentrations in livestock and related farm products . . . . . . . . . . . . . 5–105.4 COPC concentrations in surface water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–11

5.4.1 COPC loading to nearby ponds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–125.4.2 COPC dissipation in nearby ponds . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–195.4.3 COPC partitioning in nearby ponds . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–205.4.4 Bounding estimates of COPC impacts on Saco River water . . . . . . . . 5–23

5.5 COPC concentrations in fish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–245.5.1 The use of a site-specific value for the BAF fish for mercury . . . . . . 5–25

6 Quantifying exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6–1

7 Risk and hazard characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7–1

8 Uncertainty evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–18.1 Facility characterization—emission uncertainties . . . . . . . . . . . . . . . . . . . . . . . 8–2

8.1.1 Estimation of long-term emission rates from maximum rather than average measured concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–28.1.2 Extrapolation of risks to account for un-analyzed compounds . . . . . . . 8–38.1.3 Treatment of COPCs below detection limits in stack tests . . . . . . . . . . 8–58.1.4 Use of a DRE to estimate some COPC emission rates . . . . . . . . . . . . . 8–78.1.5 Chromium speciation in emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–88.1.6 Mercury speciation and distribution in emissions . . . . . . . . . . . . . . . . . 8–9

8.2 Air dispersion and deposition modeling uncertainties . . . . . . . . . . . . . . . . . . . 8–108.2.1 Superposition of maximum concentration and deposition values . . . . 8–118.2.2 Bounding estimate for COPC concentrations in the Saco River . . . . . 8–138.2.3 Receptor grid spacing at far-field maximum impact locations . . . . . . 8–15

8.3 Estimation of media concentrations uncertainties . . . . . . . . . . . . . . . . . . . . . . 8–178.3.1 Use of non-zero kse in watershed soil concentration calculations . . . 8–178.3.2 Bounding estimates of COPC levels in fish in the Saco River . . . . . . 8–178.3.3 Site-specific, BAF fish values for mercury . . . . . . . . . . . . . . . . . . . . . 8–20

8.4 Uncertainties in quantifying exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–218.5 Inherent uncertainties in toxicologic data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–22

8.5.1 Toxicity of coplanar PCB congeners . . . . . . . . . . . . . . . . . . . . . . . . . . 8–24

9 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–1


iv

10 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10–1

Appendix I Cambridge Environmental, Risk Assessment Protocol (RAP), Review Commentson the Protocol by TechLaw, and Cambridge Environmental’s Response ofComments

Appendix II COPC-specific properties

Appendix III Data used to calculate COPC emission rates

Appendix IV Air Dispersion Modeling and Data Files

Appendix V Air Dispersion Modeling Results Figures

Appendix VI Calculated Concentrations of Compounds of Potential Concern (COPC) in Environmental Media

Appendix VII Effects of the Proposed Scrubber Stack Height Increase (TRC)


ES–1

Executive SummaryThe Maine Energy Recovery Company processes municipal solid waste at its facility inBiddeford, Maine (referred to in this report as the Maine Energy facility). The facility producesrefuse-derived fuel (RDF) from the municipal solid waste and combusts this fuel in boilers togenerate steam and produce electricity. Incidental to its operations, the facility emits airpollutants from its boiler stack and odor control system. To determine whether these emissionspresent significant risks to human health, Cambridge Environmental Inc. has performed a riskassessment which evaluates the potential direct and indirect exposures of individuals living nearthe facility, as well as the likelihood that these exposures might lead to adverse health effects.

Cambridge Environmental Inc. conducted a similar risk assessment of the facility’s emissions in1996. The 1996 risk assessment found that these emissions would not lead to significant risks tohuman health. However, since the time of the 1996 risk assessment, several conditions havechanged that warrant reexamination of the health risk assessment to determine if the 1996conclusions remain valid. Significant changes that have transpired include:

• the addition of the odor control system at the facility;• the development of new regulatory guidance and models for conducting multi-pathway

risk assessments; and• the City of Biddeford’s enactment of its Air Toxics Control Ordinance designed to

evaluate emissions of facilities that release potentially hazardous air pollutants and toensure that such emissions do not cause impacts that are above the City’s health-basedambient air limits.

The risk assessment methods and results described in this report update the 1996 Maine Energyrisk assessment to contemporary standards and expand upon the previous work to include anevaluation of emissions from the odor control system.

The pollutants emitted from the stack of the Maine Energy facility at the greatest rate are thosereferred to as ‘criteria pollutants.’ Criteria pollutants include very fine particles (particulatematter, classified as PM10 and PM2.5), sulfur dioxide (SO2), nitrogen oxides (NO and NO2, orNOx), lead (Pb), and carbon monoxide (CO). The U.S. Environmental Protection Agency (U.S.EPA) has established National Ambient Air Quality Standards (NAAQS) and the MaineLegislature has established Maine Ambient Air Quality Standards for each criteria pollutantdesigned to protect public health with an adequate margin of safety. The Maine Energy facility’semission of most criteria pollutants is monitored at the facility’s stack. Compliance with theNAAQS is verified through a combination of modeling and direct measurement of ambientlevels at selected locations.


ES–2

Although these criteria pollutants are generally released in the greatest quantities, there are manyother compounds that the Maine Energy facility releases in much smaller quantities. Thesenumerous non-‘criteria’ pollutants are the focus of this study. Many of these compounds areregulated as Hazardous Air Pollutants under section 112 of the Clean Air Act, and also under theCity of Biddeford’s Air Toxics Ordinance. These compounds are evaluated according to riskassessment methodologies that have evolved over the past few decades.

Various metals and products of incomplete combustion account for most of the compounds ofpotential concern (COPCs) emitted from the Maine Energy facility’s main boiler stack. Anymetals present in the waste received at the facility are not destroyed in the combustion process,and, although most are removed as bottom ash or by pollution control equipment, very smalllevels are emitted to the environment. Although most organic compounds present in themunicipal solid waste and RDF are destroyed in the combustion process, some organiccompounds are not fully destroyed and other organic compounds are formed in the combustionzone. Together, these compounds are often referred to as products of incomplete combustion(PICs). In addition, the odor control and treatment system releases various volatile organicCOPCs in the effluent of its three exhaust stacks.

The fact that the Maine Energy facility releases small quantities of COPCs is not unusual. Forexample, automobiles emit a myriad of compounds that, if breathed at concentrations present inthe tailpipe, could be hazardous to health. From experience, however, people are exposed toundiluted auto exhaust only for limited amounts of time (if at all), and tailpipe emissionsdisperse rapidly once introduced to the atmosphere. Thus, like any other source of air pollution,a relevant issue regarding the compounds released from the Maine Energy facility is the degreeto which they become dispersed and diluted in the atmosphere. Additionally, to fully assesspotential exposures to these emitted compounds one must consider other plausible ways humansmay be exposed to them. Some compounds are capable of entering and concentrating withinsoil, water, and plants, thereby becoming available to people through means other thaninhalation.

This report focuses on the evaluation of the small levels of COPCs that are released by theMaine Energy facility and evaluates the various ways that individuals could be exposed to thecompounds, starting with the direct inhalation of the compounds while they are present in air,followed by indirect pathways whereby compounds deposit to the ground, become incorporatedwithin soils and foodstuffs, and are then consumed either inadvertently (within soil) or purposely(within people’s diets). The consideration of both direct and indirect exposure pathways istermed multi-pathway exposure assessment, and represents the attempt to develop upper-endestimates of a person’s total potential exposure to compounds released from the Maine Energyfacility.

This risk assessment is based on measurements of the compounds that are released from theMaine Energy facility. Drawing from experience with similar facilities, the U.S. EnvironmentalProtection Agency (EPA) has compiled a list of COPCs typically emitted from waste-to-energyfacilities, and the Maine Department of Environmental Protection (DEP) requires the Maine


ES–3

Energy facility to periodically test for these compounds in its boiler stack emissions. In addition,through cooperative arrangements with the City of Biddeford, the Maine Energy facility hasinstalled an odor control system, and the three exhaust stacks of this system have been tested forthe presence of a wide variety of compounds. These data are used to quantify the rates at whichany of these compounds are released from the facility. Table ES-1 is a list of the compoundsmeasured in emissions from either the boiler stack or the odor handling system, and which arehence considered in the risk assessment. As described further in this report, the emissionsestimates are conservatively health protective for the purposes of this risk assessment.

Given estimates of the rates at which these compounds are released from the Maine Energyfacility, a series of computer-based mathematical models are used to predict the concentrationsand distribution of the compounds that occur throughout the environment. These models arebased on chemical and physical principles as well as empirical data, and they have beendeveloped and updated over time by the U.S. EPA and others. To ensure that the models do notunderestimate the degree to which compounds might accumulate in the environment and foodchain, most uncertainties in the models have been resolved in a manner that over-predicts theconcentrations likely to occur. The modeling is thus designed to make high-end estimates of thedegree to which people may be exposed to compounds released by the Maine Energy facility.

The philosophy of developing high-end exposure estimates also influences the scenariosexamined within the risk assessment. These scenarios focus on a model of the people, animals,and plants living in the vicinity of the Maine Energy facility that have the highest potential toencounter compounds emitted by the facility. Table ES-2 lists the exposure scenarios consideredwithin the risk assessment. The goal of estimating high-end exposure scenarios is met in threeways:

• scenarios are evaluated at locations where the highest concentrations are predicted tooccur due to emissions from the Maine Energy facility;

• the types of personal exposure scenarios considered are those for people that consumelarge amounts of the foods that tend to accumulate compounds from the environment;and

• the rates at which compounds are encountered (e.g., through the amount of foodconsumed) are assumed to be at high-end or higher-than-average values.

The exposure scenarios listed in Table ES-2 reflect the first two criteria. The individualsconsidered in the human health risk assessment do not represent actual people, but rather serveas examples of the populations that are expected to encounter higher-than-average exposures tocompounds released by the Maine Energy facility. The hypothetical people that are studiedinclude a resident, a recreational farmer, and a recreational fisher; exposures to both children andadults are evaluated. The resident exposure scenario is intended to characterize individuals whoengage in typical activities and who live in the vicinity of the location where emissions from thefacility are expected to produce the highest concentrations in the environment and hence havethe greatest potential to affect soil, homegrown vegetables, and drinking water that can serve asindirect avenues of exposure.


ES–4

The recreational farmer and fisher scenarios represent high-end exposures of individuals whoderive a substantial portion of their food from home-grown or local sources. Like the resident,both the recreational farmer and fisher are assumed to live near the location predicted to be mostaffected by emissions from the Maine Energy facility, but their exposure profiles aresupplemented with the consumption of locally-derived foods that tend to accumulate compoundsto the greatest degree. Thus, the recreational farmer is assumed to raise a substantial portion ofhis or her meats, eggs, and dairy products near the location where the influence of the MaineEnergy facility is predicted to be highest. Similarly, the recreational fisher, is assumed toconsume a substantial quantity of fish which have been caught at locations near the MaineEnergy facility. The amount of local foods raised and caught by the recreational farmer andfisher constitute a substantial portion of their diets. In fact, the EPA risk assessment guidanceuses the term subsistence farmer and fisher to describe these scenarios.


ES–5

Table ES-1 Compounds evaluated in the Maine Energy facility risk assessment.

Metals/Inorganics Semi-volatile OrganicCompoundsArsenic *

Beryllium * Benzoic AcidCadmium * Benzyl alcoholChromium (total) * Bis(2-ethylhexyl)phthalateChromium (hexavalent) Diethyl phthalateCopper Di-n-butylphthalateLead * Methyl naphthalene, 2-Mercuric chloride Methyl phenol, 3&4-Mercury * Methyl phenol, 2-Methylmercury NaphthaleneNickel * PhenolSeleniumSilver Organic CompoundsTin AcetoneVanadium BenzeneZinc BromomethaneHydrogen chloride 2-Butanone

Carbon disulfidePolychlorinated dibenzo(p)dioxinsand furans (PCDD/PCDFs) andpolychlorinated biphenyls (PCBs)

ChloromethaneChloroformCyclohexane

2,3,7,8-TCDD * 1,4-Dichlorobenzene1,2,3,7,8-PCDD * Ethanol1,2,3,4,7,8-HxCDD * Ethylbenzene1,2,3,6,7,8-HxCDD * Freon 111,2,3,7,8,9-HxCDD * Freon 121,2,3,4,6,7,8-HpCDD * HeptaneOCDD * Hexane2,3,7,8-TCDF * Methylene chloride1,2,3,7,8-PCDF * 2-Propanol2,3,4,7,8-PCDF * Styrene1,2,3,4,7,8-HxCDF * Tetrachloroethylene2,3,4,6,7,8-HxCDF * Toluene1,2,3,7,8,9-HxCDF * 1,1,1-Trichloroethane1,2,3,4,7,8,9-HpCDF * 1,2,4-TrimethylbenzeneOCDF * Vinyl chloridePCBs Xylenes

* Compounds also evaluated in the 1996 health risk assessment


ES–6

At each stage of the environmental transport and exposure analyses, mathematical algorithms areused to model a variety of physical, chemical, or biological processes. Properties of the facility,its surroundings, the COPCs, and the hypothetical human receptors are used as inputs to thesealgorithms to estimate the various derived quantities, such as COPC emission rates,concentrations in water, or human intake rates. It should be noted that, in constructing theprofile of assumptions for an exposure scenario, each assumption is not taken at an extremevalue, but rather the suite of assumptions is designed to produce a high-end exposure estimatethat remains within plausible limits. Thus, there may be individuals who consume more of aparticular type of food than what is assumed in the risk assessment, but there are likely to be few(if any) people who live at the location most affected by facility emissions, grow and raise themajority of their own food, and who live at this location and in this manner for thirty years. Hence it is unlikely that there are any individuals who receive a greater degree of exposure tocompounds from the Maine Energy facility than is estimated for the hypothetical exposurescenarios.

Some of the important constructs and assumptions used in the risk assessment are as follows:

• Risks are assessed for hypothetical "most-exposed individuals" (MEIs), rather than for areal population with a range of potential exposures. Because MEIs are designed toreceive improbably high exposures, risk estimates deemed acceptable for MEIs suggestthat the source of contaminants (the Maine Energy facility, in this case) will not causeunacceptable risks for actual persons.

• Exposures of MEIs to COPCs in air, soil, and homegrown vegetables are evaluated at thelocations where impacts from the Maine Energy facility to each of these media areprojected to be highest, despite the fact that the maximums are in different locations.

• Exposures of MEIs to COPCs in drinking water are evaluated using bounding estimatesof the maximum possible concentrations that could be present in the Saco River.

• MEIs in the farming and fishing scenarios are assumed to produce or obtain practicallyall of their vegetables, milk, meat, and fish from these locations, even though actual landuse in the Biddeford/Saco area suggests far lower consumption rates are likely to occur atthe locations where the exposures are assessed.

• MEIs are assumed to have the same exposure to COPCs for a period of 30 to 40 years, inaccordance with U.S. EPA guidance for the evaluation of high-end exposure estimates.

• Both adult and child MEIs are considered. Separate consideration of a child MEI isimportant because exposure rates, when normalized by body weight, are often higher forchildren than adults.

• In evaluating lifetime potential cancer risks caused by the MEI’s exposures to smalldoses of emitted compounds, the carcinogenic potency of the contaminants is based on


ES–7

the response of laboratory rodents (in most cases) or humans (for some metals) toextremely high doses. In fact, it is not known if there would be any carcinogenicresponse at all at such low doses.

• For evaluating the potential chronic adverse effects of various (non-carcinogenic)contaminants, the doses to the MEIs are compared with reference doses. These referencedoses have been derived by applying margins of safety to the lowest doses observed tocause harm to humans or laboratory animals. There is no reasonable expectation ofadverse effect from doses near and below these reference doses.

Table ES-2 Summary of Risk Assessment Exposure Scenarios

Receptor Exposure Pathways Location

Human health risk assessment — adults and children

ResidentInhalationIngestion of vegetables, drinking water, andsoil

Maximum impactpoint

RecreationalFarmer

InhalationIngestion of vegetables, drinking water, andsoilIngestion of home-raised meats and eggs

Maximum impact atlocations ofcultivatable land

Recreational Fisher

InhalationIngestion of vegetables, drinking water, andsoilIngestion of locally-derived fish

Maximum impactwater body

Once the exposure scenarios for the MEIs are defined and the algorithms for estimating theCOPC concentrations in relevant environmental media are applied, individual MEI exposurerates are estimated for each of the compounds in Table ES-1 and for each of the hypotheticalexposure scenarios listed in Table ES-2.

To evaluate whether these exposures might result in significant risks to an exposed individual’shealth, the exposure rates are evaluated with respect to compound-specific toxic potency andhealth effects benchmark exposure values. Two types of health-based evaluations are madewithin the human health risk assessment. First, the potential for each compound to increase anexposed individual’s lifetime cancer risk is assessed. Second, the likelihood that each compoundmight cause adverse health effects other than cancer is evaluated.


ES–8

The incremental, or excess, lifetime cancer risk for an exposed individual is calculated bymultiplying each compound’s predicted exposure rate with its estimated potency to cause cancerin humans. The resulting cancer risk estimate is the exposed individual’s additional risk ofgetting cancer in his or her lifetime, above and beyond the background level that people getcancer from all causes, which is 1 in 2 for men and 1 in 3 for women. This excess risk iscompared with regulatory benchmark levels to evaluate whether the estimated risk is acceptable. Historically, the Maine Department of Human Services has established an acceptableincremental cancer risk level of 1 in 100,000 (or 10 in 1,000,000). This risk level may beexpressed in scientific notation as 10–5 or 1 E-5, and which represents an increase in cancer riskabove the background level of 0.003% for a woman and 0.002% for a man.

The potential for emitted compounds to cause noncancerous health effects is evaluated bycomparing the predicted level of exposure for each compound with a level of exposure that isbelieved to be safe, i.e., a level that can be tolerated without risk to health (unlike incrementalcancer risk, where a risk is assumed for any level of exposure). The ratio of the estimatedexposure to the safe, or reference, exposure level is referred to as the compound’s hazardquotient (HQ). If a compound’s HQ is less than 1, the exposure level is less than the referenceexposure level, and no adverse health effects are expected to occur. For any given scenario, thesum of all the HQs is referred to as the hazard index (HI). If the HI is less than 1, then, overall,no adverse effects are expected. Although the health effects evaluated using the hazard indexinclude diseases that affect different organs which differ among compounds, these broadcategories of potential health effects are grouped because they are evaluated in a similar manner.

If the hazard ratio is greater than one, the level of exposure exceeds the level thought to bepotentially harmful, and the possibility of adverse health effects might exist. However, since thereference doses and concentrations used to characterize safe values frequently embody safetyfactors, it is incorrect to conclude that hazard ratios greater than one will in fact correspond tothe actual incidence of health effects. Rather, hazard ratios exceeding one are indicators of thepossibility of adverse health effects. Two types of hazard quotients are assessed to reflect different types of exposures to compoundsemitted from the Maine Energy facility. Chronic hazard quotients are calculated to assess healtheffects that might be associated with exposure to compounds that could occur over extendedperiods of time. Acute hazard quotients are evaluated to gauge the nature of exposure toelevated concentrations of compounds in air that are predicted to possibly occur on an occasionalbasis.

The overall results of the risk assessment of the Maine Energy facility are summarized in TablesES-3 and ES-4. The total estimated lifetime incremental risks of cancer are listed in Table ES-3. These values reflect the sum of the estimates for all known or potentially carcinogeniccompounds found in the Maine Energy facility emissions. The compounds and exposurepathways that contribute principally to each cancer risk estimate are also provided in Table ES-3. The incremental risk levels due to Maine Energy facility emissions are larger for the recreationalfarmer and fisher scenarios, reflecting the additional indirect exposures included in these


ES–9

scenarios. Objectively, the lifetime incremental cancer risk estimates are quite small, especiallywhen compared with the background (overall) risk of getting cancer. As can be seen from thevalues in Table ES-3, the highest excess lifetime cancer risks associated with emissions from theMaine Energy facility total an incremental risk of 3 in 1,000,000 for the recreational farmer. This estimated risk level is more than a factor of three smaller than the regulatory benchmark of10 in 1,000,000, and it represents an increase of about only 0.001% above background cancerincidence levels.

Table ES-4 presents risk estimates for compounds that, at sufficient levels of exposure, couldcause adverse health effects other than cancer. The highest overall hazard index is well below 1for both chronic (long-term) and short-term risks. Potential short-term risks have been evaluatedbased on both the facility’s emission levels under normal and upset operating conditions. Thegreatest HI is 0.09 for the fishing scenario as evaluated in the unnamed pond on the GoosefareBrook. This value is far below a level at which adverse effects might occur. Additionally, thesevalues represent the sum of all of the hazard ratios for the individual compounds, and hazardratios should, strictly, be separated into categories of specific health effects. More detailedinformation on these risk estimates, including risk estimates for each COPC under each exposurescenario, is presented in Chapter 7 of the risk assessment report.

Most of the risk estimates presented in Tables ES-3 and ES-4 correspond to the estimates ofemissions from the Maine Energy facility when it is operating under normal operationalconditions, at full capacity, continuously throughout the year. Since the facility does not alwaysoperate at full capacity (e.g., it is shut down for periods of maintenance each year), the emissionrates, and hence risk estimates, are overestimated, even accounting for potential upset conditionswhen emissions might be higher over short periods. Even so, a series of risk estimates ispresented in the uncertainty section of the risk assessment report (see Chapter 8) based upon the highest emission rates measured during facility testing. These risk estimates tend to be abouttwice as large as the best-estimate values (at full operational loading) summarized in Tables ES-3 and ES-4. This factor of two does not alter conclusions relative to typical regulatory riskcriteria, as incremental cancer risks would remain well below 10 in 1,000,000, and hazardindices well below one. Thus, basing risk estimates on the highest measured emission rateswould not lead to risk estimates of significant concern. Chapter 8 also contains risk estimatesthat have been calculated using somewhat different modeling assumptions than have beenapplied in the baseline estimates. Some of these sensitivity and uncertainty analyses result inslightly higher potential risk estimates, but none of them produce estimated risk indices thatexceed the health-based criteria levels.

Table ES-4 also presents short-term risk estimates that account for occasional “upset” conditionswhen operations of the Maine Energy facility deviate outside of their normal ranges. Asdescribed in Chapter 2, the Maine Energy facility is designed and operated to minimize theeffects of process upsets, and some “upset” conditions that occur in practice (such as facilityshutdowns) actually lead to decreased long-term emissions. Consequently, the risk assessmentevaluates potential acute risks associated with short-term increases in facility emissions. Theupset scenarios summarized in Table ES-4 indicate a worst–case hazard index 0.01 over a 1-hour


ES–10

period, and a maximum sum of ratios of ambient concentrations to Biddeford 24-hour AALs of0.03, indicating overall safety factors of 30 to 100 between (1) the ambient concentrations ofCOPCs that might result during a facility upset and (2) levels of potential concern.

As another gauge of potential health risks due to emissions from the Maine Energy facility, thehighest modeled concentrations of COPCs due to emissions from the Maine Energy facility werecompared with applicable Ambient Air Limits (AALs) established by the City of Biddford’s AirToxics Ordinance. No predicted COPC concentrations exceed any 24-hour or annual-averageAALs at any location. At the worst-case, the COPC nearest its AAL is more than 100 timessmaller than the permissible level.

When one considers the incremental cancer risk estimates and non-cancer hazard indices inTables ES-3 and ES-4, it is important to recall that these values are based on parameters andmethods that intentionally overestimate the likely risks that will actually occur. This is done sothat, if the modeled risks and hazard indices are below regulatory levels of significance, then theactual risks and hazards will definitely be below these levels of significance. Among the specificportions of the risk assessment that lead to overestimation of exposures and risks are thefollowing:

• Exposures to each pollutant are evaluated at the locations where the impacts from theMaine Energy facility are the greatest despite the fact that these maxima may be indifferent locations.

• Exposures due to consumption of drinking water from the Saco River are based on thepollutant concentrations that would exist in the water if all of the facility’s emissionsentered the river directly. This is a very significant overestimate of these exposures (seeSection 8.2.2).

• The consumption rates for homegrown produce, meat, and dairy products for the farmingscenario are collectively higher than would likely occur at the maximum impact locationover the 40-year exposure period (see Table 8.11 for values).

• The consumption rates for fish caught in local ponds are higher than is likely possible forthese waterbodies over the long-term (i.e., for adults an average consumption rate of 66pounds of fish per year for 24 years, see Table 8.11).

• Short-term exposures that might occur during off-normal operation of the facility wereevaluated as if all of the system upset conditions occurred simultaneously. Because theseupsets only occur at most a few times a year on an individual basis, it is very unlikelythat they would all happen at once.

• The toxicological data used to evaluate whether these exposures would cause adversehealth effects are based on animal and/or human exposures at much higher levels thanwould be experienced due to emissions from Maine Energy. Because of the safety


ES–11

factors built into these data, the chances that the the modeled exposures might causeactual adverse health effects are likely to be much lower than the cancer risk and non-cancer hazard indices suggest.

Thus, while the estimated cancer risks and non-cancer hazard indices shown in Tables ES-3 andES-4 are well below the regulatory levels of concern, the values are based on significantoverestimations of the impacts from Maine Energy’s emissions. If the pollutant exposure levelsand potential health risks that occur due to emissions from the Maine Energy facility wereevaluated using methods and parameters that more closely reflect actual conditions, the risks andhazard indices would likely be much lower than those shown below (e.g., the actual incrementallifetime cancer risks would be well below the 1 to 4-in-a-million levels shown). This intentionaland significant overprediction of exposures and risks is a fundamental part of the risk assessmentprocess which is designed to provide a wide margin of safety and to allow for the assessment ofa wide range of facilities using standard and well-reviewed methods.

Table ES-3 Summary of Incremental Cancer Risk Estimates a

Receptor

Incremental cancerrisk estimate(Target limit = 10 in 1,000,000) b

Principal exposurepathways

Principal COPCs andfraction of total risk

Resident 2 in 1,000,000 drinking waterhomegrown produce

tetrachloroethene 34%vinyl chloride 22%PCDD/Fs 20%

RecreationalFarmer 4 in 1,000,000 homegrown animal

products/produce

PCDD/Fs 63%tetrachloroethene 16%vinyl chloride 10%

RecreationalFisher 2 in 1,000,000

locally caught fishhomegrown producedrinking water


a The risk estimates shown here include risks due to both direct (report Table 7-10) and indirect(report Table 7-9) exposures. The estimates are based on continuous operation of the facility,using compound emission rates measured under stressed operating conditions, and for theexposure pathways shown in Table ES-2. b Incremental cancer risks shown here are reported in the body of the report in scientificnotation; a risk of 8 in 100,000,000 may be also shown as 8 × 10–8 or 8 E-8.


ES–12

Table ES-4 Summary of Hazard Indices and Total Ratios to Biddeford 24–hour AmbientAir Limits Used to Evaluate Risks of Non-Cancer Health Effectsa

Receptor

HazardIndex(Acceptablelimit = 1)


Principal COPCs and fraction oftotal risk

Chronic (Long-Term) Exposure Scenarios

Residentb 0.08inhalationdrinking watersoil ingestion

n-butanol 68%mercuric chloride 7%1,3 dichlorobenzene 6%

RecreationalFarmerb 0.06

inhalationdrinking watersoil ingestion

n-butanol 72%1,3 dichlorobenzene 7%1,2,4 trimethylbenzene 6%

RecreationalFisher 0.2 locally caught fish

drinking water

methyl mercury 76%n-butanol 17%dichlorobenzene 2%

Short-Term Exposure Scenarios

1-Hour BasisHazard Indexnormal operation

0.003 Inhalation

chloroform 20%methanol 17%propanol, 2- (isopropyl alcohol)16%

1-Hour BasisHazard Indexupset conditions

0.01 Inhalationarsenic 23%lead 16%hydrogen chloride 13%

Total of Ratios to24-Hour AALsnormal operation

0.02 Inhalationbenzene 37%methanol 18%hydrogen chloride 17%

Total of Ratios to24-Hour AALsupset conditions

0.03 Inhalationbenzene 33%lead 21%hydrogen chloride 17%

a The risk estimates shown here include risks due to both direct (Table 7.1) and indirectexposures (Tables 7.3, 7.4, and 7.6). The estimates are based on continuous operation of thefacility, using compound emission rates measured under stressed operating conditions, and forthe exposure pathways shown in Table ES-2.b The maximum Hazard Indices for these scenarios are for the child receptors


ES–13

In summary,

• Emissions of a wide range of compounds from the Maine Energy facility havebeen measured;

• The highest expected personal exposures to these compounds by direct andindirect pathways have been modeled using methods that, in general, significantlyover-predict actual exposure levels;

• The modeled exposures are estimated to produce less than a 0.001% increase inthe risk of cancer and are well below the U.S. EPA’s reference dose andconcentration levels for non-cancer effects; and

• The worst-case predicted concentrations of COPCs due to Maine Energy facilityemissions are well below the Ambient Air Limits established by the City ofBiddeford to protect public health.

Based on these findings, emissions of the Maine Energy facility present no significant risks topeople living in its vicinity.

The reader is encouraged to explore additional portions of the risk assessment report. The reportis organized in the logical progression of the risk assessment, starting with the description ofcompound emission rates, and followed subsequently by air dispersion modeling, environmentalfate-and-transport modeling, exposure estimation, and culminating with the calculation of riskestimates to human health and the environment, along with a discussion of uncertainties. Sufficient detail is provided in the main body of the report and its appendices to reproduce thecalculations if desired, but the qualitative descriptions of the underlying approaches,assumptions, and philosophies are likely of greater value to the general reader. Through thesedescriptions, a sense for the risk assessment process can be gained from the report without theneed for deriving the mathematical details of its numerous equations, tables, and numericalvalues.


1–1

1 Introduction and BackgroundThis section provides background information on the operations of the Maine Energy RecoveryCompany’s Biddeford facility (Maine Energy facility), including diagrams, plan maps, and otherinformation. The area surrounding the Maine Energy facility is also described since topographyand land use have an effect on the estimation of atmospheric dispersion and deposition of facilityemissions, concentrations of compounds of potential concern in environmental media, andrelevant exposure scenarios. A description of the facility and surroundings also helps toestablish a contextual sense for the risk assessment.

1.1 Basic facility information and site description

The Maine Energy facility is located in the central downtown area of Biddeford. Figure 1.1depicts a topographic map of the area, centered roughly at the location of the facility. The pink-colored portions at the center of the map indicate the urbanized areas of the Cities of Biddefordand Saco, located to the south and north, respectively, of the Saco River. Generally, terrainelevations increase in directions to the north and south of the Saco River valley. A relativelylarge hill is located to the southeast of central Biddeford. The two small ponds included in themodeling are also identified. Figure 1.2 shows an aerial photograph of the study area in theimmediate vicinity of the Maine Energy facility; Figure 1.3 shows a wider aerial photograph ofthe study area indicating the locations of the Southern Maine Medical Center and local schoolsand educational institutions identified by Maine GIS (http://apollo.ogis.state.me.us).

The Maine Energy facility is designed to process approximately 1200 tons of municipal solidwaste (MSW) each day. Mechanical equipment is used to separate metal and othernoncombustible materials that are recycled or disposed. The remainder of the MSW, whichincludes primarily paper, plastic, and food waste, constitutes the refuse-derived fuel that thefacility combusts in two boilers. The steam produced by the boilers is fed through turbines toproduce up to 22 megawatts of electricity.

The byproducts of MSW combustion include residual ash, which is trucked to a landfill, and fluegases that are emitted to the air and subject to regulations enacted and enforced by the MaineDepartment of Environmental Protection (DEP). Prior to atmospheric release, flue gas fromeach boiler is treated by a series of air pollution control devices to reduce the levels of pollutants. First, a high efficiency cyclone separator removes most of the dust particles. Second, a spraydryer/absorber injects a lime slurry into the flue gas to remove most of the sulfur dioxide andreduce the level of acid gases. Last, a multi-compartment fabric filter, or baghouse, captures thecalcium sulfate particles formed in the spray dryer, as well as unreacted lime and small particles


1–2

not initially collected by the cyclone collector. After treatment in the baghouse, the cleaned fluegas from the two combustion units is vented through a common stack at a height of 244 feetabove ground.Figure 1.1. Topographic map of the vicinity of the Maine Energy facility.


1–3

Figure 1.2 Aerial photograph of the study area in the immediate vicinity of the Maine energy facility. The orange circle is drawnat a 1 km distance (radius) from the facility’s boiler stack. Orthophotograph from Maine GIS.


1–4

Figure 1.3 Aerial photograph of the lands around the Maine Energy facility (located at the center of the 1 km radius circle) thatdepicts the locations of the Southern Maine Medical Center (red cross) and local schools and educational institutions.

1 In the U.S., men have a 1 in 2 chance of developing cancer in their lifetime, and womenhave a 1 in 3 chance (American Cancer Society, 1996). It should also be noted that regulatoryrisk thresholds (such as a 1 in 100,000 incremental cancer risk allowable for a combustionfacility) are based on projected, or modeled, risks of contracting cancer that tend to be estimatedin a manner that is believed to overpredict actual risk. These factors should be kept in mindwhen comparing to background cancer incidence rates, which are measured, actuarial risks.


1–5

In 2000 the Maine Energy facility installed an odor control and scrubbing system to reduce odorsthat could otherwise escape the facility’s buildings to the outdoors. The system uses fans todraw air into the building (and conversely to prevent the escape of air through doors andwindows). Air is collected from the areas in which MSW is stored and processed. A portion ofthe air is used for combustion by the boilers, and the remainder is treated by filtering through atwo-stage particulate removal system, and through activated carbon. Air from the BoilerBuilding, which is a mixture of ambient air, air from the boiler building, and treated air from theother sections of the odor control system, is treated through scrubbing with a water mist toreduce odors and pollutant levels. The treated air is released through three stacks located on theroof of the boiler building. The release points of the odor scrubbing stacks are 120 feet abovethe ground, a height roughly one-half that of the boiler stack.

1.2 Risk assessment methods and study area characteristics

The goal of a multi-pathway risk assessment is to determine whether the emissions from aparticular facility pose significant risks to public health or the environment. The MaineDepartment of Human Services, Bureau of Health has historically defined significant risk as anexcess (incremental) cancer risk estimate of 10–5 (1 in 100,000). This is a relatively conservativelimit compared with the background cancer incidence (50,000 in 100,000 for men, and 33,000 in100,000 for women).1

Risk assessment methodologies focus on protecting the health of all people. Reference doses(RfDs) and concentrations (RfCs) for compounds of potential concern (COPCs) are derived fromtoxicologic data with specific consideration of individuals that might be susceptible to adversehealth effects at lower levels of exposure compared with the general population. RfDs and RfCsrepresent levels of exposure that are believed to be safe for all members of the public, includingchildren, the elderly, pregnant women, asthmatics, and other groups of people potentially moresensitive to exposure to COPCs. Figure 1.3 depicts the locations of schools, hospitals, and otherlocations of special interest in the near vicinity of the Maine Energy facility.

A multi-pathway risk assessment for a combustion facility (such as that described herein)focuses only on the risks due to compounds emitted from the facility, and does not considercompounds already present in the environment for other reasons (e.g., due to natural backgroundor emissions from other anthropogenic sources). As such, the risk assessment addresses only theincremental risk due to emissions from the particular facility under evaluation, not the


1–6

cumulative risk due to all sources of environmental exposure to compounds (i.e., the facilitycombined with background and all other sources).

The first analyses of waste-to-energy facilities considered only the hazards of airborne COPCs. Subsequent efforts demonstrated the potential importance of indirectly contacting COPCsthrough more complex routes that, for example, involve deposition to the ground andincorporation into the food chain. Such considerations have identified a variety of potentialexposure pathways that trace the movement of COPCs in the environment and their availabilityto humans. Today, a risk assessment addresses a wide range of pathways by which humansmight be exposed to COPCs originating at the Maine Energy facility.

Figure 1.4 is a conceptual representation of the multi-pathway exposure assessment. Fate andtransport models utilize mathematical algorithms to predict the travel of COPCs emitted from theMaine Energy facility. COPC emission rates are developed from stack test reports from thefacility. Air dispersion models combine information about (1) the plant (such as the height ofthe stack and the properties of the flue gas), (2) the terrain of environs surrounding the plant, and(3) hourly measurements of meteorological parameters, to predict the dispersion of COPCs in theatmosphere. A subsequent algorithm predicts the rates at which airborne COPCs are depositedto soil, water, and vegetative surfaces. Upon deposition, relevant physical and chemicalprocesses are modeled in order to predict the behavior of COPCs in each of these media. Additional models predict the transfer and accumulation of COPCs in locally-producedvegetables, meats, fish, and dairy products.


1–7

Figure 1.4 Conceptual model of a multi-pathway risk assessment. Adapted From the U.S.EPA’s Mercury Report to Congress (1997).

The arrows between the different environmental compartments indicate the pathways throughwhich COPCs are assumed to travel and reach humans. Some relationships are fairly simple; for example, COPC concentrations in air are estimated in a straightforward manner by modelingthe dispersion of emissions from the facility stack. Other routes are much more complex andrequire the pursuit of COPCs through several (sometimes connected) environmental media.

Consider, for example, the estimation of COPC concentrations in cow’s milk that is producedwithin the area affected by the facility. Empirical measurements from other studies can be usedto estimate the concentrations of COPCs in milk that will result from a cow’s exposure toCOPCs in her environment. In this case, the cow’s intake of COPCs is derived from eating foodand (incidentally) soil. As indicated in Figure 1.4, COPC concentrations in soil accumulate bydeposition of COPCs from air. The cow’s food supply (vegetation) can also becomecontaminated through two mechanisms: airborne COPCs can deposit to (or are absorbed by) the


1–8

surface of vegetation, and plants can translocate COPCs from soil (which, again, receives COPCdeposition from the air). Clearly, modeling impacts through the food chain is multi-dimensional.

Figure 1.4 illustrates the three mechanisms through which humans are exposed to COPCs —inhalation of vapors and particles, ingestion (both purposeful and incidental) of a variety ofmedia, and dermal contact with soil. Incorporating COPC uptake by these three routes allowsthe estimation of a total intake for each COPC.

1.3 The concept of a ‘most exposed individual’

Within this assessment we attempt to conservatively estimate worst-case risks — that is, someoverestimates of adverse effects that might result from exposure to chemicals that may bereleased from the stacks of the Maine Energy facility. In order to do so, we construct reasonableworst-case exposure scenarios. In this context, ‘reasonable’ does not imply average or expectedexposure, but rather indicates something plausible, even though not probable. We are wellaware that notions of plausibility are subjective and debatable; we have tried to be prudent,perhaps overly so, even as we have tried to be sensible. It is certainly possible to be moreextreme in some assumptions; one can make an overestimate arbitrarily large, just byconcatenating more layers of conservatism. We believe, though, that concatenations ofimplausible scenarios yield estimates that are not so much conservative as they are useless.

Overall, we base the risk estimates on a higher degree of exposure to plant-related COPCs thanis likely to occur from actual operations of the Maine Energy facility. Many of the methods andassumptions we adopt are typical of risk assessments conducted for other waste-to-energyfacilities. As examples, exposures are evaluated at the locations of highest impact (as predictedby the air dispersion and deposition studies), and individuals are assumed to live in this impactedarea for 40 years, and to partake heartily in activities that lead to exposure to facility-relatedCOPCs (for example, to raise essentially all of their own farm and dairy products – including thegrain used to feed livestock – and, moreover, to do so for this period of up to 40 years).

Most models and assumptions derive from published guidance (e.g., U.S. EPA, 1989; MaineDEP & DHS, 1994; and NYSDOH, 1991), and thus are typical of human health riskassessments. To the degree justifiable, we have tailored the risk assessment to the environs ofthe Maine Energy facility, and in particular to the area in which the projected effects from theplant are the greatest.


1–9

1.4 Uncertainty and conservatism

Two elements pervading risk estimates are uncertainty and conservatism. In the context of riskassessment, uncertainties are the inevitable byproduct of abstracting complicated current andfuture real-world phenomena into mathematical approximations, and conservatism is a methodof compensating for these uncertainties. For example, variations in the composition of trash andsome variability in the day-to-day operations of the waste-to-energy plant cause COPC emissionrates to fluctuate. To address this uncertainty, measurements from a number of stack tests areaveraged to provide best estimates of long-term emission rates. A high degree of conservatism isincorporated by the assumption that the facility runs continuously with no down time.

Uncertainties also accompany fate and transport modeling. The models used here are necessarilysimple in nature, including only the essential processes that influence the environmental destinyof COPCs, because no set of models can capture the full complexities of the physicalenvironment. Fortunately, simple models can be very reliable. For example, one of the modelsused to predict air dispersion incorporates empirically derived estimates of the time-averagedrate at which the plume widens as it travels from the stack. The parameters that characterize thisdispersion are estimated from hourly meteorological measurements of atmospheric stability,wind speed, and wind direction. The model also accounts for the effects of terrain and potentialaerodynamic interferences of buildings in the vicinity of the stack. The mathematical modelinggreatly simplifies the actual, turbulent atmospheric processes, but produces estimates oflong-term average air concentrations that can match observations reasonably closely over mostconditions. This degree of accuracy is quite adequate.

Perhaps the greatest uncertainty lies in the models used to predict the toxicologic potencies(especially the carcinogenic potencies) of the COPCs of interest. In order to gauge whether achemical is a human carcinogen, groups of laboratory rodents are exposed, typically for most orall of their lifetimes, to very large doses of the chemical. If the doses induce an increasedincidence of any type of cancer, compared to the rate observed in unexposed control animals,then the chemical is deemed a carcinogen. Two or more of such tests with positive resultssuffice to label the chemical a ‘probable human carcinogen,’ even if no actual or useful datafrom exposed humans are available.

This qualitative designation of carcinogenicity is, in many cases, entirely appropriate. Rats,mice, and humans are all mammals that develop cancer from a variety of exposures, and whilethere are abundant differences among the three species, these differences are not so large as tosuggest that chemicals carcinogenic to one species will not be carcinogenic to others. But whilethe qualitative extrapolation from rodents to humans may be reasonably straightforward, thequantitative extrapolation required for risk assessment is highly uncertain. This is because thedoses at which the rodents are tested are typically many thousands of times larger than dosesexperienced by humans. The central question is, are carcinogenic responses always proportionalto dose, such that even at extremely low levels of exposure there is some risk of cancer, and thatrisk becomes zero only at zero dose? The answer is largely unknown. Knowledge of how


1–10

specific chemicals cause cancer may by helpful on a case-by-case basis, but such information isin most cases still too rudimentary to drive regulatory decision-making.

Uncertainties in risk assessment can lie in both directions, since any fate, transport, exposure, ortoxicity model can either over-predict or under-predict the variable of interest. In general, riskestimates are conservatively biased — that is, models and parameters are selected intentionallyin a manner that tends to increase risk estimates. With regard to cancer, it is assumed that allrodent carcinogens are also human carcinogens, and that all chemicals carcinogenic at high dosesare also carcinogenic at vanishingly small doses. Clearly, these are conservative assumptions: if,in actuality, a minuscule dose of a substance poses no risk of cancer to humans, then ourassumption of non-zero risk at these doses is an infinite overestimate. Not every assumption inthe risk assessment is chosen in a conservative manner (for example, body weight, used in thecalculation of doses, is assigned as an average value), but, overall, the bottom-line estimates ofrisk err on the high side.

1.5 The meaning of risk estimates

The results of the risk assessment are expressed as numbers that represent quantitative estimatesof risk. As discussed previously, we believe that the methods employed almost certainlyoverestimate the actual risks that would result from the operation of the Maine Energy facility. The risk estimates derived herein are intentional overestimates and are not actual risks. Theincremental risk of cancer of 1–3 in a million derived for the MEIs does not guarantee that thereal, most-exposed individuals will incur this additional risk from exposure to emissions fromthe Maine Energy facility. Because the risk assessment is constructed with a conservative(health protective) bias, the actual excess risk (of cancer) will almost certainly be lower, andcould even be zero.

On a different but related issue, we emphasize that an estimated cancer risk of 3 in a million forthe recreational farmer does not imply that 3 additional cancers will occur in a population of onemillion. First, as stated above, the risk of cancer is almost certainly overstated, and may be aslow as zero. Second, and more importantly, the risk estimate is derived for a theoreticalconstruct — the most exposed individual. The exposure profile designed for the recreationalfarmer is not intended, by definition, to fit the general population. The recreational farmer isassumed to live at the location that the EPA models project to be most impacted by facilityemissions and consume generous amounts of vegetables, beef, milk, eggs, chicken, and pork (allraised from feed grown at this most-impacted location) for a period of forty years. Theindividual risk estimate for the MEI applies only to a very limited population — perhaps only toone or two real people; more likely to no one real person. Risk estimates to the generalpopulation surrounding the plant — which would consider geographic differences in plantimpacts and demographic differences in exposure patterns — are not herein presented. Fromprevious analyses of waste-to-energy plants, we know that once population-weighted risks areassessed, they are considerably lower than the estimates derived for MEIs.


1–11

A final consideration requires comment. Cancer from all causes is quite common: aboutone-third of all Americans develop some form of cancer in their lifetimes, and about one-fourthof all Americans die of cancer. The background risk of cancer death, then, for the MEI (as forall of us) is about 25% (or 250,000 in a million). This overall cancer risk applies to theconceptual MEI irrespective of the existence of the Maine Energy facility. If the estimatedincremental cancer risk to the adult MEI is, at most, 4 in one million, the overall cancer riskwould increased only slightly to 25.0004% (or 250,004 in a million) — an imperceptibleincrease.

1.6 Risk assessment basis and organization

Much of the risk assessment for the Maine Energy facility is based on the U.S. EPA’s draftHuman Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities (hereafterHHRAP, U.S. EPA, 1998a). The HHRAP is quite detailed and builds upon previous U.S. EPAguidance. The HHRAP is currently available in draft form, including an addendum documentissued to correct errors and omissions (U.S. EPA 1999). The HHRAP is similar to methodologyused to develop the 1996 risk assessment for the Maine Energy facility, although it has addedimportant enhancements (e.g., wet deposition whereby compounds are removed from theatmosphere by precipitation and deposited to land and water) and refined numerous assumptionsand parameters. The HHRAP is used as the framework for the updated Maine Energy facilityrisk assessment because it is consistent with contemporary risk assessment guidance and soundscientific knowledge.

Comprehensive stack testing serves as the primary source of information on compoundemissions from the Maine Energy facility. The multi-pathway risk assessment predicts, throughthe use of modeling, compound properties, and site-specific information, the disposition ofcompounds in the environment, and hence estimates how they may be contacted by people andanimals, and whether such contact presents significant risks to health.

A number of refinements to the HHRAP guidance are included in the Risk Assessment Protocol(RAP, included here as Appendix I), and additional improvements are described in the body ofthe risk assessment report. As stated above, the overall goal of these refinements is to achievebetter consistency with scientific knowledge. Peer-review of the risk assessment protocol wasalso incorporated to provide a comprehensive assessment of potential risks to both human healthand the environment.

This risk assessment report follows the HHRAP’s suggested outline and content. Subsequentsections describe elements of the risk assessment as discussed in the HHRAP and (asappropriate) in the context of conditions specific to the Maine Energy facility. The report isorganized into a series of chapters that describe the sequential steps of the multi-pathway riskassessment, with each step built upon those that preceded. Emissions of compounds of potentialconcern (COPCs) from the Maine Energy facility are described and quantified in Chapter 2. Chapter 3 describes the detailed modeling study designed to estimate the levels of COPCs in airand in wet and dry deposition that result from emissions from sources at the Maine Energy


1–12

facility. Chapters 4 through 6 describe the procedures used to estimate the levels of COPCs thatcould be contacted by people in their environment and diet, focusing on categories of individualslikely to receive the highest levels of exposure. Potential risks to human health that could resultfrom such exposure are estimated in Chapter 7, focusing (as is traditional in risk assessments) onthe incremental chance that exposure to the facility’s emissions might lead to the development ofcancer or other adverse health effects. Uncertainties of the human health risk assessment arediscussed in Chapter 8. Finally, the technical appendices contain the detailed informationneeded to reproduce the calculations of the risk assessment.


2–1

2 Facility emissions characterizationThe Maine Energy Recovery Company’s Biddeford facility (Maine Energy facility) has twosources that emit chemicals of potential concern (COPCs) to the atmosphere. The main source isthe boiler stack effluent associated with the combustion of refuse-derived fuel. The secondsource is the effluent of the odor control and treatment system. Both of these sources utilizecontrol technologies that reduce the levels of COPC emissions to the atmosphere.

2.1 Facility process information

The Maine Energy facility is designed to process approximately 1200 tons of municipal solidwaste (MSW) each day. Mechanical equipment is used to separate metal and othernoncombustible materials that are recycled or disposed. The remainder of the MSW, whichincludes primarily paper, plastic, and food waste, constitutes the refuse-derived fuel that thefacility combusts in two boilers. The steam produced by the boilers is fed through turbines toproduce up to 22 megawatts of electricity.

The byproducts of MSW combustion include residual ash, which is trucked to a landfill, and fluegases that are emitted to the air and subject to regulations enacted and enforced by the MaineDepartment of Environmental Protection (DEP). Prior to atmospheric release, flue gas from eachboiler is treated by a series of air pollution control devices to reduce the levels of pollutants.First, a high efficiency cyclone separator removes most of the dust particles. Second, a spraydryer/absorber injects a lime slurry into the flue gas to remove most of the sulfur dioxide andreduce the level of acid gases. Last, a multi-compartment fabric filter, or baghouse, captures thecalcium sulfate particles formed in the spray dryer, as well as unreacted lime and small particlesnot initially collected by the cyclone collector. After treatment in the baghouse, the cleaned fluegas from the two combustion units is vented through a common boiler stack at a height of 244feet above ground. In 2000 the Maine Energy facility installed an odor control and scrubbing


2–2

system to reduce odors that could otherwise escape to the outdoors, as described in Section 1.1.

2.2 Compounds of Potential Concern (COPCs)

The main pollutants emitted from the Maine Energy facility are particles (more commonly calledparticulate matter), sulfur dioxide, oxides of nitrogen, total (unspeciated) volatile organiccompounds, and carbon monoxide. These pollutants are known as criteria pollutants, and areregulated by DEP to ensure that emissions from the Maine Energy facility do not lead toexceedances of the National Ambient Air Quality Standards promulgated by the U.S.Environmental Protection Agency (EPA) (and adopted by the Maine Legislature as MaineAmbient Air Quality Standards) to protect human health. In fact, the Maine Energy facility issubject to continuous monitoring requirements for three of these five criteria pollutants.

Since criteria pollutants are regulated by the DEP and the U.S. EPA to protect human health, therisk assessment focuses on other pollutants released by the Maine Energy facility. Collectively,these pollutants are sometimes called air toxics, and many are designated as Hazardous AirPollutants in the context of the Clean Air Act regulations (including specific volatile organiccompounds). Air toxics tend to be released in much smaller quantities and are hence notamenable to the continuous emission methods developed for criteria pollutants. Instead, airtoxics are typically measured on a periodic basis in stack tests using methods developed andspecified by the U.S. EPA.

The list of air toxics is conceptually infinite, but through research and study regulatory agencieshave developed a knowledge base of the pollutants released by waste-to-energy facilities (U.S.EPA, 1993). The 1996 health risk assessment for the Maine Energy facility focused on a selectnumber of compounds of potential concern (COPCs) known to be released from waste-to-energyfacilities. Only boiler stack emissions were considered, and the 1996 risk assessment focused on

• arsenic;• beryllium;• cadmium;• chromium;• lead;• mercury;• nickel; and• polychlorinated dioxins and furans (PCDD/PCDFs).

All of these same COPCs are evaluated in this updated risk assessment of the Maine Energyfacility. In addition, however, the following additional COPCs are also evaluated for boilerstack emissions based on information gathered in recent testing of boiler stack emissions:

• hydrogen chloride;• six additional metals (copper, selenium, silver, tin, vanadium, and zinc);

1 PCBs in the Maine Energy stack emission were measured as Aroclor 1248, the HHRAPguidance recommends that the fate and transport of PCB mixtures with greater than 0.5%congeners of more that 4 chlorines be modeled using the properties of Aroclor 1254. BecauseAroclor 1248 contains approximately 75% congeners of more that 4 chlorines, PCBs emissionsfrom the Maine Energy facility are modeled as Aroclor 1254.


2–3

• ten semi-volatile organic compounds (phenol, naphthalene, 2-methylnaphthalene, diethylphthalate, di-n-butyl phthalate, bis(2-ethylhexyl)phthalate, benzyl alcohol, 2-methylphenol, 3&4-methylphenol, and benzoic acid); and

• polychlorinated biphenyls (PCBs1, created as products of incomplete combustion).

The second source of emissions is the odor scrubbing system, which differs fundamentally incharacter since it is not a combustion source. The principal COPCs from the odor scrubbingsystem are various organic compounds that have been identified in source testing. The specificcompounds detected in two monitoring studies of the odor scrubbing system include:

• ethanol (the organic compound detected consistently at the highest concentration);• acetone, benzene, bromomethane, 2-butanone (methyl ethyl ketone), carbon disulfide,

chloromethane, chloroform, cyclohexane, 1,4-dichlorobenzene, ethylbenzene, freon 11,freon 12, heptane, hexane, methylene chloride, 2-propanol, styrene, tetrachloroethylene,toluene, 1,1,1-trichloroethane, 1,2,4-trimethylbenzene, vinyl chloride, and xylenes.

Not all of the organic compounds identified in effluent samples of the odor scrubbing systemwere found in all samples. Some, in fact, were detected in only a few samples. All of thechemicals detected in any sample, however, are considered in the risk assessment.

Additionally, since combustion air for the boilers is derived from within the Maine Energyfacility buildings, it presumably enters the boilers with some of the same COPCs contained inthe odor handling system inlet. The majority of these hydrocarbon compounds are likelydestroyed in the combustion of the refuse-derived fuel. However, a small percentage mightescape destruction and hence be released from the boiler stack. Therefore, compounds that weredetected in the scrubber inlet testing but which were not measured as part of the stack testing areincluded in the stack emissions, with an assumed destruction efficiency of 99.9%.

Finally, because the odor scrubbing system collects air from all the enclosed portions of thefacility, there is the potential that fugitive dusts generated within the plant may be emitted fromthe scrubber. To evaluate the possible impacts of these emissions all of the particulate phasemetals and PCDD/PCDFs that are assessed as part of the stack emissions will also be included aspart of the scrubber system emissions.


2–4

2.3 COPC emission rates

COPC emission rates are derived directly from the results of recent testing conducted at thefacility. Data are considered from the last three years of boiler stack testing (2002 to 2004) anddetailed air toxics testing studies conducted in 2002 and 2003 that evaluated emissions from theodor scrubbing system (the 2002 air toxics study also included boiler stack testing). Test resultsfrom both the boiler stack and odor scrubbing system are reported as concentrations present inthe flue gas or effluent. These concentrations (in units of mass per unit volume) are multipliedby effluent discharge rates (in units of volume per unit time) to estimate mass emission rates (inunits of mass per unit time) used as input to the air dispersion modeling analysis. Three sets ofemission rates are considered in the risk assessment; (1) baseline long-term emission ratescalculated as the average of available recent emissions data for each COPC, (2) maximum orhigh-end long-term emission rates calculated as the maximum of available recent emissions data,and (3) upset condition, short-term emission rates calculated as the maximum of available recentemissions data multiplied by a process upset factor. The measurements and calculation used todetermine these emission rates for the purposes of risk assessment modeling are described in thesections that follow.

The baseline risk assessment is developed using best estimates of emission rates based on fullfacility operation, calculated with the average values of measured COPC concentrations andoperating conditions typical of full facility capacity for effluent flow rates. The use of averagemeasured COPC emission rates for the baseline risk assessment actually results in anoverestimate of the long-term facility impacts because the air dispersion modeling assumes thatthese COPC emission rates occur without interruption while each of the combustion units at theMaine Energy facility does in fact experience a significant amount of downtime over the courseof a year. Data on the extent of the facility downtime are described below in relation to theassessment of facility upset conditions on COPC impacts.

To test the sensitivity of the risk assessment results to uncertainties in the measured emissionrates, risk estimates will also be performed using high-end estimates of the COPC emission rates. Following HHRAP guidance, these emissions estimates are calculated based on the lesser of (1)the maximum COPC concentrations detected in sampling and (2) the average concentration plustwo standard deviations of the average, and also using continuous operation of the facility at thedesigned maximum capacity.

Because the COPC emissions testing was conducted under normal facility operating conditions,there is the possibility that short-term, off-normal facility operations might lead to higher COPCimpacts than would be predicted from the model using even the maximum measured COPCemission rates. Therefore, potential short-term elevated COPC emission rates have beenestimated for several process upset conditions based on facility records of the occurrences ofsuch upsets and continuously measured criteria pollutant measurements. Facility upset anddowntime data are also used to assess the degree to which the modeling assumption that thefacility operates continuously at its tested COPC emission rates produces an overestimate ofCOPC long-term impacts.


2–5

In addition to the direct use of measured data for estimating COPC emissions from the MaineEnergy facility, some specific COPCs require the application of additional data or assumptionsto provide emission rates needed for the multi-pathway modeling. The first set of assumptionsconcerns the methods used to estimate emission rates of COPCs that were not present in thetested exhaust gasses at levels high enough to be reliably measured. The second and third set ofassumptions concern the chemical and/or physical forms of the COPCs chromium and mercury. Chromium is assumed to be present in the facility’s emissions in either the trivalent orhexavalent forms (notated as Cr+3 and Cr+6 respectively), and mercury is assumed to be presentas either elemental vapor-phase mercury, divalent vapor-phase mercury, or divalent particulate-phase mercury (notated as Hg0, Hg2+(v), and Hg2+(p) respectively). Because the different formsof these metals have significantly different transport and/or toxicological properties, but they arenot distinguished from each other in standard exhaust gas testing, additional information isnecessary to allow for the assessment of their impacts in the multi-pathway modeling.

The following sections describe the methods used to derive the COPC emission rates that havebeen included in this report’s direct and multi-pathway risk estimates. Detailed data from thefacility’s emission testing programs, process upset logs, and continuous emission monitors thatwas used to calculate the emissions rates used in the risk assessment are included in AppendixIII. The COPC emission rates that are used in the risk assessment models are summarized inTables 2.2 and 2.3 which follow the descriptions of the methods used to derive these rates. Thebaseline emission rates of COPCs are similar to those considered in the 1996 health riskassessment, as described in Section 2.3.7. Additional details of the derivations are contained inthe sections that follow; measured concentrations are contained in Appendix III.

2.3.1 Procedures for estimating stack COPC emission

The modeled COPC emission rates from the Maine Energy facility’s boiler stacks are based onthe average of the measured stack gas and exhaust flow rate data for each COPC as collectedduring the stack testing programs since 2002. Because several different types of COPCs areincluded in the modeling, and different rounds of stack testing have been conducted for differentpurposes over the past few years, the sources of COPC emission rate data differ from onecompound to another. Additionally, some COPCs may be present in minor amounts in stackexhaust gases, but have never been part of any of the stack gas testing programs. The modeledstack emission rates for these compounds are based on concentrations that have been measuredin other parts of the Maine Energy facility.

The most complete set of recent stack gas test results are contained in the Maine Energy 2002Air Toxics Test Program report (Eastmount, 2002). Full details of this testing program are foundin the test program report — test procedures and conditions are summarized here. Stack testingfor this report included the measurement of trace metals, hydrogen chloride, volatile organiccompounds (VOCs), and PCDD/PCDFs in the boiler stack gases. Sampling of these gases wasconducted during the week of July 29, 2002 and August 5, 2002. All pre-test preparation,testing, analysis, and calculations were conducted in accordance with procedures approved bythe Maine DEP; the Code of Federal Regulations Chapter 40, section 60, Appendix A; the U.S.


2–6

EPA Quality Assurance Handbook (Vol.III), and a pre-test protocol. Trace metals weremeasured using EPA Reference Method 29; hydrogen chloride was measured using EPAReference Method 26/26A; VOCs were measured using EPA Reference Method 0040; andPCDD/PCDFs, PCBs (reported as Aroclor 1248), and semi-volatile organic compounds weremeasured using EPA Reference Method 23/0010. During the test program both of the facility’sboiler units were operated at or near their rated capacity.

Two subsequent rounds of sampling were performed in July 2003 and August 2004 to measureemission rates of selected metals (As, Cd, Cr, Pb, Hg, and Ni in 2003; and Cd, Pb, and Hg in2004) and hydrogen chloride. In addition to the 2002 Air Toxics testing, for PCDD/PCDFsconcentrations were measured in September 2001, July 2003, and August 2004. The averages ofthe recent test results for each COPC were used to calculate emission rates for the riskassessment. Comparisons among test results for COPCs that have recently been measured morethan once, and those which were included in the 1996 risk assessment, are included in section2.3.8.

The VOCs that are included as COPCs due to their presence at the inlet to the scrubber systembut which were not measured as part the stack emissions test programs are: n-butanol,cyclohexane, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-dichlorobenzene, ethanol,ethylbenzene, freon 11, freon 12, heptane, hexane, methane, methanol, propane, 2-propanol,1,1,1-trichloroethane, and 1,2,4-trimethylbenzene. Because the combustion air for the MaineEnergy boilers is taken from within the facility’s buildings, these compounds might be emittedfrom the boiler stacks if they were not destroyed in the combustion process. Therefore, theestimated stack emission rates for these compounds were calculated by multiplying theirconcentrations at the scrubber system inlet by the typical facility combustion air flow rate of55,000 cubic feet per minute, and a factor of 0.001 which corresponds to a combustion systemdestruction and removal efficiency (DRE) of 99.9% for these compounds. This is a fairlyconservative (i.e., probable underestimated) DRE for estimating organic COPC emissions fromthe boiler stack. For example, in a comparable context from a different industry, the U.S. EPA’sResource Conservation and Recovery Act (RCRA) hazardous waste regulations require thatboilers and industrial furnaces achieve a DRE of 99.99% for the hazardous organic constituentsof the waste, and a DRE of 99.9999% for dioxin-bearing wastes (40 CFR Part 266, Subpart H).

2.3.2 Procedures for estimating odor scrubber system COPCemission rates

The Maine Energy facility odor scrubber system is designed to collect gases that are present inthe facility’s waste handling, processing, and combustion buildings, and to pass these gasesthrough a series of filters and wet scrubbers before emitting them from three venting stacks onthe top of the building. The flow rate through the system is high enough to prevent odorousgases from exiting the facility’s buildings through any open doorways, thus preventing emissionsof untreated odorous compounds and fugitive at ground level.


2–7

The gases at the inlet and outlet of the scrubber system were sampled and analyzed for VOCsusing EPA Compendium Method TO-15 in August 2003. Details of the sampling program arecontained in the report “Emission testing from three scrubbers at MERC” (APCC, 2003). Twosets of samples were collected and two flow rate measurement were taken at the inlet and outletof each of the three scrubber units. The scrubber outlet COPC concentrations were multiplied bythe flow rates for each of the six tests, the two results for each scrubber were averaged, and theaverages were summed to produce overall average emission scrubber system COPC emissionrates. Maximum total scrubber system COPC emission rates were calculated by summing thegreater of the measured emission rates for each scrubber unit.

A few COPCs that were not measured as part of the scrubber system sampling program weremeasured in three rounds of tests performed in August and September 2004 on the gases presentin the tipping room of the facility. These data were used to supplement the scrubber system databy multiplying the tipping floor concentrations by the total scrubber system outlet flow. Average emission rates were calculated using average concentrations and flow; maximumemission rates were calculated using maximum concentrations and flow. This is a highlyconservative estimate of the emission rates for these COPCs from the scrubber system ventsbecause it does not account for any concentration reductions that might occur due to the action ofthe scrubber system or the significant dilution that occurs as the gases from the tipping room aremixed with additional air while being transported between the buildings.

In addition to the gases that are collected and processed by the odor scrubber system, fugitivedusts that are present within the facility’s buildings may also be collected, filtered and emitted bythe system. The fugitive dust within the facility that has the highest particulate-phase COPCcontent and the greatest potential for fugitive dust emissions is the ash collected from thecombustors. This material has significantly higher particulate-phase COPC concentrations thanthe waste entering the facility and combustors because the metals and low-volatility compoundspresent in the waste and combustion products are less diluted by combustible and volatilecompounds initially present in the waste. The ash has a higher tendency to be collected andemitted by the scrubber system because of the ashes elevated fraction of very fine particleswhich are more likely to be suspended as fugitive dust within the facility than are largerparticles.

An estimate of the fugitive ash emission rate from the facility was performed by Maine Energyin February 2003 and a report on this estimate submitted to the City of Biddeford in the MaineEnergy Air Toxic Control Application. The fugitive ash report indicates that 46,322.32 tons ofash were produced in 2003. The report then applies an emission factor of 1.5 pounds ofemissions per ton of material loaded into an open truck based on data from the U.S. EPAEmission Factors Handbook (AP42, Table 11.17.4, U.S. EPA, 1998c). An emission controlefficiency of 80% is applied to account for the fact that the wetting of the ash reduces itstendency to be emitted as a fugitive dust. A second control efficiency of 90% is applied toaccount for the fact that the fugitive dusts are generated in an enclosed building with the onlyemissions having to pass through the collection and treatment system. It is believed that both of


2–8

these factors underestimate the true control efficiencies. Taken together these data yield anaverage ash emission rate of 1390 pounds per year or 0.020 g/s.

These fugitive ash emission estimates were combined with COPC concentrations measured inthe ash as part of the 2002-2004 MERC Annual Solid Waste Reports. The COPCs included inthis report are: arsenic, cadmium chromium (total, and hexavalent), copper, lead, mercury,nickel, selenium, silver, vanadium, zinc, and PCDD/PCDFs. Concentrations of the COPCsberyllium and tin in the ash were not included in the analyses for solid waste reports, thereforethese concentrations were estimated based on the ratios of these metals’ concentration to those ofother metals as measured in the boiler stack emissions. Beryllium levels in the ash wereestimated based on the chromium level in the ash and the ratio of beryllium to chromium in thestack emissions because both of these metals are classified as low volatility metals for thepurposes of MACT compliance. Tin levels in the ash were estimated based on the lead level inthe ash and the ratio of tin to lead in the stack emissions based on their relatively similar meltingpoints, sources, and chemistries. Because the metal emission from the odor control system arevery small relative to the boiler stack, these approximations have very little effect on the overallresults of the risk assessment. The COPC ash concentrations (in units of mass per mass, ng/kg inthe report) were multiplied by the estimated ash emission rate to obtain an estimate of the COPCemission rates.

2.3.3 Data and procedures for estimating stack COPC emissionrates under process upset conditions

A waste-to-energy plant does not always operate under normal conditions: the plant goesthrough startups and shutdowns, and may experience upset conditions if a portion of the airpollution control system malfunctions or the combustion control system is disturbed. Emissionsthat occur during these periods will be evaluated in the risk assessment only with respect to thepotential impacts of direct short-term exposures. Emissions at the increased upset conditionrates are short-lived because once the upset is detected, waste feed to the combustion unitexperiencing the upset is automatically stopped (per facility design), or other actions are taken toeliminate the cause of the upset. For example, waste feed cutoff is required when the opacity ofthe visible emission (as monitored by the facility’s continuous emission monitor) is equal to orgreater than 15%. The possible effect of upset emissions on long-term average emission ratesand exposures is evaluated in Section 2.3.3.5.

The potentially higher than normal facility emissions during system upsets are evaluated usingupset factors developed for specific types of upset conditions, which are applied to the COPCsthat would be affected by these conditions. To the extent possible, the upset factors used in therisk assessment models are based on site-specific information. This has been done by matchinglogged information on facility upsets with data from the facility’s continuous emissionmonitoring systems (CEMS) which log hour measurements of opacity, carbon monoxide (CO),and sulfur dioxide (SO2), among other pollutants. The facility data used to calculate the upsetfactors are included in Appendix III. Because the upset factors are employed to assess maximum


2–9

potential one-hour COPC exposures, the factors are based on one-hour increases in emissions. Because the highest potential short-term emission rates would occur when the facility is runningat its maximum operating conditions, maximum non-upset emission rates are multiplied by theupset factors to estimate the maximum one-hour upset emission rates. By combining theestimates of the upset factors with maximum facility emission rates and maximum modeled airdispersion impacts, the model is very likely to significantly overpredict actual maximum short-term impacts. This is because the three events being modeled: (1) operation at maximum initialCOPC emission rates, (2) a process or control system upset, and (3) the presence of atmosphericdispersion conditions that lead to the maximum short term impact levels, are all fairlyuncommon. It is therefore very unlikely that all three would occur during the same hour, asmodeled under the upset condition short-term risk calculations.

Upset emissions may be caused by equipment malfunctions in three of the Maine Energyfacility’s systems:

• upsets to the boilers’ combustion control system that result in incompletecombustion and increased emissions of organic compounds,

• upsets to the baghouses that result in increased emissions of particulate pollutants, and

• upsets to the spray dryer system that result in increased acid gas emissions.

Although facility startup and shutdown may not be strictly classified as upset conditions, theshort-term effects of operations during startup and shutdown will be considered as part of theupset analyses. While COPC mass emission rates during startup and shutdowns may be lowerthan during normal plant operation because of reduced throughput, it is possible for themaximum ground level COPC concentrations to be higher than normal due to lower than normaldispersion of the emissions. This condition is evaluated through the use of a special airdispersion modeling run as described in Section 2.3.3.4.

To simplify the modeling of upset condition emissions, a composite, worst-case, set of COPCemission rates for the combustion control, baghouse, and spray-dryer upsets has been compiled. This overall set of emission rates uses the highest upset factor for each COPC, thus the COPC-specific risk and hazard estimates for the upset modeling are each valid for the upset conditionthat leads to the greatest impact for that compound. However, because the modeled upsetcondition approximates all the upsets occurring simultaneously (a highly unlikely occurrence),the overall risk and hazard estimates for the upset condition modeling are overestimated. Thepossibility that these upsets might occur during the low stack flow conditions of boiler startupand shutdown is modeled using the composite upset COPC mass emission rates with a specialdispersion and deposition modeling run based on low stack flow conditions. The high stackflowrate upset condition is referred to as a “normal upset”; the low stack flowrate upsetcondition is referred to as a “startup upset.”


2–10

2.3.3.1 Combustion control upsets

Disturbances of the combustion control system may result in incomplete combustion of organicCOPCs. Large increases in organic emissions during such upsets are partially controlled by thespray dryer/fabric filter system, which will retain some organics. The combustion control upsetfactor has been calculated based on Maine Energy records of boiler outages caused by fuel feedproblems or boiler malfunctions or operating problems and hourly carbon monoxideconcentrations measured before and during the period when the upset occurred. Carbonmonoxide levels are used as an indication of incomplete combustion conditions. A total of 22such upsets occurred between October1, 2003 and September 31, 2004; suitable COmeasurements are available for 12 of these episodes (because of the timing of the upsets and thehourly CO measurements definitive CO concentrations before and/or after were not available forall of the events). The ratio of CO concentrations measured during the period when the upsetoccurred to those measured before the upset ranged from 2.3 to 3.9, with a mean ratio of 2.9. These values are consistent with short-term organic compound emission increases that have beenobserved at other facilities that have experienced combustion control upsets. For example,during the testing of the Marion County facility’s startup procedures, the overfire air fan failedfor a brief time. Total hydrocarbon emissions during this period were elevated by a factor of 3–5(U.S. EPA, 1988). The mean combustion control upset factor of 2.9 will be applied to assesspotential short-term emission rate increases in the facility’s organic COPC impacts.

2.3.3.2 Spray dryer absorber upsets

Increased emissions of hydrogen chloride may result from the malfunction of the spray dryerabsorber system. Most malfunctions of this system are short term, requiring less than about10–15 minutes to address and return to normal operation. In addition, effects of partial or fullspray dryer absorber malfunction are mitigated because residual unreacted lime on the fabricfilter bags will continue to remove acid gases. Malfunctions of the system are very uncommon;from July 1, 2001 through March 31, 2005, only 3 spray dryer upsets occurred. To estimate thespray dryer upset factor, the sulfur dioxide levels measured before and during two of these upsetperiods were compared (the other upset period did not have suitable SO2 data available). Theratios of SO2 concentrations during the upset to those before the upset were 2.2 and 2.5. Becauseit was possible to calculate only two values, the higher of the two, 2.5, will be used to evaluateshort-term spray dryer upset emissions. This value is comparable to the one estimated in theRAP (2.1) which was based on a malfunction that leads to a 15-minute, tenfold increase inemissions from one of the facility’s two spray dryers.

2 The estimate that 5% of the baghouse flow would pass through the ruptured bag is based onan analysis by American Ref-Fuel for a waste to energy plant for which CambridgeEnvironmental has previously performed a multipathway risk assessment (CambridgeEnvironmental, 1992).


2–11

2.3.3.3 Baghouse/fabric filter upsets

Although total failure of a combustion unit’s entire fabric filter system is not plausible, ruptureof one or more filter bags in the unit’s baghouse system may occur. When this occurs, a portionof the flue gas stream is untreated. Operators quickly isolate the appropriate cell and replace theruptured bags. If such a rupture results in an increase in opacity to a level equal to or greaterthan 10% for 15 minutes, feeding of waste into that unit automatically ceases. As with the spraydryer system, significant baghouse system malfunctions are very uncommon; since July 1, 2001only four such upset have occurred and all of them were between July 18, 2001 and November14, 2001. Unfortunately, sufficient data are not available to establish a site-specific upset factorfor baghouse malfunctions. Therefore, the method suggested in the RAP is applied.

It is assumed that the fabric filter bag has a particle mass collection efficiency of 99.5%, thus atotal failure of the bag causes the emission rate through that bag to increase by a factor of 200. If5% of the unit’s flue gas passes through the ruptured bags2 and one hour is required to isolate thecell containing the ruptured bag, the increase in PM emissions from that unit is:

0.95 (flow through intact units) + 200 × 0.05 (flow through ruptured units) = 10.95.

Because there are two independent baghouses, the overall facility upset factor for such a filterbag rupture (averaged between the two units) is thus:

1 10 952

6+≈

.

2.3.3.4 Combustion startup/shutdown conditions

The conditions that exist during periods of combustor startup and shutdown will be included inthe estimation of upset factors. Since startup and shutdown procedures include reduced feedratesand result in lower operating temperatures, the only COPC stack gas concentrations likely toincrease are those for volatile organic compounds due to incomplete combustion of the feedmaterial. Therefore, all VOCs will be considered in the startup/shutdown upset scenario. Although VOC concentrations in the boiler exhaust gases may be elevated during startup andshutdown periods relative to during periods of normal operation, the VOC mass emission ratesmay not increase by a proportional amount due to reduced throughput during these intervals. However, the lower feed rates that occur during startup and shutdown conditions also result in a


2–12

lower gas flow rate at the stack exit which may lead to less atmospheric dispersion of emittedVOCs and thus potentially higher maximum ground level concentrations. Therefore, to estimateground level short-term VOC concentrations during startup and shutdown operations, a specialair dispersion model run was performed. This model run was based on a facility stack exitvelocity of half the normal to account for the lower total gas throughput that occurs duringstartup. Because this model run was used only to evaluate the maximum one-hour COPCconcentrations and direct exposure levels, COPC deposition was not included in the short-termupset condition modeling. The atmospheric dispersion results from this model run werecombined with upset condition VOC emission rates to estimate maximum short-termstartup/shutdown ambient VOC concentrations.

Although CEMS data are available during periods when the facility’s boilers are operating understartup conditions as well as during planned and unplanned shutdowns, the interactions betweenvariations in the fuel feed rates, combustion air flow rates, and exhaust flow rates andtemperatures on these measurements preclude a simple estimate of VOC upset factors from theavailable data. Because the condition being assessed in the startup/shutdown upsets models isone of elevated VOC levels due to incomplete combustion, the VOC emission concentrations forthe startup/shutdown conditions are modeled as equal to those used for the combustion controlupset, or 2.9 times the maximum measured concentrations.

2.3.3.5 Effects of upset emissions on long-term average

The effects of process upset conditions are not included in the long-term multi-pathway riskassessment calculations because the inclusion of upset condition emission rates would notincrease actual long-term emissions above the levels used in these calculations. The long-termaverage stack COPC emission rates used in the multi-pathway portions of the risk assessment arebased on actual stack test results, with the assumption that these emissions occur during everyhour of the year. However, each of the Maine Energy boilers experiences a significant amountof downtime or outage periods each year; therefore, the actual long-term average emission ratesfor normal facility operation are lower than the long-term emission average emission rates usedin model. To assess whether the elevated emissions that are believed to occur during periods ofupset operation might be large enough to compensate for this over estimation, the facility’s upsetand outage records between July 1, 2001 and March 31, 2005 have been examined. For theperiods when total operating and outage hours are available for either or both of the facility’sboilers, there are a total of 35,429 boiler-hours of operation and 3997.5 boiler-hours of outage. This corresponds to the facility’s boiler operating during 90% of the available hours. During thesame period a total of 107 of system upsets (including system startup/shutdowns) wereidentified. Even if the maximum calculated system upset factor (a factor of 3.9 for combustioncontrol upsets) were to be applied for each of these occurrences, this would only add an amountof COPC emissions equivalent to 310 hours or normal operation ((3.9 - 1) V 107). These addedemissions are far less than those that are assumed to occur during 3997.5 boiler-hours when thefacility’s boiler are not operating, and the actual emissions are zero. Therefore, the long-termemission rates used in the multi-pathway portions of the risk assessment are higher than thosethat would be calculated by taking the facility’s actual long-term average emission rates


2–13

(adjusted for facility downtime) and adding the effects of short-term elevated emission ratescaused by upset operations.

2.3.4 Procedures for non-detected compounds

As described in the Maine Energy RAP, and in Section 2.2 of this report, the only compoundsthat are included as COPCs in the risk assessment are those that have been detected in eitherboiler stack emission gas samples, odor scrubber system inlet or outlet samples, or in facility ashsamples. The RAP indicated that an exception would be made for specific PCDD/PCDFcongeners, and for hexavalent chromium. However, each of the 17 carcinogenic CDD/PCDFcongeners have been detected in at least one of the stack gas samples, and hexavalent chromiumwas detected in some of the facility ash samples, so the potential exception for non-detects isirrelevant.

The estimation of emission rates for COPCs that are detected in some (but not all) of the boilerstack or scrubber emission tests can be a source of uncertainty in a risk assessment. To produceestimates of the emission rates for these compounds, two different methodologies are applied. For those COPCs that have not been detected in the recent stack or scrubber tests (but have beendetected in older tests), the assumed baseline emission rates are taken as one-half the detectionlimit of the most recent testing program. For those COPCs that have been detected in some (butnot all) of the most recent tests, the test results in which the COPC is not detected are averagedwith the detected results at the full detection limit.

The specific detection limit for each COPC and test result that is used in emission ratescalculations is dependent on the data that are available for each testing program. The goals forthis portion of the risk assessment are to use as much data as is available, maintain aconservative bias (designed to overestimate actual emissions, but not introduce overlyconservative methodologies to compensate for uncertainty). The detection limits used toestimate concentrations of non-detected COPCs are the maximum concentration level for whichthe COPC would not be indicated as a detected compound. Therefore, if method detection limits(MDLs) are given, and COPCs present at levels just above the MDL would be shown as beingdetected, the MDL value is used as the detection limit. If COPC concentrations are reported inthe test results at just above MDLs (perhaps with a qualifier indicating an estimatedconcentration), the value is used as given (consistent with the treatment of estimated values inthe Superfund program). In this case, the use of the HHRAP recommended MDL-derivedreliable detection limit (RDL) values for non-detected POCs could result in test results with non-detects being averaged into the emission calculations at higher concentrations than detected tests. Detailed, COPC-specific measurements and the COPC-specific treatments of non-detectedvalues are included in the tables in Appendix III.


2–14

2.3.5 Chromium speciation

Chromium can exist in two forms in environmental compounds, bonding either in trivalent orhexavalent forms. Because these two forms have significantly different toxicological properties,they should ideally be measured and modeled as two different COPCs in the assessment of directand multi-pathway potential health risks. However, the measurement of hexavalent chromium inexhaust gases is difficult due to both limitations of the analytical methods and the lowconcentrations of hexavalent chromium in combustion exhaust gases, so stack testing forhexavalent chromium levels has not been attempted at the Maine Energy facility. Data fromother similar facilities are scarce. Because the fraction of chromium present in the hexavalentform can have a significant effect on the overall estimated risks caused by a facility’s emissions,it is necessary to estimate this fraction from other available data.

Based on previous risk assessments of municipal waste combustors, theoretical chemicalequilibria and kinetics at typical municipal waste combustion conditions, measurements ofhexavalent chromium in combustion exhaust gases, and the maximum fraction of hexavalentchromium found in ash from the Maine Energy facility, the anticipated level of hexavalentchromium in the Maine Energy facility’s emissions is believed to be negligible. It should benoted that the 1996 Maine Energy Risk Assessment (Cambridge Environmental, 1996) evaluatedchromium in trivalent form only (i.e., it was assumed that there was no hexavalent chromiumemitted from the facility).

In a recent evaluation of emissions from the Harrisburg, Pennsylvania Waste to Energy facilityJones (2003) conservatively assumed a hexavalent chromium fraction of 2%. This value wasbased on a risk assessment of the Falls Township Waste to Energy facility submitted to thePennsylvania Department of Environmental Protection, and test data from the Bridgeport,Connecticut Waste to Energy facility which found no detectable levels of hexavalent chromium,with a conservative estimate of the detection limits of 3–5% of the total chromium level. Thehexavalent chromium fraction of 2% was assumed to be an upper confidence limit (percentileunspecified) of the actual mean fraction. The conservative nature of the 2% estimate issupported by the theoretical and laboratory combustion studies of Persson et al. (2000) andSandelin et al. (2001) which found that the potential and measured fraction of hexavalentchromium in combustion exhaust gases is negligible (less than few percent) for gas temperaturesup to approximately 1300°C, well above typical municipal waste combustion temperatures of1000°C. Although hexavalent chromium measurements have not been performed in the MaineEnergy exhaust stack, they have been performed in the facility’s collected combustion ash ineight quarterly measurements of ash collected in 2002 and 2003. Hexavalent chromium wasonly detected in the four tests conducted in 2002. Using the detection limits for the non-detectedhexavalent chromium concentrations, the fraction of hexavalent chromium in the ash isapproximately 1% of the total chromium concentration. Therefore, the baseline risk estimateswill be performed with an assumed hexavalent chromium fraction of 2% (a conservative estimatebased on the facility-specific ash measurements). Sensitivity analyses are described in Section8.1.5 using other hexavalent chromium fractions of 1, 5, and 10%.


2–15

2.3.6 Mercury speciation

Because the potential health effects caused by exposures to emitted mercury often dominate thenon-cancer portion of the risk assessment, and because the modeling of mercury emissions andtransport is very sensitive to the selection of several modeling parameters, the measurement orestimation of the speciation of the mercury emissions (i.e., the distribution of mercury among itsvarious chemical and physical forms) is critical in the multi-pathway modeling of this pollutant. Within the HHRAP guidance and this risk assessment it is assumed that mercury is emitted inthree forms: vapor-phase elemental mercury, vapor-phase divalent mercury, and particulate-phase divalent mercury. The divalent mercury species are further assumed to all be present asmercuric chloride (HgCl2). It is assumed that a fourth form of mercury, methyl mercury, is notemitted from the facility, but instead is formed in soils and surface waters from the emitteddivalent mercury. Methyl mercury is the form that is found in fish tissues, and it is in theconsumption of mercury in fish that the majority of the potential human health effects occur. The assumption that all of the divalent mercury is present as mercuric chloride results in anoverestimate of the mercury impacts because mercuric chloride is among the most reactive formsof mercury, and it thus deposits from the atmosphere and can transform into methyl mercury farmore rapidly than less reactive yet common divalent forms such as mercuric oxide (HgO).

Mercury measurements in stack testing at the Maine Energy facility use U.S. EPA ReferenceMethod 29. The components of the sampling train used for Method 29 are shown in Figure 2.2. Although the method is not explicitly designed for determining the speciation of mercuryemissions, the U.S. EPA Report to Congress (U.S. EPA, 1997a) notes that the distribution ofmercury in the Method 29 sampling train can be used to infer the form and speciation of mercuryin MWC stack gas. The probe and filter of the sampling train collect mercury adsorbed ontoparticulate matter. Vapor-phase ionic mercury compounds that are soluble in water are collectedin the nitric acid/hydrogen peroxide impingers, and elemental mercury is collected in thepotassium permanganate/sulfuric acid impingers. The details of the most recent mercury testresults at the Maine Energy facility are given in Table 2.1, with the mercury speciation fractionsassumed for stack emissions in the multi-pathway risk assessment modeling summarized in thefinal column.

Although there are uncertainties in the use of these test results to model mercury speciation inthe Maine Energy stack emissions, the speciation values shown in Table 2.1 and used in the riskassessment are more likely to overestimate rather than underestimate the mercury impacts. Theform that was found to comprise that majority of the emissions, Hg2+ vapor, is also the form thatis deposited most rapidly from the atmosphere. Further, if it were assumed that the amount of mercury in the catches where none was detected was equal to the detection limit (rather than atone-half the detection limit as assumed in Table 2.1), then the fraction of assumed vapor-phaseelemental mercury, which has very little impact on modeled health effects, would increase. Therefore any changes in the assumed distribution would likely decrease the estimated mercuryimpacts of the Maine Energy facility’s emissions, and so the modeled mercury speciation likelyprovides a conservative estimate of potential mercury related health risks.


2–16

It should also be noted that the fraction of mercury assumed in divalent vapor form (77%)exceeds the value of the HHRAP default value (60%) suggested for municipal solid wastecombustors. Adopting the speciation estimates based on facility-specific sampling thus results ina larger estimated fraction of mercury emissions from the Maine energy facility depositing in thelocal Biddeford/Saco vicinity.

Table 2.1 Results of the August 2004 mercury stack concentration tests at the Maine EnergyFacility. The catch is the amount of mercury measured in each stage of EPAReference Method 29 that is analyzed for mercury. The overall mercuryspeciation fractions shown in the last column are based on catches with nodetected mercury having mercury present at one-half the detection limit.

Sample Assumed Hgspecies

Catch (:g) % of total Hg

test 1 test 2 test 3Probe rinse and filter Hg2+ Particulate 0.19 0.29 0.286 15%HNO3/H2O2 impinger Hg2+ Vapor 1.26 1.37 1.25

77%Empty impinger (between HNO3 and MnO4 impinger) Hg2+ Vapor <0.02 <0.02 <0.02

KMnO4/H2SO4 impinger Hg0 Vapor <0.1 <0.1 <0.18%HCl rinse of KMnO4/H2SO4 Hg0 Vapor 0.26 <0.1 <0.1


2–17

Figure 2.2 EPA Reference Method 29 sampling train for the collection of metals emissionsfrom stationary sources. Mercury speciation may be assessed through theseparate analysis of the glass fiber filter (particulate bound mercury species), thenitric acid/peroxide impinger solutions (vapor-phase ionic mercury species), andthe permanganate/sulfuric acid impinger (vapor-phase elemental mercury).

The HHRAP (in Figure 2-4 of the guidance) recommends adjusting the emission rates of thethree types of mercury emissions to account for the fraction of each form that is likely to bedeposited locally vs. entering the global mercury cycle. The recommendation is to multiply theelemental mercury emission rate by a factor of 0.01, the vapor-phase mercuric chloride emissionrate by a factor of 0.68, and the particulate-phase mercuric chloride emission rate by a factor of0.36. As discussed in the Maine Energy RAP, these adjustment factors are based on regionalrather than local-scale modeling of mercury deposition, and therefore they are not used in themulti-pathway modeling of mercury emissions from the Maine Energy facility.

Tables 2.2 and 2.3 contain the COPC emission rates (respectively for the boiler stack andscrubber stacks) used in the risk assessment modeling calculations. These emission rates arebased on the procedures described above and the data contained in Appendix III. The columnslabeled ‘data source’ contain information on whether the emission rates are based on directCOPC concentration measurements in the relevant exhaust gas or on measurements in a differentmedium.


2–18

2.3.7 Summary of COPC emission rates used in Maine Energy RiskAssessment modeling

Table 2.2 Emission rates of COPCs from the Maine Energy facility stack used in the riskassessment modeling. Data source entries indicate: 2002: 2002 Air ToxicsReport; 2003, and 2004: indicates additional stack gas testing data in those yearswas also used; DRE: rates based on scrubber inlet concentrations and 99.9%COPC destruction and removal by combustion and control systems. * Emissionrate estimates for mercury species and hexavalent chromium include additionalcalculation described above. Upset condition emission rates are used inconjunction with dispersion models at both typical stack flowrates (referred to as“normal upsets”), and startup/shutdown condition, low stack flowrates (referredto as “startup upsets”).

COPC emitted from Maine Energy stack data sourceAverage emissionrates (g/s)

Maximum emissionrates (g/s)

Upsetcondition emissionrates (g/s)

MetalsArsenic 2002, 2003 1.50E-05 2.30E-05 1.38E-04Beryllium 2002 1.87E-06 1.93E-06 1.16E-05Cadmium 2002, 2003, 2004 3.03E-05 1.06E-04 6.34E-04Chromium (total) 2002, 2003 1.14E-04 1.92E-04 1.15E-03Chromium (hexavalent)* 2002, 2003 2.27E-06 9.59E-06 5.75E-05Copper 2002 3.74E-04 4.98E-04 2.99E-03Lead 2002, 2003, 2004 8.08E-04 3.24E-03 1.95E-02Mercury (elemental)* 2002, 2003, 2004 1.02E-05 1.61E-05 1.61E-05Mercuric chloride (vapor)* 2002, 2003, 2004 6.56E-05 1.04E-04 1.04E-04Mercuric chloride (particle)* 2002, 2003, 2004 1.29E-05 2.03E-05 1.22E-04Nickel 2002, 2003 1.51E-04 2.97E-04 1.78E-03Selenium 2002 2.18E-05 2.77E-05 1.66E-04Silver 2002 7.76E-06 9.46E-06 5.68E-05Tin 2002 4.18E-04 4.44E-04 2.66E-03Vanadium 2002 1.27E-05 1.46E-05 8.75E-05Zinc 2002 2.88E-03 5.24E-03 3.15E-02

Hydrogen chloride 2002, 2003, 2004 2.71E-01 3.19E-01 7.97E-01Volatile organic compounds (VOCs)acetone 2002 1.15E-02 1.54E-02 4.46E-02benzene 2002 7.91E-03 2.67E-02 7.73E-02benzoic acid 2002 7.38E-04 1.27E-03 3.69E-03benzyl alcohol 2002 8.77E-05 1.42E-04 4.13E-04bis(2-ethylhexyl)phthalate 2002 7.07E-04 2.57E-03 7.45E-03bromomethane DRE 5.36E-04 1.64E-03 4.75E-03butanol, – 2002 4.10E-02 8.60E-02 6.48E-03butanone, 2- (methyl ehyl ketone) 2002 7.35E-04 1.08E-03 3.12E-03carbon disulfide 2002 1.31E-03 2.10E-03 6.10E-03chloroform 2002 1.50E-04 2.54E-04 7.37E-04chloromethane 2002 1.28E-03 4.74E-03 1.37E-02cyclohexane DRE 5.73E-08 6.54E-08 4.92E-09di-n-butylphthalate 2002 2.25E-05 2.99E-05 8.66E-05

COPC emitted from Maine Energy stack data sourceAverage emissionrates (g/s)

Maximum emissionrates (g/s)

Upsetcondition emissionrates (g/s)


2–19

dichlorobenzene, 1,2- DRE 4.53E-08 5.71E-08 4.30E-09dichlorobenzene, 1,3- DRE 4.53E-08 5.71E-08 4.30E-09dichlorobenzene, 1,4- DRE 9.53E-08 1.14E-07 8.60E-09diethyl phthalate 2002 2.32E-05 3.28E-05 9.50E-05ethanol DRE 4.02E-05 5.10E-05 3.84E-06ethylbenzene DRE 8.98E-08 1.30E-07 9.79E-09freon 11 DRE 8.98E-08 1.30E-07 9.79E-09freon 12 DRE 9.97E-08 1.50E-07 1.13E-08heptane DRE 8.95E-08 1.60E-07 1.20E-08hexane DRE 9.75E-08 1.40E-07 1.05E-08methane DRE 9.18E-04 1.31E-03 9.83E-05methanol DRE 5.83E-03 1.08E-02 8.13E-04methylene chloride 2002 3.09E-03 4.41E-03 1.28E-02methylnapthalene, 2- 2002 5.81E-05 9.06E-05 2.63E-04methylphenol, 2- 2002 1.55E-04 5.22E-04 1.51E-03methylphenol, 3 2002 5.65E-05 1.30E-04 3.78E-04methylphenol, 4 2002 5.65E-05 1.30E-04 3.78E-04naphthalene 2002 8.80E-05 1.99E-04 5.77E-04phenol 2002 9.00E-04 3.46E-03 1.00E-02propane DRE 2.05E-03 7.53E-03 5.67E-04propanol, 2- DRE 5.60E-07 7.80E-07 5.87E-08styrene 2002 3.54E-04 5.64E-04 1.64E-03tetrachloroethene 2002 3.93E-04 6.15E-04 1.78E-03toluene 2002 3.41E-03 4.21E-03 1.22E-02trichloroethane, 1,1,1- DRE 9.10E-08 1.10E-07 8.28E-09trimethylbenzene, 1,2,4- DRE 9.03E-08 1.20E-07 9.03E-09vinyl chloride 2002 3.68E-04 6.67E-04 1.93E-03xylene, m- 2002 1.50E-04 2.54E-04 7.37E-04xylene, o- 2002 1.50E-04 2.54E-04 7.37E-04xylene, p- 2002 1.50E-04 2.54E-04 7.37E-04Polychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 2002, 2004 2.07E-10 3.27E-10 1.00E-091,2,3,7,8-PCDD 2002, 2004 5.71E-10 1.10E-09 5.17E-091,2,3,4,7,8-HxCDD 2002, 2004 4.99E-10 1.09E-09 6.16E-091,2,3,6,7,8-HxCDD 2002, 2004 6.49E-10 1.12E-09 6.52E-091,2,3,7,8,9-HxCDD 2002, 2004 9.14E-10 1.83E-09 1.08E-081,2,3,4,6,7,8-HpCDD 2002, 2004 4.17E-09 7.76E-09 4.58E-08OCDD 2002, 2004 6.18E-09 1.39E-08 8.32E-082,3,7,8-TCDF 2002, 2004 1.45E-09 2.38E-09 4.80E-091,2,3,7,8-PCDF 2002, 2004 1.36E-09 2.34E-09 8.92E-092,3,4,7,8-PCDF 2002, 2004 1.62E-09 2.57E-09 1.14E-081,2,3,4,7,8-HxCDF 2002, 2004 3.18E-09 5.42E-09 3.09E-081,2,3,6,7,8-HxCDF 2002, 2004 1.62E-09 2.83E-09 1.61E-082,3,4,6,7,8-HxCDF 2002, 2004 1.53E-09 2.56E-09 1.45E-081,2,3,7,8,9-HxCDF 2002, 2004 1.49E-10 2.95E-10 1.67E-091,2,3,4,6,7,8-HpCDF 2002, 2004 4.21E-09 6.92E-09 4.01E-081,2,3,4,7,8,9-HpCDF 2002, 2004 5.10E-10 9.36E-10 5.50E-09OCDF 2002, 2004 1.66E-09 3.62E-09 2.17E-08Polychlorinated biphenyls (PCBs, as Aroclor 1248) 2002 4.08E-07 6.64E-07 1.93E-06


2–20

Table 2.3 Emission rates of COPCs from the Maine Energy facility odor scrubber systemused in the risk assessment modeling. Data source entries indicate: ash: ratesbased on fugitive ash emission estimates and measured ash composition;scrubber: rates based on individual scrubber outlet concentrations and flow rates;tipping: rates based on tipping floor concentrations and total scrubber flow rates. * Emission rate estimates for beryllium and tin are extrapolated as describedabove.

COPC emitted from Maine Energy odorscrubber system data source

Averageemission rates

(g/s)

Maximumemission rates

(g/s)MetalsArsenic ash 8.26E-07 1.45E-06Beryllium ash* 3.04E-08 9.35E-08Cadmium ash 8.17E-07 1.87E-06Chromium (total) ash 1.85E-06 9.29E-06Chromium (hexavalent) ash 2.05E-08 2.93E-08Copper ash 4.35E-05 4.52E-05Lead ash 3.47E-05 7.11E-05Mercuric chloride (particle) ash 1.43E-07 2.64E-07Nickel ash 2.66E-06 4.48E-06Selenium ash 3.35E-08 7.40E-08Silver ash 2.28E-07 3.25E-07Tin ash* 1.79E-05 9.73E-06Vanadium ash 7.99E-07 1.86E-06Zinc ash 9.18E-05 1.87E-04Volatile organic compounds (VOCs)acetone scrubber 7.45E-02 9.71E-02benzene scrubber 4.26E-03 5.28E-03bromomethane scrubber 2.59E-03 3.21E-03butanol, – tipping 3.69E+00 8.20E+00carbon disulfide scrubber 8.43E-03 1.03E-02chloroform scrubber 3.26E-03 4.03E-03chloromethane scrubber 5.59E-03 6.85E-03cyclohexane scrubber 5.76E-03 8.15E-03dichlorobenzene, 1,2- scrubber 4.01E-03 4.96E-03dichlorobenzene, 1,3- scrubber 4.01E-03 4.96E-03dichlorobenzene, 1,4- scrubber 8.50E-03 1.09E-02ethanol scrubber 3.90E+00 4.70E+00ethylbenzene scrubber 8.29E-03 1.02E-02freon 11 scrubber 7.68E-03 9.67E-03freon 12 scrubber 8.70E-03 1.06E-02heptane scrubber 8.41E-03 9.91E-03hexane scrubber 8.57E-03 9.73E-03

COPC emitted from Maine Energy odorscrubber system data source

Averageemission rates

(g/s)

Maximumemission rates

(g/s)


2–21

methane tipping 8.25E-02 1.24E-01methanol tipping 5.24E-01 1.03E+00methylene chloride scrubber 7.82E-03 1.12E-02propane tipping 1.85E-01 7.18E-01propanol, 2- scrubber 5.56E-02 7.18E-02styrene scrubber 9.03E-03 1.15E-02tetrachloroethene scrubber 9.33E-03 1.18E-02toluene scrubber 3.34E-02 4.00E-02trichloroethane, 1,1,1- scrubber 7.75E-03 9.69E-03trimethylbenzene, 1,2,4- scrubber 8.35E-03 9.95E-03vinyl chloride scrubber 1.71E-03 2.11E-03xylene, m- scrubber 1.17E-02 1.62E-02xylene, o- scrubber 7.66E-03 9.92E-03xylene, p- scrubber 1.17E-02 1.62E-02Polychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD ash 1.79E-12 8.66E-121,2,3,7,8-PCDD ash 1.01E-11 8.13E-111,2,3,4,7,8-HxCDD ash 2.64E-12 1.34E-111,2,3,6,7,8-HxCDD ash 3.79E-12 1.65E-111,2,3,7,8,9-HxCDD ash 3.74E-12 1.95E-111,2,3,4,6,7,8-HpCDD ash 2.23E-11 8.39E-11OCDD ash 4.18E-11 1.48E-102,3,7,8-TCDF ash 1.00E-11 5.24E-111,2,3,7,8-PCDF ash 1.37E-11 7.01E-112,3,4,7,8-PCDF ash 1.40E-11 6.66E-111,2,3,4,7,8-HxCDF ash 1.16E-11 6.15E-111,2,3,6,7,8-HxCDF ash 1.41E-11 6.41E-112,3,4,6,7,8-HxCDF ash 1.13E-11 5.24E-111,2,3,7,8,9-HxCDF ash 2.89E-12 1.19E-111,2,3,4,6,7,8-HpCDF ash 2.82E-11 1.16E-101,2,3,4,7,8,9-HpCDF ash 3.61E-12 1.42E-11OCDF ash 1.04E-11 3.48E-11


2–22

1 10 100 1000 10000

Arsenic

Cadmium

Chromium

Lead

Mercury

Nickel

PCDD/PCDF pgTEQ

Log ug/s emission rate

200420032002

2.3.8 Recent variations and long-term trends in COPC emissions

As mentioned above, some of the COPCs evaluated in this risk assessment were measuredduring several stack testing programs, and were also evaluated as part of the 1996 riskassessment. Figure 2.3 show a comparison the COPC emission rates of those compounds forwhich test data are available from several recent years. A significant degree of variation(roughlyan order of magnitude) is seen for the COPCs lead and cadmium, which elements show a similarpattern of emission rates. Emission rates for other COPCs vary by about a factor of 3 or lessamong the recent measurements. The use of maximum measured emission rates in the short-term risk assessment calculations accounts for the variability in short-term rates as seen in theshort-duration measurements, and the potential for short duration emission rates to besignificantly higher than estimated long-term averages. The use of maximum measured emissionrates in the sensitivity analysis of the long-term, multi-pathway risk estimates provides a meansof evaluating the effects of using short-duration measurements to estimate long-term emissionrates.

Figure 2.3 Emission rates of COPCs measured during several recent stack testing programs. So that all of the COPCs may be shown on the same figure, rates are shown aslog10 of the :g/s emission rates except for PCDD/PCDFs which are shown aslog10 of the pg TEQ/s.

Figure 2.4 compares the emission rates used in the updated health risk assessment to the valuesused in the 1996 health risk assessment for the Maine Energy facility. Only a small fraction of


2–23

Emission Rate Comparison

2005 Update v. 1996 Risk Assessment2005 Percentages of 1996 Values

0% 20% 40% 60% 80% 100%

Arsenic

Beryllium

Cadmium

Chromium

Lead

Mercury

Nickel

2,3,7,8-TCDD TEQs

the COPCs considered in the 2005 risk assessment update appear in Figure 2.4 because the 1996risk assessment included a limited number of COPCs. Each bar in Figure 2.4 represents the ratioof the 2005 emission rate divided by the 1996 emission rate, expressed as percentage values. Allof the emission rates used in the 2005 health risk assessment update, which reflect the mostrecent stack test data, are lower than those used in the 1996 health risk assessment. For example,the 2005 emission rate for arsenic is about 37% as large as the value used in the 1996 riskassessment. The decreases in emission rates of COPCs from 1996 to 2005 are likely caused bytwo factors:

• emissions of most COPCs have likely decreased with time, especially with respect to datataken during the early operating history of the facility (the late 1980s) that were averagedinto the 1996 emission rates;

• analytical methods have improved over time that make it possible to detect some COPCs(or achieve lower detection limits) in recent tests that had not been detected in previousstack emission tests.

Figure 2.4 Comparison of emission rates used in this 2005 risk assessment update toemission rates used in the 1996 health risk assessment for the Maine Energyfacility. Plotted values are the 2005 emission rates divided by the 1996 emissionrates.

1 Although the dispersion algorithms of AERMOD have been reviewed and were recentlypromulgated as the U.S. EPA’s preferred air dispersion model, the deposition algorithms areincluded in a version that is currently available only as a beta-test version.(http://www.epa.gov/ttn/scram/dispersion_prefrec.htm#aermod last accessed December 13,2005).


3–1

3 Air dispersion and deposition modelingThe 1996 health risk assessment is based on a detailed atmospheric dispersion and depositionmodel for emissions from the Maine Energy facility using the U.S. EPA’s Industrial SourceComplex – Short-Term (ISCST3) model. Two aspects of the 1996 modeling study, however, areinadequate to meet the needs of this updated health risk assessment. First, the 1996 modelingstudy does not include an evaluation of emissions from the odor scrubbing systems. Second, ananalysis of wet deposition (pollutant washout from the air through rain and snow fall) was notincluded in the 1996 study.

Since the ISCST3 model is still approved by the U.S. EPA for refined modeling applications,and it is also the model recommended in the HHRAP, the 1996 modeling analysis could beextended to meet the needs of the updated risk assessment. However newer dispersion modelsare emerging that are based on improved scientific knowledge. In particular, the AMS/EPARegulatory Model – AERMOD – has been issued (U.S. EPA, 2002a). AERMOD has replacedISCST3 as the preferred general purpose dispersion model. Developed in a collaborative effortby the American Meteorological Society and the U.S. EPA, AERMOD incorporates a greatlyimproved model of dispersion due to atmospheric turbulence, and also includes the improvedPRIME algorithms for simulating the aerodynamic effects of buildings on near-field plumedispersion. AERMOD has recently been used at the Maine Energy facility to investigate theimproved dispersion characteristics that would occur from raising the height of the stack vents ofthe odor scrubbing system. Most recently, dry and wet deposition algorithms have been added toa “beta” trial version of AERMOD, enabling its use in multi-pathway risk assessments.

Since AERMOD requires inputs similar to those of the ISCST3 model, much of the informationfrom the 1996 modeling study was transferred and adapted. AERMOD was initially used tomodel the dispersion of emissions from the entire Maine Energy facility. However, in reviewingthe preliminary modeling results, a serious flaw was identified in the deposition algorithms builtinto the beta-test version of AERMOD.1 Specifically, the full method for modeling drydeposition in the beta-test version of AERMOD is technically incorrect. Dry deposition iscalculated as the product of a compound’s concentration in air (in units of e.g., :g/m3) and itsdry deposition velocity (in units of e.g., m/s), yielding a deposition flux (here in units of :g/m2-s). For the estimation of dry deposition to be valid, the compound’s concentration and its


3–2

deposition velocity must be evaluated at the same height above the ground. This requirement isnotable because the dry deposition of a compound from a plume does not cause a uniformdepletion of the compound’s concentration throughout the plume (which depletion is a functionof distance from the source, but not height), but rather favors depletion of the plume near thesurface where deposition occurs, causing a preferential near-surface change in the vertical profileof the compound’s concentration (which depletion is a function of distance from the source andheight). This height-dependent concentration profile is modeled in ISC using a profile correctionfactor, an example of which is shown in Figure 3.1 (a reproduction of Figures 1-6 and 1-7 ofVolume II of the ISCST3 Model User’s Guide, U.S. EPA, 1995).

When the dry deposition algorithms developed for ISCST3 were added to AERMOD (beta-testversion 04079), the methods for calculating dry deposition velocities were added to AERMOD,but the profile correction factor of the dry depletion algorithms was not added (the depletionalgorithms are separate from the deposition algorithms). Thus, the dry depletion calculationsperformed in AERMOD incorrectly account for a uniform depletion throughout the plume , rather than a change in the plume’s vertical profile emphasizing near-surface deposition. Whilethis uniform depletion approximation is appropriate for estimating wet deposition, sincecontaminants are removed by precipitation throughout the entire vertical extent of a plume,depletion by dry deposition must preferentially consider the portion of the plume closest to theground where the deposition (removal) occurs. The difference is illustrated in the left-hand plotin Figure 3.1 (a reproduction of Figure 1-6 of the ISCST3 Model User’s Guide). The curvelabeled “depletion factor” is used by ISCST3 to estimate the fraction of the plume remainingaloft (i.e., that has not been deposited), which is calculated by integrating deposition along theplume travel path from the source. However, rather than applying the “depletion factor”uniformly through the plume (as suggested by the straight vertical line), ISCST3 redistributes thedepleted portion of the plume using a “profile correction” factor, as indicated in the figure.

By not considering the “profile correction” factor in its dry depletion algorithms, AERMODincorrectly matches the dry deposition velocity algorithm (developed for ISC) withconcentrations that are over-estimated for the height at which the deposition velocities arecomputed. AERMOD therefore incorrectly over-predicts dry deposition fluxes. Because COPCdeposition is a significant factor in the multi-pathway risk assessment, the decision was made torevert to the ISCST3 model to assess the dispersion and deposition of stack emissions. AERMOD was retained to model the dispersion of emissions from the odor treatment system forthe following reasons:


3–3

FIGURE 1-6. ILLUSTRATION OF THE DEPLETION FACTOR FQ AND THECORRESPONDING PROFILE CORRECTION FACTOR P(x,z).

FIGURE 1-6. ILLUSTRATION OF THE DEPLETION FACTOR FQ AND THECORRESPONDING PROFILE CORRECTION FACTOR P(x,z).

FIGURE 1-7. VERTICAL PROFILE OF CONCENTRATION BEFORE ANDAFTER APPLYING FQ AND P(x,z) SHOWN IN FIGURE 1-6.

FIGURE 1-7. VERTICAL PROFILE OF CONCENTRATION BEFORE ANDAFTER APPLYING FQ AND P(x,z) SHOWN IN FIGURE 1-6.

Figure 3.1 Figures 1-6 and 1-7 of Volume II of the ISCST3 model’s user guide (U.S. EPA, 1995). The figures show the verticalprofile of the depletion correction and resulting concentration as applied in ISCST3 for Fz equal to 1.5 times the plumeheight.

2 Note that boiler stack emissions are not subject to building downwash as the stack heightmeets the Good Engineering Practice height criterion. Thus, the advanced building downwashalgorithms incorporated in AERMOD offer no advantage to the boiler stack evaluation.


3–4

• deposition is not a significant concern for most of the COPCs released from the odortreatment system;

• the PRIME algorithms included in AERMOD to assess the effects of building downwashon plume dispersion are believed to be significantly advanced over the algorithms inISCST3;2 and

• previous modeling conducted for the odor treatment system already utilizes AERMOD.

The specific version of AERMOD used for the modeling of odor control system emissions is#04079, with the preprocessor programs AERMET version #03273, and AERMAP version#03107. These versions of AERMOD and AERMET are the most recently available whichenable the modeling of wet deposition, and the most recent version of AERMAP. The mostrecent version of ISCST3, #02035, was used for the modeling of boiler stack emissions.

3.1 Background and general air modeling description

Air dispersion modeling requires a substantial amount of input data, and preliminary plans anddescriptions of the modeling study are detailed in subsequent sections. Table 3.1 lists theprincipal source parameter values which are used to model the dispersion of pollutant emissionsfrom the Maine Energy facility emission sources. The parameters for the boiler stack are thoseused in the 1996 risk assessment of the Maine Energy facility (Cambridge Environmental, 1996),which parameters were based on modeling and testing performed on the facility prior to 1996(Earth Tech, 1995; Entropy, 1992, 1994).

Table 3.1 also provides model parameters for the stacks of the odor scrubbing system, which arederived from documents related to the odor scrubbing system. These parameters are based on ananalysis of the odor scrubbing system conducted for the Maine Energy facility to evaluate theconsequences of increasing the height of the odor scrubbing system stacks (TRC, 2003); the summary report of this work is attached as Appendix VII of the risk assessment. As constructed,the stack vents for the odor scrubbing system are not tall enough to avoid the potential influenceof aerodynamic plume downwash by the boiler building. Consequently, the U.S. EPA’sBuilding Profile Input Processor for Prime (BPIPPRM) program was used to determinedirection-specific building dimensions based on final engineering drawings of the Maine Energyfacility.


3–5

Table 3.1 Primary source parameters for atmospheric dispersion modeling

ParameterValue(s)

Boiler Stack Odor Scrubbing SystemStacks (3)

Stack-base elevation(above mean sea level) 18.3 m 17.98 m

Stack height 74.4 m 36.6 m

Stack inner (flue) diameter 1.98 m 1.83 m

Stack-gas temperature 295 °F 110 °F

Stack-gas velocity 21.4 m/s 14.3 m/s

Downwash potential? No Yes

3.2 General modeling options

The ISCST3 and AERMOD model simulations are based on default regulatory modelingrecommendations. Land use is assumed to be rural, based on consideration of the characteristicsof the area. Figure 3.2 depicts a circle of 3 km radius superimposed on topographic maps. Thecircle is centered at the location of the Maine Energy facility’s main boiler stack. Auer’s (1978)method, as described in U.S. EPA (1996), suggests the designation rural land use. The pink-shaded areas, indicative of urban development in the cities of Biddeford and Saco, cover lessthan one-half of the area of the 3-km radius circle. Strictly, the urban designation as describedby Auer (1978) demands dense urban development with housing lacking significant yard anddriveway space. Consequently, the urban fraction of land around the Maine Energy facility iseven smaller than that suggested by the pink-shaded regions in Figure 3.2. Since less than halfof the 3-km radius is urban, modeling based on rural land use is appropriate.

Since multiple compounds of potential concern are considered, modeling files are based onnominal emission rates, and the results are scaled according the COPC-specific emission rates. For example, a boiler stack emission rate of 1 g/s is assumed in each of the ISCST3 model runs. For COPCs emitted at 0.3 g/s and 0.06 g/s, respectively, the results of the model runs at thenominal emission rate of 1 g/s are multiplied by 0.3 (0.3 g/s ÷ 1 g/s = 0.3) and 0.06 (0.06 g/s ÷ 1g/s = 0.06).

Both the ISCST3 and AERMOD models are used to model COPC concentrations over threedifferent time periods to evaluate the risk assessment endpoints outlined in the HHRAP and toprovide estimates comparable to the ambient air quality standards established by the City ofBiddeford’s Air Toxics Ordinance. Short-term 1-hour average predictions are developed for the


3–6

assessment of upset conditions, and 24-hour average predictions are modeled to evaluate theshort-term standards of Air Toxics Ordinance. Long-term (multi-year) predictions are developedto evaluate potential chronic health risks and to compare with the long-term standards of AirToxics Ordinance.

3.3 Receptor locations

The receptor locations used in the 1996 dispersion modeling analysis were used in both theupdated ISCST3 and AERMOD simulations. A standard polar receptor grid was used toexamine potential impacts over the area within a 15-km radius of the Maine Energy facility. Atotal of 46 receptor rings (of constant radius) consisting of 36 receptors each spaced at 10 degreeintervals were used. The receptor rings are centered at the boiler stack location. The networkconsist of radii (rings) of 50 m, 100–2500 m at increments of 100 m, 2,750–5,000 m atincrements of 250 m, and 6–15 km at increments of 1 km. The locations of the 1,656 receptorsare indicated on Figures 3.3 to 3.5, which depict the modeling grid superimposed on topographicmap images. Figure 3.3 depicts the full modeling grid out to its 15 km (radius) extent, whileFigures 3.4 and 3.5 provide more detailed views of the region closer to the Maine Energy facilitywhere receptor locations are more closely spaced. To verify that the maximum COPC impactsare properly identified at locations relatively far from the facility (where the receptors are spacedfurther apart), a sensitivity analysis was performed using a refined grid around the maximum far-field impact location. The results of this sensitivity analysis are described in Section 8.2.3.

Ground-level elevations of all receptor locations were determined with the AERMAP program (apreprocessor to AERMOD) obtained from topographic maps. AERMAP uses Digital ElevationModel (DEM) files for gridded topographic elevations developed by the U.S. Geological Survey. Consistent with the available configuration of AERMAP, 30-m resolution DEM files were used. The “HILL” receptor input information provided by AERMAP, which is used only byAERMOD, was excluded from the ISCST3 model input files.


3–7

Figure 3.2 Tiled topographic map images of the model study area (Maine GIS quadrangles). The red circle is 3 km in radius from the Maine Energy facility (boiler stack), andencircles the urbanized areas of Biddeford and Saco (indicated in pink).


3–8

Figure 3.3 Tiled topographic map images of the model study area (Maine GIS quadrangles) overlain with the dispersion modelgrid. Receptor locations are located at the intersections of the black circles and lines. The outer circle is 15 km inradius from the Maine Energy facility (boiler stack).


3–9

Figure 3.4 Tiled topographic map images of the inner model study area (Maine GIS quadrangles) overlain with the dispersionmodel grid. Receptor locations are located at the intersections of the black circles and lines. The dense inner modeling(100 m spacing) grid extends to a radius of 2.5 km from the Maine Energy facility (boiler stack).


3–10

Figure 3.5 Tiled topographic map images of the inner model study area (Maine GIS quadrangles) overlain with the dispersionmodel grid. Receptor locations are located at the intersections of the black circles and lines. Figure depicts the receptorlocations in the immediate vicinity of the Maine Energy facility, starting at 50 m and 100 m distances (inner twocircles), and proceeding outward at 100 m increments along each of the 36 radials (spaced at 10° increments).

3 The 1996 air modeling study was based on meteorological data over a 1987 to 1991 period. The fact that the modeling in this report employs data from 1986 to 1990 is unlikely to lead to significantly different results on its own, as meteorological data averaged over multiple yearsremain similar.


3–11

3.4 Meteorological data processing

Similar to the 1996 modeling study, meteorological data for the updated modeling study of boilerstack emissions were obtained from the SCRAM Bulletin Board maintained by the U.S. EPA'sOffice of Air Quality Planning and Standards (U.S. EPA, 2004). On-site meteorological data arenot available for the facility, so it is not possible to directly evaluate the representativeness of thePortland Jetport data. From a geographic perspective, we feel that the Portland Jetport data arelikely representative of conditions in Biddeford and Saco because both locations are locatedquite close to the coastline, which at both locations is oriented from the southwest to thenortheast. The sensitivity of the modeling to the selection of this meteorological data isdiscussed in Section 8.2. Data were downloaded for the weather station operated by the NationalWeather Service at the Portland International Jetport. Surface observations at Portland arecollected at a 20 ft (6.1 m) anemometer height. Upper air data are also collected at the PortlandJetport location. A continuous five-year period from 1986 to 1990 was used based oncoincidentally available data for both surface and upper air (mixing height) observations.3 Thepurpose of using a five-year modeling period is to cover the range of meteorological conditionslikely to occur over time. Figure 3.6 depicts a wind rose of nine years of meteorological data(1984 to 1992), and the pattern of observations is quite similar to that of the analogous wind rosedepicted in Figure A.3 of the 1996 risk assessment report (Cambridge Environmental, 1996). The greatest frequency of winds originate from the south (slightly more than 10%), and windswith westerly components are significantly more frequent than winds with easterly components. The bulk of wind speeds range between 4 and 17 knots.

Hourly precipitation data for the same period and site were extracted from a surface observationdatabase compiled by the U.S. Department of Commerce (NCDC, 1993), as these data are notincluded in the SCRAM files. The AERMET processor was used to integrate the meteorologicaldata files into a format amenable to AERMOD using surface data files in SAMSON format, andupper air data in TD6201-VB format. For the ISCST3 dispersion modeling the meteorologicaldata files were processed with the U.S. EPA’s PCRAMMET program.

Both the PCRAMMET and AERMET programs also require information on local land use todevelop meteorological parameters for deposition modeling. Specifically, values of the surfacealbedo, Bowen ratio (a measure of soil moisture), and surface roughness length are required. The PCRAMMET program requires typical values for these parameters averaged over themodeling domain and seasons, while the AERMET program differentiates values by seasons,directions from the facility location, and land use.


3–12

Figure 3.6 Wind rose observations collected at the Portland Jetport from 1984 through 1992.


3–13

The Maine GIS provides land use information in its GOMLC7 data layer, which wasdownloaded and processed to provide a breakdown of the various types of land uses in thevicinity of the Maine Energy facility. Figure 3.7 depicts the land use patterns in theBiddeford/Saco area. Different colors correspond to different land uses according to the legend. The location of the Maine Energy facility is at the center of the 3 km radius circle superimposed on Figure 3.7. Table 3.2 provides a breakdown of the percentages of land uses in pie-shapedsectors originating from the Maine Energy facility out to a distance of 3 km. The percentagevalues are based on pixel counts of the various color-coded land uses from the GIS land useimage. The overall distribution of land use in the 3 km radius region is depicted in Figure 3.8.About half of the land within 3 km of the Maine Energy facility is either developed or grassland,a little more than a quarter is forested, and the remainder is split among various other uses.

The AERMET documentation recommends values of meteorological/deposition parameters forvarious land use categories, and the appropriate values are provided for each land usedesignation in Table 3.3. These recommendations are contained in Tables 4-1 to 4-3 in theAERMET User's Guide and its Addendum (U.S. EPA, 1998b and U.S. EPA, 2002b,c). Valuesare provided seasonally and, when combined with the percentages of land use in each sector(direction) from the Maine Energy facility, yield the seasonally- and spatially- averaged valueslisted in Table 3.3. These values are used in the AERMET processing of meteorological data,with the assumption that the four principal seasons cover the following months:

Winter: December, January, February, and MarchSpring: April, May, and JuneSummer: July and AugustAutumn: September, October, and November

As stated above, the PCRAMMET model uses single values for the deposition parameters inprocessing meteorological data. Values of 0.22 for the surface albedo, 1.1 for the Bowen ratio,and 0.66 m for the surface roughness length were used, constructed as averages of the values inTable 3.3. In addition, two additional PCRAMMET deposition-related parameters, theanthropogenic heat flux and net radiation of radiation absorbed by the ground, were assignedvalues of 10 W/m2 and 0.2, respectively, based on recommendations in the PCRAMMETdocumentation and professional judgement.

The specific land use parameters for the meteorological data processing in Table 3.4 are weighted averages calculated across different land use categories using (1) the distribution oflocal land uses in a given sector/season (Table 3.2), and (2) values for the surface albedo, Bowenratio, and surface roughness length as a function of land use and season (Table 3.3). Thefollowing example demonstrates the calculation of a weighted average value. The surfacealbedo parameter for the autumn season for the 90 to 120 degree land sector is listed as 0.161 inTable 3.4 (fourth column, third data row). This value is calculated by taking the land-usespecific surface albedo values in Table 3.3 for autumn (third data column) and multiplying eachvalue by the percentage of land use designations within the 90 to 120 degree sector in Table 3.2(fourth data column). This calculation is written out in full below Table 3.4.


3–14

Figure 3.7 Land use characteristics in the vicinity of the Maine Energy facility. Thered-outlined circular area is 3 km in radius, centered at the Maine Energyfacility’s boiler stack. The twelve pie slices correspond to the land usesectors used in AERMET meteorological/deposition parameter processing. Land use data from the Maine GIS’s GOMLC7 data layer, with color-coded designations indicated in the legend to the right.


3–15

Table3.2 Land use categories within 3 km of the Maine Energy facility (Maine GIS data)

Land use designationPercentage of land within sector range (degrees clockwise from north)

0 to 30 30 to 60 60 to 90 90 to120

120 to150

150 to180

180 to210

210 to240

240 to270

270 to300

300 to330

330 to360

Upland deciduous forest 6.3% 11.6% 6.0% 9.3% 12.9% 23.9% 8.0% 4.4% 17.1% 8.6% 15.2% 8.9%Grassland 22.1% 24.8% 13.5% 12.3% 7.6% 1.3% 11.9% 15.9% 12.3% 23.2% 19.1% 20.5%Upland scrub/shrub 10.0% 6.1% 9.1% 11.2% 4.4% 4.5% 6.0% 3.6% 7.4% 7.8% 11.8% 8.0%Riperian perennial stream 0.9% 0.8% 0.9% 0.2% 0.2% 0.2% 0.0% 0.0% 0.0% 17.7% 2.0% 1.1%Fresh marsh 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.6% 0.0% 0.6%Coniferous swamp 0.3% 0.0% 1.4% 6.5% 0.1% 0.0% 1.7% 0.5% 0.0% 0.0% 0.0% 0.0%Cultivated 0.0% 0.1% 0.1% 0.2% 0.1% 0.0% 0.0% 0.0% 0.0% 0.3% 0.1% 0.0%Upland mixed forest 13.2% 10.6% 17.7% 16.8% 22.4% 39.9% 13.8% 3.3% 15.9% 10.6% 24.4% 16.6%Deciduous shrub swamp 0.2% 0.3% 0.7% 0.3% 1.4% 0.5% 0.1% 0.0% 1.2% 0.2% 1.6% 1.2%Upland coniferous forest 6.9% 0.6% 4.4% 2.3% 3.4% 2.7% 0.6% 0.2% 1.0% 2.7% 5.5% 0.3%Deciduous swamp 1.5% 0.5% 1.2% 0.3% 1.9% 10.5% 0.8% 0.3% 0.8% 7.2% 3.7% 2.1%Developed 38.4% 44.2% 44.7% 16.9% 23.1% 15.4% 55.8% 71.6% 43.9% 20.3% 15.8% 40.5%Bare ground 0.0% 0.2% 0.2% 0.2% 0.0% 0.1% 0.6% 0.0% 0.1% 0.1% 0.2% 0.1%Lake/pond open water 0.0% 0.0% 0.3% 0.3% 0.0% 0.8% 0.7% 0.2% 0.2% 0.9% 0.7% 0.0%River bottom 0.0% 0.0% 0.0% 0.7% 0.8% 0.3% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%Estuarine sand/mud shore 0.0% 0.0% 0.0% 6.8% 6.3% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%Estuarine open water 0.0% 0.0% 0.0% 8.3% 12.7% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%Estuarine marsh 0.0% 0.0% 0.0% 7.3% 2.7% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%


3–16

Table 3.3 Meteorological parameters for deposition analysis for land use categoriesLand use designation Surface Albedo Bowen Ratio (avg. moisture) Surface Roughness Length (m)

Spring Summer Autumn Winter Spring Summer Autumn Winter Spring Summer Autumn WinterUpland deciduous forest 0.12 0.12 0.12 0.5 0.7 0.3 1 1.5 1 1.3 0.8 0.5Grassland 0.18 0.18 0.2 0.6 0.4 0.8 1 1.5 0.05 0.1 0.01 0.001Upland scrub/shrub 0.18 0.18 0.2 0.6 0.4 0.8 1 1.5 0.05 0.1 0.01 0.001Riperian perennial stream 0.12 0.1 0.14 0.2 0.1 0.1 0.1 1.5 0.0001 0.0001 0.0001 0.0001Fresh marsh 0.12 0.14 0.16 0.3 0.1 0.1 0.1 1.5 0.2 0.2 0.2 0.05Coniferous swamp 0.12 0.14 0.16 0.3 0.1 0.1 0.1 1.5 0.2 0.2 0.2 0.05Cultivated 0.14 0.2 0.18 0.6 0.3 0.5 0.7 1.5 0.03 0.2 0.05 0.01Upland mixed forest 0.12 0.12 0.12 0.5 0.7 0.3 1 1.5 1 1.3 0.8 0.5Deciduous shrub swamp 0.12 0.14 0.16 0.3 0.1 0.1 0.1 1.5 0.2 0.2 0.2 0.05Upland coniferous forest 0.12 0.12 0.12 0.35 0.7 0.3 0.8 1.5 1.3 1.3 1.3 1.3Deciduous swamp 0.12 0.14 0.16 0.3 0.1 0.1 0.1 1.5 0.2 0.2 0.2 0.05Developed 0.14 0.16 0.18 0.35 1 2 2 1.5 1 1 1 1Bare ground 0.14 0.2 0.18 0.6 0.3 0.5 0.7 1.5 0.03 0.2 0.05 0.01Lake/pond open water 0.12 0.1 0.14 0.2 0.1 0.1 0.1 1.5 0.0001 0.0001 0.0001 0.0001River bottom 0.12 0.1 0.14 0.2 0.1 0.1 0.1 1.5 0.0001 0.0001 0.0001 0.0001Estuarine sand/mud shore 0.14 0.2 0.18 0.6 0.3 0.5 0.7 1.5 0.03 0.2 0.05 0.01Estuarine open water 0.12 0.1 0.14 0.2 0.1 0.1 0.1 1.5 0.0001 0.0001 0.0001 0.0001Estuarine marsh 0.12 0.14 0.16 0.3 0.1 0.1 0.1 1.5 0.2 0.2 0.2 0.05


3–17

Table 3.4 Sector-average values of meteorologic variables used in deposition analysis

SeasonSector range (degrees clockwise from north)

0 to 30 30 to 60 60 to 90 90 to 120 120 to150

150 to180

180 to210

210 to240

240 to270

270 to300

300 to330

330 to360

Surface AlbedoSpring 0.147 0.147 0.143 0.139 0.133 0.127 0.142 0.146 0.141 0.143 0.142 0.145

Summer 0.155 0.156 0.152 0.148 0.140 0.132 0.154 0.160 0.150 0.145 0.146 0.154Autumn 0.170 0.172 0.167 0.161 0.152 0.139 0.169 0.179 0.163 0.164 0.157 0.169Winter 0.457 0.460 0.439 0.444 0.425 0.453 0.426 0.410 0.448 0.425 0.480 0.456

Bowen RatioSpring 0.701 0.728 0.739 0.507 0.589 0.655 0.791 0.850 0.759 0.507 0.606 0.705


Surface Roughness Length (m)Spring 0.689 0.689 0.758 0.502 0.649 0.852 0.798 0.806 0.796 0.461 0.651 0.686


The values in Table 3.4 are based on data from Tables 3.2 and 3.3 as described above. As and example, the calculation of the autumnsurface albedo for the 90 to 120 degree land sector (0.161; data column 4, row 3) is written out in full below. The first parameter ineach product is the autumn surface albedo for a particular land use (Table 3.3, data column 3); the second parameter in each product isthe percentage of the 90 to 120 degree land sector comprised of that land use (Table 3.2, data column 4).

Surface albedo = (0.12)(9.3%) + (0.2)(12.3%) + (0.2)(11.2%) + (0.14)(0.2%)+ (0.16)(0.0%) + (0.16)(6.5%) + (0.18)(0.2%) + autumn season (0.12)(16.8%) + (0.16)(0.3%) + (0.12)(2.3%) + (0.16)(0.3%) + (0.18)(16.9%) + (0.18)(0.2%) + (0.14)(0.3%) +90 to 120° (0.14)(0.7%) + (0.18)(6.8%) + (0.14)(8.3%) + (0.16)(7.3%) = 0.161


3–18

Uplanddeciduousforest

Grassland

Uplandscrub/shrub

Riperianperennialstream

Fresh marsh Coniferousswamp

Cultivated Uplandmixed forest

Deciduousshrub swamp

Uplandconiferousforest

Deciduousswamp Developed

Bare ground Lake/pondopen water

River bottomEstuarinesand/mudshore

Figure 3.8 Land use distribution within 3 km of the Maine Energy facility


3–19

3.5 COPC deposition estimation

The HHRAP risk assessment algorithms require the calculation of COPC deposition from theatmosphere at each receptor location. Deposition estimates are used in the estimation of COPCconcentrations in environmental media. Deposition occurs in both dry and wet modes. Drydeposition occurs as particle-bound COPCs settle onto surfaces, or as gaseous COPCs sorb toand/or react with soils, water, and vegetative surfaces.

The selection of appropriate parameters for modeling COPC deposition is critical for theestimation of COPC concentrations in environmental media because the deposition defines thefirst step in determining the portions of COPCs in air that eventually appear in other media. Uncertainties in the parameter values can therefore have significant effects on the uncertaintiesin the overall risk assessment results. This is especially true for COPCs such as mercury forwhich the risks due to multi-pathway (i.e., foodchain) exposures can be far greater than the risksdue to direct inhalation.

The chemical and physical processes that occur during atmospheric deposition are complex andin some cases incompletely understood. For the purposes of multi-pathway modeling of theCOPCs in this risk assessment, several simplifying assumptions are made in order to modelatmospheric deposition. Where greater uncertainties exist in the modeling or parameters, theassumptions tend to err on the side of conservatism, i.e., overestimating the deposition rates. The use of models derived from first principles and recently measured values are employedwhere appropriate and prudent.

Most of the deposition calculations are developed directly within the ISCST3 and AERMODsimulations. Table 3.5 summarizes the use of the U.S. EPA dispersion models in predictingCOPC deposition. For particle-bound COPCs, both dry and wet deposition are predicted by thedispersion models. AERMOD requires only the specification of a particle-size distribution, anddeposition estimates proceed from built-in equations. ISCST3 similarly uses internal algorithmsand a specified particle size distribution to estimate dry particle deposition, but wet deposition isless automatic and demands that particle size dependent scavenging coefficients be provided asmodel input. For gaseous COPCs, AERMOD and ISCST3 are used to estimate wet deposition,while dry deposition is scaled from ground-level predictions of COPCs in air as recommended inthe HHRAP guidance. Wet deposition scavenging coefficients for gases are estimated internallywithin AERMOD based on COPC physicochemical properties, while they are specified as modelinput values within ISCST3.


3–20

Table 3.5 COPC deposition modeling techniques

Type of COPCISCST3 model for boiler stack AERMOD model for odor scrubbing

system stacks

dry deposition wet deposition dry deposition wet deposition

Particle-boundbuilt-in

algorithms basedon particle size

user-specifiedparticle

scavengingcoefficients

built-inalgorithms basedon particle size

built-inalgorithms basedon particle size

Gaseous

not modeled –based onairborne

concentrationsand deposition

velocities

user-specifiedparticle

scavengingcoefficients

not modeled –based onairborne

concentrationsand deposition

velocities

built-inalgorithms basedon gas properties

3.5.1 Plume depletion

Plume depletion options were used in both the ISCST3 and AERMOD simulations. Use of thedepletion options has little effect on predicted concentrations near the facility, but produces morerealistic COPC modeling estimates at more distant locations. Near surface plume depletion is animportant factor in estimating dry deposition to surfaces, and the failure of AERMOD toproperly account for this phenomenon led to the decision to use ISCST3 to model the dispersionof boiler stack emissions.

3.5.2 Particulate-phase COPC deposition

As in the 1996 study, a facility-specific particle size distribution measured in 1987 is used in theISCST3 calculation of dry and wet particle deposition. Details of the particle size data for theMaine Energy facility are provided in the 1996 risk assessment report (CambridgeEnvironmental, 1996). Two COPC particle size distributions (mass fractions) are specifiedbased on how the specific COPCs are found in the particles:

• mass-weighted values are for COPCs that tend to be distributed uniformly throughoutparticles in the stack emissions; and

• surface-weighted values are for COPCs that tend to condense (or form) onto thesurfaces of existing (seed) particles as combustion gases cool prior to their releasefrom the stack.

Information regarding the facility-specific particle size distribution is presented in Table 3.6.


3–21

For the ISCST3 model, values of wet scavenging coefficients for particles are a function ofparticle size and are assigned values based on default values recommended in the HHRAP. Scavenging coefficients for frozen precipitation (snow and ice) are assumed to be one-third aslarge as the values for liquid precipitation (rain) also based on recommendations in the HHRAP. The particulate-phase wet scavenging coefficients are listed in Table 3.6 as a function of particlesize and are extracted from a figure presented in the documentation of the ISCST3 dispersionmodel (U.S. EPA, 1999b).

AERMOD is also used to estimate the deposition of the small amount of particles resulting fromfugitive emissions internal to the Maine Energy facility that escape through the odor scrubbingsystem. The primary COPCs in these particles are metals, and are modeled as a uniform particlesize of 1 :m diameter per AERMOD recommendations (Wesely et al., 2002). Additionally,AERMOD requires seasonal characterization of surface vegetation. Months assigned to eachAERMOD category are as follows

• Seasonal Category 1: Midsummer with lush vegetation – June, July, and August;• Seasonal Category 2: Autumn with unharvested cropland – September and October;• Seasonal Category 3: Late autumn after frost and harvest, or winter with no snow –

November and December;• Seasonal Category 4: Winter with snow on ground – January and February;• Seasonal Category 5: Transitional spring with partial green coverage or short annuals –

March, April, and May.

Also, like AERMET’s processing of meteorological data, AERMOD requires a generaldesignation of land use in the model study area. Based on the available choices, the “suburbanareas, grassy” (category 5) designation was assigned (consistent with the dominant land uses inthe Maine GIS’s GOMLC7 datalayer within 3 km of the Maine Energy facility).

3.5.3 Vapor-phase COPC wet deposition

The atmospheric deposition of vapor-phase compounds is less understood than the deposition ofparticles. Little guidance regarding the deposition of gases is provided in the HHRAP, and thelimited amount of information that is presented inadequately characterizes the phenomenon. Asrecommended in the HHRAP, only wet vapor deposition is explicitly estimated usingAERMOD. Dry vapor deposition is calculated in subsequent post-dispersion modeling portionsof the multi-pathway assessment. For modeling wet deposition, the HHRAP suggests thatvapors be treated as small particles, which may seem intuitively correct, but is in fact inaccuratefrom a physical perspective. Plotted as a function of particle size, wet deposition scavengingcoefficients follow a U-shaped curve that reaches a minimum for particles about a micron indiameter. For large particles (i.e., particles greater than a micron in diameter), scavengingcoefficients decrease as particle diameters decrease in conjunction with a greater ability forparticles to deflect around raindrops (and hence resist scavenging). A reversal occurs, however,for sub-micron sized particles, for which attractive electrostatic effects become large enough toovercome momentum-based forces and cause scavenging coefficients to increase as particle size

4 A similar U-shaped tendency is characteristic of dry particle deposition as well.


3–22

decreases.4 These electrostatic effects do not apply to gases; hence a different approach isrequired.

Table 3.6 Particle size distributions and wet scavenging coefficients for particle-boundCOPCs. Based on particle size data presented in the 1996 risk assessment(Cambridge Environmental, 1996).

Particlediameter (:m)

Fraction of particles assigned toparticle diameter

Wet scavenging coefficient(hr/mm-s)

Mass-weighted Surface-weighted

Liquidprecipitation

(rain)

Frozenprecipitation

(ice and snow)

0.5 0.0343 0.2324 5 × 10–5 2 × 10–5

0.815 0.0267 0.1107 5 × 10–5 2 × 10–5

1.125 0.0167 0.0502 6 × 10–5 2 × 10–5

1.625 0.0517 0.1076 1.1 × 10–4 4 × 10–5

2.25 0.0317 0.0476 2.0 × 10–4 7 × 10–5

4.25 0.3670 0.2922 3.2 × 10–4 1.1 × 10–4

8 0.2490 0.1053 5.4 × 10–4 1.8 × 10–4

12.5 0.1400 0.0379 6.6 × 10–4 2.2 × 10–4

17.5 0.0830 0.0161 6.6 × 10–4 2.2 × 10–4

In addition, COPC solubility is an important parameter to consider in modeling wet depositionscavenging. To more accurately predict the wet deposition of vapor-phase COPCs (other thanionic mercury which is addressed below), a wet scavenging model based on Henry’s Lawpartitioning and mass balance will be used. The model calculates the maximum amount of avapor that could dissolve into a given depth of rainfall within a specified period, based onHenry’s Law and mass conservation. It is assumed that the chemical vapor reaches equilibriumbetween vapor and dissolved phases in the air column during a precipitation event. Themaximum possible scavenging coefficient for a compound that dissolves into water is derivedfrom this mass balance.


3–23

The wet scavenging coefficient model is based on the amount of the chemical that deposits inprecipitation, calculated as:

where the terms are:Cair the average concentration of the vapor in air;Cprecip the average concentration in precipitation;S the precipitation scavenging coefficient;Dmix the atmospheric mixing height;R the rate of precipitation; andJ the time during which precipitation occurs.

The Henry’s Law equilibrium condition requires that:

where H is the Henry’s Law constant. Combining the previous two expressions, the scavengingrate can be estimated as:

A very similar model is presented in the EPA’s Mercury Study Report to Congress (U.S. EPA,1997a). If one considers a pollutant that simply dissolves into water, the chemical reaction termsdrop out of the U.S. EPA (1997) model, and one obtains a simple relationship between thewashout ratio W (which equals the concentration of the chemical in rainwater divided by theconcentration of the chemical in air) and the non-dimensional Henry’s Law constant H:

By definition, the scavenging coefficient S is related to the washout ratio W and the atmosphericmixing height Dmix (Seinfeld, 1986):

Combining the above equations, one finds the same relationship proposed for calculating thescavenging coefficient:


3–24

Consideration of chemical-specific Henry’s Law constants could conceivably require separateruns of the ISCST3 model for each COPC. As an alternative, it is proposed that the COPCs begrouped into three categories on the basis of their Henry’s Law constants (with the exception ofmercury species, as discussed below), and each of these categories be assigned a single set ofwet scavenging coefficients. For high and moderately high H values, equilibrium partitioningbased on a single surrogate value of H will be used, with application of the above equation for S. For chemicals with low Henry’s Law constants (and hence not limited by solubility), the smallparticle default values consistent with examples in the HHRAP guidance will be used. Valuesfor scavenging coefficients are listed in Table 3.7 grouped according to Henry’s Lawcoefficients.

Vapor-phase ionic mercury has several unique properties that require its wet deposition to bemodeled differently than other compounds. Because the potential health effects related tomercury emissions may dominate the overall non-cancer portion of the risk assessment, it isessential that the first stage of the multi-pathway modeling of ionic mercury is as realistic aspossible.

Mercuric chloride, the form of mercury assumed to comprise all of the ionic mercury in themulti-pathway modeling, has a very low Henry’s Law constant (7.1 × 10–10 atm@m3/mol), and ishighly soluble in water (69,000 mg/l). The Henry’s Law constant for mercuric chloride is wellbelow any of the other COPCs that have appreciable vapor fractions (the next lowest Henry’sLaw constant for a COPC with a vapor fraction of greater than 0.01 is 8.36 × 10–7 atm@m3/mol forbenzo(a)pyrene). Because mercuric chloride scavenged into precipitation dissociates rather thansimply partitions from the air, it is not correctly modeled using the Henry’s Law principlesdescribed above. Fortunately mercury concentrations and speciation in air and total mercury inwet deposition have been measured and assessed so that the scavenging coefficient for this POCmay be estimated empirically.


3–25

Table 3.7 Gas scavenging coefficients for wet deposition modeling in ISCST3

Range of Hdim, in units ofatm-m3/mol

(non-dimensional Hvalues in parentheses) b

Proposedliquid

scavengingcoefficient (s-

mm/hr)–1

Rationale

Proposedscavenging

coefficient forfrozen

precipitation(s-mm/hr)–1

Rationale

High

Hdim $ 1×10–4

(H $ 4×10–3)

9 ×10–8Based on S =1/(DmixH)

with H = 0.004 (non-dimensional)and Dmix = 750 m a

3 ×10–8

Values based on theassumption that

snow/sleet isroughly a as

efficient atscavenging relative

to rainfall (HHRAP, p. 3-52)

Moderately High

1×10–6 # Hdim < 1×10–4

(4×10–5 # H < 4×10–3)


with H = 0.00004 (non-dimensional) and

Dmix = 750 m a

3 ×10–6

Low

Hdim < 1×10–6

(H < 4×10–5)

5 ×10–5Representative value

for small particlesfrom Table 3-1) c

2 ×10–5

Ionic Hg 4 ×10–5Based on empirical

data described below 1 ×10–5

Notes: a A mixing height of 750 m is assumed (average value for Portland, Maine for

1984–1991 data). b The dimensional and non-dimensional Henry’s Law constants are related by:

where T is temperature and R is the Universal Gas Constant. Assuming a temperature of25°C (298°K), the product RT is about 0.02445 mol/atm-m3.

c Also corresponds to the value predicted by S =1/(DmixH) with H = 0.0000074 (non-dimensional) and Dmix = 750 m.

As described above, the washout ratio W is defined as the concentration of a compound inprecipitation divided by its concentration in air, and the scavenging coefficient S is estimatedfrom the washout ratio W by:

5 Mixing height data local to Indiana are used in this derivation as to estimate a scavengingcoefficient from a common set of data. The assumption then follows that the scavengingcoefficient is transferrable to any geographic area. In contrast, the generic gas scavengingcoefficients in Table 3.3 for the high and moderately high categories rely on an area-specificmixing height (derived from Portland, ME data) as an integral model parameter.


3–26

where Dmix is the atmospheric mixing height. Atmospheric concentrations of mercuric chloridevapor have been measured in Tennessee and Indiana at levels between 0.050 – 0.200 ng/m3 overa 4-year period from 1992 to 1995 (Lindberg and Stratton, 1998). The mean concentration of the177 samples collected at the Indiana site was 0.104 ng/m3. Total mercury in wet deposition hasbeen measured for several years at locations in Indiana as part of the National AtmosphericDeposition Program/Mercury Deposition Network (MDN, 2004). Table 3.4 presentsmeasurements of the concentration of mercury in precipitation taken at the two Indiana locationsclosest to the ambient measurements of mercuric chloride. Values in Table 3.8 representvolume-weighted averages of weekly samples, which are currently available for three years. Theannual-average mercury concentrations range from 11.1 to 13.2 ng/l. Averaged across calendaryears, values range from 11.3 to 12.2 ng/l at individual sites, and averaged across sites, valuesrange from 11.3 to 12.3 ng/l. The grand average of all mercury concentration values is 11.8 ng/l(weighting each site-year value equally). To estimate the mercuric chloride washout ratio fromthese data, the average deposition concentration (11.8 ng/l) is divided by the averageatmospheric concentration (1.07 × 10–4 ng/l), yielding a unitless washout ratio W of 1.1 × 105.

Application of the washout ratio equation requires an estimate of an average atmospheric mixingheight in the area of eastern Indiana where the concentration and deposition data were collected.Since there are no upper air monitoring stations in Indiana, data from Dayton, Ohio were used toobtain an average mixing height Dmix of 833 m (U.S. EPA, 2004).5 Converting to the unitsrequired by AERMOD, the liquid scavenging coefficient for mercuric chloride vapor iscalculated as 4 × 10–5 (s-mm/hr)–1. This value is a conservative estimate of the scavengingcoefficient because its derivation assumes that all of the mercury in wet deposition is derivedfrom vapor-phase mercuric chloride when a significant portion of it is actually derived fromparticulate-phase mercury species (Keeler et al., 1995), and because it assumes that there is nomercury in the cloud water before precipitation begins.

Table 3.8 Mercury Deposition Network (MDN, 2004) Data for Two Indiana Locations

Monitoring Site

Mercury concentration in precipitation (ng/l)

Calendar YearSite Average

2001 2002 2003

IN20 Roush Lake 11.7 11.2 11.1 11.3

IN21 Clifty Falls State Park 12.2 11.4 13.2 12.3

Calendar Year Average 12.0 11.3 12.2 11.8


3–27

A comparison can be made between this proposed wet scavenging coefficient and estimates ofscavenging coefficients derived for nitric acid as presented by Seinfeld (1986). Nitric acid is oneof the few compounds for which there is a significant database of measured values for bothatmospheric and deposition concentrations. It is also used as a surrogate for mercuric chloridebecause their relevant chemical properties are similar (U.S. EPA, 1997a and 1998a). Becausemercuric chloride and nitric acid both dissociate in water, the Henry’s Law model isinappropriate to use for estimating their scavenging coefficients. Seinfeld (1986) presents valuesof wet scavenging coefficients for nitric acid under twelve different precipitation scenarios thatrange from 1.3×10–5 to 1.2×10–4 (s-mm/hr)–1. The proposed coefficient for mercuric chloride4×10–5 is well within this range. As for other vapors, ionic mercury scavenging coefficients forice/snow will be assigned to be one-third of the values estimated for liquids.

The AERMOD model calculates wet scavenging coefficients for gases internally based uponCOPC-specific physicochemical parameters. The beta version of AERMOD that calculates vapordeposition requires several additional model inputs. Many of these parameters are relevant todry deposition, which for AERMOD is described in the discussion of particulate deposition. Anadditional parameter for gases is the reactivity, which for the multi-pathway risk assessment isset to zero (if the COPC does react, it is eliminated from the possibility of entering the foodchain pathways).

The gaseous COPCs emitted from the odor scrubbing system fall into the three basic categoriesdescribed in Table 3.7. The low Henry’s Law constant category is modeled as small particledeposition, as previously described in section 3.5.2. For the medium and high Henry’s Lawconstant categories, the following COPC-specific parameters are assigned based on (1) theproperties of the suite of chemicals considered, and (2) the goal of emphasizing values that willmodel high-end deposition rates in each category:

• for both groups, mid-range values of 0.07 cm2/s and 0.000008 cm2/s are assumed forCOPC diffusivities in air and water, respectively;

• the medium Henry’s Law constant group is assigned a typical Henry’s Law constant of0.000001 atm-m3/mol and a cuticular resistance of 25 (a low-end value based onrecommendations in Wesely et al, 2002, for the COPCs in the category); and

• the high Henry’s Law constant group is assigned a typical Henry’s Law constant of0.0001 atm-m3/mol and a low-end cuticular resistance of 500.

6 The GDISCDFT dry vapor deposition algorithms have now been incorporated into theISCST3 model. The GDISCDFT modeling as described was developed prior to the release ofthe updated ISCST3 model.


3–28

3.5.4 Vapor-phase COPC dry deposition

At the time the HHRAP was developed, U.S. EPA dispersion models did not contain algorithmsto calculate dry deposition rates of gases, and consequently dry vapor deposition was insteadincorporated directly in the HHRAP model equations (Appendix B) using a deposition velocityapproach which simply relates the flux of the vapor-phase species to its average ambientconcentration through a multiplicative constant, the deposition velocity. However, little detailedinformation is provided in the HHRAP concerning the estimation of dry gas depositionvelocities. A default deposition velocity of 3 cm/s is suggested in Appendix B of the HHRAP,based on the recommendations in a 1994 draft guidance for screening level risk analyses ofhazardous waste combustion emissions (U.S. EPA, 1994). The original database on which thisrecommendation is based contained dry deposition velocities for nitric acid, ozone, and sulfurdioxide. The deposition velocity of 3 cm/s is for nitric acid which was considered the mostsimilar to the constituents covered by the screening level risk analyses. The HHRAP notes(Appendix B, Table B-1-1) that this deposition velocity should be applicable to any organiccompound having a low Henry’s Law constant, but gives no support for the use of nitric acid as asurrogate for such COPCs, nor does it give any recommendation for COPCs with high Henry’sLaw constants (nor the value below which the analogy is applicable). In addition, the originalsource of this dry deposition data is not cited by the EPA in either the HHRAP or the 1994guidance, and is therefore not subject to review.

The U.S. EPA’s algorithms for estimating gas deposition velocities were initially incorporatedinto GDISCDFT, a previous, draft version of the ISCST3 model.6 In a previous applicationevaluating emissions from a hazardous waste combusting cement kiln in Indiana, theGDISCDFT model was investigated to better estimate chemical-specific deposition velocities foruse in risk assessment calculations, and also to account for area-specific land use andmeteorologic data (Cambridge Environmental, 2002). The GDISCDFT model predicts averagedeposition velocities significantly lower than the HHRAP’s default recommendation. Based onthe GDISCDFT modeling, a value of 0.36 cm/s was found to be a conservative Vdv value forchemicals of limited solubility and reactivity.

Similar dry deposition algorithms for gases have been incorporated into the draft AERMODsoftware. To maintain consistency with the HHRAP, however, the AERMOD dry depositionoption will not be used for gases, but a more realistic value for the dry deposition velocity willbe used based on consideration of the AERMOD algorithms and values that have beendetermined in studies of dry deposition.

A figure presented by Seinfeld (1986), and referenced to the National Center for AtmosphericResearch (NCAR, 1982) shows experimental data on gas dry deposition velocities ranked

7 CASTNet data are available at: http://www.epa.gov/castnet/data.html, accessed July 2004.


3–29

approximately in order of reactivity. The velocities are shown on a logarithmic scale rangingfrom 0.001 cm/s to about 5 cm/s; the gases range from the highly reactive HF to the less reactiveCO, with the more reactive gases having higher deposition velocities. The dry deposition datafor nitric acid, contains 12 values, ranging from 0.06 to 4.5 cm/s; 10 of these are below 3 cm/s. The HHRAP default deposition velocity of 3 cm/s thus almost certainly overestimates thedeposition of gases that are less reactive and less than soluble nitric acid, and is likely tooverestimate the velocity even for species that are as reactive and soluble as nitric acid.

More recent and extensive empirical modeling of dry deposition of common pollutants has beenperformed as part of the U.S. EPA’s Clean Air Status and Trends Network (CASTNet, 2004). Dry deposition is assessed as part of the program using the Multi-Layer Model (MLM) based onmeasured atmospheric concentrations of sulfur and nitrogen based pollutants, andmeteorological, vegetation, and land use data. The MLM simulates dry deposition processes andcalculates deposition velocities (Meyers et al., 1998, and Finkelstein et al., 2000). The MLMhas been evaluated for a limited number of scenarios (summarized by Baumgardner et al., 2002)with the finding that it generally underestimates SO2 dry deposition and has a small positive biasfor HNO3.

CASTNet currently has three sites in Maine that have available data from years ranging from1989 through 20037. Summary data of annual average deposition velocities for four atmosphericspecies at stations in Maine and nationally are given in Table 3.9.

Table 3.9 Deposition velocity estimates from CASTNet (2004) data

Species

Annual average deposition velocities (cm/s)(26 Maine annual summaries, 953 nationwide annual summaries)

Values for Maine stations (nationwide in parentheses)

Minimum Maximum Average

Ozone (O2) 0.15 (0.058) 0.30 (0.33) 0.19 (0.17)

Sulfur dioxide (SO2) 0.23 (0.12) 0.42 (0.54) 0.33 (0.31)

Nitric acid (HNO3) 0.98 (0.52) 1.6 (2.8) 1.4 (1.3)

Particulate matter 0.065 (0.021) 0.15 (0.31) 0.11 (0.11)

The deposition velocities presented are a function of solubility and reactivity, with nitric acidhaving the highest values and particulate matter the lowest. Ozone, though reactive, is relativelyinsoluble, so surface water or moisture inhibits its dry deposition (Seinfeld, 1986). Because drydeposition is also a function of meteorology, vegetation, and land use, the national values cover a


3–30

broader range than the Maine values. It is also clear from the data that the HHRAP defaultdeposition velocity of 3 cm/s is a significant overestimate for all but the most soluble/reactivespecies and under meteorological and geographic conditions that lead to the highest depositionrates.

Although it would be possible to use a different dry deposition velocity in the multi-pathwaymodeling for each vapor-phase COPC, the large uncertainties and lack of a well validated modelfor estimating these values (especially for the organic compounds) make this approach difficultto justify. Therefore, based on the dry deposition velocities for nitric acid derived for locationsin Maine as part of the CASTNet program, the risk assessment will employ a vapor-phasedeposition velocity of 1.4 cm/s for all COPCs. This value should accurately model the mostcritical compound with respect to dry deposition and estimated risk, mercuric chloride, andshould conservatively model all of the other COPCs.

3.6 Modeling of startup and shutdown emissions

COPC emissions during conditions of unit startup and shutdown are considered to evaluatewhether maximum, one-hour average, direct COPC exposure levels under these conditionsexceed those that occur under normal plant operation. This model run employs a stack exitvelocity of 0.5 times the normal full operating velocity. Because the results of this modeling willonly be used for evaluating maximum direct COPC exposure levels, it will not require themodeling of COPC deposition rates, nor the use of the large receptor grid. Therefore only asingle, simplified set of modeling runs for a passive tracer species is needed, a scenario modeledin ISCST3 as vapor emissions with no deposition.

3.7 Summary of atmospheric dispersion and deposition modeling results

The updated atmospheric modeling of COPC emissions from the Maine Energy facility wasconducted with a combination of the ISCST3 and AERMOD models (the latter a moresophisticated model recently made available by the U.S. EPA). Similar to the 1996 riskassessment study, the modeling includes a receptor grid extended to a distance of 15 km from theMaine Energy facility.

The HHRAP guidance suggests the use of three sets of model runs to simulate vapor-phase, andmass- and surface-weighted particle-phase COPCs. In order to more accurately model the wetdeposition of critical vapor-phase COPCs with differing partitioning and solubility properties,three different runs were performed for organic vapor-phase COPCs, and a separate run wasdeveloped for vapor-phase ionic mercury. Dispersion and deposition modeling were conductedfor the following POC types:

• mass-weighted particle-bound chemicals (emitted metals except mercury);


3–31

• surface-weighted particle-bound chemicals (particulate-phase mercuric chloride andthe fraction of organic compounds adsorbed onto particles);

• vapors with high Henry’s Law constants (H > 10–4 atm-m3/mol);• vapors with moderate Henry’s Law constants; (10–6 < H < 10–4 atm-m3/mol)• vapors with low Henry’s Law constants (H < 10–6 atm-m3/mol);• vapor-phase ionic mercury.

Each emission type was assigned a nominal emission rate (e.g., a generic emission rate of 10 g/s)so that model predictions could be scaled easily to COPC-specific emission rates. It wasnecessary in some cases to assign large nominal emission values (e.g., cases with low vaporscavenging rates) so that the models provided output with sufficient numbers of significantfigures. Several COPCs such as PCBs, dioxins/furans, and several semi-volatile organiccompounds are present in both the particle and vapor phase. The vapor fraction for each COPC isgiven by the parameter Fv in Appendix II. The modeled dispersion and deposition parameters forfor these compounds are the weighted sum of the values for their vapor and particulate phases.

Figures 3.9 to 3.20 typify model predictions. Each figure depicts the pattern of modeledconcentrations in the vicinity of the Maine Energy facility (located at the center of each figure). Each figure provides two projections: a domain-wide projection that covers the entire 15 kmradius study area, and an expanded view of the 6 km by 6 km area closest to the Maine Energyfacility. The color-coded shading in each figure indicates the spatial variation of predictions. Representative figures of all of the modeling runs are provided in Appendix VI. A cross at thecenter of each figure indicates the location of the Maine Energy facility, and the GoosefareBrook and Wilcox Pond watersheds are outlined.

Figures 3.9 to 3.14 depict results from the ISCST3 modeling of boiler stack emissions ofparticulate-phase COPCs that have volume-weighted (rather than surface area-weighted)distributions among the particle size classes. These figures show estimated concentration anddeposition levels for a nominal emission rate of 1 g/s. Figure 3.9 shows the maximum 1-houraverage concentrations peaking in the near vicinity of the Maine Energy facility, although adistinct “donut-hole” of lower concentrations is predicted immediately adjacent to the facility. The pattern is similar in Figure 3.10 for the maximum 24-hour average predictions, although the“donut-hole” effect is somewhat smaller. The annual average concentration predictions inFigure 3.11 exhibit well-defined maxima over two areas just to the north and to the southeast ofthe Maine Energy facility. As expected, the magnitude of the predicted concentrations decreaseas the averaging period lengthens, with peak 1-hour maxima roughly a factor of thirty greaterthan the annual average predictions (Figure 3.9 v. Figure 3.11). Figures 3.12 to 3.14 depictmodeled annual deposition rates. The pattern of total (wet plus dry) deposition (Figure 3.14) isvery similar to the predicted pattern of wet deposition (Figure 3.12) because for these emissionswet deposition predictions are much greater than those of dry deposition (Figure 3.13).

Figures 3.15 to 3.20 display the AERMOD model predictions of dispersion and deposition ofemissions from the three odor scrubbing stacks. The figures depict the series of runs for low


3–32

Henry’s Law constant COPCs, based on a nominal emission rate of 300 g/s (100 g/s for eachstack). Figure 3.15 shows the maximum 1-hour average concentrations peaking in the nearvicinity of the Maine Energy facility, although a distinct “donut-hole” of lower concentrations ispredicted immediately adjacent to the facility. The pattern is similar in Figure 3.16 for themaximum 24-hour average predictions, although the “donut-hole” effect is less distinct. Theannual average concentration predictions in Figure 3.17 exhibit well-defined maxima overlimited areas just to the north and to the southeast of the Maine Energy facility. As expected, themagnitude of the predicted concentrations decrease as the averaging period lengthens, with peak1-hour maxima roughly a factor of thirty greater than the annual average predictions (Figure 3.15v. Figure 3.17). Figures 3.18 to 3.20 depict modeled annual deposition rates. The pattern oftotal (wet plus dry) deposition (Figure 3.20) is very similar to the predicted pattern of drydeposition (Figure 3.19) because dry deposition predictions are much greater than those of wetdeposition (Figure 3.18), which are predicted to peak in the immediate vicinity of the MaineEnergy facility. This is in contrast to the deposition results for volume-weighted particulateCOPC emissions from the facility stacks where the rates for dry deposition (Figure 3.13) aresmaller than those for wet deposition (Figure 3.12).

Table 3.10 summarizes the set of modeled concentrations identified as maximum values over themodeling domain for the two short-term and one long-term averaging period. One-hour averageconcentrations for stack emissions were modeled using the normal operating stack flow rate andat a flow rate of one-half normal so that upset emissions that occur during facilitystartup/shutdown conditions can be evaluated. Table 3.11 summarizes the long-term maximummodeled deposition rates over the domain. Vapor-phase dry deposition is not modeledseparately, but is calculated from concentration levels and an assumed dry deposition velocity of1.4 cm/s. Annual average concentration and deposition values over the watersheds of interestare shown in Table 3.12. Domain-wide deposition and watershed concentration and depositionare only modeled for assessment of long-term effects. These values are used in subsequentchapters along with modeled deposition rates to develop the multi-pathway exposure and riskestimates. Table 3.13 summarizes Annual average concentration and deposition values at thelocation identified as having the maximum potential health risks for the farming exposurescenario. The farming scenario is evaluated only at locations further that 1 km from the facility(see Chapter 4 for details). To find the maximum impact location that is at least 1 kilometerfrom the Maine Energy facility, a Microsoft Excel macro was written to calculate the overallpotential cancer and non-cancer health effects for the farming scenario at all of the receptorlocations, and to generate a list of overall risk indices and receptor numbers. Because the highestimpacts for air concentration, wet deposition and dry deposition do not coincide, and these pointsalso differ by contaminants based on fate and transport properties, each potential exposure pointhad to be tested using its specific combination of parameters. Once the receptor location at whichthe highest potential health impacts for the farming scenario was identified, the full analysis wasdocumented using the atmospheric dispersion and deposition results for that location.


3-33

Figure 3.9 Maximum 1-hour concentration, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


3-34

Figure 3.10 Maximum 24-hour concentration, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


3-35

Figure 3.11 Annual average concentration, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


3-36

Figure 3.12 Annual average wet deposition, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


3-37

Figure 3.13 Annual average dry deposition, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


3-38

Figure 3.14 Annual average total deposition, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


3-39

Figure 3.15 Maximum 1-hour concentration, AERMOD modeling of odor scrubbing systememissions of small particles and vapors with low Henry’s Law constants (normalized to300 g/s emission rate). Top projection depicts entire modeling domain, lower projectiona 6-km by 6-km region around the Maine Energy facility. Color-coded legend indicatesrelative values. Cross indicates facility location, and black outlines pond watersheds.


3-40

Figure 3.16 Maximum 24-hour concentration, AERMOD modeling of odor scrubbing systememissions of small particles and vapors with low Henry’s Law constants (normalized to300 g/s emission rate). Top projection depicts entire modeling domain, lower projectiona 6-km by 6-km region around the Maine Energy facility. Color-coded legend indicatesrelative values. Cross indicates facility location, and black outlines pond watersheds.


3-41

Figure 3.17 Annual average concentration, AERMOD modeling of odor scrubbing system emissionsof small particles and vapors with low Henry’s Law constants (normalized to 300 g/semission rate). Top projection depicts entire modeling domain, lower projection a 6-kmby 6-km region around the Maine Energy facility. Color-coded legend indicates relativevalues. Cross indicates facility location, and black outlines pond watersheds.


3-42

Figure 3.18 Annual average wet deposition, AERMOD modeling of odor scrubbing system emissionsof small particles and vapors with low Henry’s Law constants (normalized to 300 g/semission rate). Top projection depicts entire modeling domain, lower projection a 6-kmby 6-km region around the Maine Energy facility. Color-coded legend indicates relativevalues. Cross indicates facility location, and black outlines pond watersheds.


3-43

Figure 3.19 Annual average dry deposition, AERMOD modeling of odor scrubbing system emissionsof small particles and vapors with low Henry’s Law constants (normalized to 300 g/semission rate). Top projection depicts entire modeling domain, lower projection a 6-kmby 6-km region around the Maine Energy facility. Color-coded legend indicates relativevalues. Cross indicates facility location, and black outlines pond watersheds.


3-44

Figure 3.20 Annual average total deposition, AERMOD modeling of odor scrubbing systememissions of small particles and vapors with low Henry’s Law constants (normalized to300 g/s emission rate). Top projection depicts entire modeling domain, lower projectiona 6-km by 6-km region around the Maine Energy facility. Color-coded legend indicatesrelative values. Cross indicates facility location, and black outlines pond watersheds.


3–45

Table 3.10 Maximum modeled air dispersion concentrations of COPCs emitted from theMaine Energy facility. Concentrations are in units of :g/m3 normalized to aCOPC emission rate of 1 g/s. To obtain actual modeled concentrations thesevalues are multiplied by the COPC specific emission rates. The X and Y valuesgive the location of the maxima in units of meters to the east (X) and north (Y) ofthe facility stack; negative X and Y values indicate locations to the west and southof the stack respectively. Particulate-phase COPC emissions classified as eithermass-weighted (m) or surface-weighted (s); vapor-phase COPC emissions areclassified based on their Henry’s Law constant (high, medium, or low), withvapor-phase mercury (Hg) classified separately. See Table 3.7 for details of theseclassifications.

Stack emissions

COPC type1-hour average

normal flow1-hour average

startup flow 24-hour average 1-year average

Conc. X Y Conc. X Y Conc. X Y Conc. X Y

Part.(m) 2.64 0 1400 3.20 -5909 -1042 0.212 0 1400 0.014 0 2200

Part.(s) 3.07 -689 122 3.45 -953 -550 0.302 -689 -2349 0.022 0 4000

Vap.(h) 3.27 -689 122 3.75 -308 -846 0.413 -855 -2349 0.030 0 4000

Vap.(m) 3.27 -689 122 3.73 -308 -846 0.371 -608 -3447 0.031 0 4000

Vap.(l) 3.27 -689 122 3.75 -308 -846 0.412 -855 -2349 0.030 0 4000

Vap.(Hg) 3.27 -689 122 3.75 -308 -846 0.412 -855 -2349 0.030 0 4000

Scrubber emissions

Part.(m) 27.2 376 -137 27.2 376 -137 11.0 -43 25 1.67 -49 9

Part.(s) 27.2 376 -137 27.2 376 -137 11.0 -43 25 1.67 -49 9

Vap.(h) 27.2 376 -137 27.2 376 -137 11.0 -43 25 1.67 -49 9

Vap.(m) 27.2 376 -137 27.2 376 -137 11.0 -43 25 1.67 -49 9

Vap.(l) 27.2 376 -137 27.2 376 -137 11.0 -43 25 1.67 -49 9

Vap.(Hg) 27.2 376 -137 27.2 376 -137 11.0 -43 25 1.67 -49 9


3–46

Table 3.11 Maximum modeled deposition rates of COPCs emitted from the Maine Energyfacility. Deposition rates are in units of g/m2-year normalized to a COPCemission rate of 1 g/s. To obtain actual modeled concentrations these values aremultiplied by the COPC specific emission rates. The X and Y values give thelocation of the maxima in units of meters to the east (X) and north (Y) of thefacility stack; negative X and Y values indicate locations to the west and south ofthe stack respectively. Particulate-phase COPC emissions classified as eithermass-weighted (m) or surface-weighted (s); vapor-phase COPC emissions areclassified based on their Henry’s Law constant (high, medium, or low), withvapor-phase mercury (Hg) classified separately. See Table 3.7 for details of theseclassifications.

Stack emissions

COPCtype

Vapor-phase wet deposition

Particulate-phase wetdeposition

Particulate-phase drydeposition

Dep. X Y Dep. X Y Dep. X Y

Part.(m) — — — 1.52 -43 -25 0.0667 0 2200

Part.(s) — — — 0.839 -43 -25 0.0333 0 2200

Vap.(h) 0.187 -43 -25 — — — — — —

Vap.(m) 0.0331 -43 -25 — — — — — —

Vap.(l) 0.00034 -43 -25 — — — — — —

Vap.(Hg) 0.148 -43 -25 — — — — — —

Scrubber emissions

Part.(m) — — — 0.000132 -87 -50 0.017 -49 9

Part.(s) — — — 0.000132 -87 -50 0.017 -49 9

Vap.(h) 0.000069 -87 -50 — — — — — —

Vap.(m) 0.0069 -87 -50 — — — — — —

Vap.(l) 0.000132 -87 -50 — — — — — —

Vap.(Hg) 0.0069 -87 -50 — — — — — —


3–47

Table 3.12 Maximum modeled air dispersion concentrations and deposition rates at the twoassessed watersheds (Goosefare Brook and Wilcox Pond) for COPCs emittedfrom the Maine Energy facility. Concentrations are in units of :g/m3; depositionrates are in units of g/m2-yr, both are normalized to a COPC emission rate of 1g/s. To obtain actual modeled concentrations these values are multiplied by theCOPC specific emission rates. Particulate-phase COPC emissions classified aseither mass-weighted (m) or surface-weighted (s); vapor-phase COPC emissionsare classified based on their Henry’s Law constant (high, medium, or low), withvapor-phase mercury (Hg) classified separately. See Table 3.7 for details of theseclassifications. Only the parameters shown are used for multi-pathway modelingof water sheds, see Chapter 5, Section 2 for details.

Stack emissions

COPC typeGoosefare Brook Wilcox Pond

Concen-tration

Wetdeposition

Totaldeposition

Concen-tration

Wetdeposition

Totaldeposition

Part.(m) — — 0.0405 — — 0.0311

Part.(s) — — 0.0208 — — 0.0165

Vap.(h) 0.0190 0.0000027 — 0.0144 0.0000045 —

Vap.(m) 0.0190 0.000269 — 0.0144 0.000430 —

Vap.(l) 0.0190 0.00138 — 0.0144 0.00216 —

Vap.(Hg) 0.0190 0.00112 — 0.0144 0.00170 —

Scubber emissions

COPC typeGoosefare Brook Wilcox Pond

Concen-tration

Wetdeposition

Totaldeposition

Concen-tration

Wetdeposition

Totaldeposition

Part.(m) — — 0.00029 — — 0.00016

Part.(s) — — 0.00029 — — 0.00016

Vap.(h) 0.0387 7.0 E-7 — 0.0219 1.3 E-6 —

Vap.(m) 0.0387 6.9 E-5 — 0.0219 1.3 E-4 —

Vap.(l) 0.0386 1.5 E-6 — 0.0219 2.5 E-6 —

Vap.(Hg) 0.0387 6.9 E-5 — 0.0219 1.3 E-4 —


3–48

Table 3.13 Modeled air dispersion concentrations and deposition rates for COPCs emittedfrom the Maine Energy facility at the site identified as having the greatest risksfor the farming exposure scenario. Concentrations are in units of :g/m3;deposition rates are in units of g/m2-yr, both are normalized to a COPC emissionrate of 1 g/s. To obtain actual modeled concentrations these values are multipliedby the COPC specific emission rates. Particulate-phase COPC emissionsclassified as either mass-weighted (m) or surface-weighted (s); vapor-phaseCOPC emissions are classified based on their Henry’s Law constant (high,medium, or low), with vapor-phase mercury (Hg) classified separately. See Table3.7 for details of these classifications. Only the parameters shown are used formulti-pathway modeling of water sheds, see Chapter 5, Section 2 for details.

Stack emissions

COPC type Concentration Wet deposition Total deposition

Part.(m) — — 0.083

Part.(s) — — 0.044

Vap.(h) 0.029 3.2 E-3 —

Vap.(m) 0.029 6.3 E-4 —

Vap.(l) 0.029 3.2 E-3 —

Vap.(Hg) 0.029 2.6 E-3 —

Scubber emissions

COPC type Concentration Wet deposition Total deposition

Part.(m) — — 0.00052

Part.(s) — — 0.00013

Vap.(h) 0.063 1.3 E-6 —

Vap.(m) 0.063 1.3 E-4 —

Vap.(l) 0.063 2.6 E-6 —

Vap.(Hg) 0.063 1.3 E-4 —


4–1

4 Exposure scenario selectionThe multi-pathway exposure assessment builds on the air dispersion and deposition modeling byestimating the concentrations of COPCs in a variety of environmental media to which humansand wildlife may be exposed. To determine which media need to be evaluated, the pathwayswhich lead to exposures must be defined. The pathways that will be assessed in this riskassessment include the direct inhalation of airborne contaminants, and a variety of indirectpathways that consider the deposition of contaminants to soil, water, and vegetation, withpossible transfer and accumulation in the food-chain. Exposure scenarios are defined as acombination of such exposure pathways evaluated for a receptor at a specific location. Thelocations to be evaluated are those where there is the potential for the reasonable maximum long-term human exposures to emitted COPCs to occur through a few specific pathways. Asrecommended in the HHRAP, the following exposure scenarios will be considered for theevaluation of chronic risks:

• Residents (adult and child);• Recreational farmers (adult and child);• Recreational fishers (adult and child); and• Nursing infants.

Children are distinguished from adults because their rates of exposure to chemicals (as expressedper unit body weight) are frequently higher.

Recreational fishers and farmers represent individuals whose diet includes a substantial portionof food that they catch in local waters and raise on local lands. These scenarios have beenrenamed from the subsistence fisher and farmer scenarios that are described in the HHRAP tobetter characterize the habits of people living in the Cities of Biddeford and Saco and nearbyareas. The term subsistence suggests that essentially all of a person’s food source derives from asingle source. An examination of the HHRAP’s assumptions reveals that the rates of foodingestion for the subsistence scenarios are well below levels required for sustained existence. Hence, the term subsistence is an inappropriate descriptor for the scenarios characterized in theHHRAP.

In order to avoid the erroneous implications that could be associated with the term subsistence,the updated risk assessment for the Maine Energy facility will use the descriptor “recreational”to refer to high-end exposure scenarios. A recreational fisher is intended to represent a personliving in the Biddeford/Saco area who fishes frequently in local waters and regularly consumes asubstantial portion of the catch. Similarly, a recreational farmer is intended to represent a personliving within the area who raises vegetables and livestock to derive a significant portion of theirfood supply.


4–2

Allowing for the change in descriptors, the exposure scenarios to be evaluated are essentiallythose recommended in the HHRAP. Table 4.1, reproduced and adapted from the HHRAP,delineates the exposure pathways to be evaluated for each exposure scenario. Evaluation of thesurface water pathway as a source of drinking water is evaluated based on the Saco River, whichserves as the source of municipal water to many area residents.

Table 4.1 Exposure scenarios to be evaluated in the human health risk assessment

Exposure pathwaysExposure ScenariosA

Resident RecreationalFarmer

RecreationalFisher

Inhalation of vapors and particlesB x x x

Incidental ingestion of soil x x x

Ingestion of drinking water x x x

Ingestion of homegrownC produce x x x

Ingestion of homegrown beef x

Ingestion of milk from homegrown cows x

Ingestion of homegrown chickens x

Ingestion of eggs from homegrown chickens x

Ingestion of homegrown pork x

Ingestion of fishC x

Infant ingestion of breast milkD x x xA All of these exposure scenarios will be evaluated for adults and children.B The acute risks of one-hour and 24-hour direct inhalation of COPCs will be evaluated at theresidential receptor site.C Ingestion of homegrown produce and livestock as well as fish are evaluated at ingestion rates thatreflect a substantial dietary intake of foods raised or caught locally in the Biddeford/Saco area. D Ingestion of breast milk will be evaluated for dioxin exposure to infants of mothers exposed toCOPCs in each of the three exposure scenarios

As indicated in Table 4.1, the ingestion of breast milk is evaluated as a special pathway ofpotential concern independent of the other exposure scenarios, as recommended in the HHRAP. Infants can be exposed to concentrated doses of pollutants that are transferred through theirmother’s milk. The nursing infant pathway is based on the assumption that the mother receivesexposure to contaminant emissions from the Maine Energy facility, and hence is a member of the


4–3

resident, recreational fishing, and/or recreational farming populations evaluated in the riskassessment.

The first step in the multi-pathway exposure assessment for each of these scenarios involves theinterpretation and use of the atmospheric modeling analysis. As described in Chapter 3 for boththe boiler stack and odor scrubbing system emissions, the maximum projected ambientconcentration and dry deposition impacts are found some distances beyond the property line atwhich the elevated plume touches down (on average), and the locations for the two sources willdiffer. However the maximum wet deposition impacts occur very close to the facility. Consideration has been given to land use and the prediction of impacts at specific receptorlocations of interest.

The residential receptor scenarios are evaluated at the locations of highest projected facilityimpacts outside of the facility property (as there are residential areas fairly close to the facility). For the recreational fishing scenario, the fate-and-transport modeling, however, considers theactual locations and characteristics of water bodies in estimating pollutant levels in fish. It isassumed that the individual fishers live at the worst-case residential location, as it is plausiblethat any resident can be a recreational fisher. The 1996 risk assessment focused on two smallponds because it is more likely that facility emissions could more substantially affect their waterquality. As a sensitivity calculation, the updated health risk assessment also considers fish takenin the Saco River, a more significant fishing resource, to test the assumption that the river’sgreater dilution volume reduces potential impacts from facility emissions (See Chapter 8).

The recreational farming scenario has been evaluated under two sets of assumptions regardingconsumption of home-grown animal products in the vicinity of the Maine Energy facility. First,that there may be residential locations where sufficient space exists for the growth of sufficientvegetables and fruits to support the HHRAP home-grown consumption rates at any location inthe vicinity of the Maine Energy facility. Second, that there may be residential locations wheresufficient space exists for the growth of sufficient vegetables and fruits, and animal products tosupport the HHRAP home-grown consumption rates at any location beyond 1 kilometer from theMaine Energy facility. The assumption that there is no substantial consumption of animalproducts (i.e., beef, pork, poultry, eggs, and milk) within 1 km of the facility is supported byFigures 1.1, 1.2, and 3.6. Figures 1.1 and 1.2 show the relatively dense urban setting in the areawithin 1 km of the facility. Examination of Figure 3.6 reveals that the nearest identifiable areaof cultivated land is approximately 2 km to the east-southeast of the Maine Energy facility (inthe area to the south of the laurel Hill Cemetery on Figure 1.1). The maximum estimated healthrisks for the recreational farming scenario are somewhat insensitive to the specific distancechosen for this cutoff (at distance between around 700 and 5000 meters) because the maximumCOPC deposition rates do not change significantly once the receptors are outside the small areanear the facility where the high wet deposition rates are at their highest. Even if there arelocations with the 1 km distance from the facility where chickens may exist, it is unlikely that asufficient number might be kept to sustain the assumed long-term consumption rates used toevaluate this scenario (roughly 10.5 ounces of poultry and eggs consumed per adult per week); itis highly unlikely that pigs, and dairy and beef cattle exist in this location. The method used to


4–4

identify the location of the maximum potential health risks under these assumptions for thefarming scenario are described in Section 3.7.

In addition to the resident, recreational farmer, and recreational fisher scenarios, an acute riskscenario will also be considered to evaluate the potential for facility emissions to adversely affectnearby residents over short time periods (e.g., one hour, one day) via the inhalation of chemicalsof potential concern. This scenario will be evaluated at the location of the highest estimated one-hour, off-site ambient air COPC concentrations. Because the updated risk assessment willconsider two sources of emissions from the Maine Energy facility released from differentheights, there will likely be different worst-case projected points of impact. Consequently, theresident, recreational farmer, and recreational fisher scenarios will be considered at the locus ofeach of the worst-case projections for emissions from the boiler stack and the odor scrubbingsystem. The potential for such acute health effects is evaluated using the maximum 1-houraverage COPC concentrations from the air dispersion modeling per HHRAP guidance, and bycomparing modeled 24-hour COPC concentrations with the Air Toxics Ordinance ambient airlimits (AALs) promulgated by the City of Biddeford.


5–1

5 Estimation of media concentrationsIn order to evaluate the impact of atmospheric emissions from the Maine Energy facility, theconcentrations of each COPC are estimated in a variety of media, specifically: air, soil, naturalvegetation, fruit and vegetable crops, livestock and related farm products, surface and drinkingwater supplies, and fish. A wide range of fate and transport parameters are needed to conductsuch a multi-pathway assessment, including compound-specific properties of COPCs, whichwere discussed in Chapter 2, and site-specific land-use characteristics, which will be described inthe relevant sections below. Table 5.1 contains the required general default parameters from theHHRAP guidance for time durations, and air, water and soil properties, as well as site-specificparameters for the watersheds for Wilcox pond and the unnamed pond on the Goosefare Brook. For each medium addressed in the calculations, detailed algorithms and equations are applied, asdescribed in the HHRAP’s Chapter 5 and its Appendix B. The HHRAP algorithms are primarilybased on previous guidance set forth by the U.S. EPA and other regulatory agencies. TheHHRAP algorithms and default assumptions are used except where site-specific considerationssuggest the use of different models and assumptions. Deviations from the HHRAP guidance andits default parameters are noted in the descriptions of the calculations and the impacts of thesedeviations are addressed in the uncertainty evaluations in Chapter 8.

The concentration estimates for a given medium are frequently passed on to another mediumfollowing the natural progression for the transport of compounds in the environment (e.g. soilconcentrations progress to vegetation concentrations which progress to livestock concentrations). Eventually these concentrations are incorporated into human exposure estimates which then leadto estimates of possible health impacts. Air concentrations and depositions rates for each COPChave been described in Chapter 3, and have been used to calculate concentrations in otherenvironmental media in the following order: soil, produce, animal tissue, water, and fish. Onlythe equations and parameters used to calculate COPC concentrations are given in the text below. The COPC-specific properties required for the calculations are given in full in Appendix II, andthe calculated COPC concentrations for each medium are given in Appendix IV.


5–2

Table 5.1 General and site-specific parameters and properties required for the calculation ofCOPC concentrations in various environmental media.

Parameter name Symbol Value Units ReferenceTime duration parametersTime period at beginning ofcombustion T1 0 yrs HHRAP Table B-1-1

Length of exposure, child T2 6 yrs HHRAP Table B-1-1Length of exposure, adult periodfor resident and subsistencefisher

T2 24 yrs HHRAP Table B-1-1

Length of exposure, subsistencefarmer T2 40 yrs HHRAP Table B-1-1

Time period of combustion tD 100 yrs HHRAP Table B-1-1Standard air and waterparametersTemperature ambient Ta 298.1 °K HHRAP Eqn. 5-6ADry deposition velocity Vdv 1.4 cm/s see RAPAir density Da 1200 g/m3 HHRAP Table B-2-8Water density Dw 1 g/cm3 HHRAP Eqn. 5-41Bvon Karman's constant k 0.4 unitless HHRAP Table B-4-20Viscous sublayer thickness 8z 4 unitless HHRAP Table B-4-20Viscosity of water :w 0.0169 g/cm-s HHRAP Table B-4-20Viscosity of air :a 1.81 E-4 g/cm-s HHRAP Table B-4-21Drag coefficient Cd 0.0011 unitless HHRAP Eqn. 5-41B

Ideal gas constant R 8.21 E-5 atm-m3/mol-K at20°C HHRAP Eqn. 5-40

Temperature correction factor 2 1.026 unitless HHRAP Eqn. 5-40Soil related parametersPrecipitation, annual average P 109 cm/yr Geraghty et al.,1973Irrigation, annual average I 0 cm/yr conservative assumption Evapotranspiration, annualaverage Ev 58 cm/yr Geraghty et al.,1973

Surface runoff, annual average RO 51 cm/yr Geraghty et al.,1973Soil mixing zone depth, untilled Zs 1 cm HHRAP Table B-1-1Soil mixing zone depth, tilled Zs 20 cm HHRAP Table B-1-1Soil bulk density BD 1.5 g/cm3 HHRAP Table B-1-1Soil solids particle density Ds 2.7 g/cm3 HHRAP Errata, page 18

Soil volumetric water content 2sw 0.2 unitless HHRAP Table B-1-3, andUSDA (1981)

Soil volumetric water content 2v 0.24 unitless HHRAP Errata, page 18Soil bioavailability Bs 1 unitless HHRAP Table B-3-10Rainfall factor RF 115 yr–1 Wischmeire, 1978Erodability factor K 0.19 ton/acre Soil Conservation Service,

1982Length slope factor LS 0.55 unitless


5–3

Table 5.1 (continued) General and site-specific parameters and properties required for the calculation ofCOPC concentrations in various environmental media.

Parameter name Symbol Value Units ReferenceCover management factor C 0.1 unitless HHRAP Table B-4-13Supporting practice factor PF 1 unitless HHRAP Table B-4-13Sediment delivery ratiocoefficient — Wilcox Pond a 1.92 unitless interpolated from values in

HHRAP Table B-4-14Sediment delivery ratiocoefficient — Goosefare pond a 1.74 unitless

Sediment delivery ratio exponent b 0.125 unitless HHRAP Table B-4-14Sediment delivery ratio —Wilcox Pond SD 0.311 unitless

HHRAP Table B-4-14Sediment delivery ratio —Goosefare pond SD 0.252 unitless

Unit soil loss Xe 0.269 kg/m2-yr HHRAP Table B-4-13Watershed parametersWater temperature Twk 293 °K HHRAP Eqn. 5-30Water body surface area —Wilcox Pond Aw 3.4 E+4 m2

Determined from USGStopological map 7.5 minuteseries

Water body surface area —unnamed Goosefare pond Aw 3.4 E+4 m2

Total watershed area — WilcoxPond A(L) 2.1 E+6 m2

Total watershed area —unnamed Goosefare pond A(L) 5.3 E+6 m2

Impervious watershed area A(I) 1 %Volume flow through water body— Wilcox Pond Vfx 2.0 E+6 m3/yr estimated from precipitation

recharge, CambridgeEnvironmental, 1996Volume flow through water body

— unnamed Goosefare pond* Vfx 5.0 E+6 m3/yr

Suspended solids, total —Wilcox Pond TSS 2.72 mg/L HHRAP Eqn.5-36C

Suspended solids, total —unnamed Goosefare pond TSS 5.31 mg/L HHRAP Eqn.5-36C

Deposition rate, suspended solids Dss 1825 m/yr HHRAP default Eqn.5-36C

Wind speed, average annual W 4.177 m/s averaged from 1986 - 1990hourly data

Water column depth — WilcoxPond* dwc 1.07 m Maine Department of Inland

Fisheries & Wildlife, 2001Benthic sediment depth dbs 0.03 m HHRAP Table B-4-15Porosity, bed sediment 2bs 0.6 unitless HHRAP Table B-4-16Concentration, bed sediment Cbs 1 g/cm3 HHRAP Table B-4-16Fish lipid content flipid 0.07 unitless HHRAP Table B-4-28Organic content of bottomsediment OCsed 0.04 unitless HHRAP Table B-4-28

* The water column depth for Wilcox pond was also used in the modeling of the pond onGoosefare Brook and in the bounding estimates for the Saco River. The TSS concentration forthe pond on Goosefare Brook was also used in the bounding estimates for the Saco River.


5–4

( )( ) ( )

CsD

ks tD TtD

ks tDks

Tks T

kss=

⋅ −⋅ +

− ⋅

− +

− ⋅

1

11exp exp

( )[ ]Cs

D ks tDkstD

s=⋅ − − ⋅1 exp

5.1 COPC concentrations in soil

The incremental concentrations of COPCs in soils due to emissions from the Maine Energyfacility are dependent on the COPC’s air-to-soil deposition rate, the rate at which the COPC islost from or degraded in the soil, and the length of time over which these processes haveoccurred. Two equations are required to calculate the concentrations based on whether they areto be estimated at given moment in time, or averaged over a period of time. The formercalculation is applied to COPCs being evaluated for noncancer health risks, which are notassumed to be dependent on cumulative exposures; the latter calculation is applied to COPCsbeing evaluated for cancer risks, which are based on lifetime average COPC exposures. SomeCOPCs are evaluated for cancer and noncancer risks, therefore both calculations have beenperformed for all COPCs. Because the deposition of COPCs to the soil is assumed to beconstant over the operating lifetime of the Maine Energy facility and the loss of COPCs from thesoil is proportional to their concentrations, the equations predict COPC levels in soil to increaseover time asymptotically approaching a steady state value at which the deposition and loss termswould be equal. Therefore, in order to estimate the highest levels of COPCs in soil to which anindividual might be directly or indirectly exposed, COPC concentrations are calculated fornoncancer risks at the end of the facility’s predicted lifetime, and for cancer risks are averagedover an individual’s assumed exposure duration up to the end of the facility’s predicted lifetime.

The equation used to calculate soil concentrations of COPCs evaluated for cancer risks is:

and the equation used to calculate soil concentrations of COPCs evaluated for noncancer risks is:

where the terms are:

Cs Average soil concentration over exposure duration (mg COPC/kg soil);Ds Deposition term (mg COPC/kg soil/yr);T1 Time period at the beginning of combustion (yr);ks COPC soil loss constant due to all processes (yr–1);tD Time period over which deposition occurs (time period of combustion) (yr); CstD Soil concentration at time tD (mg/kg).

Default values for T1=0, and tD=100 years are taken from HHRAP Appendix Table B-1-1; thevalues for Ds, and ks are calculated below. The deposition term, Ds, is calculated from the COPC


5–5

( ) ( ) ( )[ ]DsQ

Z BDF Vdv Cyv Dywv Dydp Dywp F

sv v=

⋅⋅

⋅ ⋅ ⋅ ⋅ + + + ⋅ −

1000 31536 1.

ks ksg kse ksr ksl ksv= + + + +

atmospheric concentrations and deposition rates determined by the ISCST3 modeling describedin Chapter 3. The ISCST3 values for unitized wet and dry deposition of particles and vapors arecombined with the COPC emission rates (described in Chapter 2) and converted into a soilconcentration deposition term Ds by including the soil mixing depth and density in thedenominator:


Ds Deposition term (mg COPC/kg soil-yr);100 Units conversion factor (mg-m2/kg-cm2);Q COPC emission rate (g/s);Zs Soil mixing zone depth (cm);BD Soil bulk density (g soil/cm3 soil);Fv Fraction of COPC air concentration in vapor-phase (yr–1);0.31536 Units conversion factor (m-g-s/cm-:g-yr);Vdv Dry deposition velocity (cm/s);Cyv Unitized yearly average air concentration in the vapor-phase (:g-s/g-m3);Dywv Unitized yearly average wet deposition from vapor-phase (s/m2-yr);Dydp Unitized yearly average dry deposition from particle-phase (s/m2-yr);Dywp Unitized yearly average wet deposition from particle-phase (s/m2-yr).

The calculation of COPC emission rates, Q, were described in Chapter 2. Based on HHRAPAppendix Table B-1-1, two soil mixing zone depths have been modeled to account for differenttransport and exposure scenarios: 20 cm for tilled soils, and 1 cm for untilled soils. The soil bulkdensity, BD, is 1.5 g/cm3, and the vapor-phase deposition velocity, Vdv, is 1.4 cm/s. Thefraction of each COPC concentration in air in the vapor-phase, Fv, is a COPC-specific parameter.

The loss rate for COPCs from soils is the sum of several terms:


ks COPC soil loss constant due to all processes (yr–1);ksg COPC loss constant due to biotic and abiotic degradation (yr–1);kse COPC loss constant due to soil erosion (yr–1);ksr COPC loss constant due to surface runoff (yr–1);ksl COPC loss constant due to leaching (yr–1);ksv COPC loss constant due to volatilization (yr–1).


5–6

ksv Ke Kt= ⋅

( )[ ]kslP I RO E

Z BD Kdv

sw s s sw

=+ − −

⋅ + ⋅θ θ1 /

( )ksrRO

Z Kd BDsw s s sw

=⋅

⋅+ ⋅

θ θ

11 /

Based on HHRAP Appendix Table B-1-2, kse is taken as zero for all COPC’s at the point ofmaximum emissions impact, but is included in the soil concentration calculations within thewatershed as discussed below in Section 5-4; ksg values are COPC-specific and are based onHHRAP Appendix Tables A-3 and Howard et al. (1991). The other loss terms are calculated asfollows:

Losses of COPCs due to surface runoff and leaching are dependent on the COPC’s soil-waterpartitioning coefficient and the amount of water available for these processes:


ksr COPC loss constant due to surface runoff (yr–1);ksl COPC loss constant due to leaching (yr–1);RO Average annual surface runoff from pervious areas (cm/yr);P Average annual precipitation (cm/yr);I Average annual irrigation (cm/yr);Ev Average annual evapotranspiration (cm/yr);2sw Soil volumetric water content (mL water/cm3 soil);Zs Soil mixing zone depth (cm);Kds Soil-water partition coefficient (mL water/g soil);BD Soil bulk density (g soil/cm3 soil).

Based on HHRAP Appendix Tables B-1-4 and B-1-5, and data from the Geraghty et al. (1973),site-specific values used are RO = 51 cm/yr, P = 109 cm/yr, I = 0 cm/yr, and E = 58 cm/yr;default values used for BD = 1.50 g/cm3 and 2sw = 0.2 mL/cm3, and COPC-specific values areused for Kds.

The calculation of the COPC loss constant due to volatilization, ksv, is described in the HHRAPErrata memorandum (U.S. EPA, 1999, pages 17-19) as the product of the gas equilibriumcoefficient, Ke, and the gas-phase mass transfer coefficient, Kt:


5–7

KeH

Z K R T BDs ds a=

× ⋅⋅ ⋅ ⋅ ⋅

31536 107.

KDZ

BDt

a

s ssw= −

−

1

ρθ

The equilibrium coefficient, Ke, is given by:


Ke COPC gas equilibrium coefficient (s/yr-cm);3.1536×107 Units conversion (s/yr);H Henry’s Law constant (atm-m3/mol);Zs Soil mixing zone depth (cm);Kds Soil-water partition coefficient (mL/kg);R Ideal gas constant (atm-m3/mol-K);Ta Average ambient air temperature (K);BD Soil bulk density (g soil/cm3 soil).

The gas-phase mass transfer coefficient, Kt, is given by:


Kt Gas-phase mass transfer coefficient (cm/s);Da Diffusion coefficient of COPC in air (cm2/s);Zs Soil mixing zone depth (cm);BD Soil bulk density (g soil/cm3 soil);Ds Density of soil solids (g/cm3);2sw Volumetric soil water content (unitless).

Based on HHRAP Appendix Table B-1-3 and the Errata memorandum (U.S. EPA, 1999), defaultvalues are used Zs = 1 cm (untilled) or 20 cm (tilled), Ta = 298 °K, BD = 1.50 g/cm3, 2sw = 0.2mL/cm3, and Ds = 2.7 g/cm3. The ideal gas constant, R, is 8.205 ×10–5 atm-m3/mol-K. COPC-specific values are used for H, Kds and Da.


5–8

( ) ( )[ ] ( )[ ]Pd

Q F Dydp Fw Dywp Rp kp TpYp kpi

v i i

i=

⋅ ⋅ − ⋅ + ⋅ ⋅ ⋅ − − ⋅

⋅

1 000 1 1, exp

5.2 COPC concentrations in produce, grain, and vegetation

Natural vegetation and agricultural produce are assumed to receive COPCs through threemechanisms: direct deposition of particulate COPCs, direct air-to-plant transfer of vapor-phaseCOPCs, and uptake of COPCs in soils through the plant’s root system. The wide range ofvegetation and produce for which COPC concentrations need to be estimated is divided withinthe HHRAP guidance into the following categories: aboveground, belowground, and protectedproduce; forage; silage; and grain. For types of plants with edible portions below ground orotherwise protected from direct atmospheric deposition and transfer, only COPC uptake throughthe plant’s root system is modeled. The equations and parameters needed to calculate COPCconcentrations by all three mechanisms have been evaluated in the HHRAP for each plant type,and are described below.

The concentration of COPCs in the exposed and edible portions of vegetation due to directatmospheric deposition of particles is calculated by:


Pdi Plant (aboveground produce) concentration due to direct (wet and dry)deposition (mg COPC/kg DW);

1,000 Units conversion factor (mg/g);Q COPC emission rate (g/s);Fv Fraction of COPC air concentration in vapor-phase (unitless);Dydp Unitized yearly average dry deposition from particle-phase (s/m2-yr);Fw Fraction of COPC wet deposition that adheres to plant surfaces (unitless);Rpi Interception fraction of the edible portion of plant for the ith plant group

(unitless);kp Plant surface loss coefficient (yr–1);Tpi Length of plant exposure to deposition per harvest of the edible portion of the

ith plant group (yr);Ypi Yield or standing crop biomass of edible portion of the ith plant group (kg

DW/m2).

Values of Rp, kp, Tp, and Yp for the various plant groups are given in Table 5.2. Values forabove ground produce are from HHRAP Appendix Table B-2-7, and the values for forage andsilage from Table B-3-7. Based on HHRAP Appendix Table B-3-7, Fw is 0.2 for anions and 0.6for cations and all organic COPCs examined in this report.


5–9

Pr = ⋅Cs Br

Pv Q FCyv Bv VG

vag ag

= ⋅ ⋅⋅ ⋅

ρα

Table 5.2 Parameters for calculating the direct particle-phase deposition of COPCs toexposed vegetation and produce.

Rp (unitless) kp (yr–1) Tp (yr) Yp (kg DW/m2)

Abovegroundproduce 0.39 18 0.164 2.24

Forage 0.5 18 0.12 0.24

Silage 0.46 18 0.16 0.8

The concentration of COPCs in the exposed and edible portions of vegetation due to directtransfer from the vapor-phase is calculated by:


Pv Concentration of COPC in the plant resulting from air-to-plant transfer (:gCOPC/g DW);

Q COPC emission rate (g/s);Fv Fraction of COPC air concentration in vapor-phase (unitless);Cyv Unitized yearly average air concentration from vapor-phase (:g- s/g-m3);Bvag COPC air-to-plant biotransfer factor ([mg COPC/g DW]/[mg COPC/g air])

(unitless);VGag Empirical correction factor for aboveground produce (unitless);Da Density of air (g/m3).

The parameter Bvag is COPC-specific; for aboveground produce the parameter VGag is 0.01 forCOPCs with a log Kow greater than 4, and 1.0 for COPCs with a log Kow less than 4; for foragethe parameter VGag is 1, for silage the parameter VGag is 0.5.

The concentration of COPCs in vegetation due to transfer from soil through the roots ofvegetation is calculated for exposed and protected aboveground produce, forage, silage, andgrain by:

and for belowground produce by:


5–10

( )( )A F Qp P Qs Cs Bs Baj i ij ij j j= ⋅ ⋅ + ⋅ ⋅ ⋅∑

Pr =⋅ ⋅

⋅

Cs RCF VGKd

rootveg

s 1kg / L


Pr Concentration of COPC in produce due to root uptake (:g COPC/g DW);Br Plant-soil bioconcentration factor for produce (unitless);VGrootveg Empirical correction factor for belowground produce (unitless);Kds Soil-water partition coefficient (mL/kg);Cs Average soil concentration over exposure duration (mg COPC/kg soil);RCF Root concentration factor (unitless).

The values for Br for each aboveground plant type, and Kds and RCF for belowground produceare COPC-specific and either derived from HHRAP Appendix Table A-3, or from thecorrelations in HHRAP Appendix A-3; for the parameter VGrootveg is 0.01 for COPCs with a logKow greater than 4, and 1.0 for COPCs with a log Kow less than 4.. Although some types ofvegetation, such as forage, are not likely to be grown in tilled soil, the HHRAP recommends(page 5-20) that the COPC concentrations in soil be derived from the tilled soil calculations toreflect the depth of the plants’ root zone.

5.3 COPC concentrations in livestock and related farm products

The COPC concentrations in animal tissues (beef, pork, chicken) and dairy products (milk, eggs)are determined by the COPC concentrations in the various parts of the animal’s diets (includingsoil), each component’s intake rate, and COPC-to-animal product biotransfer functions:


Aj Concentration of COPC in animal product j (mg COPC/kg);Fi Fraction of plant type I grown in contaminated soil and ingested by the animal

(unitless);Qpij Quantity of plant type I eaten by animal type j each day (kg DW plant/day);Pi Concentration of COPC in plant type I eaten by the animal type j (mg/kg

DW);Qsj Quantity of soil eaten by animal type j each day (kg soil/day);Cs Average soil concentration over exposure duration (mg COPC/kg soil);


5–11

Bs Soil bioavailability factor (unitless).

The intake rates (Q’s) for each animal group are shown in Table 5.3 (HHRAP Appendix B-3-10for beef, B-3-11 for milk, B-3-12 for pork, B-3-13 for eggs and B-3-14 for chicken). Both thefraction of plants grown in contaminated soil, Fi, and the soil bioavailability factor, Bs, areassumed to be equal to one. All soil ingested by farm animals is assumed to be untilled.

Table 5.3 Intake rates of various feed types and soil required for the calculation of COPCconcentrations in farm animals and animal products.

AnimalAnimal food material intake rate (kg/day) (dry weight basis)

forage silage grain soil

beef (cattle) 8.8 2.5 0.47 0.5

milk (cows) 13.2 4.1 3 0.4

pork (pigs) 0 1.4 3.3 0.37

chicken/eggs(chickens) 0 0 0.2 0.022

5.4 COPC concentrations in surface water

As described in Chapter 3, potential COPC impacts are estimated for two small ponds withwatersheds in areas that are projected to receive the highest deposition levels of contaminantsfrom the Maine Energy facility. The two ponds were identified from topographic maps of thearea, in conjunction with the patterns of projected impacts over the modeling domain. The firstis an unnamed pond located about 3.3 km northwest of the Maine Energy facility. This pond liesjust to the east of Goosefare Hill, and is fed by Goosefare and Innis Brooks. The second isWilcox Pond, which is situated about 2.8 km to the south of the Maine Energy facility.

The concentrations of COPCs in these ponds have been calculated using the following equation,which includes terms for the total input (loading) and loss (outflow and dissipation) of COPCsfrom the water body:

( )CL

Vf f k A d dwtotT

x wc wt W wc bs

=⋅ + ⋅ ⋅ +



5–12

Ctot Total water body COPC concentration (including water column and bedsediment) (g COPC/m3 water body);

LT Total COPC load to the water body (g/yr);VfX Average volumetric flow rate through the water body (m3/yr);fwc Fraction of total water body COPC concentration in the water column

(unitless);kwt Overall total water body COPC dissipation rate constant (yr–1);Aw Water body surface area (m2);dwc Depth of water column (m);dbs Depth of upper benthic sediment layer (m).

The relevant parameters for Wilcox Pond and the unnamed Goosefare pond were estimated inthe 1996 Maine Energy Risk Assessment Report (Cambridge Environmental, 1996). Theaverage volumetric flow rate through Wilcox Pond is 2 × 106 m3/yr; the average volumetric flowrate through the unnamed Goosefare pond is 5 × 106 m3/yr. The surface area of both ponds is3.4 × 104 m2; and the average depth of the water column is 1.07 m (Maine Department of InlandFisheries & Wildlife, 2001). The depth of the upper benthic sediment layer is taken as 0.03 mbased on HHRAP Appendix Table B-4-15. Because the terms for COPC loading, dissipation,and fractionation are each dependent on the calculation of several additional terms, thedeterminations of LT, kwt, and fwc are described separately below.

Potential COPC impacts on surface water quality in the Saco River are estimated based on asimplified bounding model which assumes that all the COPCs emitted from the Maine Energyfacility enter the Saco River directly, as was done in the 1996 Maine Energy Risk Assessment(Cambridge Environmental, 1996). The methods for these estimates are described in section5.4.3 following the methods for estimating COPC impacts on the small ponds near the facility.

5.4.1 COPC loading to nearby ponds

The total COPC loading to the water body is comprised of direct wet and dry deposition ofparticulate-phase COPCs, direct wet deposition and diffusion of vapor-phase COPCs, runoff ofCOPCs from pervious and impervious surfaces within the watershed, erosion of COPCcontaining soils from within the watershed into the water body, and internal chemical orbiological transformation of COPCs. The following equation gives the sum of these terms; thecalculation of each of these terms are defined below.

L L L L L L LT DEP dif RI R E I= + + + + +


LT Total COPC load to the water body (g/yr);LDEP Total (wet and dry) particle-phase and wet vapor-phase COPC direct

deposition load to the water body (g/yr);


5–13

Ldif Vapor-phase COPC diffusion (dry deposition) load to the water body (g/yr);LRI Runoff load from impervious surfaces (g/yr);LR Runoff load from pervious surfaces (g/yr);LE Soil erosion load (g/yr);LI Internal transfer (g/yr).

The loading terms are calculated as follows:

The direct wet deposition of atmospheric vapor-phase COPCs and the total wet and drydeposition of atmospheric particulate-phase COPCs is simply the product of their averagewatershed unitized deposition rates (as determined by the ISCST3 air modeling described inChapter 4), their emission rates, and the surface area of the lake.

( )[ ]L Q F D F D ADEP V ywwv V ytwp W= ⋅ ⋅ + − ⋅ ⋅1


LDEP Total (wet and dry) particle-phase and wet vapor-phase COPC directdeposition load to the water body (g/yr);

Q COPC emission rate (g/s);FV Fraction of COPC air concentration in the vapor-phase (unitless);Dywwv Unitized yearly (water body and watershed) average wet deposition from

vapor-phase (s/m2-yr);Dytwv Unitized yearly (water body and watershed) average total (wet and dry);

deposition from particulate-phase (s/m2-yr);AW Water body surface area (m2).

Atmospheric vapor-phase COPCs are also transferred to surface waters by direct air-to-waterdiffusion as determined by the COPC’s emission rate, unitized air concentration, vapor fraction,and Henry’s law constant, by a COPC-specific mass transfer coefficient (calculated as shownbelow), and by the lake’s surface area.

LK Q F C A

HR T

difV V ywv W

wk

=⋅ ⋅ ⋅ ⋅ ⋅ ×

⋅

−1 10 6


Ldif Vapor-phase COPC diffusion (dry deposition) load to the water body (g/yr);KV Overall COPC transfer rate coefficient (m/yr);Q COPC emission rate (g/s);FV Fraction of COPC air concentration in the vapor-phase (unitless);


5–14

Cywv Unitized yearly (water body and watershed) average air concentration fromvapor-phase (:g-s/m2-yr);

AW Water body surface area (m2);10–6 Units conversion factor (g/:g);H Henry’s Law constant (atm-m3/mol);R Universal gas constant (atm-m3/mol-K);Twk Water body temperature (K).

The value for Kv, the overall COPC transfer rate coefficient, is determined using the followingseries of equations:

K K KH

R TV L Gwk

Twk= + ⋅⋅

⋅−

− −

−1

1 1

293θ


KV Overall COPC transfer rate coefficient (m/yr);KL Liquid-phase transfer rate coefficient (m/yr);KG Gas-phase transfer rate coefficient (m/yr);H Henry’s Law constant (atm-m3/mol);R Universal gas constant (atm-m3/mol-K);Twk Water body temperature (K);2 Temperature correction factor (unitless).

For quiescent lakes or ponds:

( )K C Wk

DL da

w z

w

w w= ⋅ ⋅

⋅ ⋅

⋅

⋅ ×−

0 5

0 5 0 33 0 67

731536 10.

. . .

.ρρ λ

µρ


KL Liquid-phase transfer rate coefficient (m/yr);Cd Drag coefficient (unitless);W Average annual wind speed (m/s);Dw Diffusivity of COPC in water (cm2/s);Da Density of air (g/cm3);Dw Density of water (g/cm3);k von Karman’s constant (0.4, unitless);8z Dimensionless viscous sublayer thickness (unitless);:w Viscosity of water corresponding to water temperature (g/cm-s);3.1536×107 Units conversion factor (s/yr);

and


5–15

( )K C Wk

DG dz

w

w w= ⋅ ⋅ ⋅

⋅

⋅ ×−

0 50 33 0 67

731536 10.. .

.λ

µρ


KG Gas-phase transfer rate coefficient (m/yr);Cd Drag coefficient (unitless);W Average annual wind speed (m/s);Dw Diffusivity of COPC in water (cm2/s);Da Density of air (g/cm3);k von Karman’s constant (0.4, unitless);8z Dimensionless viscous sublayer thickness (unitless);:w Viscosity of water corresponding to water temperature (g/cm-s);3.1536×107 Units conversion factor (s/yr).

The loading of COPCs to the lake by direct surface runoff of rainwater from impervious surfaceswithin the watershed is calculated similarly to the direct deposition of COPCs but with theimpervious surface area of the watershed substituted for surface area of the water body itself:

( )[ ]L Q F Dywwv F Dytwp ARI V V I= ⋅ ⋅ + − ⋅ ⋅1


LRI Runoff load from impervious surfaces (g/yr);Q COPC emission rate (g/s);FV Fraction of COPC air concentration in the vapor-phase (unitless);Dywwv Unitized yearly (water body and watershed) average wet deposition from

vapor-phase (s/m2-yr);Dytwv Unitized yearly (water body and watershed) average total (wet and dry)

deposition from particulate-phase (s/m2-yr);AI Impervious watershed area receiving COPC deposition (m2).

The values for AI, the impervious watershed areas receiving COPC deposition, has beenestimated as 2.1×104 m2 for Wilcox Pond and as 5.3×104 m2 for the unnamed Goosefare pond,using an estimate of 1% impervious areas in the watersheds based on the USGS.

The next two loading terms (LR , the COPC loading due to water runoff from pervious surfaces,and LE, the COPC loading due to the erosion of soil) are proportional to the average COPCconcentrations in the watershed soils. The COPC concentrations in the watershed soils wereestimated using the same equations as were employed in Section 5.2 with the following inputvalues, parameters, and additions:


5–16

The COPC air concentration and deposition terms (Cyv, Dywv, Dydp, and Dywp) areevaluated for the average values over the entire watershed rather than at the location ofmaximum impact, the soil mixing zone depth is assumed to be 1 cm, the value for untilled soil, based on theevaluation that the land within the watershed is not primarily used as cropland (IDEM,2001b), anda non-zero term for the COPC loss constant due to soil erosion, kse, has been used asdescribed below.

For calculating kse, the loss rate for COPCs from the soil within an area due to the erosion of soilfrom the area, the HHRAP gives the following equation:

( )kseX SD ERBD Z

Kd BDKd BD

e

s

s

sw s

=⋅ ⋅ ⋅

⋅⋅

⋅

+ ⋅

01.θ


kse COPC soil loss constant due to erosion (yr–1);0.1 Units conversion factor (1,000 g-kg/10,000 cm2-m2);Xe Unit soil loss (kg/m2-yr);SD Sediment delivery ratio (unitless);ER Soil enrichment ratio (unitless);Kds Soil-water partition coefficient (mL water/g soil);BD Soil bulk density (g soil/cm3 soil);Zs Soil mixing zone depth (cm);2sw Soil volumetric water content (mL water/cm3 soil).

The unit soil loss, Xe, and the sediment delivery ratio, SD are calculated using equationsdescribed below. The HHRAP default values of 1.5 g/cm3 for BD, 1 cm for Zs, and 0.2 mLwater/cm3 for 2sw are used. Kds is a COPC-specific property.

The HHRAP guidance recommends that the constant kse should be set equal to zero based on theassumption that the amount of contaminated soil eroding off of the site being evaluated iscountered by a roughly equal amount of contaminated soil eroding onto the site. While this isperhaps a valid assumption for receptor sites the size of a residential property or farm, it is not avalid assumption for the evaluation of a watershed as a whole because, by definition, there is noflow of water (or by extension soil eroded by flowing water) into a watershed from areas outsideits boundary. COPCs emitted from the Maine Energy facility and subsequently bound towatershed soils that are eroded from the land areas of the watershed are not replaced by COPCsemitted from the Maine Energy facility eroding into the watershed. Additionally, if the loadingof COPCs into the water body by the erosion of watershed soils is included in the transportmodeling (by the water body loading term LE, described below), then this must be balanced by


5–17

the loss of COPCs from the same soils. For these reasons a non-zero value for kse has been usedin the calculation of average COPC concentrations within the watershed.

The loading to the water body caused by runoff of dissolved COPCs from pervious soils iscalculated by:

( )L RO A ACs BD

Kd BDR L Isw s

= ⋅ − ⋅⋅

+ ⋅⋅

θ0 01.


LR Runoff load from pervious surfaces (g/yr);RO Average annual surface runoff from pervious areas (cm/yr);AL Total watershed area receiving COPC deposition (m2);AI Impervious watershed area receiving COPC deposition (m2);Cs Average soil concentration over exposure duration (in watershed soils) (mg

COPC/ kg soil);BD Soil bulk density (g soil/cm3 soil);2sw Soil volumetric water content (mL water/cm3 soil);Kds Soil-water partition coefficient (mL water/g soil);0.01 Units conversion factor (kg-cm2/mg-m2).

The values for RO, AL, and AI are site-specific as described in Table 5.1; Cs is calculated asdescribed in Section 5.1 for untilled soils, with the inclusion of a term for COPC loss by erosion,kse. The HHRAP default values of 1.5 g/cm3 for BD, and 0.2 mL water/cm3 for 2sw are used. Kds is a COPC-specific property.

The loading due to COPCs associated with eroding soils entering the water body is calculatedby:

( )L X A A SD ERCs Kd BD

Kd BDE e L Is

sw s= ⋅ − ⋅ ⋅ ⋅

⋅ ⋅+ ⋅

⋅θ

0 001.


LE Soil erosion load (g/yr);Xe Unit soil loss (kg/m2-yr);AL Total watershed area receiving COPC deposition (m2);AI Impervious watershed area receiving COPC deposition (m2);SD Sediment delivery ratio (watershed) (unitless);ER Soil enrichment ratio (unitless);Cs Average soil concentration over exposure duration (in watershed soils) (mg

COPC/ kg soil);


5–18

BD Soil bulk density (g soil/cm3 soil);2sw Soil volumetric water content (mL water/cm3 soil);Kds Soil-water partition coefficient (mL water/g soil);0.001 Units conversion factor (mg/g).

The soil enrichment ratio, ER, is 1 for inorganic COPCs and 3 for organic COPCs. HHRAPdefault values from Appendix Table B-4-11 of 1.5 g/cm3 are used for BD, and 0.2 mL water/cm3

for 2sw. Kds is a COPC-specific property. The value for unit soil loss for the watershed, Xe, iscalculated by applying the Universal Soil Loss Equation (USLE):

X RF K LS C PFE = ⋅ ⋅ ⋅ ⋅ ⋅907184047

.


Xe Unit soil loss (kg/m2-yr);RF USLE rainfall (or erosivity factor) (yr–1);K USLE erodability factor (ton/acre);LS USLE length-slope factor (unitless);C USLE cover management factor (unitless);PF USLE supporting practice factor (unitless);907.18 Units conversion factor (kg/ton);4047 Units conversion factor (m2/acre).

The value of 115 for RF was taken from Figure 1 of Wischmeire (1978), while values of 0.39tons per acre for K, 1.5 for LS, 0.1 for C, and 1 for PF are based on default values found inHHRAP Appendix Table B-4-13.

The sediment delivery ratio, SD is calculated as 0.082 by the empirical correlation:

( )SD a AL

b= ⋅

−


SD Sediment delivery ratio (watershed) (unitless);a Empirical intercept coefficient (unitless);b Empirical slope coefficient (unitless);AL Total watershed area receiving COPC deposition (m2).

Values for the coefficients a and b are derived from HHRAP Appendix Table B-4-14. The slopecoefficient, b, is 0.125. The value of the intercept coefficient a has been logarithmicallyinterpolated as 1.7 for Wilcox Pond and 1.9 for the unnamed Goosefare pond based on the valuesfor the intercept coefficients from HHRAP Table B-4-14.


5–19

5.4.2 COPC dissipation in nearby ponds

The dissipation rate of COPCs from the water body is the sum of losses through volatilizationfrom the water surface and burial to bottom sediments:

k f k f kwt wc v bs b= ⋅ + ⋅


kwt Overall total water body dissipation rate constant (yr–1);fwc Fraction of total water body COPC concentration in the water column

(unitless);kv Water column volatilization rate constant (yr–1);fbs Fraction of total water body COPC concentration in the benthic sediment

(unitless);kb Benthic burial rate constant (yr–1).

The two loss terms are given by:

( )kK

d Kd TSSvv

z sw

=⋅ + ⋅ ⋅ × −1 1 10 6


kv Water column volatilization rate constant (yr–1);Kv Overall COPC transfer rate coefficient (m/yr);dz Total water body depth;Kdsw Suspended sediments/surface water partition coefficient (L water/kg suspended

sediments);TSS Total suspended solids concentration (mg/L);1×10-6 Units conversion factor (kg/mg); and

kX A SD Vf TSS

A TSSTSS

C dbe L x

w BS bs=

⋅ ⋅ ⋅ × − ⋅⋅

⋅

⋅ ×⋅

−1 10 1 103 6


5–20


kb Benthic burial rate constant (yr–1);Xe Unit soil loss (kg/m2-yr);AL Total watershed area receiving COPC deposition (m2);SD Sediment delivery ratio (watershed) (unitless);Vfx Average volumetric flow rate through the water body (m3/yr);TSS Total suspended solids concentration (mg/L);Aw Water body surface area (m2);CBS Bed sediment concentration (g/cm3);dbs Depth of upper benthic sediment layer (m);1×10-6 Units conversion factor (kg/mg);1×103 Units conversion factor (g/kg).

Values for the watershed’s unit soil loss, Xe, and sediment delivery ratio, SD, were calculatedbased on equations described above. Values for the total watershed area, AL, the water bodyarea, AW, average volumetric flow rate, Vfx, and total suspended solids concentration, TSS, havebeen based on site-specific data also described above, and HHRAP default values fromAppendix Table B-4-16 were used for the bed sediment concentration, CBS, and the depth of theupper benthic sediment layer, dbs.

5.4.3 COPC partitioning in nearby ponds

It is necessary to calculate the partitioning of COPCs within the water body in order to accountfor COPC loss to outflow (the Vfx @fwc term in the equation for Cwtot), and to employ the correctCOPC concentrations in the calculations for COPC concentrations in fish and in drinking water. The partitioning divides concentrations of the compounds between the water column and thebenthic sediments, and within the water column between concentrations in the dissolved-phaseand bound to suspended sediments. The fraction of each COPC within the water column is givenby:

( )( ) ( )f

Kd TSS d d

Kd TSS d d Kd C d dwcsw wc z

sw wc z bs bs BS bs z

=+ ⋅ ⋅ × ⋅

+ ⋅ ⋅ × ⋅ + + ⋅ ⋅

−

−

1 1 10

1 1 10

6

6 θ

the balance of each COPC in the water body is contained within the benthic sediment:

f fbs wc= −1


5–21


fwc Fraction of total water body COPC concentration in the water column(unitless);

fbs Fraction of total water body COPC concentration in benthic sediment(unitless);

Kdsw Suspended sediments/surface water partition coefficient (L water/kgsuspended sediment);

TSS Total suspended solids concentration (mg/L);1×10-6 Units conversion factor (kg/mg);dz Total water body depth (m);2bs Bed sediment porosity (Lwater/Lsediment);Kdbs Bed sediment/sediment pore water partition coefficient (L water/kg bottom

sediment);CBS Bed sediment concentration (g/cm3 [equivalent to kg/L]);dwc Depth of water column (m);dbs Depth of upper benthic sediment layer (m).

The average water column depth, dwc, of 1.07 m is based on data from the Maine Department ofInland Fisheries & Wildlife (2001) for Wilcox Pond; the same depth is assumed for the pond onGoosefare Brook. The values for 2bs of 0.6, CBS of 1 g/cm3, and dbs of 0.03 m, are default valuesfor HHRAP Appendix Tables B-4-15 and B-4-16: Total water body depth dz is the sum of dwcand dzbs. The partitioning coefficients Kdsw, and Kdbs are COPC-specific.

The concentration of total suspended solids (TSS) within the water column can be estimatedusing the following equation:

( )TSS

X A A SDVf D A

e L I

x ss W=

⋅ − ⋅ ⋅ ×+ ⋅

1 103


TSS Total suspended solids concentration (mg/L);Xe Unit soil loss (kg/m2-yr);AL Total watershed area receiving COPC deposition (m2);AI Impervious watershed area receiving COPC deposition (m2);SD Sediment delivery ratio (watershed) (unitless);1×103 Units conversion factor (L/m3);Vfx Average volumetric flow rate through the water body (m3/yr);Dss Suspended solids deposition rate (a default value of 1,825 for quiescent lakes

and ponds) (m/yr);Aw Water body surface area (m2).


5–22

The concentration of each COPC within the water body (Cwtot) is apportioned between the watercolumn (Cwctot), which has both dissolved-phase COPCs (Cdw) and COPCs bound to suspendedsediments, and COPCs sorbed to the bed sediments (Cbs) as follows:

C f Cd d

dwctot wc wtotwc bs

wc= ⋅ ⋅

+


Cwctot Total COPC concentration in water column (mg COPC/L water column);fwc Fraction of total water body COPC concentration in the water column

(unitless);Cwtot Total water body COPC concentration, including water column and bed

sediment (mg COPC/L water column);dwc Depth of water column (m);dbs Depth of upper benthic sediment layer (m);

CC

Kd TSSdwwctot

sw=

+ ⋅ ⋅ × −1 1 10 6


Cdw Dissolved-phase water concentration (mg COPC/L water);Cwctot Total COPC concentration in water column (mg COPC/L water column);Kdsw Suspended sediments/surface water partition coefficient (L water/kg

suspended sediment);TSS Total suspended solids concentration (mg/L);1×10–6 Units conversion factor (kg/mg); and

C f CKdKd C

d ddsb bs wtot

bs

bs bs BS

wc bs

bs= ⋅ ⋅

+ ⋅

⋅

+

θwhere the terms are:

Csb COPC concentration sorbed to bed sediment (mg COPC/kg sediment);fbs Fraction of total water body COPC concentration in benthic sediment

(unitless);Cwtot Total water body COPC concentration, including water column and bed

sediment (mg COPC/L water column);Kdbs Benthic sediments/sediment pore water partition coefficient (L water/kg

sediment);2bs Bed sediment porosity (Lwater/Lsediment);


5–23

CQ

VSaco=

CBS Bed sediment concentration (g/cm3);dwc Depth of water column (m);dbs Depth of upper benthic sediment layer (m).

The distribution fractions, fwc and fbs, have been calculated based on equations described above. The depth of the water column, dwc, and the total suspended solids concentration, TSS, are site-specific parameters. The depth of the upper benthic sediment layer, dbs, the bed sedimentporosity, 2bs, and the bed sediment concentration, CBS,, are HHRAP default parameters fromAppendix Table B-4-16. Finally, the partitioning coefficients, Kdsw and Kdbs, are COPC-specificproperties.

5.4.4 Bounding estimates of COPC impacts on Saco Riverwater

The Saco River originates roughly 190 km (120 miles) from Biddeford in the White Mountainsof New Hampshire and its watershed covers approximately 4,400 km2 (1,700 square miles). Because the EPA generally considers steady-state Gaussian plume models such as ISC andAERMOD to be applicable only up to a distance of 50 km (40 CFR 51, App. W), using theprograms to estimate model COPC dispersion and deposition to the whole area is neitherpractical nor recommended. Therefore, a conservative screening analysis has been performed toassess the maximum potential impacts emissions from the Main Energy facility might have onCOPC concentrations in the Saco River. As a worst-case, bounding estimate, it is assumed thatthe impacts can be no larger than if all of the COPCs emitted from the Maine Energy facilityentered the Saco River directly. This method of estimating COPC impacts in the Saco River is asignificant overestimation, because only a small fraction of the facility’s emissions will actuallylikely enter the Saco River. The Saco River watershed includes only a small portion of the areaaround the Maine Energy facility, and only emissions that are transported to west from thefacility can even potentially enter the watershed. Moreover, this bounding analysis assumes thatprecipitation scavenging effectively deposits COPCs close to the facility. Even if 100%effective, however, precipitation scavenging could only be important the fraction of time that itsnows or rains. Under this assumption, the concentration of COPCs in water is determined bydividing the rate of COPC emissions by the rate at which water flows in the river:

where the terms are:C COPC concentration in river water (mg/l);Q total emission rate of COPC from Maine Energy (mg/s); andVSaco volume flow of water in the Saco River (l/s).

As in the 1996 Maine Energy Risk Assessment (Cambridge Environmental, 1996), the averagedischarge of the Saco River (VSaco) at Biddeford is estimated to be 96,600 l/s based on the


5–24

average measured discharge of the river at Cornish Maine (2,695 ft3/s = 76,300 l/s, based onlong-term gauging) multiplied by the ratio of drainage area at Biddeford (1636 mi2) to that atCornish (1293 mi2).

To model the partitioning of COPCs in the Saco River among the dissolved, suspendedsediment, and benthic sediment phases, the same water column depth and total suspendedsediment concentrations as for the Goosefare Pond were used. Although the Saco River is a verydifferent water body than the Goosefare Pond, based on available data, the values of theseparameters are fairly similar. Based on the USGS map for Biddeford Maine, the depth of theSaco River down stream of the facility varies from areas shown as tidal flats, to sections withdepths of only 1 to 2 feet (0.3 to 0.6 meters), to central sections with depths from about 8 to 22feet (2.4 to 6.7 meters). The depth of the river in this area also varies with the tide. Upstream ofthe facility, the river is significantly narrower, so the deep sections present downstream do notoccur. Depths at the upstream gaging station vary over the seasons, with an average depth overthe past 5 years of approximately 4.3 feet (1.3 meters, http://nwis.waterdata.usgs.gov/nwis/measurements, site17 number 01066000). The average water column depth for GoosefarePond used in the modeling is 3.5 feet (1.07 meters). Measured TSS levels in the Saco River varyover the course of a year ranging from 1 to 11 mg/L (USGS Water Resources Data, Maine,Water year 1994, U.S. Department of the Interior). A simple average of measured TSS valuescollected from November 1, 1993 through July 27, 1994 gives a TSS concentration of 5.2 mg/L.The calculated TSS concentration for Goosefare pond is 5.3 mg/L. Although the use of thesevalues may over or underestimate the COPC partitioning to relevant compartments in the SacoRiver, the uncertainty in the partitioning is minor relative to the significant overestimates ofCOPC loadings to the river due to the use of the simple bounding estimate described above.

5.5 COPC concentrations in fish

The concentration of COPCs in fish is calculated using either a COPC-specific bioconcentrationfactor (BCF, for compounds with a log Kow less than 4.0), a COPC-specific bioaccumulationfactor (BAF, for compounds with a log Kow greater than 4.0), or a biota-sediment accumulationfactor (BSAF, for compounds which are extremely hydrophobic and listed as such in the HHRAPAppendix Tables A-3: PCDDs, PCDFs, and PCBs). Depending on which factor is appropriate,one of three equations has been used to calculate COPC concentrations in fish tissue:

C C BCFfish dw fish= ⋅

C C BAFfish dw fish= ⋅

CC f BSAF

OCfishsb lipid fish

sed=

⋅ ⋅



5–25

Cfish Concentration of COPC in fish (mg COPC/kg FW tissue);Cdw Dissolved-phase COPC concentration in water (mg COPC/L);Csb Concentration of COPC sorbed to bed sediment (mg COPC/kg bed sediment);BCFfish Bioconcentration factor for COPC in fish (l/kg);BAFfish Bioaccumulation factor for COPC in fish (l/kg);BSAFfish Biota-to-sediment accumulation factor for COPC in fish (unitless);flipid Fish lipid content (unitless);OCsed Fraction of organic carbon in bottom sediment (unitless).

The COPC concentrations dissolved in lake water and sorbed to bed sediments were calculatedas described above; the BCFfish, BAFfish, and BSAFfish values are based on HHRAP AppendixTables A-3 or guidance for their calculation in HHRAP Appendix A-3; a site-specific value forthe BAFfish of mercury has been used in the calculations. Justification for and a derivation of thevalue used is described in below. An flipid value of 0.07, and a OCsed value of 0.04 were based ondefault values from HHRAP Appendix Table B-4-28.

5.5.1 The use of a site-specific value for the BAFfish formercury

A critical parameter in the estimation of mercury levels in fish through the use of the HHRAPalgorithms is the mercury bioaccumulation factor (BAF). This factor is the assumed ratio of themercury concentration in fish tissue to the mercury concentration in surface water. DifferentBAFs may be derived for different types of fish (larger, older fish tend to have higher mercuryconcentrations, as do fish that are higher up on the food chain), and based on different sorts ofmercury measurements (e.g., total, dissolved, or methyl mercury concentrations in surfacewaters). Because the potential noncancer health effects estimated to be caused by the MaineEnergy facility emissions may be dominated by incremental mercury concentrations in local fish,it is essential that the value and form of this parameter provides as realistic an estimate ofmercury levels in fish as possible. The transport and transformation of mercury from theambient atmosphere to fish tissues involves a complex set of processes, many of which and notentirely well understood or well characterized in all but the most well studied systems.

The bioaccumulation of Hg in fish is not a simple chemical partitioning but is dependent on avariety of parameters as the Hg progresses up the food chain to trophic level 4 fish. Thetransformation of mercury from inorganic species into methyl mercury and the subsequentbiotransfer of methyl mercury up the food chain at a specific location is affected not only by thesimple physical properties of the lake, but also by its surface and sediment chemistry and by thevarious species which make up its biological community. The U.S. EPA’s Mercury Report toCongress (U.S. EPA, 1997a; Vol. III, page 8-2), states that “the BAF value contains a substantiallevel of uncertainty.” The HHRAP guidance (Appendix Table B-4-27) specifically notes that“The COPC-specific BAF values may not accurately represent site-specific water body


5–26

conditions, because estimates of BAFs can vary, based on experimental conditions.” The PeerReview Comments on the HHRAP explicitly address this issue:

“...major data gaps and limitations associated with fate and transport modeling are...noted[as]: mercury behavior in watersheds, and mercury bioaccumulation in fish...We believethat these data gaps are sufficiently large so that regulatory decisions should not be madewithout more detailed evaluations of these issues” U.S. EPA, 2000, page 100).

The fact that mercury methylation and bioaccumulation are the subjects of major, currentresearch efforts underlines both the scientific complexities and the modeling uncertaintiesassociated with the process. The use of a single parameter to model the final step of thiscomplex set of processes is a great oversimplification of the actual mechanisms that transformionic, inorgainc mercury in surface waters into organic mercury in fish tissues.

The bioaccumulation factor (BAF) recommended for methyl mercury, in Appendix Table A-3-140 of the HHRAP is 6,800,000 l/kg. There are three reasons that this value and form of themercury BAFfish will not be applied in this risk assessment. First, this value, according to theequation in Appendix Table B- 4-27, is to be applied to the total of the dissolved-phaseconcentrations of ionic and methyl mercury for estimating methyl mercury levels in trophic level4 (piscivorous) fish. The reference for BAF is the 1997 U.S. EPA Mercury Study Report toCongress (U.S. EPA, 1997a). This BAF value is found specifically in Volume III, Appendix Din section D.3.4.1 “Bioaccumulation Factors Directly Estimated from Field Data – Methylmercury in Piscivorous Fish.” The definition given for the BAF in the original document is:“average methyl mercury concentrations in piscivorous fish (trophic level 4) divided by averagedissolved methyl mercury concentrations in water, accumulated by all possible routes ofexposure.” This BAF is not derived from the methyl mercury concentration in trophic level 4fish divided by dissolved total mercury concentration in water as described in the HHRAP. Hence the HHRAP-recommended value is inappropriate as used in the guidance, as it should notbe applied to the sum of the methyl and ionic mercury concentrations in water.

Second, the use of a mercury BAFfish based on methyl mercury concentrations in surface watersis problematic because the estimation of methyl mercury concentrations in the HHRAP is basedon very simple default transformation and partitioning coefficients. Also, the measurement ofmethyl mercury levels in waterbodies is subject to a greater degree of analytic error than themeasurement of total mercury and is more affected by seasonal and other environmentalvariations (U.S. EPA, 1997a). A mercury BAFfish based on total mercury levels in waterbodiesprovides a more reliable and stable value than one based on methyl mercury levels. Modeling ofmercury bioaccumulation based on the total mercury BAF also allows easier benchmarking ofestimated waterbody concentrations because these are most often measured as total mercuryrather than methyl mercury. A BAF of 500,000 based on total dissolved mercury levels andtrophic level 4 fish is derived in the Mercury Study Report to Congress(U.S. EPA, 1997a,Volume 3, Appendix D).


5–27

Third, and perhaps most importantly, because the transformation of mercury from inorganicforms into methyl mercury at a specific location is affected not only by the simple physical andchemical properties of the mercury compounds involved, but also by the site-specific watershed,surface water, and sediment chemistry, and by the various biological species which are present,it is preferable to use a BAF that is derived in waterbodies that are as close to the ones beingevaluated as possible. The mercury BAFfish recommended in the HHRAP is derived from theresults of four studies that were conducted in waterbodies that have very little in common withthe two ponds evaluated in this risk assessment (U.S. EPA, 1997a). The waterbodies where themercury BAFfish values were measured were either very large (i.e., Lake Michigan and OnondagaLake, NY), or very far from Biddeford (i.e., Manitoba, Canada and Clear Lake, CA).

As such, it is deemed prudent to use a mercury BAFfish that is based on total mercurymeasurements in waterbodies that are closer to those evaluated in this risk assessment than thoseused to develop the mercury BAFfish values found in the Mercury Study Report to Congress(U.S.EPA, 1997a). A recent study of mercury in water, sediment, and biota of small lakes in Vermontand New Hampshire (Kamman, et al., 2004) provides a very good dataset and methodology forderiving such a BAF. This study includes measurements of total mercury levels in yellow perchfillets and adjusted mercury levels to a mean fish age of 4.9 years. Measurements taken in fishfilets are more representative of levels that humans would be exposed to than measurements ofwhole fish, and the adjustment to a standard fish age reduces the variability among themeasurements due to sampling of fish with different ages. There were 49 measurementscollected for total mercury in yellow perch and water in the epilimnion (the upper warmer layerof lakes), and 29 in the hypolimnion (the lower cooler layer of lakes). The mean log BAF for theepilimnion measurements was 5.25 (range: 4.72 to 6.01), and the mean log BAF for thehypolimnion measurements was 4.37 (range: 3.58 to 5.12). The overall mean log value of thesesamples is thus 4.91, which gives a geometric mean BAF of 82,000 for total mercury in thewaterbody and suitable fish fillets. The range of total mercury BAFs from this dataset is from3,800 to 1,020,000. The study authors note that the epilimnetic values were in excellentagreement with those found in other published studies. For this risk assessment’s baselineestimates of mercury concentrations in fish, the geometric mean BAFfish of 82,000 will be used. The effects of using other BAF values on the risk estimates will be evaluated in the uncertaintysection of this report.

It should be noted that the mercury BAFfish used in the 1996 Maine Energy Risk Assessment(Cambridge Environmental, 1996) was 5,500 based on a value in the 1986 U.S. EPA SuperfundPublic Health Evaluation Manual for total dissolved phase mercury concentration in water. ThisBAF will not be used because, like the value recommended within the HHRAP, it is based onnational-level default data.


6–1

6 Quantifying exposureAn exposure assessment builds upon the estimation of concentrations of COPCs in variousmedia by defining, through various assumptions, the rates and frequencies at which receptorsmight breathe, ingest, and otherwise contact the media to which COPCs have migrated. Exposure assumptions are in general designed to estimate a high-end level of exposure (althoughnot necessarily the highest potential degree of exposure). The calculation of human exposures toCOPCs depends on (1) the COPC’s concentration in media relevant to the exposure scenariobeing considered; (2) the rate at which the individual consumes (i.e., ingests or inhales) the givenmedium; (3) the frequency and duration of the exposure; and in order to normalize the exposurefor body size, (4) the individual’s weight. Exposures can be expressed in a generalized way bythe following equation:

IC CR EF ED

BW ATgen =⋅ ⋅ ⋅

⋅where the terms are:

Igen Intake–the amount of COPC at the exchange boundary (mg/kg-day); forevaluating exposure to noncarcinogenic COPCs, the intake is referred to asaverage daily dose (ADD); for evaluating exposure to carcinogeniccompounds, the intake is referred to as lifetime average daily dose (LADD);

C COPC concentration in media of concern (e.g., mg/kg for soil or mg/L forsurface water);

CR Consumption rate–the amount of contaminated medium consumed per unittime or event (e.g., kg/day for soil or L/day for water);

EF Exposure frequency (days/year);ED Exposure duration (years);BW Average body weight of the receptor over the exposure period (kg);AT Averaging time–the period over which exposure is averaged (days); for

carcinogens, the averaging time is 25,550 days, based on a lifetime exposureof 70 years; for noncarcinogens, averaging time equals ED (years) multipliedby 365 days per year.

Exposures to COPCs occur due to the direct inhalation of the compounds, and due to theiringestion within food, water and soils. The calculation of COPC intake rates by indirectpathways are contained in the HHRAP Appendices C-1-1 through C-1-5, with the total given inAppendix C-1-6:


6–2

I I I I I I II I I

ind soil prod beef milk pork poultry

eggs fish dw

= + + + + +

+ + +


Iind Total daily intake of COPC by indirect pathways (mg/kg-day);Isoil Daily intake of COPC from soil (mg/kg-day);Iprod Daily intake of COPC from above ground produce (mg/kg-day);Ibeef, Imilk, Daily intake of COPC from beef, milk, pork, poultry, eggs, and fishIpork, Ipoultry, respectively (mg/kg-day);Ieggs, IfishIdw Daily intake of COPC from drinking water (mg/kg-day).

Depending on the exposure scenario selected for analysis, some of these intake terms may be setto zero (see Table 4.1). Separate individual intake rates for adults and children are calculatedusing the equations below and parameters from Table 6.1.

The intake of COPCs due to the incidental ingestion of soil is calculated by:

IC CR F

BWsoils soil soil=⋅ ⋅


Isoil Daily intake of COPC from soil (mg/kg-day);Cs Average soil concentration over exposure duration (mg/kg);CRsoil Consumption rate of soil (kg/day);Fsoil Fraction of soil that is contaminated (unitless);BW Body weight (kg).

The COPC concentration in soil is calculated as described in Section 5.1 for untilled soil. Default values for CRsoil and BW for adults and children are listed in Table 6.1, and the parameterFsoil is assumed to be 1 (HHRAP Appendix Table C-1-1).

The intake of COPCs due to the ingestion of produce is calculated by:

( )( ) ( ) ( )[ ]I Pd Pv CR CR CR Fprod ag ag ag ag pp pp bg bg= + + ⋅ + ⋅ + ⋅ ⋅Pr Pr Pr


6–3


Iprod Daily intake of COPC from produce (mg/kg-day DW);Pd, Pv, Pr Average COPC concentration in produce over exposure duration

due to direct deposition, air-to-plant transfer, and root uptakerespectively (mg/kg), with the subscripts ag, pp, and bgreferencing above ground, protected and below ground producerespectively;

CRag, CRpp, CRbg Consumption rate of above ground, protected and below groundproduce respectively (kg/kg-day DW);

F Fraction of produce that is contaminated (unitless).

The calculations of COPC concentrations in produce due to the listed mechanisms are describedin section 5.2. Default values for the parameters CRag, CRpp, and CRbg for adults and children arelisted in Table 6.1. The parameter F is assumed to be 1 for subsistence farmers and theirchildren, and 0.25 for residents and subsistence fishers and their children (HHRAP AppendixTable C-1-2).

The intake of COPCs due to the ingestion of beef, milk, pork, poultry, eggs, and fish iscalculated by:

I A CR Fi i i i= ⋅ ⋅where the terms are:

Ii Daily intake of COPC from animal tissue or product I (mg/kg-day);Ai Average COPC concentration in animal tissue or product I over exposure

duration (mg/kg FW);CRi Consumption rate of animal tissue or product I (kg/kg-day FW);Fi Fraction of animal tissue or product I that is contaminated (unitless);

The calculations of COPC concentrations in animal tissues are described in section 5.3. Defaultvalues for the parameters CRbeef, CRmilk, CRpork, CRchicken, and CReggs for adults and children arelisted in Table 6.1, and the corresponding parameter Fi is assumed to be 1 and is applicable onlyto the subsistence farmer and child exposure scenarios (HHRAP Appendix Table C-1-3). Thecalculation of COPC concentrations in fish are described in Section 5.5. Default values for theparameters CRfish for adults and children are listed in Table 6.1, and the parameter Ffish isassumed to be 1 and is applicable only to the subsistence fisher and child exposure scenarios(HHRAP Appendix Table C-1-4).

The intake of COPCs due to the ingestion of drinking water is calculated by:

IC CR F

BWdwdw dw dw=

⋅ ⋅


6–4

ADIC IR ET EF ED

BW ATa=⋅ ⋅ ⋅ ⋅ ⋅

⋅ ⋅0 001

365.


Idw Daily intake of COPC from drinking water (mg/kg-day);Cdw Dissolve-phase water concentration over exposure duration (mg/L);CRdw Consumption rate of drinking water (L/day);Fdw Fraction of drinking that is contaminated (unitless);BW Body weight (kg).

The COPC concentrations in surface waters are calculated as described in Section 5.4. Defaultvalues for CRdw and BW for adults and children are listed in Table 6.1, and the parameter Fdw isassumed to be 1, based on HHRAP Appendix Table C-1-5.

Table 6.1 Parameters for calculation of human exposure to COPCs by indirect pathways.

Parameter adult childBody weight (kg) BW 70 15Consumption ratessoil adult (kg/day) CRsoil 0.0001 0.0002above ground produce (kg/kg-day DW) CRag 0.0003 0.00042produce protected (kg/kg-day DW) CRpp 0.00057 0.00077below ground produce (kg/kg-day DW) CRbg 0.00014 0.00022beef (kg/kg-day DW) CRbeef 0.00114 0.00051milk (kg/kg-day DW) CRmilk 0.00842 0.01857pork (kg/kg-day DW) CRpork 0.00053 0.000398poultry (kg/kg-day DW) CRchicken 0.00061 0.000425eggs (kg/kg-day DW) CReggs 0.00062 0.000438fish (kg/kg-day FW) CRfish 0.00117 0.000759drinking water (L/day) CRdw 1.4 0.67

The COPC exposure levels by indirect pathways which result from these calculations are used inChapter 7 to estimate the incremental cancer risks and noncancer hazard quotients due toemissions from the Maine Energy facility.

Exposures to COPCs by direct inhalation is calculated using the following equation from theHHRAP Appendix Tables C-2-1 and C-2-2:


ADI Average daily intake of COPC via direct inhalation (mg COPC/kg-day);Ca Total COPC air concentration over exposure duration (:g/m3);


6–5

Cm h f

fmilkfat =⋅ × ⋅ ⋅

⋅1 100 693

91

2.

IR Inhalation rate (m3/hr);ET Exposure time (hr/day);EF Exposure frequency (days/yr);ED Exposure duration (yr);BW Body weight (kg);AT Averaging time (yr);0.001 Conversion factor (:g/mg);365 Conversion factor (days/year).

The total COPC concentrations in air are calculated as the sum of the 5-year averageconcentrations at the maximum impact locations using the ISCST3 modeling described inChapter 3. Default values (as listed in HHRAP Appendix Tables C-2-1, and C-2-2) forinhalation rates, IR, are 0.30 m3/hr for children, and 0.63 m3/hr for adults; the exposure time, ET,is 24 hr/day; the exposure frequency, EF, is 350 days/year; the exposure durations, ED, are 6, 30,or 40 years (depending on the exposure scenario described in Chapter 4); the body weights, BW,are 15 kg for children, and 70 kg for adults; and the averaging times, AT, are 6, 30, or 40 yearsfor noncancer hazard calculations, and 70 years for the calculation of cancer risks.

The special exposure scenarios of nursing infants exposed to PCDDs and PCDFs through theingestion of contaminated breast milk requires the calculation of COPC concentrations in thebreast milk as described by the following equation from HHRAP Appendix Table C-3-1:


Cmilkfat Concentration of COPC in milk fat of breast milk for a mother in a specificexposure scenario (pg/kg milkfat);

m Average maternal intake of PCDDs and PCDFs for each adult exposurescenario (mg COPC/kg BW-day);

h Half-life of PCDDs and PCDFs in adults (days);f1 Fraction of ingested PCDDs and PCDFs that are stored in fat (unitless);f2 Fraction of mother’s weight that is fat (unitless);1×109 Conversion factor (pg/mg);0.693 Conversion factor (ln2, to convert half-life to decay rate constant).

The average maternal intakes of PCDDs and PCDFs for each adult exposure scenario arecalculated using the equations for adult COPC exposures described above. Default values (aslisted in HHRAP Appendix Table C-3-2) for the half-life of PCDDs and PCDFs in adults, h, is2,555 days; fraction of ingested PCDDs and PCDFs that are stored in fat, f1, is 0.9; and thefraction of mother’s weight that is fat, f2, is 0.3.


6–6

ADDC f f IR ED

BW ATantmilkfat milk

antinf

inf=

⋅ ⋅ ⋅ ⋅

⋅3 4

The exposure of nursing infants to PCDDs and PCDFs is then evaluated using the followingequation from HHRAP Appendix Table C-3-2:


ADDinfant Average daily intake of COPC for an infant exposed to contaminated breastmilk (pg COPC/kg-day);

Cmilkfat Concentration of COPC in milk fat of breast milk for a mother in a specificexposure scenario (pg/kg milkfat);

f3 Fraction of a mother’s breast milk that is fat (unitless);f4 Fraction of ingested COPC that is absorbed (unitless);IRmilk Ingestion rate of breast milk by the infant (kg/day);ED Exposure duration (yr);BWinfant Body weight (kg);AT Averaging time (yr).

The concentration of COPC in the milk fat of breast milk is calculated using the equation above. Default values (as listed in HHRAP Appendix Table C-3-2) for the fraction of a mother’s breastmilk that is fat, f3, is 0.04; the fraction of ingested COPC that is absorbed, f4, is 0.9; the ingestionrate of breast milk by the infant, IRmilk, is 0.8 kg/day; the exposure durations, ED, is 1 year); thebody weight of the infant, BWinfant, is 10 kg; and the averaging time, AT, is 1 year.


7–1

7 Risk and hazard characterizationThe assessment of human health risks due to the main stack and odor system emissions from theMaine Energy facility are incremental in nature, and do not reflect a person’s total or cumulativerisks from exposure to compounds in the environment, since there are background levels ofcompounds present in the atmosphere that are unrelated to operation of the Maine Energyfacility. These incremental risks are examined in conjunction with the regulatory frameworkthat treats facilities as independent entities.

Two categories of incremental risks of chronic health effects have been considered: cancer andnon-carcinogenic endpoints. Dose-response relationships for carcinogens are characterized byunit risk factors and potency slope factors. These factors are derived for assessing exposures viainhalation and ingestion pathways, respectively. Dose-response data for non-carcinogenic healtheffects are derived in a similar manner. Reference concentrations and reference doses are usedto assess the likelihood of chronic (noncancer) health effects from inhalation and oral exposure,respectively. Both cancer and non-cancer risks have been evaluated for direct exposures (e.g.inhalation of directly emitted COPCs) and indirect exposures (e.g. food chain and drinking waterrelated).

The potential for long-term exposures to the COPCs to result in adverse chronic health effectshas been evaluated using toxicological data principally obtained from U.S. EPA databases. Ahierarchy of databases was used, with information from databases further down in the prioritylist being used only when data for a COPC is not available from a database higher up on the list.

The preferred database is the Integrated Risk Information System (IRIS, available at: http://www.epa.gov/ngispgm3/iris/subst/index.html), followed by the Provisional Peer ReviewedToxicity Values (PPRTVs, http://hhpprtv.ornl.gov/index.shtml) and Health Effects AssessmentSummary Tables (HEAST, 1997). Some additional toxicological data has also been derivedfrom the U.S. EPA Region III’s Risk-Based Concentration Table (U.S. EPA 2001b). Finally, theHHRAP itself recommends compound-specific toxicologic data that are derived from data inIRIS, HEAST, and other sources, by extrapolating from one route of exposure to another (e.g.,deriving an ingestion potency from inhalation data).

Carcinogenic risks are calculated as the product of the long-term average dose (concentration forinhalation exposure) and carcinogenic potency (unit risk). The exposure periods listed in Table4.1 are used to assess incremental cancer risk. Individual risk estimates have been summedacross compounds and exposure pathways to provide a total estimate of incremental cancer riskdue to emissions from the Maine Energy facility.


7–2

ELCR LADD CSF= ×

Estimated excess lifetime cancer risks are a conservative, high-end estimate of the incrementalprobability that an individual will develop cancer as a result of a specific exposure to acarcinogenic compound; they are estimated by multiplying an individual’s lifetime average dailydose (LADD) of a compound (mg/kg-day) by the compound’s cancer slope factor (CSF),(mg/kg-day)–1. The LADD for each COPC and exposure scenario has been calculated in Chapter6 based on results contained in chapters 2 through 5; the COPC CSFs are contained in the COPCProperties Tables in Appendix III. An individual’s overall cancer risk due to a given facility’semissions is the sum of the cancer risks from all of the compounds of concern, and thus includespotential cancers of all types.


ELCR Excess Lifetime Cancer Risk (unitless),LADD Lifetime Average daily dose (mg/kg-day), andCSF Cancer Slope Factor ((mg/kg-day)–1.

Hazard quotients (HQs) have been calculated for noncarcinogenic endpoints as the ratio of theestimated dose (or concentration) due to facility-related emissions to the reference dose (orconcentration) identified in the toxicity assessment. An overall hazard index (HI) has beenconstructed as the sum of all hazard ratios calculated for individual exposure routes andcompounds. Because none of the hazard indices exceed a value of one, target-specific analyseswere not conducted.

Noncancer risk agents are assumed to exhibit a threshold below which no adverse effects areexpected to be observed. As such, noncancer health hazards are evaluated by comparing anindividual’s exposure to a compound against a reference dose (RfD) for oral exposures or areference concentration (RfC) for inhalation exposures. The ratio of an individual’s exposure toa compound to the compound’s reference exposure level is the known as the hazard quotient forthat compound and exposure:

HQADDRfD

or HQCRfC

a= =


HQ Hazard quotient (unitless)ADD Average daily dose (mg/kg-day)Ca Total COPC air concentration (mg/m3)RfD Reference dose (mg/kg-day)RfC Reference concentration (mg/m3)


7–3

The values for, ADD, and Ca in the above equation have been calculated in Chapter 6 based onresults contained in chapters 2 through 5; the COPC-specific RfDs and RfCs are contained in theCOPC Properties Tables in Appendix III. Because of the threshold assumption inherent in RfDsand RfCs, HQs below 1 are considered to be protective of human health. Additionally, anindividual’s total noncarcinogenic hazard due to a given facility’s emissions is referred to as thehazard index (HI), which is calculated as the sum of the hazard quotients for all of thecompounds of concern. As stated in the HHRAP guidance, the HI concept involves aconsiderable oversimplification of an individual’s potential to experience adverse health effectsdue to a facility’s emissions because it assumes that the effects of different COPCs are additive,even though they may include different (i.e., unrelated) health effects and compounds that mayact synergistically or antagonistically with each other.

Acute hazard quotients and indices have also been calculated as the ratio of modeled short-termexposure point concentrations in air to acute reference levels. The potential for acute effectscaused by one-hour exposures have been evaluated using Acute Inhalation Exposure Criteria(AIEC), which are primarily referenced in Appendix A of the HHRAP guidance. Someadditional AIEC values have been updated following the hierarchy described above. Forexample, some values are taken from a report issued by the Office of Environmental HealthHazard Assessment (OEHHA) at the California Environmental Protection Agency (CalEPA,OEHHA, 2000). Since the reference exposure levels (RELs) in this report supercede theformerly acute toxic effects levels (ATELs) that are currently used in the HHRAP guidance, theyare also used to update the AIECs.

In addition to these risk and potential hazard level calculations that are based on the HHRAPguidance, the estimated maximum average annual and 24-hour ambient air concentrations foreach COPC have been calculated and compared with the City of Biddeford’s Air ToxicsOrdinance ambient air limits (AALs, Biddeford, 2004). Because the Biddeford AALs aredesigned for direct comparison with ambient air concentrations rather than for use in calculatinghazard quotients, the AALs and concentrations are both given in the tables below; HQs were notcalculated based on these values.

The acute hazard quotient and index evaluations have been performed using upset conditionCOPC emission rates (g/s) and dispersion modeling results for both normal operation “normalupset” and startup operation “startup upset” (i.e., at full and one-half normal stack flow ratesrespectively) as described in Sections 2.3.3 and 3.6. The 24-hour ambient air concentrations thathave been estimated for comparison with the Biddeford 24-hour AALs have also been calculatedbased on Maine Energy emissions under normal operating conditions, as well as under upsetconditions that occur during normal operation and upset conditions that occur during startupoperation. For calculating the maximum 24-hour average ambient concentrations under upsetconditions, it was assumed that the upset emissions and stack flows lasted for one hour and thatnormal emissions and flows existed for the other 23 hours. Because the upsets considered in theemissions estimations generally result in one or both of the Maine Energy boilers being shutdown, the scenario essentially evaluates the average concentrations in the 24 hours leading up to,

1 As a sensitivity calculation, a screening-level analysis of Saco River fish consumption isprovided in Chapter 8.


7–4

and including the hour in which the upset occurs. During the hours after the upset, theconcentrations are expected to be lower because of the shutdown of one or both of the boilers.

Tables 7.1 through 7.8 contain the estimated cancer risks and hazard quotients for each COPCemitted from the Maine Energy facility and for which the appropriate toxicological data wasavailable. For those COPCs which do not have the potential to cause both cancer or noncancereffects (based on the available toxicological data), only one set of values are given. SomeCOPCs are evaluated for their potential short-term effects only, therefore they are not includedin the long-term effects tables.

The health risk indices in Tables 7.1 and 7.2 are based on direct exposures (i.e., exposure byinhalation only) to COPC emissions. Table 7.1 evaluates potential chronic effects due to long-term direct exposures; Table 7.2 evaluates potential acute effects due to short-term exposures. The potential for long-term health effects to be caused by direct exposures to COPCs isexceedingly small, with the ELCRs below 1 × 10–8, HIs below 0.001, and all of the maximumannual average concentrations are more than 1000 times smaller than the Biddeford annualAALs. The potential for short-term health effects to be caused by direct exposures to COPCs isalso small, with the overall HI equal to 0.021 for short-term exposures under upset operations,and with all of the maximum 24-hour concentrations more than 200 times lower than theBiddeford 24-hour AALs.

Tables 7.3 through 7.7 contain the health risk indices estimated for indirect exposures to COPCemissions. The first of these, Table 7.3, is for the residential receptor scenario which includesexposures from homegrown vegetables. Table 7.4 contains the ELCRs and HQs for therecreational farmer scenario which, as described in Chapter 4, is evaluated at receptor locationsfurther than 1 km from the Maine Energy facility. Tables 7.5 and 7.6 are for the recreationalfisher scenarios evaluated for fish caught from Wilcox Pond and the unnamed pond onGoosefare Brook.1 Overall, the potential for indirect exposures COPCs emitted from the MaineEnergy facility to cause adverse chronic health effects, is fairly small. The greatest estimatedELCR value is 3 × 10–6 for the adult recreational farmer, and the greatest HI is 0.09 for the adultrecreational fisher evaluated at the unnamed pond on Goosefare Brook.

Finally, Table 7.7 contains the estimated average exposure levels of adults, children, and nursinginfants to PCDDs and PCDFs by indirect pathways. These exposures are on a ToxicityEquivalent Quotient (TEQ) basis. As described in the HHRAP guidance (Section 2.3.1.2), thepotential for non-cancer health effects to be caused by exposure to PCDDs and PCDFs byindirect pathways is evaluated by comparing the estimated exposures with national averagebackground exposure levels of 1 to 3 pg TEQ/kg-day for adults and 60 pg TEQ/kg-day forinfants. As can be seen in Table 7.8, the incremental exposures caused by emissions from theMaine Energy facility are well below the typical national background exposures for all of theexposure scenarios.


7–5

Table 7.1 COPC-specific, potential chronic health risk indices based on long-term direct exposures (inhalation). Direct exposure levels are for the the maximum impactlocation and are used for all of the the exposure scenarios. ELCR values are theexcess lifetime cancer risk estimates for exposure periods shown. HQ values arethe hazard quotients for each COPC; values below 1 indicate that no adversehealth effects are expected to occur due to the exposure. The total of the HQvalues is the hazard index (HI) for the scenario. The rightmost two columnsprovide a direct comparison of the Biddeford annual AAL with the estimatedannual average COPC concentrations (:g/m3). The sum of the ratios of theannual average concentration and the Biddeford annual AALs is given as well (initalics to indicate that it is not the sum of the concentrations above it).

COPC ELCR ELCR HQ HQBiddeford

annualAAL

Annualaverageconcen-tration

adult child adult child — —Arsenic 2.7E-09 9.5E-10 3.9E-05 8.6E-05 2.4E-02 1.6E-06Beryllium 7.2E-11 2.6E-11 2.8E-06 6.3E-06 2.0E-02 7.8E-08Cadmium 1.4E-09 5.1E-10 7.4E-06 1.6E-05 2.4E-02 2.0E-06Chromium (total) — — 6.5E-10 1.5E-09 1.2E+00 4.7E-06Chromium (hexavalent) 3.1E-10 1.1E-10 4.8E-07 1.1E-06 2.4E-02 6.7E-08Copper — — 2.4E-05 5.3E-05 — —-Lead 3.5E-10 1.3E-10 — — 1.2E-01 7.6E-05Mercury (elemental) — — 7.7E-07 1.7E-06 3.0E-01 3.2E-07Mercuric chloride — — 1.7E-06 3.7E-06 6.0E-01 2.5E-06Nickel 6.7E-10 2.4E-10 9.6E-05 2.1E-04 2.4E-01 6.6E-06Selenium — — 1.3E-08 3.0E-08 4.8E-01 3.7E-07Silver — — 2.0E-08 4.4E-08 — —Tin — — 1.2E-08 2.8E-08 — —Zinc — — 1.3E-07 3.0E-07 — —Hydrogen chloride — — 3.0E-04 6.6E-04 2.0E+01 8.2E-03Acetone — — 2.9E-05 6.4E-05 — —Benzene 2.2E-08 7.9E-09 1.8E-04 4.0E-04 3.8E+00 7.4E-03Benzoic acid — — 1.2E-09 2.6E-09 — —Benzyl alcohol — — 1.1E-09 2.4E-09 — —Bis(2-ethylhexyl)phthalate 3.4E-11 1.2E-11 2.3E-07 5.1E-07 — —Bromomethane — — 6.3E-04 1.4E-03 — —Butanol, n- — — 1.3E-02 2.8E-02 — —Butanone, 2- — — 3.3E-09 7.4E-09 1.0E+03 2.3E-05Carbon disulfide — — 1.5E-05 3.3E-05 7.0E+02 1.4E-02Chloroform 4.9E-08 1.7E-08 1.3E-05 2.9E-05 1.2E+02 5.5E-03Chloromethane 6.5E-09 2.3E-09 7.6E-05 1.7E-04 2.5E+02 9.4E-03Cyclohexane — — 1.2E-06 2.6E-06 —- —Di-n-butylphthalate — — 1.4E-09 3.2E-09 — —Dichlorobenzene, 1,2- — — 2.4E-05 5.4E-05 — —-Dichlorobenzene, 1,3- — — 1.5E-03 3.4E-03 — —-

Table 7.1 COPC-specific, potential chronic health risk indices based on long-term direct exposures (inhalation). Direct exposure levels are for the the maximum impactlocation and are used for all of the the exposure scenarios. ELCR values are theexcess lifetime cancer risk estimates for exposure periods shown. HQ values arethe hazard quotients for each COPC; values below 1 indicate that no adversehealth effects are expected to occur due to the exposure. The total of the HQvalues is the hazard index (HI) for the scenario. The rightmost two columnsprovide a direct comparison of the Biddeford annual AAL with the estimatedannual average COPC concentrations (:g/m3). The sum of the ratios of theannual average concentration and the Biddeford annual AALs is given as well (initalics to indicate that it is not the sum of the concentrations above it).

COPC ELCR ELCR HQ HQBiddeford

annualAAL

Annualaverageconcen-tration

adult child adult child — —


7–6

Dichlorobenzene, 1,4- 6.0E-08 2.2E-08 1.3E-05 2.9E-05 — —Diethyl phthalate — — 1.8E-10 4.0E-10 — —Ethylbenzene 5.9E-09 2.1E-09 1.0E-05 2.2E-05 1.0E+03 1.4E-02Freon 11 — — 1.3E-05 3.0E-05 — —Freon 12 — — 5.3E-05 1.2E-04 — —Hexane — — 1.5E-05 3.3E-05 2.0E+02 1.4E-02Methanol — — 1.6E-04 3.5E-04 2.4E+01 8.8E-01Methylene chloride 2.3E-09 8.3E-10 3.2E-06 7.1E-06 4.1E+02 1.3E-02Methylnaphthalene, 2- — — 9.1E-08 2.0E-07Methyl phenol, 2- — — 5.7E-08 1.3E-07 7.4E+01 4.8E-06Methyl phenol, 3- — — 2.1E-08 4.7E-08 7.4E+01 1.8E-06Methyl phenol, 4- — — 2.1E-08 4.6E-08 7.4E+01 1.8E-06Naphthalene — — 6.4E-07 1.4E-06 3.0E+00 2.7E-06Phenol — — 9.8E-08 2.2E-07 4.5E+01 2.8E-05Propanol, 2- — — 9.6E-06 2.1E-05 — —Styrene — — 1.1E-05 2.4E-05 — —Tetrachloroethene 3.5E-08 1.2E-08 4.0E-05 9.0E-05 — —Toluene — — 8.1E-06 1.8E-05 4.0E+02 5.6E-02Trichloroethane, 1,1,1- — — 4.3E-06 9.5E-06 — —Trimethylbenzene, 1,2,4- — — 1.7E-03 3.8E-03 — —Vinyl chloride 9.8E-09 3.5E-09 2.1E-05 4.6E-05 1.0E+02 2.9E-03Xylene, m- — — 2.0E-05 4.5E-05 1.0E+03 2.0E-02Xylene, o- — — 1.3E-05 3.0E-05 1.0E+03 1.3E-02Xylene, p- — — 2.0E-05 4.5E-05 1.0E+03 2.0E-022,3,7,8-TCDD — — — — 1.0E-03 8.5E-12Total PCDD/PCDF 1.6E-09 5.6E-10 — — — —PCB Aroclor 1248 2.7E-12 9.7E-13 1.3E-07 2.8E-07 1.0E-01 1.2E-08TOTAL 2.0E-07 7.1E-08 1.8E-02 4.0E-02Sum of Biddeford ratios 0.040


7–7

Table 7.2 COPC-specific, potential acute health risk indices based on direct short-term exposures. HQ values are the hazard quotients for each COPC; values below 1 indicate that noadverse health effects are expected to occur due to the exposure. One-hour HQs arebased on HHRAP Acute Inhalation Exposure Criteria; the total of the HQ values is thehazard index (HI) for the scenario. The rightmost four columns provide a comparison ofthe Biddeford 24-hour AALs with the estimated maximum 24–hour COPCconcentrations (:g/m3) for various emission scenarios. The sum of the ratios of the 24-hour average concentration and the Biddeford 24-hour AALs are given as well (in italicsto indicate that they are not the sum of the concentrations above them).

COPC1-hour HQ

24-hour

BiddefordAAL

estimated maximumconcentration

normaloperation

normalupset

startupupset

normaloperation

normalupset

startupupset

Arsenic 3.3E-04 2.2E-03 2.6E-03 3.6E-02 1.2 E-05 1.4 E-05 1.5 E-05Beryllium 1.2E-06 6.7E-06 8.0E-06 2.0E-02 7.3 E-07 8.5 E-07 9.2 E-07Cadmium 3.9E-06 6.7E-05 7.5E-05 3.6E-02 1.8 E-05 2.6 E-05 3.3 E-05Chromium (total) 2.3E-07 2.2E-06 2.7E-06 1.8E+00 4.4 E-05 5.8 E-05 6.4 E-05Chromium (hexavalent) 4.4E-08 1.0E-06 1.2E-06 3.6E-02 7.1 E-07 1.2 E-06 1.5 E-06Copper 2.2E-05 9.4E-05 1.1E-04 — 5.6 E-04 5.9 E-04 6.0 E-04Lead 9.0E-05 1.6E-03 1.8E-03 1.8E-01 6.2 E-04 8.8 E-04 1.1 E-03Mercury (elemental) 1.9E-05 2.9E-05 3.4E-05 3.0E-01 4.2 E-06 4.3 E-06 4.5 E-06Mercuric chloride 1.4E-04 4.0E-04 4.5E-04 6.0E-01 3.3 E-05 3.5 E-05 3.7 E-05Nickel 7.9E-05 8.1E-04 9.8E-04 3.6E-01 6.1 E-05 7.7 E-05 8.7 E-05Selenium 2.0E-05 1.5E-04 1.8E-04 7.1E-01 5.0 E-06 6.3 E-06 7.2 E-06Silver 8.9E-08 5.3E-07 6.4E-07 — 4.1 E-06 4.7 E-06 5.0 E-06Tin — — — — 2.9 E-04 3.0 E-04 3.2 E-04Vanadium 1.8E-06 9.7E-06 1.1E-05 — 1.1 E-05 1.3 E-05 1.3 E-05Hydrogen chloride 4.2E-04 1.2E-03 1.4E-03 2.7E+01 1.1 E-01 1.2 E-01 1.3 E-01Benzene 1.1E-04 3.3E-04 3.6E-04 5.7E+00 5.0 E-02 5.2 E-02 5.3 E-02Benzyl alcohol 4.8E-09 2.3E-08 2.6E-08 — 3.3 E-05 3.8 E-05 4.2 E-05Bromomethane 1.9E-05 3.1E-05 3.1E-05 — 2.9 E-02 2.9 E-02 2.9 E-02Butanone, 2- 1.8E-07 7.9E-07 9.0E-07 1.0E+03 2.7 E-04 3.1 E-04 3.4 E-04Carbon disulfide 3.8E-05 5.8E-05 5.8E-05 7.0E+02 9.3 E-02 9.5 E-02 9.5 E-02Chloroform 5.9E-04 8.9E-04 8.9E-04 1.8E+02 3.6 E-02 3.7 E-02 3.7 E-02Chloromethane 7.5E-07 1.3E-06 1.3E-06 3.7E+02 6.2 E-02 6.3 E-02 6.3 E-02Dichlorobenzene, 1,2- 3.6E-07 5.4E-07 5.4E-07 — 4.4 E-02 4.5 E-02 4.5 E-02Dichlorobenzene, 1,4- 3.5E-07 5.4E-07 5.4E-07 — 9.3 E-02 9.5 E-02 9.5 E-02Diethyl phthalate 5.1E-09 2.1E-08 2.4E-08 — 8.6 E-06 9.7 E-06 1.1 E-05Ethylbenzene 4.1E-07 6.1E-07 6.1E-07 1.0E+03 9.1 E-02 9.3 E-02 9.3 E-02Freon 11 7.4E-08 1.1E-07 1.1E-07 — 8.4 E-02 8.6 E-02 8.6 E-02Freon 12 1.6E-08 2.3E-08 2.3E-08 — 9.6 E-02 9.7 E-02 9.7 E-02Hexane — — — 8.9E+02 9.4 E-02 9.5 E-02 9.5 E-02Methanol 5.1E-04 1.2E-03 1.2E-03 1.3E+03 5.8E+00 6.1E+00 6.1E+00

Table 7.2 COPC-specific, potential acute health risk indices based on direct short-term exposures. HQ values are the hazard quotients for each COPC; values below 1 indicate that noadverse health effects are expected to occur due to the exposure. One-hour HQs arebased on HHRAP Acute Inhalation Exposure Criteria; the total of the HQ values is thehazard index (HI) for the scenario. The rightmost four columns provide a comparison ofthe Biddeford 24-hour AALs with the estimated maximum 24–hour COPCconcentrations (:g/m3) for various emission scenarios. The sum of the ratios of the 24-hour average concentration and the Biddeford 24-hour AALs are given as well (in italicsto indicate that they are not the sum of the concentrations above them).

COPC1-hour HQ

24-hour

BiddefordAAL

estimated maximumconcentration

normaloperation

normalupset

startupupset

normaloperation

normalupset

startupupset


7–8

Methylene chloride 1.6E-05 2.9E-05 3.0E-05 6.2E+02 8.7 E-02 9.0 E-02 9.0 E-02Methyl phenol, 2- — — — 1.1E+02 5.7 E-05 7.8 E-05 9.5 E-05Methyl phenol, 3- — — — 1.1E+02 2.1 E-05 2.6 E-05 3.0 E-05Methyl phenol, 4- — — — 1.1E+02 2.1 E-05 2.6 E-05 3.0 E-05Naphthalene 3.7E-09 2.4E-08 2.7E-08 1.9E+02 3.3 E-05 4.0 E-05 4.6 E-05Phenol 5.1E-07 5.7E-06 6.5E-06 6.8E+01 3.3 E-04 4.7 E-04 5.8 E-04Propanol, 2- 4.7E-04 7.3E-04 7.3E-04 — 6.1 E-01 6.2 E-01 6.2 E-01Styrene 1.2E-05 1.8E-05 1.8E-05 — 9.9 E-02 1.0 E-01 1.0 E-01Tetrachloroethene 3.8E-07 5.8E-07 5.8E-07 — 1.0 E-01 1.0 E-01 1.0 E-01Toluene 2.5E-05 3.6E-05 3.6E-05 6.7E+02 3.7 E-01 3.7 E-01 3.7 E-01Trichloroethane, 1,1,1- 3.1E-06 4.6E-06 4.6E-06 — 8.5 E-02 8.7 E-02 8.7 E-02Trimethylbenzene, 1,2,4- — — — — 9.2 E-02 9.3 E-02 9.3 E-02Vinyl chloride 2.6E-07 4.2E-07 4.2E-07 1.0E+02 1.9 E-02 1.9 E-02 1.9 E-02Xylene, m- 1.5E-05 2.4E-05 2.4E-05 1.6E+03 1.3 E-01 1.3 E-01 1.3 E-01Xylene, o- 9.5E-06 1.5E-05 1.5E-05 1.6E+03 8.4 E-02 8.6 E-02 8.6 E-02Xylene, p- 1.5E-05 2.4E-05 2.4E-05 1.6E+03 1.3 E-01 1.3 E-01 1.3 E-012,3,7,8-TCDD — — — 1.0E-03 9.6 E-11 1.1 E-10 1.2 E-10PCB Aroclor 1248 — — — 1.0E-01 1.5 E-07 1.7 E-07 2.0 E-07TOTAL 3.0E-03 1.0E-02 1.1E-02Sum of Biddeford ratios 2.4 E-02 2.7 E-02 2.8 E-02


7–9

Table 7.3 Residential scenario, COPC-specific, potential chronic health riskindices due to direct and indirect long-term exposures. ELCRvalues are the excess lifetime cancer risk estimates for exposureperiods shown. HQ values are the hazard quotients for each COPC;values below 1 indicate that no adverse health effects are expectedto occur due to the exposure. The total of the HQ values is thehazard index (HI) for the scenario.

COPCELCR ELCR HQ HQ

adult child adult childArsenic 1.5E-08 5.7E-09 1.0E-04 2.1E-04Beryllium 2.1E-08 1.3E-08 9.6E-06 2.8E-05Cadmium 1.5E-08 4.9E-09 1.2E-04 1.9E-04Chromium (total) — — 6.2E-07 6.3E-07Chromium (hexavalent) 4.9E-08 1.8E-08 1.4E-06 2.8E-06Copper — — 6.4E-04 1.5E-03Lead 1.5E-08 9.4E-09 — —Mercury (elemental) — — 7.7E-07 1.7E-06Mercuric chloride — — 1.7E-03 5.6E-03Methyl mercury — — 1.0E-04 3.0E-04Nickel 6.7E-10 2.4E-10 1.1E-04 2.4E-04Selenium — — 5.0E-06 8.0E-06Silver — — 2.5E-06 3.7E-06Tin — — 2.9E-06 8.2E-06Vanadium — — 1.7E-05 5.7E-05Zinc — — 4.6E-05 7.4E-05Hydrogen chloride — — 3.0E-04 6.6E-04Acetone — — 7.5E-05 1.4E-04Benzene 9.0E-08 3.2E-08 9.0E-04 1.7E-03Benzoic acid — — 1.2E-07 1.9E-07Benzyl alcohol — — 1.2E-07 1.9E-07Bis(2-ethylhexyl)phthalate 4.8E-11 1.8E-11 3.4E-07 7.7E-07Bromomethane — — 1.2E-03 2.4E-03Butanol, n- — — 2.8E-02 5.3E-02Butanone, 2- methyl ethyl ketone — — 3.3E-07 5.8E-07Carbon disulfide — — 3.8E-05 7.4E-05Chloroform 5.1E-08 1.8E-08 1.0E-04 1.8E-04Chloromethane 1.6E-08 5.7E-09 1.4E-04 2.9E-04Cyclohexane — — 1.2E-06 2.6E-06Di-n-butylphthalate — — 3.4E-09 7.0E-09

Table 7.3 Residential scenario, COPC-specific, potential chronic health riskindices due to direct and indirect long-term exposures. ELCRvalues are the excess lifetime cancer risk estimates for exposureperiods shown. HQ values are the hazard quotients for each COPC;values below 1 indicate that no adverse health effects are expectedto occur due to the exposure. The total of the HQ values is thehazard index (HI) for the scenario.

COPCELCR ELCR HQ HQ

adult child adult child


7–10

Dichlorobenzene, 1,2- — — 1.1E-04 1.7E-04Dichlorobenzene, 1,3- — — 2.5E-03 5.0E-03Dichlorobenzene, 1,4- 8.7E-08 3.0E-08 9.9E-05 1.7E-04Diethyl phthalate — — 7.8E-09 1.4E-08Ethylbenzene 5.9E-09 2.1E-09 2.6E-05 5.0E-05Freon 11 (trichlorofluoromethane) — — 1.9E-05 4.0E-05Freon 12 (dichlorodifluoromethane) — — 6.3E-05 1.4E-04Hexane — — 3.1E-05 6.2E-05Methanol — — 4.5E-04 8.6E-04Methylene chloride 1.1E-08 4.0E-09 5.0E-05 8.9E-05Methylnaphthalene, 2- — — 8.1E-07 1.4E-06Methyl phenol, 2- — — 1.1E-06 1.9E-06Methyl phenol, 3- — — 3.0E-07 5.4E-07Methyl phenol, 4- — — 2.7E-06 4.9E-06Naphthalene — — 4.2E-07 7.6E-07Phenol — — 9.3E-07 1.6E-06Propanol, 2- (isopropyl alcohol) — — 9.6E-06 2.1E-05Styrene — — 2.2E-05 4.3E-05Tetrachloroethene 5.4E-07 1.9E-07 2.6E-04 4.8E-04Toluene — — 1.1E-04 2.0E-04Trichloroethane, 1,1,1- — — 1.3E-05 2.5E-05Trimethylbenzene, 1,2,4- — — 1.7E-03 3.8E-03Vinyl chloride 3.4E-07 1.2E-07 1.9E-04 3.5E-04Xylene, m- — — 2.2E-05 4.7E-05Xylene, o- — — 1.4E-05 3.1E-05Xylene, p- — — 2.2E-05 4.7E-05Total PCDD/PCDF 3.1E-07 2.0E-07 — —PCB Aroclor 1248 6.7E-11 2.4E-11 3.9E-06 7.0E-06TOTAL 1.6E-06 6.5E-07 4.0E-02 7.8E-02


7–11

Table 7.4 Recreational farmer scenario beyond 1 km from the facility, COPC-specific, potential chronic health risk indices due to directand indirect long-term exposures. ELCR values are the excesslifetime cancer risk estimates for exposure periods shown. HQvalues are the hazard quotients for each COPC; values below 1indicate that no adverse health effects are expected to occur due tothe exposure. The total of the HQ values is the hazard index (HI)for the scenario.

COPCELCR ELCR HQ HQ

adult child adult childArsenic 1.0E-08 2.6E-09 6.8E-05 1.3E-04Beryllium 2.2E-09 9.7E-10 3.3E-06 7.8E-06Cadmium 5.3E-09 1.4E-09 3.2E-05 5.6E-05Chromium (total) — — 5.6E-07 2.8E-07Chromium (hexavalent) 1.2E-07 3.2E-08 2.2E-06 4.0E-06Copper — — 1.8E-04 3.2E-04Lead 2.2E-09 9.6E-10 — —Mercury (elemental) — — 7.7E-07 1.7E-06Mercuric chloride — — 4.5E-04 1.1E-03Methyl mercury — — 1.8E-05 4.4E-05Nickel 6.7E-10 2.4E-10 1.1E-04 2.4E-04Selenium — — 2.8E-05 5.7E-05Silver — — 3.1E-05 6.8E-05Tin — — 7.3E-06 5.3E-06Vanadium — — 1.3E-06 3.8E-06Zinc — — 9.5E-06 1.5E-05Hydrogen chloride — — 3.0E-04 6.6E-04Acetone — — 5.1E-05 1.1E-04Benzene 9.4E-08 3.2E-08 7.5E-04 1.7E-03Benzoic acid — — 5.8E-08 1.2E-07Benzyl alcohol — — 5.6E-08 1.1E-07Bis(2-ethylhexyl)phthalate 1.2E-10 3.5E-11 7.7E-07 1.5E-06Bromomethane — — 1.1E-03 2.4E-03Butanol, n- — — 2.1E-02 4.6E-02Butanone, 2- methyl ethyl ketone — — 2.7E-07 5.9E-07Carbon disulfide — — 3.3E-05 7.4E-05Chloroform 5.0E-08 1.8E-08 5.3E-05 1.2E-04Chloromethane 6.5E-09 2.3E-09 7.6E-05 1.7E-04Cyclohexane 1.0E-08 3.4E-09 5.4E-05 1.2E-04Di-n-butylphthalate — — 4.6E-09 9.5E-09

Table 7.4 Recreational farmer scenario beyond 1 km from the facility, COPC-specific, potential chronic health risk indices due to directand indirect long-term exposures. ELCR values are the excesslifetime cancer risk estimates for exposure periods shown. HQvalues are the hazard quotients for each COPC; values below 1indicate that no adverse health effects are expected to occur due tothe exposure. The total of the HQ values is the hazard index (HI)for the scenario.

COPCELCR ELCR HQ HQ



7–12



7–13

Table 7.5 Recreational fisher scenario at Wilcox Pond, COPC-specific,potential chronic health risk indices due to direct and indirect long-term exposures. ELCR values are the excess lifetime cancer riskestimates for exposure periods shown. HQ values are the hazardquotients for each COPC; values below 1 indicate that no adversehealth effects are expected to occur due to the exposure. The totalof the HQ values is the hazard index (HI) for the scenario.

COPCELCR ELCR HQ HQ


Table 7.5 Recreational fisher scenario at Wilcox Pond, COPC-specific,potential chronic health risk indices due to direct and indirect long-term exposures. ELCR values are the excess lifetime cancer riskestimates for exposure periods shown. HQ values are the hazardquotients for each COPC; values below 1 indicate that no adversehealth effects are expected to occur due to the exposure. The totalof the HQ values is the hazard index (HI) for the scenario.

COPCELCR ELCR HQ HQ



7–14



7–15

Table 7.6 Recreational fisher scenario at unnamed pond on Goosefare Brook,COPC-specific, potential chronic health risk indices due to directand indirect long-term exposures. ELCR values are the excesslifetime cancer risk estimates for exposure periods shown. HQvalues are the hazard quotients for each COPC; values below 1indicate that no adverse health effects are expected to occur due tothe exposure. The total of the HQ values is the hazard index (HI)for the scenario.

COPCELCR ELCR HQ HQ


Table 7.6 Recreational fisher scenario at unnamed pond on Goosefare Brook,COPC-specific, potential chronic health risk indices due to directand indirect long-term exposures. ELCR values are the excesslifetime cancer risk estimates for exposure periods shown. HQvalues are the hazard quotients for each COPC; values below 1indicate that no adverse health effects are expected to occur due tothe exposure. The total of the HQ values is the hazard index (HI)for the scenario.

COPCELCR ELCR HQ HQ



7–16



7–17

Table 7.7 Exposures to PCDD/PCDFs by indirect pathways for evaluation of potential noncancereffects under six exposure scenarios. National-average, background, total daily TEQexposures are: 1 to 3 pg/kg-day TEQ for adults, and 60 pg/kg-day TEQ for nursinginfants. Nursing infant exposures are listed under the exposure scenario that describesthe adult from which the infant is nursing.

Indirect exposure levels

residentadult

residentchild farm adult farm child fishing adultfishing child

PCDD/PCDF total pg/kg-day TEQ 0.019 0.0025 0.036 0.034 0.026 0.015

PCDD/PCDF total pg/kg-day TEQ,nursing infants

0.072 — 0.96 — 0.41 —


8–1

8 Uncertainty evaluationThe health risk assessment for the Maine Energy facility relies on a wide variety of data andprocedures:

• facility-, site-, and COPC-specific properties and parameters;• environmental transport, fate and exposure modeling assumptions; and• toxicological reference doses and slope factors.

All of these elements are subject to varying degrees of uncertainty based on whether they aremeasured directly, calculated from basic physical and chemical principles, or extrapolated fromindirect measurements. In general, the more assumptions required for determining each propertyor parameter, the more uncertain the resulting value. Uncertainties may arise due to a lack ofbasic information, the need to make predictions outside the realm of present or availableknowledge, or the use of overly conservative assumptions in the calculations. The impact ofeach of these uncertainties on the overall risk estimates depends on the interactions among theparameters and model (e.g., fate-and-transport uncertainties for COPCs with that dominate riskestimates have a much greater impact on the overall conclusions than those for COPCs with lowrisk estimates). For this reason, and because the number of possible permutations is so great, thefollowing sections are directed towards the evaluation of property, parameter, modeling, andtoxicity uncertainties which have the greatest impacts on the overall risk estimates.

Several specific sources of uncertainties that were expected to impact the overall risk assessmentresults were described in the Maine Energy RAP. Some of these did not have as large an impacton the risk assessment as anticipated because the use of facility or site-specific data resulted inmodeling parameter values were not very different from those that were suggested as defaults bythe HHRAP. Additional uncertainties found to have a significant influence on the final resultswill also be discussed. Where applicable, these discussions include quantitative comparisons ofthe range of possible values for critical properties and parameters and for various options aimedat reducing the overall uncertainty. Also, significant departures from HHRAP guidance methodsor default assumptions are addressed with regard to their impact on the risk assessment’s overalllevel of uncertainty.

The uncertainty evaluations in this chapter are arranged in the same basic order as in theassessment itself. The areas which are discussed are:

• Facility characterization—emissions• Estimated long-term emission rates based on maximum rather than average

measured COPC concentrations• Accounting for unmeasured organic compounds by a TOE factor


8–2

• Emission rates for COPCs emitted below detection limits• Use of DREs to estimate some COPC emission rates• Hexavalent chromium fraction in stack emissions• Measured (rather than default) values for mercury speciation and partitioning

fractions• Air dispersion and deposition modeling

• Superposition of maximum concentration and deposition values• Bounding estimates for COPC concentrations in the Saco River• Receptor grid spacing at far-field maximum impact locations

• Estimation of media concentrations• Non-zero values for kse in calculating average watershed soil concentrations• Site-specific, empirical BAFfish values for mercury

• Quantifying exposure• Use of HHRAP default ingestion rates for local animal products

• Risk and hazard characterization• Inherent uncertainties in toxicological data due to extrapolation from original

research results• Toxicity of coplanar PCB congeners

8.1 Facility characterization—emission uncertainties

8.1.1 Estimation of long-term emission rates from maximum ratherthan average measured concentrations

The baseline, long-term health risk estimates given in Chapter7 are based on COPC emission rates from the Maine Energy facility that have been calculated using average measured COPCconcentrations in the facility’s exhaust gases. Because the tests in which COPC concentrationswere measured lasted at most a few hours, there is some uncertainty in extrapolating from short-term test results to long term emission rates. To test the sensitivity of the risk assessment resultsto uncertainties in the measured emission rates and the extrapolation of short-term results tolong-term estimates, the full risk calculations were performed using both baseline and high-endestimates of the COPC emission rates. Following HHRAP guidance (page 2-7), the high-endemissions estimates are calculated based on the lesser of (1) the maximum COPC concentrationsdetected in sampling and (2) the average concentration plus two standard deviations of theaverage, and also using continuous operation of the facility at the designed maximum capacity.

Table 8.1 provides the results of these sensitivity calculations for the various risk estimatesgenerated in the health risk assessment. In each case, the baseline risk estimates are paired withthe sensitivity estimate developed for the maximum emission rates. All of the risk estimatesincrease (as would be expected), though none of them exceeds the target risk criteria ( hazardindex of one, or an incremental cancer risk of ten in a million). The highest hazard index (non-cancer risk) for the maximum emission rate scenario is 0.13 for the adult recreational fisher, avalue seven times lower than the acceptable value. The highest incremental cancer risk of 4.9E-06, also for the recreational fisher, is more than two times smaller than the acceptable limit.


8–3

Table 8.1 Comparisons of the health risk indices as calculated using COPC emission rates based onthe average measured COPC concentrations in exhaust gases and on maximum measuredCOPC concentrations in exhaust gases. Direct exposures for all scenarios are evaluatedat the maximum impact location.

MeasuredCOPCconcentrationused foremission rate

Residential scenario, indirect exposure Residential scenario, direct exposure

cancer non-cancer cancer non-canceradult child adult child adult child adult child

Average 1.4 E-06 5.8 E-07 2.2 E-02 3.9 E-02 2.0 E-07 7.1 E-08 1.8 E-02 4.0 E-02

Maximum 2.2 E-06 9.6 E-07 4.5 E-02 7.7 E-02 2.6 E-07 9.2 E-08 3.5 E-02 7.7 E-02

Increase 62% 65% 105% 100% 31% 31% 95% 95%

MeasuredCOPCconcentrationused foremission rate

Farming scenario, indirect exposure Fishing scenario (Goosefare Brook),indirect exposure

cancer non-cancer cancer non-cancer adult child adult child adult child adult child

Average 3.3 E-06 7.3 E-07 1.1 E-02 2.5E-02 2.0 E-06 6.7 E-07 1.5 E-01 1.3 E-01Maximum 5.4 E-06 1.2 E-06 2.2 E-02 4.8 E-02 3.3 E-06 1.1 E-06 2.5 E-01 2.2 E-01Increase 62% 57% 93% 96% 68% 67% 65% 71%

8.1.2 Extrapolation of risks to account for un-analyzed compounds

The estimated potential health risks due to emission of organic compounds from the MaineEnergy facility are based on measured concentrations of these compounds in the facility’scombustion stack and odor control system outlet. However, organic compounds that are notidentified by laboratory analysis (principally because they are not on the analyte lists ofpotentially hazardous substances) were not treated as COPCs in the risk calculations. Althoughthere is no reason to suspect appreciable risks due to these compounds (since the lists of targetanalytes focus on the inclusion of potentially toxic compounds), these unknown compounds maystill contribute to overall risks. The HHRAP guidance (section 2.2.1.3) recommends thecalculation of a Total Organic Emission (TOE) test to account for the potential health effects ofunidentified organic compounds. Although emissions from the Maine Energy facility have beenanalyzed for organic compounds on several occasions, because the facility does not combusthazardous waste, the specific tests for determining TOE described in the HHRAP have not beenperformed for the facility’s stack or odor control. Therefore a more general method is used toassess the uncertainty in the potential for organic compounds that could not be identified by thestack and odor control system testing to lead to significant estimated health risks.


8–4

The first step in assessing this uncertainty is to determine the fraction of the overall estimatedrisk indices that are due to organic emissions from the Maine Energy stack and odor controlsystem. The percentages of the multi-pathway risk indices due to emissions from these sourcesare given in Table 8.2. From examination of the values in the table, it is clear that organicemissions from the Maine Energy boiler stack have a very minor impact on the overall riskestimates, especially for the recreational fisher and farmer scenarios where indirect exposurepathways have a significant impact on the estimates. Although a full TOE test cannot be appliedto account for the potential health effects of unidentified organic compounds, even if there werean equal amount of unidentified compounds as identified compounds in the stack emissions (i.e.,if the TOE adjustment factor were 2), this would have only a minor impact on the overall riskassessment findings.

In contrast, the organic emissions from the Maine Energy facility’s odor control system lead to asignificant proportional contribution of the overall risk estimate in some cases. Therefore, anadjustment to the risk estimates to account for the possible health effects of unidentified organiccompounds emitted from the odor control system might have a significant effect on the overallresults. The potential level of unidentified organic compounds in the odor control system stackhave been measured as part of the odor control system efficiency testing conducted in Augustand September 2004. Over three sampling periods, measurements of total hydrocarbonemissions were measured with a flame ionization detector (FID) and speciated organicmeasurements were made with a Fourier-transform infrared (FTIR) detector. Comparing a totalof 931 one-minute measurements, finds that an average of 94.2% of the total hydrocarbonsmeasured by the FID system were identified as specific compounds by the FTIR detector. Itshould be noted that the FTIR detector measured the concentrations of only eleven compounds(methane, propane, methanol, ethanol, propanol, butanol, o-, m-, and p-xylene, toluene, andacetic acid) rather than the 61 compounds included in the VOC testing performed in August2003 using EPA method TO-15. If the concentrations of the extra compounds in the TO-15analytical set were added to those in the FTIR set, then the fraction of identified compoundswould be even higher. Nevertheless, using the FTIR to FID fraction of identified compounds, anadjustment factor of 1.06 (the inverse of 0.942) may be applied to the odor control system’sorganic emissions to account for organic compounds that were not part of the system’s emissiontesting (assuming, as recommended in the HHRAP, that unidentified compounds are of equaltoxicity on average to those identified). Even for the exposure scenario that had the highestfractional impact from these emissions (noncancer effects for the adult residential scenario)where odor control system organic compounds contributed 87% of the total risk, application ofthe adjustment factor would increase the overall estimate by only 5.2% (i.e., 0.87 × 0.06).

Based on the facts that organic emissions from the Maine Energy combustion system stackcontribute very little to the overall risk estimates, and the fact that the organic emissions from theodor control system are almost entirely identified, the potential health impacts of unanalyzedorganic compounds are small relative to the overall risk estimates. The data that have been usedto make this estimate of possible unidentified organic odor control system emissions areincluded in Appendix III.


8–5

Table 8.2 Percentages of baseline risk indices that are due to organic emissions from the MaineEnergy boiler stack and odor control system.

Exposurescenario

Resident Recreational fisher Recreational farmeradult child adult child adult child adult child adult child adult child

Health endpoint cancer(ELCR)

non-cancer(HI)

cancer(ELCR)

non-cancer(HI) cancer (ELCR) non-cancer

(HI)

organicemissions fromboiler stack

8.7% 7.2% 1.4% 1.5% 4.8% 5.7% 0.2% 0.5% 0.005% 0.007% 0.6% 0.5%

organicemissions fromodor controlsystem

37% 31% 87% 78% 20% 24% 12% 23% 0.032% 0.041% 44% 39%

8.1.3 Treatment of COPCs below detection limits in stack tests

A frequent source of uncertainty in developing a multi-pathway risk assessment centers on thetreatment of toxicologically important compounds that may be emitted from the facility beingstudied at concentrations below the detection limits of the analytical methods used to measuretheir presence. Various approaches call for assuming that such non-detected compounds (1) arenot present at all in the emissions if they are never detected, (2) are present at one-half thedetection limit, or (3) are present at the full detection limit.

The method for treating non-detected compounds that was described in the Maine Energy RAP,and further detailed in responses to comments on the RAP, entails a combination of approaches(2) and (3) as described above. Specifically, for those COPCs that have not been detected in therecent stack or odor control system tests (but which are nevertheless included in the riskassessment), the assumed baseline emission rates are taken as one-half the detection limit of themost recent testing program. For those COPCs that have been detected in some but not all of themost recent tests, the test results in which the COPCs is not detected are averaged with thedetected results at the full detection limit.

Most of the compounds that were detected in some but not all of the emissions tests (and forwhich test results were reported as ‘non-detects’) were organic compounds emitted from both thefacility’s boiler stack and odor control system. For emission estimates of metals from the facilitycombustion stack, only three non detects occurred among 66 measurements. For emissionestimates of individual PCDD/PCDF congeners from the facility combustion stack, 87% (222 of255) of the individual congener measurements were “detects.” For emission estimates of organiccompounds from the facility combustion stack, among the compounds that were measured inrecent tests, the detection rate was 69%. Emission estimates of metals and PCDD/PCDF


8–6

congeners from the odor control system were based on measured values for the facility ash, forwhich no substitution of detection limit-based concentrations were necessary.

The high overall frequencies of detections among the various COPC categories generally resultfrom the use of high quality (sensitive) test and analysis methods. The only COPCs that wereassumed to be present at half their detection limit in the stack emissions were organiccompounds: chloroform, 1,2- dichlorobenzene,, ethylbenzene, 1,1,1- trichloroethane, and o-xylene. The only COPCs that were assumed to be present at half their detection limit in the odorcontrol system emissions were also organic compounds, namely bromomethane, carbondisulfide, chloroform, chloromethane, dichlorobenzene, (1,2-, and 1,3- only), and vinyl chloride.

The effects of employing different treatments of undetected COPCs on the final risk assessmentresults are shown in Table 8.3. The largest sensitivities are seen for the residential scenario forwhich contribution of organic compounds comprises a larger fraction of the risk estimates thanfor the other two scenarios. The cancer risk increases are primarily due to the assumed emissionrates of vinyl chloride emissions from the odor control system, where none was measured. Thenon-cancer HI increases are primarily due to the assumed emission rates of dichlorobenzeneemissions from both the stack and the odor control system. The small decreases seen withdecreasing the assumed levels of COPCs that are detected in some but not all tests are due to thefact that, for the most part, the compounds with the largest risk estimates were nearly alwaysdetected. None of the percentage increases indicated in Table 8.3 make any overall riskestimates exceed or even approach target risk levels of concern. For example, the highestprojected increase of 30% for the adult resident’s incremental cancer risk increases the baselinevalue from 1.2 E-06 to 1.6 E-06, a value that is still more than a factor of six times smaller thanthe target risk criterion.

Table 8.3 Effects of different assumptions regarding COPC measurements in which the compoundwas not detected relative to the baseline assumptions described above.

Exposurescenario


Health endpoint cancer non-cancer cancer non-cancer cancer non-cancer

increase with allnon-detects atdetection limit

30% 25% 8% 8% 16% 19% 1% 2% 17% 17% 10% 9%

decrease with allnon-detects atone-halfdetection limit

-4% -4% -1% -1% -2% -3% -0.1% -0.3% -3% -3% -1% -1%


8–7

8.1.4 Use of a DRE to estimate some COPC emission rates

Some of the COPCs included in the risk assessment were measured in the odor control system,but were not included in the list of analytes for as the combustion stack testing. Because thesame source of air (from the MSW and RDF handling buildings) that is processed by the odorcontrol system is also used for RDF combustion in the boiler, the compounds measured at theodor control system inlet are also likely present at the combustion system inlet, and may bepresent at the combustion stack outlet. Since most of these organic compounds are combustible,they are likely destroyed during combustion of the RDF. The stack emission rates for theseorganic COPCs were estimated from their concentrations at the odor control system inlet and anassumed combustion system destruction and removal efficiency (DRE) as described in section2.3.1. The baseline DRE 99.9% was chosen as a fairly conservative value — a more realisticDRE might be as high as 99.99% (the U.S. EPA’s required DRE for hazardous wastecombustors, as described in the HHRAP), of even 99.9999% (the required DRE for dioxin-bearing wastes). These higher DRE values would result in lower estimated COPC emissionrates, with each extra ?9” reducing the estimate by a factor of 10. Because the use of an assumedDRE was only employed in estimating emissions of some organic compounds from thecombustion system stack, and because the estimated health impacts of organic emissions fromthis stack comprise a small portion of the overall health risks, changes in the assumed DRE valuehave very little impact on the risk assessment results. Table 8.4 shows the fractional changes inthe overall health hazard and risk indices based on changing the assumed DRE to lower andhigher values. The positive values in the table represent fractional increases in the overall multi-pathway ELCR and HI values that would result in assuming a lower DRE value; while negativevalues represent decreases in the health risk estimates due to higher assumed DRE values. Forexample, the first value in the table of 3 E-7 indicates that if the assumed DRE were changedfrom 99.9% to 90% (i.e., the modeled emissions of COPCs estimated using the DRE methodfrom the combustion stack were to increase by a factor of 100), that the residential adult cancerrisk would increase by 0.3-in-a-million. Only one higher DRE value is shown because, even atthis change of DRE from 99.9% to 99.99%, the change in estimated risks is remarkably small. The largest change in health risk indices is for the noncancer effects in the residential exposurescenario where the HI increases by only 1.3% for a decrease in assumed DRE to only 90%. Thereason the effect of changing the DRE is so small is that the estimated potential health impacts oforganic compounds emitted from the combustion stack comprise only a minor portion of theoverall risk (see section 8.1.2 above), and because emission rates for only a few of the organiccompounds emitted from the stack are estimated using the DRE method. None of the potentialchanges associated with the DRE value would increase overall risk estimates to levelsapproaching or exceeding target risk criteria.


8–8

Table 8.4 Fractional change in multipathway risk indices for different assumed values of organiccompound combustion system destruction and removal efficiencies (DRE) relative to thebaseline DRE value of 99.9%.

Exposurescenario


Health cancer non-cancer cancer non-cancer cancer non-cancer

DRE = 90% 3 E-07 3 E-07 1 E-02 1 E-02 2 E-07 2 E-07 2 E-03 4 E-03 1 E-08 2 E-08 1 E-02 1 E-02

DRE = 99% 3 E-08 2 E-08 1 E-03 1 E-03 2 E-08 2 E-08 2 E-04 4 E-04 1 E-09 1 E-09 9 E-04 9 E-04

DRE = 99.99% -3 E-09 -2 E-09 -1 E-04 -1 E-04 -2 E-09 -2 E-09 -2 E-05 -4 E-05 -1 E-10 -1 E-10 -9 E-05 -9 E-05

8.1.5 Chromium speciation in emissions

For the baseline risk assessment calculations the fraction of chromium that is assumed present inthe hexavalent form is 2%. As described in section 2.3.5, this value is based on the chemicalthermodynamics of chromium in combustion system, measurements of chromium speciation inlaboratory scale testing, and the measured fraction of hexavalent chromium in the ash of theMaine Energy facility. Nevertheless, because hexavalent chromium concentrations have notbeen measured in the facility’s combustion stack emissions, there is some uncertainty regardingthe actual fraction of emitted chromium present in the hexavalent form. To test the impact ofdifferent hexavalent chromium fractions on the overall health risk estimates, several other valueswere tested. Because the potential health impacts of hexavalent chromium are principally relatedto increased incremental cancer risks (i.e., the cancer risk estimates are more sensitive to changesin the hexavalent chromium fraction), the changes in estimated ELCR values have beenexamined for hexavalent chromium fractions of 1, 2, 5, and 10 %. Based on the analysisdescribed in section 2.3.5, 2% is considered the baseline estimate, which is a plausible but stillsomewhat conservative (i.e., over predictive) estimate; 1% is the value that matches the meanmeasured fraction in the Maine Energy facility’s ash samples, 5% is a likely upper level fractionbased on the data described in section 2.3.5, and 10 % is included in this uncertainty analysis asan extreme upper bound for the hexavalent fraction. The overall ELCR values for each exposurescenario and assumed hexavalent chromium fraction are shown in Table 8.5. The ELCRestimates are expanded to two decimal places so that some of the small changes in potential risklevels can be observed. Although hexavalent chromium is a fairly potent carcinogen, the overallestimated cancer risks for the most significantly impacted receptor (the adult farmer) would onlyincrease by about 30% if the assumed hexavalent chromium fraction is increased by a factor of 5relative to the baseline level. Even at this higher estimated risk level, the ELCR estimates arestill well below the target criterion of 10 in a million (1 E-5).


8–9

Table 8.5 Overall excess lifetime cancer risks for different assumed fractions of emitted chromiumthat is present in the hexavalent form.

Exposure scenario 6

hexavalent chromiumfraction 9

Resident Recreational fisher(Goosefare Brook) Recreational farmer

adult child adult child adult child

1% 1.54 E-06 6.45 E-07 2.12 E-06 7.27 E-07 3.49 E-06 7.88 E-072% 1.56 E-06 6.54 E-07 2.15 E-06 7.36 E-07 3.55 E-06 8.04 E-075% 1.64 E-06 6.81 E-07 2.23 E-06 7.64 E-07 3.73 E-06 8.52 E-07

10% 1.76 E-06 7.26 E-07 2.37 E-06 8.11 E-07 4.03 E-06 9.32 E-07

8.1.6 Mercury speciation and distribution in emissions

The estimates of health risks due to mercury (Hg) exposure through ingestion are based onmercury speciation and distribution fractions in the facility’s stack emissions, which are in turnare calculated from detailed analytical results of the most recent mercury testing of the MaineEnergy stack gas. The details of the speciation/ distribution data and associated calculations aredescribed in section 2.3.6. Mercury is assumed to partition among three forms in stackemissions: (1) as elemental vapor-phase mercury, (2) as divalent vapor-phase mercury, and (3)as divalent particulate-phase (or particulate bound) mercury. The divalent forms are assumed tobe present as mercuric chloride (HgCl2), which is among the most reactive of mercury species. This assumption is fairly conservative (health protective) because mercuric chloride is morelikely to be transformed to the toxicologically important species methyl mercury than, forexample, would a relatively unreactive divalent species such as mercuric oxide (HgO).

The choice of mercury partitioning fractions among the three physical/chemical forms has asignificant impact on the estimated health risks for recreational fishers. Because an individual’sexposure to methyl mercury is almost exclusively due to fish ingestion, the other exposurescenarios are not greatly effected by predicted Hg levels. The primary reason that thepartitioning fractions have a large effect on the final hazard quotients is that divalent mercuricchloride deposits much more readily from the atmosphere than other forms of mercury.

Although the baseline mercury speciation and distribution fractions in the facility’s stackemissions are based on the most recent measurements of the Maine Energy facility’s boiler(combustion) stack gases, the test used for these measurements is not officially promulgated bythe U.S. EPA as a method for performing speciated mercury measurements. Therefore, someuncertainty exists relative to the validity of the modeling estimates. To test the impact ofemploying different mercury emission speciation fractions on the overall risk assessment results,mercury exposures and associated hazard potentials for the recreational fisher scenarios wereestimated using two other mercury distributions (1) the default one from the HHRAP guidance,and (2) the distribution derived from among all of the individual Maine Energy stack tests thatresults in the highest fraction of HgCl2 vapor (the baseline estimates use averages of the


8–10

distributions inferred from stack testing). Table 8.6 shows the three distributions and theassociated hazard indices for the recreational fisher scenarios. The differences among these HIvalues are not very large in part because the baseline, default, and maximum vapor-phase HgCl2fractions are all fairly high. If the measured fraction of vapor-phase HgCl2 were much lower(fractions on the order of a few percent have been measured for some combustion sources suchas coal-fired power plants), then the differences between the measured and default impactswould be much greater. It is interesting that the use of facility-specific data results in slightlyhigher risk estimates than those based on the HHRAP default recommendations, but even ifmaximum (worst-case) facility-specific data are used, the non-cancer risk estimates remain morethan a ten smaller than the acceptable risk criterion.

Table 8.6 Three mercury speciation distributions and the corresponding recreational fisher hazardindices.

Basis for mercuryspeciation distribution

Fraction of mercury emitted as: Recreational fisher scenario HI(Goosefare Brook)

Hg0 vapor HgCl2particulate HgCl2 vapor adult child

Average of most recentmeasured values 0.08 0.15 0.77 0.15 0.13

HHRAP defaultdistribution 0.20 0.20 0.60 0.13 0.12

Distribution withmaximum measuredHgCl2 vapor fraction

0.03 0.01 0.96 0.16 0.13

8.2 Air dispersion and deposition modeling uncertainties

Along with the estimation of facility emissions, the air dispersion and deposition modelingserves as one of the backbones of multi-pathway risk assessment, as all exposure routes dependon its predictions. As with all models, however, uncertainties are inherent to air dispersionmodeling analyses. There is an oft-quoted statement that air dispersion models are accurate towithin a “factor of two.” This statement, however, applies to the prediction of pollutantconcentrations in air under fairly idealized conditions. Additional uncertainties arise in theatmospheric modeling with the introduction of terrain features, and algorithms to predictpollutant deposition, etc. While these uncertainties should be recognized in assessing the overallresults of a dispersion and deposition model, the uncertainties are difficult to evaluatequantitatively, or to reduce through the use of additional site-specific data or detailed modeling.

Among the uncertainties in the modeling of atmospheric dispersion and deposition is the degreeto which the meteorological data used in the modeling corresponds to the conditions present atthe location being modeled. On-site meteorological data are not available for the facility, so it is


8–11

not possible to directly evaluate the representativeness of the Portland Jetport data used in themodeling. From a geographic perspective, we feel that the Portland Jetport data are likelyrepresentative of conditions in Biddeford and Saco because both locations are located quite closeto the coastline, which at both locations is oriented from the southwest to the northeast. Concern about the representativeness of meteorological data was raised by the Maine DEP inconjunction with the previous 1996 risk assessment of the Maine Energy facility. To addressthis issue, the Maine DEP provided a five-year (1989–1993) meteorological data set from theS.D. Warren facility located in Westbrook, located about 10 miles inland to the northwest ofPortland. A comparison of wind roses was provided in the 1996 risk assessment. The generalpattern of winds is similar between the Portland Jetport and S.D. Warren locations, although theS.D Warren site lacks the strong southerly component of the Portland Jetport data and generallyexhibits lower wind speeds. Similar to the 1996 study, sensitivity modeling was conducted usingthe S.D. Warren meteorological data, with similar results. These runs do not considercontaminant deposition or depletion (as the S.D. Warren set lacks the parameters for depositionanalysis). Peak estimates of annual average concentrations are about 17% lower using the S.D.Warren meteorological data, although peak short-term impacts are higher than those modeledusing the Portland Jetport data. The highest one-hour impact prediction using the S.D. Warrenmeteorological data was 5% higher than that predicted using the Portland Jetport data (the basisof the risk assessment), and hence would have little impact on the overall short term riskestimate. The peak 24-hour prediction using the S.D. Warren data, however, was 1.7 timesgreater than the Portland Jetport-based value used in the risk assessment. Even so, the differencewould have no effect on the risk assessment conclusions, as the 24-hour hazard ratio of 0.01(including the upset scenario) is so small.

Within the specific dispersion and deposition modeling of the Maine Energy facility, twoconservative, simplifying assumptions have been applied in the dispersion and depositionmodeling. The impact of these simplifying assumptions on the overall modeling results arediscussed below.

8.2.1 Superposition of maximum concentration and depositionvalues

To simplify the modeling of exposures of residential receptors, and the modeling of non-fishrelated exposures of recreational fishing receptors, the separate maximum impacts of COPCsemitted from the Maine Energy stack and odor control system and deposited by either dry or wetdeposition were added together, despite the fact that these maxima occur at different physicallocations. This simplification precludes the need to calculate COPC concentrations for eachenvironmental medium at each receptor location (six interconnected media, some with severaldifferent compartments, and 1656 receptor locations). An examination of Figures 3.8 – 3.19show the different patterns of estimated COPC atmospheric concentrations and deposition levels. The greatest differences among these figures are between the wet deposition, which is highestvery close to the facility and drops off rapidly, and dry deposition, which is very low near thefacility and reaches a maximum around 2 km away.


8–12

Because of these differences in the geographic deposition patterns among sources (boiler stackvs. odor control system) and types of deposition, the risk estimates for any specific exposurescenario at any specific location will be lower than those estimated in the risk assessment simplybecause all of the maximum values are not predicted to occur at the same place. An evaluationof the implications of incorrectly superimposing modeled maxima in the health risk assessmentwas performed using a special receptor scenario similar to the baseline recreational farmerscenario, but simplified to exclude consumption of animal products, and placing no restriction onthe distance of the receptor from the Maine Energy facility (the baseline risk estimates assumethe recreational farmer lives at least 1 km away from the Maine Energy facility). Although thisspecial scenario does not correspond to any of the HHRAP’s recommended exposure scenarios,it allows for the quantitative assessment of sensitivity to the “incorrect” superposition methodused in the baseline risk assessment. The calculated cancer and non-cancer health risk indicesfor this scenario, as compared with the same calculations made by superposing maxima (as isdone in the risk assessment), are shown in Table 8.7. The differences between the risk estimatesare rather small (less that 10%) for the cancer risk indices because these risks are not heavilyinfluenced by either wet deposition or emissions from the odor control system, both of whichhave their greatest impacts near the facility (i.e., with maxima only 50 m from the stack). Fornon-cancer indices, which are more influenced by emissions from the odor control system, thesimplified addition of maximum impacts near the plant with other maxima further awayproduces approximately three times the more accurate receptor location-specific adding ofimpacts.

Table 8.7 Differences in health risk indices for special receptor scenario based on the use ofseparate maximum COPC impact levels for each source and dispersion/depositionpathway, and based on the COPC levels at the location of the maximum totalhealth risk impact from all of the sources and pathways.

Maximum exposure calculationmethod

cancer (ELCR) non-cancer (HI)

adult child adult childCOPC exposures evaluated bysuperposing the separatemaximum impact locations foreach source dispersion/deposition

4.3 E-06 1.2 E-06 3.8 E-02 6.8 E-02

Maximum COPC exposuresevaluated with impacts at thesame location

4.0 E-06 1.1 E-06 1.3 E-02 2.2 E-02


8–13

8.2.2 Bounding estimate for COPC concentrations in the SacoRiver

As described in section 5.4.4, the dispersion models used in this risk assessment (ISC andAERMOD) are not approved to model COPC dispersion and deposition over the entire SacoRiver watershed (the models have only been approved for regulatory modeling applications outto a distance 50 km, the Saco River watershed extends 190 km from the facility). Therefore avery simple bounding calculation has been performed to estimate maximum possible COPClevels in the river based on the extreme assumption that all of the COPCs emitted from thefacility enter the river, and that they are only diluted by the volume of water flowing in the river(i.e., not by atmospheric dilution, soil or surface water dissipation factors, etc.). This boundingestimate clearly overestimates the incremental COPC concentrations in the river that actuallyresult from Maine Energy’s emissions because winds do not always blow the emitted compoundsover the river’s watershed, and even those emissions that are blown over the watershed do maynot wholly deposit to the land and water within it, and the fraction that that does deposit may notreach or remain within the water.

A first order estimate of the extent to which these bounding calculations over predict COPClevels in the Saco River can be performed by examining the fraction of the time that winds blowfrom the Maine Energy facility towards areas within the Saco River watershed. Figure 8.1shows an outline of the watershed and the location of the City of Biddeford (Biddeford & SacoWater Company, http://www.biddefordsacowater.com/water/). By comparing this figure withthe windrose for the Portland Jetport (Figure 3.5) that shows the frequencies with which windsblow from various directions, an estimate can be made of the fraction of time emissions from theMaine Energy facility are transported over the Saco River watershed. Because the Saco Riverwatershed covers a sector from roughly north-northwest to west-northwest, winds blowing fromthe south-southeast to east-southeast will send COPC emitted is Biddeford over the watershed. Summing the three windrose petals in this sector yields and estimated fraction of 11% for thetime that these conditions exist. Therefore, the incremental COPC levels estimated in the SacoRiver are overestimated by at least a factor of 9. Additional modeling or application of otherfactors would further lower this percentage by accounting for the facts that not all of theemissions that are dispersed over the watershed are deposited there, and that, even when somefraction of the emitted compounds are deposited, not all of this amount would ultimately makeits way into and or remain suspended within the river.


8–14

Figure 8.1 The Saco River watershed. Note that the map is somewhat rotatedcounterclockwise from the usual position where a north/south line would bevertical; the border between Maine and New Hampshire, shown to the right ofNorth Conway runs due north and south.

If the incremental COPC concentrations estimated in the Saco River are reduced to 11% oflevels derived using the bounding estimate, the overall risk estimates decrease significantly forthe residential exposure scenarios and for the recreational fisher scenario evaluated for fishcaught from the river (see Section 8.3.2, further on). The decreases in the residential scenariosare due to the reduction in estimated risks due to COPCs in drinking water; the fishing scenarioreductions also include concomitant reduction in estimated COPC levels in fish. Table 8.8compares the total health risk indices for exposure scenarios in which estimated COPC levels inthe Saco River have the most significant impacts. The greatest reduction is for the noncancerHIs for recreational fisher scenarios because these risk levels are dominated by exposure tomethyl mercury in fish. As stated above, application of the same COPC loss algorithms to theseestimates as have been used in the other watershed evaluations would further reduce the healthrisk estimates.


8–15

Table 8.8 Comparisons of health risk indices for exposure scenarios most impacted bychanges in estimated COPC concentration in the Saco River. The first row ofresults are based on the extreme bounding estimate for these concentrations;results in the second row are based on concentration estimates that include anadditional factor to account for the fact that the wind only blows from the MaineEnergy facility towards the Saco River watershed 11% of the time.

Exposure scenarioResident Recreational fisher (Saco River)

adult child adult child adult child adult child

Health endpoint cancer (ELCR) non-cancer (HI) cancer (ELCR) non-cancer (HI)

Bounding COPCestimate 1.6 E-06 6.5 E-07 4.0 E-02 7.8 E-02 2.9 E-06 8.4 E-07 5.4 E-02 8.8 E-02

Bounding COPCestimate with winddirection factor

7.4 E-07 3.6 E-07 2.9 E-02 5.9 E-02 8.8 E-07 3.8 E-07 3.0 E-02 6.0 E-02

8.2.3 Receptor grid spacing at far-field maximum impact locations

The maximum impact locations for some of the atmospheric dispersion and depositionparameters, and the location of the maximum farming scenario risk levels are rather far from thefacility. For example Figure 3.11 shows the maximum annual average concentration of volume-weighted particles at approximately 2200 meters north of the facility. At this distance the radialdistance between receptor locations is 100 m, but because the modeling receptor locations wereset up on a polar grid with an angular spacing of 10°, the angular spacing is approximately 400meters. To verify that the maximum modeled impact does not fall between these receptorlocations, an additional modeling run was performed using a refined receptor grid in the vicinityof the projected maximum impact location. A Cartesian grid spaced at 100 m intervals wascentered about the location of highest projected health risk for the farming scenario (2.2 km duenorth of the facility). The grid was extended 500 m in each direction. Surface-weighted, particledeposition per unit emission rate was modeled because COPCs in this category (e.g., PCDD/Fs)lead to the highest estimated health risks for the farming scenario. Contours of modeled surface-weighted particle deposition per unit emission rate are depicted in the Figure 8.2.

As can be seen, the maximum values form a narrow band to the north, indicating that thenortherly radial was sufficient to capture the maximum value (the baseline modeling is spaced at100 m intervals along the radial). Although the peak value is not precisely at the center of thefigure (it is a bit further north), this peak location was captured in the identification of themaximum risk estimates as it is centered around a receptor included in the risk assessmentmodeling. Importantly, higher modeled values at locations to the east and west of the northerlyradial do not occur in the sensitivity modeling, indicating that refinement of the receptor grid inthe maximum impact area would not substantially affect the risk estimates.


8–16

-500 -400 -300 -200 -100 0 100 200 300 400 5001700

1800

1900

2000

2100

2200

2300

2400

2500

2600

2700

Figure 8.2 Modeled surface-weighted particle deposition rates per unit emission rate (g/m2

per g/s) at locations near the maximum impact location (x and y coordinates are inunits of meters from the Maine Energy stack).


8–17

8.3 Estimation of media concentrations uncertainties

8.3.1 Use of non-zero kse in watershed soil concentrationcalculations

In developing watershed calculations, the baseline risk estimates assume that COPCconcentrations in soil decrease when soil erosion occurs. This assumption differs from theHHRAP’s recommendation to ignore soil erosion losses (and hence “double count” COPCsdeposited to soil). The justification for the risk assessment’s use of a calculated value for COPCloss from soils in the watershed due to erosion, kse, is given in Section 5.4.1. Briefly, the reasoncited in the HHRAP guidance for using a uniform value of zero for kse is that soil eroding off asite would be replaced by soil eroding onto the site. However, this assumption cannot be appliedto the evaluation of soil concentrations over an entire watershed because by definition no soilerodes into the area being considered. The primary impact on predicted health risks caused byusing a non-zero value for this parameter (rather than the value of zero as recommended by theHHRAP guidance), is that it decreases the mercury exposure of the recreational fisher adult andchild by a factor of about 40 – 50% by reducing the predicted amount of mercury that enters themodeled waterbodies. The overall hazard index for recreational fishers at the Goosefare Brooksite are (respectively) 0.17 using calculated (non-zero) kse values, compared with an index of0.21 employing the default value of zero for kse. While the differences between these values issignificant, even with the HHRAP’s default kse value of zero, the hazard indices are well belowone.

8.3.2 Bounding estimates of COPC levels in fish in the Saco River

As described in Chapter 4, and section 5.4.4, bounding calculations of COPC levels in the SacoRiver have been performed to conservatively estimate potential exposures of by way of ingestionof drinking water from the river. As a means of assessing the upper bounds of potential COPCexposures by way of fish ingestion, these bounding estimate concentrations have been used hereto estimate the potential maximum COPC levels that might be present in fish in the Saco River. Table 8.9 shows the COPC-specific ELCR and HQ values for the recreational fisher scenariothat as calculated using these upper bound COPC fish concentrations.

Even using the upper bound of possible COPC concentrations in the Saco River, the overallELCR and HI are still below the criteria levels of 10–5 and 1, respectively. Based on the simpleanalysis of section 8.2.2, the bounding calculations overestimate COPC levels in the river by atleast a factor of 9. Therefore the calculations of COPC levels in Saco River fish based on thebounding calculations are also probably overestimated by at least this amount. Reducing thebounding estimates of COPC levels in the Saco River by this factor, and calculating the fishconcentrations with these lower concentrations yields ELCR and HQ values that are smaller thanthose found using the full multi-pathway model for the unnamed pond on the Goosefare Brook. Therefore, the potential health risks and hazards that might result from exposure to emittedCOPCs in the Saco River and its fish are less than those estimated in the baseline riskassessment.


8–18

Table 8.9 Recreational fisher scenario using bounding estimate of COPCs in the SacoRiver, COPC-specific, potential chronic health risk indices based on direct andindirect long-term exposures. ELCR values are the excess lifetime cancer riskestimates for exposure periods shown. HQ values are the hazard quotients foreach COPC; values below 1 indicate that no adverse health effects are expectedto occur due to the exposure. The total of the HQ values is the hazard index(HI) for the scenario.—

COPCELCR ELCR HQ HQadult child adult child

Arsenic 1.6E-08 5.8E-09 1.1E-04 2.1E-04Beryllium 2.1E-08 1.3E-08 9.6E-06 2.8E-05Cadmium 2.1E-08 5.7E-09 1.5E-04 2.1E-04Chromium (total) — — 3.0E-06 1.0E-05Chromium (hexavalent) 5.0E-08 1.8E-08 1.4E-06 2.8E-06Copper — — 6.4E-04 1.5E-03Lead 1.5E-08 9.4E-09 — —Mercury (elemental) — — 7.7E-07 1.7E-06Mercuric chloride — — 1.7E-03 5.6E-03Methyl mercury — — 2.7E-03 2.1E-03Nickel 6.7E-10 2.4E-10 1.1E-04 2.4E-04Selenium — — 9.9E-06 1.1E-05Silver — — 5.6E-06 5.8E-06Tin — — 2.9E-06 8.2E-06Vanadium — — 1.7E-05 5.7E-05Zinc — — 1.3E-04 1.3E-04Hydrogen chloride — — 3.0E-04 6.6E-04Acetone — — 7.5E-05 1.4E-04Benzene 1.6E-07 4.2E-08 1.7E-03 2.2E-03Benzoic acid — — 1.6E-07 2.2E-07Benzyl alcohol — — 1.3E-07 1.9E-07Bis(2-ethylhexyl)phthalate 1.1E-08 1.6E-09 9.4E-05 6.6E-05Bromomethane — — 1.3E-03 2.5E-03Butanol, n- — — 2.9E-02 5.4E-02Butanone, 2- methyl ethyl ketone — — 3.4E-07 5.9E-07Carbon disulfide — — 5.8E-05 8.8E-05Chloroform 5.1E-08 1.8E-08 1.1E-04 1.9E-04Chloromethane 1.7E-08 5.9E-09 1.5E-04 2.9E-04Cyclohexane — — 1.2E-06 2.6E-06Di-n-butylphthalate — — 4.0E-07 2.8E-07Dichlorobenzene, 1,2- — — 1.9E-04 2.3E-04Dichlorobenzene, 1,3- — — 9.9E-03 1.0E-02

Table 8.9 Recreational fisher scenario using bounding estimate of COPCs in the SacoRiver, COPC-specific, potential chronic health risk indices based on direct andindirect long-term exposures. ELCR values are the excess lifetime cancer riskestimates for exposure periods shown. HQ values are the hazard quotients foreach COPC; values below 1 indicate that no adverse health effects are expectedto occur due to the exposure. The total of the HQ values is the hazard index(HI) for the scenario.—

COPCELCR ELCR HQ HQadult child adult child


8–19

Dichlorobenzene, 1,4- 2.2E-07 4.8E-08 5.2E-04 4.6E-04Diethyl phthalate — — 7.2E-07 5.1E-07Ethylbenzene 5.9E-09 2.1E-09 1.1E-04 1.1E-04Freon 11 (trichlorofluoromethane) — — 3.1E-05 4.8E-05Freon 12 (dichlorodifluoromethane) — — 7.4E-05 1.4E-04Hexane — — 3.0E-04 2.5E-04Methanol — — 4.5E-04 8.6E-04Methylene chloride 1.3E-08 4.3E-09 6.0E-05 9.7E-05Methylnaphthalene, 2- — — 1.4E-05 1.1E-05Methyl phenol, 2- — — 1.7E-06 2.3E-06Methyl phenol, 3- — — 5.3E-07 7.0E-07Methyl phenol, 4- — — 4.8E-06 6.4E-06Naphthalene — — 4.9E-06 4.9E-06Phenol — — 1.3E-06 2.0E-06Propanol, 2- (isopropyl alcohol) — — 9.6E-06 2.1E-05Styrene — — 6.1E-05 7.0E-05Tetrachloroethene 1.6E-06 3.4E-07 7.2E-04 8.0E-04Toluene — — 3.7E-04 3.8E-04Trichloroethane, 1,1,1- — — 2.9E-05 3.6E-05Trimethylbenzene, 1,2,4- — — 2.0E-03 4.0E-03Vinyl chloride 3.7E-07 1.3E-07 2.1E-04 3.6E-04Xylene, m- — — 2.8E-05 5.2E-05Xylene, o- — — 1.8E-05 3.4E-05Xylene, p- — — 2.8E-05 5.2E-05Total PCDD/PCDF 3.2E-07 2.0E-07 — —PCB Aroclor 1248 1.8E-10 4.0E-11 1.0E-05 1.2E-05TOTAL 2.9E-06 8.4E-07 5.4E-02 8.8E-02


8–20

8.3.3 Site-specific, BAFfish values for mercury

A second departure from the HHRAP default guidance with regard to modeling mercury fate andtransport is in the area of the biotransfer of mercury from surface waters to fish. Rather thanemploying the HHRAP default value and method for estimating the mercury bioaccumulation,the baseline mercury fate and transport models used in this risk assessment use abioaccumulation factor (BAF) more appropriate for evaluating the potential impact of mercuryemitted from the Maine Energy on the local lakes and ponds near the facility. The reasons forusing a non-default BAF value are described in Section 5.5.1. The BAF value used in thebaseline mercury fate and transport calculations is based on a recent study of mercury in water,sediment, and biota of small lakes in Vermont and New Hampshire (Kamman, et al., 2004). This study provides a very good dataset and methodology for deriving such a BAF that isappropriate for evaluating the potential impact of mercury emitted from the Maine Energy on thelocal lakes and ponds near the facility. The study itself gives four different values for the meanlog BAF, one for each combination of measured total mercury and methyl mercuryconcentrations and for measurements taken in both the hypolimnion and the epilimnion layers ofthe study lakes. The BAF used for the baseline calculations in this risk assessment wascalculated as the overall mean log value of the total mercury results. As a means of assessing thesensitivity of the overall risk levels to the selected BAF value and basis (i.e., total mercury ormethyl mercury), additional noncancer mercury hazard quotients and total exposure hazardindices for the recreational fisher scenario at the Goosefare Brook site have been calculatedusing all four of the BAF values given in the study. The HQ and HI values for these five BAFvalues and bases are shown in Table 8.10. As described in Section 5.5.1, the selection of a BAFbased on total mercury levels chosen for the baseline calculations because the estimation of totalmercury concentrations in surface waters is less subject to modeling uncertainties than theestimation of methyl mercury concentrations. The use of a BAF based on a combination of thehypolimnion and epilimnion data was chosen for the baseline calculations because recreationalanglers are likely to catch fish from both levels depending on the fish species and time of year. The HQs calculated using methyl mercury-based BAF values and those calculated using totalmercury-based BAF values are not proportional to the BAF values because the methyl mercuryBAFs are applied to only the fraction of the total mercury in the water that is estimated to bepresent as methyl mercury. It should be noted that all mercury in fish is assumed to be present asmethyl mercury under all modeling conditions. Although there is considerable variation amongthe results, even the maximum HI value of the sensitivity calculations is below the target non-cancer risk criterion of 1.0.


8–21

Table 8.10 Noncancer hazard quotients for exposure to mercury in fish, and overall totalhazard indices for the recreational adult fisher scenario using the baselinemercury BAF value and basis, and the four BAF values and bases from Kamman,et al., (2004).

Mercury speciesused as basis forBAF

total mercury methyl mercury

Waterdepth/temperaturefor which BAF wascalculated

baseline(weightedaverage)

hypolimnion epilimnion hypolimnion epilimnion

BAF value 82,000 23,000 180,000 440,000 870,000

HQ (methylmercury) 0.13 0.036 0.28 0.25 0.50

HI (all COPCs) 0.16 0.064 0.31 0.27 0.52

8.4 Uncertainties in quantifying exposure

The final step in estimating the public’s exposure levels to compounds emitted from the MaineEnergy facility involves the use of various adult and child ingestion (and inhalation) rates for theenvironmental media being considered. The ingestion rates for the recreational fisher and farmerscenarios are based on USDA food consumption rates as cited in the U.S. EPA Exposure FactorsHandbook (U.S. EPA 1997b). Because site-specific ingestion rates for recreational fishers andfarmers near the Maine Energy facility might differ from these national-based values, there issome uncertainty in the use of these parameters in the model. While, the ingestion rates are notnecessarily high for overall consumption of the modeled foods, it is difficult to quantitativelyassess the degree to which these ingestion rates might over or under-estimate actual conditions,and, as applied in the risk assessment, it is assumed that all of the food ingested by theseindividuals is from the area impacted by the COPCs emitted from the Maine Energy facility. Forexample, all of the fish ingested by the recreational fisher is assumed to be from the waterbody atthe location where the greatest impact is predicted from the Maine Energy facility. Likewise, forthe recreational farmer scenario, all of the ingested vegetable, meat, and dairy products areassumed to have been grown or raised at the location with the greatest impact from the facility.

Table 8.11 shows the assumed ingestion rates for homegrown foods and locally caught fish. Therates themselves may not be significant overestimates of local consumption rates. However, inassessing the values in the table, it should be considered that it is assumed that the foods are allof local origin, and that these rates are assumed to apply for 6 years for the child scenarios, 40

1 The tests must be suitable in other respects, and generally performed in accord with "goodlaboratory practice."


8–22

years (total) for the adult farmer scenario, and 30 year (total) for the adult fisher scenario. Itshould also be noted that for the recreational farmer scenario, it is assumed that all of these foodsare homegrown (including the feed used to raise livestock). As used in the exposure model,these ingestion rates are normalized to body weight and typically expressed in units such asmg/kg-day; they are expressed in Table 8.11 in more familiar units.

Table 8.11 Assumed consumption rates of homegrown produce, meat, and dairy products forthe recreational farmer scenario, and locally caught fish for the recreational fisherscenario.

Child ingestion rate(ounces per week, except milk)

Adult ingestion rate(ounces per week except milk)

Above ground produce 1.6 5.2

Protected produce 2.9 9.9

Below ground produce 0.8 2.4

Beef 1.9 19.7

Milk 1.8 quarts per week 3.9 quarts per week

Poultry 1.6 10.6

Eggs 1.6 10.7

Pork 1.5 9.2

Fish 2.8 20.3

8.5 Uncertainties in toxicologic data

Perhaps the greatest uncertainty in the risk estimates lies in the models used to predict thetoxicologic potencies (especially the carcinogenic potencies) of the contaminants of interest. Itis also the most difficult uncertainty to quantify and evaluate, and as such is usually treated in amanner that will overestimate potential risks.

Consider the case of predicting incremental cancer risk caused by a given level of exposure to aparticular compound that a person may encounter in the environment. In order to gauge whethera compound is a human carcinogen, groups of laboratory rodents are exposed, typically for mostor all of their lifetimes, to very large doses of the compound — much higher doses than peopletypically (if ever) experience. If the doses induce an increased incidence of any type of cancer,compared to the rate observed in unexposed control animals, then the compound is deemed acarcinogen.1 Two or more of such tests with positive results suffice to label the compound a“probable human carcinogen,” even if no actual or useful data from exposed humans areavailable.

2 This discussion is necessarily simplified and greatly condensed; and there are exceptions to therules outlined in this portion of the text. Some highly inbred strains of mice, for example, areuniquely susceptible to certain carcinogens — and other species, indeed even outbred strains ofthe same species, will not develop cancer at all under the same scenario of exposures. Somecancers in rats are found to occur in organs that are not present in humans. Decades of researchand analysis have gone into the design, interpretation, and extrapolation of results from chronicrodent bioassays, and there are still improvements to be made. Regardless, the simplificationspresented in the text are essentially accurate.


8–23

This qualitative designation of carcinogenicity is, in many cases, entirely appropriate. Rats,mice, and humans are all mammals that develop cancer from a variety of exposures, and whilethere are abundant differences among the three species, these differences are not so large as tosuggest that compounds carcinogenic to one species will not be carcinogenic to others.2 Butwhile the qualitative extrapolation from rodents to humans may be reasonably straightforward,the quantitative extrapolation required for risk assessment is highly uncertain. This is becausethe doses at which the rodents are tested are typically many thousands of times larger than dosesexperienced by humans. The central question is, are carcinogenic responses always proportionalto dose, such that even at extremely low levels of exposure there is some risk of cancer, and thatrisk becomes zero only at zero dose? The answer is largely unknown. Knowledge of howspecific compounds cause cancer may by helpful on a case-by-case basis, but such information isin most cases still too rudimentary to drive regulatory decision-making.

The model assumed by the U.S. EPA in deriving carcinogenic potencies (as used in this riskassessment) assumes that there is a risk of cancer — however small — at any level of exposure,i.e., that a single molecule, if encountered in the critical (but not understood) manner, can causecancer. The U.S. EPA has considered alternative types of models in which a threshold level ofexposure is assumed to be necessary to cause or promote tumors, and in the case of chloroformin drinking water, has recently determined that the body of empirical evidence supports thethreshold model. Similar determinations may also be likely for other compounds, casting doubton the validity of low dose extrapolations. If other compounds are determined to behave in amanner similar to chloroform, many of the incremental cancer risk estimates within the riskassessment may be found to be zero (i.e., for exposures below the threshold level).

With regard to cancer, it is assumed here that all rodent carcinogens are also human carcinogens,and that all compounds carcinogenic at high doses are also carcinogenic at vanishingly smalldoses. Even if these assumptions are valid, however, incremental cancer risk levels are stilllikely overestimated on average because the cancer slope factors that are derived by the U.S.EPA are intentionally designed to overestimate the true potency. The U.S. EPA quantifies thecarcinogenic potency slope factors as upper confidence limits on mean values, meaning that thevalues are purposely biased on the high side to account for uncertainty in the empirical data.

For similar reasons, non-cancer risks are also more likely to be overestimated than they are to beunderestimated. The reference doses and concentrations developed by the U.S. EPA aredesigned to be levels that are likely to not cause adverse health effects. Typically, they are basedon the weighted evidence of multiple studies in laboratory animals and (sometimes) humans, and


8–24

are based on levels that are observed to be free of health effects or on the lowest levels observedto cause health effects. The data from the toxicologic studies are rarely used directly, but ratherare reduced in magnitude through the application of one or more safety factors that are designedto ensure that the affects-free level observed in laboratory studies also reflects a safe level ofexposure for the general population. In deriving reference doses of concentrations from animalstudy data, safety factors are typically applied to:

• account for the fact that people may be more sensitive to a compound than are animals;• protect individuals who might be more sensitive to the compound than the animals that

were used in the study; and• provide an extra degree of protection when the body of toxicologic data on a particular

compound is limited.

Although there is no reason to assume a particular direction or bias with respect to any of theseuncertainties, all are resolved in the direction of safety. In each case, an adjustment is made toreduce the empirical toxicity data to derive a “safer” level. In the end, the actual safe level forhumans may be substantially higher than the derived reference dose or reference concentration, afactor that influences the interpretation of predicted hazard quotients in excess of one.

The other factor that clouds the interpretation of data from animal studies is the fact that testingtypically occurs at high doses that, in some cases, may affect or compromise bodily systems inways that do not occur at the low doses that are characteristic of environmental exposure. Forexample, making animals ill through the feeding of large quantities of a compound may reducetheir ability to fight off diseases and infections unrelated to the compound’s toxicity at normal,everyday levels of exposure.

In general, the biases used to derive toxicologic data are likely to overestimate actual risk levels. Although it is not possible to quantify the degree of bias, it is by convention a prudent measuredesigned to compensate for other potential uncertainties, and overall, produce bottom-lineestimates of risk such that they err on the high side of actual levels.

8.5.1 Toxicity of coplanar PCB congeners

A specific factor that may add to the uncertainty of assessing the toxicological effects ofexposures to various compounds is the lack of a full, detailed identification of the compound’smakeup. In this risk assessment, this condition occurs for PCBs. As noted in Section 2.2, PCBemissions from the Maine Energy facility were measured only as Aroclor 1248; theconcentrations of specific congeners were not measured. Because 13PCB congeners which arereferred to as either co-planar or dioxin-like, have greater carcinogenic potencies than the othercongeners, the health effects of these congeners are often evaluated independently from the totalPCB effects. Although the lack of congener-specific concentration data precludes the detailedevaluation of these congeners, an estimate of their potential health effects is possible. Thetypical composition of Aroclor 1248 has been tabulated by the U.S. Agency for ToxicSubstances and Disease Registry (ATSDR, 2000). Using this profile for Aroclor 1248, the TEFs


8–25

for dioxin-like congeners from the HHRAP, and the cancer slope factor for 2,3,7,8-TCDD, anestimated cancer slope factor of 6.87 kg-d/mg can be estimated for the dioxin-like congeners ofAroclor 1248. This factor is approximately 3.4 times the slope factor of 2 kg-d/mg for totalPCBs. However, because the ELCRs estimated in the risk assessment for PCB exposures are allbelow 10–10, the effect of this risk on the overall results is negligible.


9–1

9 ConclusionsThe multi-pathway risk assessment for the Maine Energy facility examines plausible ways thatpeople might be exposed to potentially hazardous chemicals it releases into the environment. The analysis is developed in a conservative (health protective) manner according to regulatoryguidance that considers activities and habits that might lead to elevated (high-end) exposurelevels. To evaluate whether these high-end exposures might result in significant risks to humanhealth, the exposure levels are evaluated with respect to compound-specific toxicological data. Two types of health-based evaluations are made within the risk assessment. First, the potentialfor each compound to increase an exposed individual’s lifetime cancer risk is assessed. Second,the likelihood that each compound might cause adverse health effects other than cancer isevaluated.

The incremental, or excess, lifetime cancer risk for an exposed individual is calculated bymultiplying each compound’s predicted exposure rate with its estimated potency to cause cancerin humans. The resulting cancer risk estimate is the exposed individual’s additional risk ofgetting cancer in his or her lifetime, above and beyond the background level that people getcancer from all causes, which is 1 in 2 for men and 1 in 3 for women. This excess risk iscompared with regulatory benchmark levels to evaluate whether the estimated risk is acceptable. Historically, the Maine Department of Human Services has established an acceptableincremental cancer risk level of 1 in 100,000 (or 10 in 1,000,000). This risk level may beexpressed in scientific notation as 10–5 or 1 E-5, and it represents an increase in cancer risk abovethe background level of 0.003% for a woman and 0.002% for a man.

The potential for emitted compounds to cause noncancerous health effects is evaluated bycomparing the predicted level of exposure for each compound with a level of exposure that isbelieved to be safe, i.e., a level that can be tolerated without risk to health (unlike incrementalcancer risk, where a risk is assumed for any level of exposure). The ratio of the estimatedexposure to the safe, or reference, exposure level is referred to as the compound’s hazardquotient (HQ). If a compound’s HQ is less than 1, the exposure level is less that the referenceexposure level, and no adverse health effects are expected to occur. For any given scenario, thesum of all the HQs is referred to as the hazard index (HI). If the HI is less than 1, then, overall,no adverse effects are expected. Although the health effects evaluated using the hazard indexinclude diseases that affect different organs which differ among compounds, these broadcategories of potential health effects are grouped because they are evaluated in a similar manner.

If the hazard ratio is greater than one, the level of exposure exceeds the level thought to bepotentially harmful, and the possibility of adverse health effects might exist. However, since thereference doses and concentrations used to characterize safe values frequently embody safetyfactors, it is incorrect to conclude that hazard ratios greater than one will in fact correspond to


9–2

the actual incidence of health effects. Rather, hazard ratios exceeding one are indicators ofpotential concern over the possibility of adverse health effects. Two types of hazard quotients are assessed to reflect different types of exposures to compoundsemitted from the Maine Energy facility. Chronic hazard quotients are calculated to assess healtheffects that might be associated with exposure to compounds that could occur over extendedperiods of time; acute hazard quotients are evaluated to gauge the nature of exposure to elevatedconcentrations of compounds in air that are predicted to possibly occur on an occasional basis.

The overall results of the risk assessment of the Maine Energy facility are summarized in Tables9-1 and 9-2. The total estimated lifetime incremental risks of cancer are listed in Table 9-1. These values reflect the sum of the estimates for all known or potentially carcinogeniccompounds found in the Maine Energy facility emissions. The compounds and exposurepathways that contribute principally to each cancer risk estimate are also provided in Table 9-1. The incremental risk levels due to Maine Energy facility emissions are larger for the recreationalfarmer and fisher scenarios, reflecting the conservative nature of the risk assessment andadditional indirect exposures included in these scenarios. Objectively, the lifetime incrementalcancer risk estimates are quite small, especially when compared with the background (overall)risk of getting cancer. As can be seen from the values in Table 9-1, the highest excess lifetimecancer risks associated with emissions from the Maine Energy facility total an incremental riskof 4 in 1,000,000 for the recreational farmer. This estimated risk level is more than a factor oftwo smaller than the regulatory benchmark of 10 in 1,000,000, and it represents an increase ofabout only 0.001% above background cancer incidence levels.

Table 9-2 presents risk estimates for compounds that, at sufficient levels of exposure, couldcause adverse health effects other than cancer. The highest overall hazard index is well below 1for both chronic (long-term) and short-term risks. Potential short-term risks have been evaluatedbased on both the facility’s emission levels under normal and upset operating conditions. Thegreatest HI is 0.2 for the fishing scenario as evaluated in the unnamed pond on the GoosefareBrook. This value is far below a level at which adverse effects might occur. Additionally, thesevalues represent the sum of all of the hazard ratios for the individual compounds, and, strictly,hazard ratios should be separated into categories of specific health effects. More detailedinformation on these risk estimates, including risk estimates for each COPC under each exposurescenario, is presented in Chapter 7 of the risk assessment report.

Most of the risk estimates presented in Tables 9-1 to 9-2 correspond to the estimates ofemissions from the Maine Energy facility when it is operating under normal operationalconditions, at full capacity, continuously throughout the year. Since the facility does not alwaysoperate at full capacity (e.g., it is shut down for periods of maintenance each year), the emissionrates, and hence risk estimates, are overestimated, even accounting for potential upset conditionswhen emissions might be higher over short periods. Even so, a series of risk estimates ispresented in the uncertainty section of the risk assessment report (see Chapter 8) based upon the highest emission rates measured during facility testing. These risk estimates tend to be abouttwice as large as the best-estimate values (at full operational loading) summarized in Tables 9-1and 9-2. This factor of two does not alter conclusions relative to typical regulatory risk criteria,


9–3

as incremental cancer risks would remain well below 10 in 1,000,000, and hazard indices wellbelow one. Thus, basing risk estimates on the highest measured emission rates would not lead torisk estimates of concern. Chapter 8 also contains risk estimates that have been calculated usingsomewhat different modeling assumptions than have been applied in the baseline estimates. Some of these sensitivity and uncertainty analyses result in slightly higher potential riskestimates, but none of them produce estimated risk indices that exceed the health-based criterialevels.

Table 9-1 Summary of Incremental Cancer Risk Estimates a

Receptor

Incrementalcancer riskestimate (Targetlimit = 10 in 1,000,000)b


Principal COPCs and fractionof total risk

Resident 2 in 1,000,000 drinking waterhomegrown produce

tetrachloroethene 34%vinyl chloride 22%PCDD/Fs 20%

RecreationalFarmer 4 in 1,000,000 homegrown animal

products/produce


RecreationalFisher 2 in 1,000,000

locally caught fishhomegrown producedrinking water


a The risk estimates shown here include risks due to both direct (Table 7.1) and indirectexposures (Tables 7.3, 7.4, and 7.6). The estimates are based on continuous operation of thefacility, using compound emission rates measured under stressed operating conditions, and forthe exposure pathways shown in Table ES-2. b Incremental cancer risks shown here are reported in the body of the report in scientificnotation; a risk of 8 in 100,000,000 may be also shown as 8 × 10–8 or 8 E-8.


9–4

Table 9-2 Summary of Hazard Indices and Total Ratios to Biddeford 24–hour AmbientAir Limits Used to Evaluate Risks of Non-Cancer Health Effectsa

Receptor

HazardIndex(Acceptablelimit = 1)


Principal COPCs and fraction of totalrisk

Chronic (Long-Term) Exposure Scenarios

Residentb 0.08inhalationdrinking watersoil ingestion

n-butanol 68%mercuric chloride 7%1,3 dichlorobenzene 6%

RecreationalFarmerb 0.06

inhalationdrinking watersoil ingestion

n-butanol 72%1,3 dichlorobenzene 7%1,2,4 trimethylbenzene 6%

RecreationalFisher 0.2 locally caught fish

drinking water

methyl mercury 76%n-butanol 17%dichlorobenzene 2%

Short-Term Exposure Scenarios

1-Hour BasisHazard Indexnormal operation

0.003 Inhalationchloroform 20%methanol 17%propanol, 2- (isopropyl alcohol) 16%

1-Hour BasisHazard Indexupset conditions

0.01 Inhalationarsenic 23%lead 16%hydrogen chloride 13%

Total of Ratiosto 24-HourAALsnormal operation

0.02 Inhalationbenzene 37%methanol 18%hydrogen chloride 17%

Total of Ratiosto 24-HourAALsupset conditions

0.03 Inhalationbenzene 33%lead 21%hydrogen chloride 17%

a The risk estimates shown here include risks due to both direct (Table 7.1) and indirectexposures (Tables 7.3, 7.4, and 7.6). The estimates are based on continuous operation of thefacility, using compound emission rates measured under stressed operating conditions, and forthe exposure pathways shown in Table ES-2.b The maximum Hazard Indices for these scenarios are for the child receptors


9–5

Table 9-2 also presents short-term risk estimates that account for occasional “upset” conditionswhen operations of the Maine Energy facility deviate outside of their normal ranges. Asdescribed in Chapter 2, the Maine Energy facility is designed and operated to minimize theeffects of process upsets, and some “upset” conditions that occur in practice (such as facilityshutdowns) actually lead to decreased long-term emissions. Consequently, the risk assessmentevaluates potential acute risks associated with short-term increases in facility emissions. Theupset scenarios summarized in Table 9-2 indicate a worst–case hazard index 0.01 over a 1-hourperiod, and a maximum sum of ratios of ambient concentrations to Biddeford 24-hour AALs of0.03, indicating overall safety factors of 30 to 100 between (1) the ambient concentrations ofCOPCs that might result during a facility upset and (2) levels of potential concern.

As another gauge of potential health risks due to emissions from the Maine Energy facility, thehighest modeled concentrations of COPCs due to emissions from the Maine Energy facility werecompared with applicable Ambient Air Limits (AALs) established by the City of Biddeford’s AirToxics Ordinance. No predicted COPC concentrations exceed any 24-hour or annual-averageAALs at any location. At the worst-case, the COPC nearest its AAL is 200 times smaller thanthe permissible level.

In summary,

• Emissions of a wide range of compounds from the Maine Energy facility havebeen measured;

• The highest expected personal exposures to these compounds by direct andindirect pathways have been modeled using methods that, in general, significantlyover-predict actual exposure levels;

• The modeled exposures are estimated to produce less than a 0.001% increase inthe risk of cancer and are well below the U.S. EPA’s reference dose andconcentration levels for non-cancer effects; and

• The worst-case predicted concentrations of COPCs due to Maine Energy facilityemissions are well below the Ambient Air Limits established by the City ofBiddeford to protect public health..

Based on these findings, emissions of the Maine Energy facility present no significant risks topeople living in its vicinity.


10–1

10 ReferencesAmerican Cancer Society (1996). Cancer Facts and Figures — 1996. Atlanta, GA: American

Cancer Society.

ATSDR (2000). Agency for Toxic Substances and Disease Registry , Toxicological Profile forPolychlorinated Biphenyls (PCBs) U.s. Department of Health and Human Services,Public Health Service, Atlanta, Georgia.

Auer, H.A. Jr. (1978). Correlation of land use and cover with meteorological anomalies. Journal of Applied Meteorology 17:636-643.

BIDDEFORD (2004). City of BIDDEFORD, Maine: Revised Code of Ordinances, Codifiedthrough Ord. No. 2004.102, adopted Nov. 3, 2004. Chapter 115 Regulated Toxic AirPollutants Appendix I. Table I. Available at:http://library7.municode.com/gateway.dll/ME/maine/309?f=templates&fn=default.htm&npusername=10440&nppassword=MCC&npac_credentialspresent=true&vid=default,accessed October, 2005.

Cambridge Environmental (1992). A Health Risk Assessment of the Waste-to-Energy PlantProposed for Green Island, New York. April 15, 1992.

Cambridge Environmental (1996). A Health Risk Assessment for the Maine Energy RecoveryCompany Facility, BIDDEFORD Maine. October 31, 1996.

Cambridge Environmental (2002). Risk Assessment for the Evaluation of Kiln Stack Emissionsand RCRA Fugitive Emissions from the Lone Star Alternative Fuels Facility, Greencastle, Indiana. Submitted to U.S. EPA Region 5, report dated April 2002.

Cambridge Environmental (2004). Risk Assessment Protocol for the Evaluation of Multi-pathway Impacts of Emissions from the Maine Energy Recovery Company Facility inBIDDEFORD, Maine. November 2004.

Earth Tech (1995). Air Quality Impact Analysis for use in Permit Application for Maine EnergyRecovery Company, Biddeford Maine (Chapter6).

Entropy (1992). Stationary Source Sampling Report , Maine Energy Recovery Company,Biddeford Maine. Stack testing conducted February/March, 1992, Report no.12690.


10–2

Entropy (1994). Stationary Source Sampling Report , Maine Energy Recovery Company,Biddeford Maine. Stack testing conducted July 8–10, 1994, Report no.10912.

HEAST (1997). Health Effects Summary Tables: FY-1997 Update. Washington, DC: Office ofResearch and Development and Office of Emergency and Remedial Response, U.S. EPA. July 1997. EPA 540/R-97-036.

Howard, P.H., Boethling, R.S., Jarvis, W.F., Meylan, W.M., and Michalenko E.M. (1991). Handbook of Environmental Degradation Rates. Chelsea, MI: Lewis Publishers Inc.

IRIS (2001). U.S. EPA, Integrated Risk Information Systemhttp://www.epa.gov/ngispgm3/iris/subst/index.html

Jones, K.H. (2003). Harrisburg Screening Risk Assessment. Prepared for City of Harrisburg,August 22, 2003.

Kamman, N., Driscoll, C.T., Estabrook, B., Ever, D.C., and Miller, E.K., (2004). Biogeochemistry of Mercury in Vermont and New Hampshire Lakes: An Assessment ofMercury in Water, Sdiment, and Biota of Vermont and New Hampshire Lakes. Comprehensive Final Project Report, May, 2004. Vermont Deportment ofEnvironmental Conservation, Waterbury, VT.

Maine Department of Inland Fisheries & Wildlife (2001). Depth map for Wilcox Pond,surveyed August 1959, revised - 2001. Available at http://www.state.me.us/ifw/pdf/depthmaps/Region%20A/L5620A.PDF.

NCDC (1993). Solar and Meteorological Surface Observation Network, 1961–1990(SAMSON). CD-ROM database, Version 1. National Climatic Data Center (U.S.Department of Commerce), September 1993.

OEHHA (2000). Consolidated Table of OEHHA/ARB Approved Risk Assessment Health Values. California Environmental Protection Agency: Office of Environmental Health HazardAssessment. October 2000.

Persson A.., Dayton, D.C., and Nordin, A. (2000). Chromium speciation in combustionatmospheres. Presented at the EF Conference, Park City, Utah, May 2000. Available athttp://www.chem.umu.se/dep/inorgchem/forskning/Combust/ON-LINE%20Presentations_files/Chromium%20poster.pdf.

Sandelin, K., Backman, R., and Nordin, A. (2001). Equilibrium distribution of arsenic,chromium, and copper in the burning of impregnated wood. The 6th InternationalConference on Technologies and Combustion for a Clean Environment “Clean Air.” Porto, Portugal, July 9-12 2001.


10–3

Seinfeld, J.H. (1986). Atmospheric Chemistry and Physics of Air Pollution. New York: JohnWiley & Sons.

Soil Conservation Service (1982). Soil Survey of York County Maine. United States Departmentof Agriculture.

U.S. EPA (1995). User's Guide for the Industrial Source Complex (ISC3) Dispersion Models. Volume II - Description of Model Algorithms. EPA-454/B-95-003b.

U.S. EPA (1996). 40 CFR Part 51 Appendix W: Guideline on Air Quality Models, Section 8.2.3

U.S. EPA. (1997a). Mercury Study Report to Congress. Office of Air Quality Planning andStandards and Office of Research and Development. EPA-452/R-97-005.

U.S. EPA (1997b). Exposure Factors Handbook. EPA/600/P-95/002Fa, August 1997.

U.S. EPA (1998a). Human health risk assessment protocol for hazardous waste combustionfacilities. (HHRAP) Peer review draft. Office of Solid Waste and Emergency Response. July 1998. EPA530-D-98-001A, B & C.

U.S. EPA (1998b). User's Guide for the AERMOD Meteorological Preprocessor (AERMET).Revised Draft. U.S. Environmental Protection Agency, Office of Air Quality Planningand Standards, November 1998.

U.S. EPA (1998c). AP 42, Fifth Edition. Compilation of Air Pollutant Emission Factors,Volume 1: Stationary Point and Area Source. Chapter 11.17 Lime Manufacturing. February 1998. Available at http://www.epa.gov/ttn/chief/ap42/ch11/final/c11s17.pdf.

U.S. EPA (1999). Human health risk assessment protocol for hazardous waste combustionfacilities. Peer review draft. Errata—August 2, 1999. Memorandum from BarnesJohnson, Director Economics, Methods, and Risk Analysis Division.

U.S. EPA (2000). External Peer Review-Human Health Risk Assessment Protocol for HazardousWaste Combustion Facilities—Peer Review Comments. TechLaw, Inc. Dallas. May,2000. RCRA Docket No. F-1998-HHRA-FFFFF.

U.S. EPA (2002a). User’s Guide for the AMS/EPA Regulatory Model - AERMOD.EPA-454/R-02-001. U.S. Environmental Protection Agency, Research Triangle Park,North Carolina.

U.S. EPA (2002b). User’s Guide for the AERMOD Meteorological Processor (AERMET).EPA-454/R-02-002. U.S. Environmental Protection Agency, Research Triangle Park,North Carolina.


10–4

U.S. EPA (2002c). Addendum to User's Guide for the AERMOD Meteorological Preprocessor(AERMET) (August 2002). U.S. Environmental Protection Agency, Office of AirQuality Planning and Standards. EPA 454/R-02-002b.

Wesely, M.L, P.V. Doskey, and J.D. Shannon (2002). Deposition Parameterizations for theIndustrial Source Complex (ISC3) Model. Draft ANL report ANL/ER/TR–01/003,Argonne National Laboratory, Argonne, Illinois.

Wischmeire, W.H., and Smith, D.D. (1978). Predicting Rainfall Erosion Losses—A Guide toConservation Planning. Agricultural Handbook No. 537. U.S. Department of AgricultureWashington, D.C.

Appendix I Cambridge Environmental, RiskAssessment Protocol,

Review Comments on the Protocol byTechLaw, and

Cambridge Environmental’s Response toComments


Risk Assessment Protocol for the Evaluation of Multi-pathway Impactsof Emissions from the Maine EnergyRecovery Company Facility inBiddeford, Maine

Prepared for:The Maine Energy Recovery Company

by:Stephen G. Zemba, Ph.D., P.E.,Michael R. Ames, Sc.D., andLaura C. Green, Ph.D., D.A.B.T.

November 2004

Cambridge Environmental Inc i58 Charles Street Cambridge, Massachusetts 02141617-225-0810 FAX: 617-225-0813 www.CambridgeEnvironmental.com

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–11.1 Overview of the risk assessment update . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–11.2 Multi-pathway risk assessments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–21.3 Outline of the Risk Assessment Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–2

2 Facility characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–12.1 Basic facility and site description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–12.2 Pollutants of Concern (POCs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–32.3 POC emission rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–42.4 Procedures for non-detected compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–52.5 Chromium speciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–52.6 Mercury speciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–6

2.6.1 Basic atmospheric behavior and modeling of mercury species . . . . . . . 2–62.6.2 Distribution of mercury species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–7

2.6.2.1 Measurement-Based Speciation . . . . . . . . . . . . . . . . . . . . . . . . . 2–82.6.2.2 Default Mercury Speciation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–8

2.7 Process upset emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–112.7.1 Combustion startup/shutdown upsets . . . . . . . . . . . . . . . . . . . . . . . . . 2–132.7.2 Combustion control upsets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–142.7.3 Baghouse/fabric filter upsets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–15

3 Air dispersion and deposition modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–13.1 Background and general air modeling description . . . . . . . . . . . . . . . . . . . . . . 3–13.2 Meteorological data and receptor locations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–23.3 POC deposition parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–4

3.3.1 Plume depletion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–43.3.2 Particulate-phase POC deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–53.3.3 Vapor-phase POC wet deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–53.3.4 Vapor-phase POC dry deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–11

3.4 Modeling of startup and shutdown emissions . . . . . . . . . . . . . . . . . . . . . . . . . 3–133.5 Summary of atmospheric dispersion and deposition modeling . . . . . . . . . . . . 3–13

4 Exposure scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4–1

5 Estimation of media concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–1

6 Exposure assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6–1

Cambridge Environmental Inc ii58 Charles Street Cambridge, Massachusetts 02141617-225-0810 FAX: 617-225-0813 www.CambridgeEnvironmental.com

7 Risk characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7–1

8 Uncertainty and sensitivity evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–1

9 Risk assessment conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–1

10 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10–1

Cambridge Environmental Inc Page 1-158 Charles Street Cambridge, Massachusetts 02141617-225-0810 FAX: 617-225-0813 www.CambridgeEnvironmental.com

1 Introduction

The Maine Energy Recovery Company processes municipal solid waste at its facility inBiddeford, Maine, producing refuse-derived fuel (RDF) that it combusts in boilers. Steamproduced in the boilers is used to produce electricity. Incidental to its operations, the facilityemits air pollutants from its boiler stack and odor scrubbing system. This protocol describesplans to conduct a detailed risk assessment to determine whether emissions from the facilitypresent significant risks to human health.

Cambridge Environmental Inc. conducted a similar risk assessment of facility emissions in 1996. The 1996 risk assessment found that there were no significant risks to human health. Since thetime of the 1996 risk assessment, however, several conditions have changed that warrantreexamination of the health risk assessment to determine if the 1996 conclusions remain valid. Significant changes that have transpired include:

• the addition of the odor scrubbing system;• the development of new regulatory guidance and models for conducting risk assessments;

and• the enactment of regulations by the City of Biddeford designed to evaluate emissions of

facilities that release potentially hazardous air pollutants.

The proposed update of the health risk assessment for the Maine Energy facility will update the1996 risk assessment to contemporary standards and expand it to include an evaluation ofemissions from the odor scrubbing system. Details of the procedures and approaches to be usedare described in the remainder of the document.

1.1 Overview of the risk assessment updateThe major changes and additions that will be used to update the Maine Energy facility include:

• an update of the air dispersion modeling of stack emissions to use AERMOD (a morerecent U.S. EPA dispersion model) and an expansion of the modeling analysis to includeboth wet and dry deposition (the 1996 risk assessment examines only dry deposition);

• the development of expanded meteorological data files to support the air dispersionmodeling and deposition analysis;

• the consideration of emissions from the odor scrubbing system in the risk assessment,including application of AERMOD with its sophisticated PRIME algorithms to moreaccurately predict plume downwash and dispersion;


• an update of contaminant emissions estimates based on a review of recent and historicstack test data and consideration of recent test results from the odor scrubbing system;

• an update of the multi-pathway fate-and-transport algorithms to correspond to the mostrecent guidance published by the U.S. EPA, specifically rhe Human Health RiskAssessment Protocol (http://www.epa.gov/epaoswer/hazwaste/combust/risk.htm);

• an update of the toxicologic data used to evaluate the stack-related emissions and anexpansion of the evaluation to consider pollutants identified in emissions of the odorscrubbing system; and

• evaluation of modeled air pollutant concentrations with respect to the Air ToxicsOrdinance promulgated by the City of Biddeford.

1.2 Multi-pathway risk assessments A multi-pathway human health risk assessment for a combustion facility focuses on estimatingthe potential health risks to individuals exposed to the facility’s emissions by either directinhalation or through ingestion of food and water that have incorporated these compounds. Thepotential for adverse health effects to result from exposure to pollutants emitted from the MaineEnergy facility by way of these environmental media is assessed with respect to toxicologicaldata for these compounds and regulatory guidance on safety factors and acceptable risk levels. The goal of these assessments is to determine whether the emissions from the Maine Energyfacility pose significant risks to public health, as defined (typically) by stringent regulatoryguidance. The assessed risks include chronic carcinogenic and non-carcinogenic risks associatedwith normal airborne emissions from the facility, and acute risks due to direct exposuresassociated with both normal maximum operation and process upset conditions.

This Risk Assessment Protocol (RAP) describes the procedures that will be followed for themulti-pathway risk assessment. The protocol for assessing multi-pathway human health risks isbased on the U.S. EPA’s draft Human Health Risk Assessment Protocol for Hazardous WasteCombustion Facilities (hereafter HHRAP, U.S. EPA, 1998). The HHRAP is quite detailed andbuilds upon previous U.S. EPA guidance, but is currently available in draft form only. Since theHHRAP’s release, the U.S. EPA issued an errata document (U.S. EPA, 1999a), and an externalpeer review (U.S. EPA, 2000a) that addresses additional problems in the HHRAP, ranging fromsimple typographical errors to issues of technical implementation and conceptual errors. Specific consideration of these errors and the use of data to tailor the updated risk assessment arediscussed as part of the RAP.

1.3 Outline of the Risk Assessment ProtocolThe RAP for the Maine Energy facility follows the outline of the HHRAP. Subsequent sectionsdescribe elements of the risk assessment as discussed in the HHRAP and other guidancedocuments in the context of conditions specific to the Maine Energy facility. The riskassessment will include the following chapters:


1. Introduction: a general description of the facility and the risk assessment structure andgoals.

2. Facility characterization: a basic facility and site description, identification of emissionsources and associated Pollutants of Concern (POCs) and the estimation of their emissionrates.

3. Air dispersion and deposition modeling: a description of the air dispersion/depositionmodeling that will be used to estimate POC concentrations in ambient air and POCdeposition rates.

4. Exposure scenarios: delineation of the categories of individuals to be evaluated in the riskassessment, with special focus on exposure pathways that can yield the greatest levels ofpotential exposure to POCs, as well as the differences between adult and child scenarios,and the nursing infant scenario.

5. Estimation of media concentrations: a description of the models and parameters used toestimate POC concentrations in environmental media surrounding the Maine Energyfacility.

6. Exposure assessment: presentation of the information used to estimate individual rates ofexposure to POCs.

7 Risk characterization: discussion of the toxicological information used to evaluate thepotential for POC exposures to result in adverse health effects.

8. Uncertainty evaluation: the sensitivity of the risk assessment results to uncertainties incritical modeling equations and parameters.

9. Conclusions.10. References.11. Appendices: added to the risk assessment as necessary for completeness.

Relevant aspects of these items are discussed in subsequent sections of this protocol.


2 Facility characterization

The risk assessment will contain a physical and operational description of the Maine Energyfacility, including diagrams, plan maps, and other information. The area surrounding the facilitywill be described to the extent that topography and land use have an effect on the estimation ofatmospheric dispersion and deposition, POC concentrations in environmental media, andrelevant exposure scenarios. A description of the facility and surroundings also helps toestablish a contextual sense for the risk assessment. For the purposes of the multi-pathway riskassessment, the most important aspect of the facility characterization chapter is the identificationof the emission sources.

2.1 Basic facility and site descriptionThe Maine Energy facility is located in the central downtown area of Biddeford. Figure 2.1depicts a topographic map of the area, centered roughly at the location of the facility. The pink-colored portions at the center of the map indicate the urbanized areas of the Cities of Biddefordand Saco, located to the south and north, respectively, of the Saco River. Generally, terrainelevations increase in directions to the north and south of the Saco River valley. A relativelylarge hill is located to the southeast of central Biddeford.

The Maine Energy facility is designed to process 1200–1500 tons of municipal solid waste(MSW) each day. Mechanical equipment is used to separate metal and other noncombustiblematerials that are recycled or disposed. The remainder of the MSW, which includes primarilypaper, plastic, and food waste, constitutes the refuse-derived fuel that the facility combusts intwo boilers. The steam produced by the boilers is fed through turbines to produce up to 22megawatts of electricity.

The byproducts of MSW combustion include residual ash, which is trucked to a landfill, and fluegases that are emitted to the air and subject to regulations enacted and enforced by the MaineDepartment of Environmental Protection (DEP). Prior to atmospheric release, flue gas fromeach boiler is treated by a series of air pollution control devices to reduce the levels of pollutants. First, a high efficiency cyclone separator removes most of the dust particles. Second, a spraydryer/absorber injects a lime slurry into the flue gas to remove most of the sulfur dioxide andreduce the level of acid gases. Last, a multi-compartment fabric filter, or baghouse, captures thecalcium sulfate particles formed in the spray dryer, as well as unreacted lime and small particlesnot initially collected by the cyclone collector. The caked material collected on the filter clothactually enhances the removal of sulfur dioxide by providing an additional opportunity for it tocontact the unreacted lime. After treatment in the baghouse, the cleaned flue gas from the twocombustion units is vented through a common stack at a height of 244 feet above ground.


Figure 2.1. Topographic Map of the Vicinity of the Maine Energy Facility


In 2000 the Maine Energy facility installed an odor control and scrubbing system to reduce odorsthat could otherwise escape to the outdoors. The system uses fans to draw air into the building(and conversely to prevent the escape of air through doors and windows). Air is collected fromthe areas in which MSW is stored and processed. A portion of the air is used for combustion bythe boilers, and the remainder is treated by filtering and scrubbing with a water mist to reduceodors and the levels of pollutants. The treated air is released through three stacks located on theroof of the boiler building. The release point of the odor scrubbing stack is 120 feet above theground, a height roughly one-half that of the boiler stack.

2.2 Pollutants of Concern (POCs)The main pollutants emitted from the Maine Energy facility are particles (more commonly calledparticulate matter), sulfur dioxide, oxides of nitrogen, total (unspeciated) volatile organiccompounds, and carbon monoxide. These pollutants are known as criteria pollutants, and areregulated by DEP to ensure that emissions from the Maine Energy facility do not lead toexceedances of the National Ambient Air Quality Standards that the U.S. EnvironmentalProtection Agency (EPA) has developed to protect human health. In fact, the Maine Energyfacility is subject to continuous monitoring requirements for three of these five criteriapollutants.

Since criteria pollutants are regulated by the DEP and the U.S. EPA to protect human health, therisk assessment focuses on other pollutants released by the Maine Energy facility. Collectively,these pollutants are sometimes called air toxics, and many are designated as Hazardous AirPollutants in the context of the Clean Air Act regulations (including specific volatile organiccompounds). Air toxics tend to be released in smaller quantities and are hence not amenable tothe continuous emission methods developed for criteria pollutants. Instead, air toxics aretypically measured on a periodic basis in stack tests using methods developed and specified bythe U.S. EPA.

The list of air toxics is conceptually infinite, but through research and study regulatory agencieshave developed a knowledge base of the pollutants released by waste-to-energy facilities (U.S.EPA, 1993). The1996 health risk assessment for the Maine Energy facility focused on a selectnumber of pollutants of concern (POCs) known to be released from waste-to-energy facilities. Only boiler stack emissions were considered, and the 1996 risk assessment focused on

• arsenic;• beryllium;• cadmium;• chromium;• lead;• mercury;• nickel; and• polychlorinated dioxins and furans (PCDD/PCDFs).


All of these same POCs will be evaluated in the updated risk assessment of the Maine Energyfacility. In addition, however, the following additional POCs will be evaluated for boiler stackemissions based on information gathered in recent testing of boiler stack emissions:

• hydrogen chloride;• six additional metals (copper, selenium, silver, tin, vanadium, and zinc);• ten semi-volatile organic compounds (phenol, naphthalene, 2-methylnaphthalene, diethyl

phthalate, di-n-butyl phthalate, bis(2-ethylhexyl)phthalate, benzyl alcohol, 2-methylphenol, 3&4-methylphenol, and benzoic acid); and

• polychlorinated biphenyls (created as products of incomplete combustion).

The second source of emissions is the odor scrubbing system, which differs fundamentally incharacter since it is not a combustion source. The principal POCs from the odor scrubbingsystem are various volatile organic compounds (VOCs) that have been identified in sourcetesting. The specific compounds detected in two monitoring studies of the odor scrubbingsystem include:

• ethanol (the VOC detected consistently at the highest concentration);• acetone, benzene, bromomethane, 2-butanone (methyl ethyl ketone), carbon disulfide,

chloromethane, chloroform, cyclohexane, 1,4-dichlorobenzene, ethylbenzene, freon 11,freon 12, heptane, hexane, methylene chloride, 2-propanol, styrene, tetrachloroethylene,toluene, 1,1,1-trichloroethane, 1,2,4-trimethylbenzene, vinyl chloride, and xylenes.

Not all of the VOCs identified in effluent samples of the odor scrubbing system were found in allsamples. Some, in fact, were detected in only a few samples. All of the chemicals, however,will be considered in the risk assessment.

2.3 POC emission ratesPOC emission rates will be derived directly from the results of recent testing conducted at thefacility. Data will be considered from the last four years of boiler stack testing (2001 to 2004)and detailed air toxics testing studies conducted in 2002 and 2003 that evaluated emissions fromthe odor scrubbing system (the 2002 air toxics study also included boiler stack testing).

Test results from both the boiler stack and odor scrubbing system are reported as concentrationspresent in the flue gas or effluent. These concentrations (in units of mass per unit volume) aremultiplied by effluent discharge rates (in units of volume per unit time) to estimate massemission rates (in units of mass per unit time) used as input to the air dispersion modelinganalysis.

Two sets of emission rates will be considered in the risk assessment to test the sensitivity of therisk assessment results. The baseline risk assessment will be developed using best estimates ofemission rates, calculated with the average values of measured POC concentrations and typicaloperating conditions for effluent flow rates. However, a second set of calculations will be


developed in the uncertainty section to test worst-case assumptions. These high-end estimates ofemission rates will be based on maximum detected concentrations in sampling and assumedcontinuous operation of the facility at the designed maximum capacity.

2.4 Procedures for non-detected compoundsPOCs uniformly not identified in any test samples will not be considered in the risk assessment. If a POC is detected in some, but not all, of the sampling runs, the average POC emission ratewill be calculated assuming an emission rate of one-half the detection limit for each test runwhere the compound is not detected. Should, non-detected POCs dominate the risk estimates,assumptions concerning their emission rates will likely be evaluated in the analysis ofuncertainties.

An exception will be made to this non-detection policy for PCDD/PCDFs. Frequently, stack testresults for PCDD/PCDF yield detection of some, but not all, congeners. To be conservative(health protective), the baseline calculations will assume that all PCDD/PCDF congeners arepresent in stack emissions, and hence all congeners will be carried through the risk assessment. In cases where a congener is not detected in any of the three stack test runs, its emission rate willbe based on one-half of the average limit of detection among the three runs. Additionalsensitivity calculations will likely be developed in the assessment of uncertainties to test theproposed treatment of PCDD/PCDF emissions. For example, sets of sensitivity calculations maybe developed treating non-detected congeners at zero to test the range of the risk estimates thatcould result from different assumptions regarding non-detected congeners. The precisesensitivity calculations to be performed will depend in part on the nature of the stack test results(e.g., if all congeners are detected, there will be no need for sensitivity calculations).

2.5 Chromium speciationChromium can exist in two forms in environmental compounds, bonding either in trivalent orhexavalent forms. Stack testing at the Maine Energy facility has not attempted to differentiatethese forms. However, the trivalent and hexavalent forms of chromium exhibit differenttoxicological characteristics. Based on theoretical chemical equilibria, reaction kinetics, andtypical combustion conditions in municipal waste combustors (i.e., combustion temperatures andresidence times) the anticipated level of hexavalent chromium in stack emissions is believed tobe negligible. Consequently, the 1996 health risk assessment evaluated chromium in trivalentform, and this assumption will be retained in the updated health risk assessment calculations. However, sensitivity analysis calculations regarding chromium speciation will be included aspart of the analysis of risk assessment uncertainties.


2.6 Mercury speciationBecause the potential health effects caused by exposures to emitted mercury often dominate thenon-cancer portion of the risk assessment, and because the modeling of mercury emissions andtransport is very sensitive to the selection of several modeling parameters, it is essential that thispollutant be modeled as accurately as possible. Therefore, details of several portions of theproposed mercury modeling will be discussed in some detail here and in sections to follow. Themeasurement or estimation of the speciation of the mercury emissions (i.e., the distribution ofmercury among its various chemical and physical forms) is critical in the multi-pathwaymodeling of this pollutant. The more accurately this can be speciated, the more accuratelymercury can be evaluated.

Mercury exists in combustion stack emissions in a variety of chemical and physical forms whichbehave very differently with respect to their atmospheric dispersion and deposition, and theirsubsequent transport through the environment. In the multi-pathway modeling of mercury, theemissions are generally grouped into three categories: vapor-phase elemental mercury (Hg0),vapor-phase ionic mercury compounds, and particulate-phase mercury (which includes bothsolid-phase mercury compounds and mercury compounds bound or adsorbed to solid particles). Although organic mercury compounds are included in the later stages of the multi-pathwaymodeling, they are not considered in the stack emissions; these species are unlikely to exist inthe emissions of high temperature combustion sources at significant levels. In order toconservatively model the fate and transport of the non-elemental mercury emissions it isassumed that both vapor- and particulate-phase ionic mercury exist as the soluble and reactivecompound mercuric chloride (HgCl2).

2.6.1 Basic atmospheric behavior and modeling of mercury speciesThe reason it is essential that emitted mercury is characterized and modeled in three differentforms is that elemental, vapor-, and particulate-phase ionic mercury behave very differently inthe atmosphere. The basic atmospheric fate and transport of these three categories of mercurycompounds are easily understood if one considers their primary physical and chemicalproperties. Elemental mercury is largely insoluble in water (solubility is 5.62 × 10–2 mg/l) with aHenry’s law constant of 7.1 × 10–3 atm-m3/mol. The atmospheric lifetime of elemental mercuryvapor is on the order of one year—very little elemental mercury that is emitted from a stackdeposits locally (i.e., within 50 km of the emission point). Mercuric chloride is highly soluble inwater (6.90 × 104 mg/l) with a Henry’s law constant of 7.1 × 10–10atm-m3/mol. Mercuricchloride is deposited from the atmosphere in the area surrounding its source far more readilythan elemental mercury in both vapor and particulate forms.

To account for the fraction of each form that is likely to be deposited locally vs. entering theglobal mercury cycle, the HHRAP (in Figure 2-4 of the guidance) recommends adjusting theemission rates of the three types of mercury emissions. Although the full amount of emittedmercury is considered in assessing the inhalation exposure pathway, in estimating mercury levelsin subsequent environmental media, the elemental mercury emission rate is reduced (multiplied)by a factor of 0.01, the vapor-phase mercuric chloride emission rate is reduced by a factor of


0.68, and the particulate-phase mercuric chloride emission rate is reduced by a factor of 0.36. The guidance references the U.S. EPA’s Mercury Study Report to Congress (U.S. EPA, 1997) asthe source of these factors. The portion of the emissions that are not included in the modeling(e.g., 32% of the vapor-phase mercuric chloride emissions) are assumed to be “transportedoutside of the U.S. or . . . vertically diffused to the free atmosphere to become part of the globalcycle.” (HHRAP page 2.63). However, the section of the Mercury Study Report to Congress thatassesses how much emitted mercury is “transported outside of the U.S.” covers the regional scalemodeling (i.e. modeling on scales of up to 1000s of km) of all the mercury emitted in thecontinental U.S. In fact, some of the mercury that is “transported outside of the U.S.” does sobecause it is emitted near the coast and is blown out to sea. The adjustment factors are not basedon local-scale modeling but on the mercury balance for the continental U.S. It is thereforeinappropriate to use these adjustment factors in the modeling of emissions from the MaineEnergy facility where the amount of mercury deposited in the region of interest is explicitlymodeled in the deposition calculations. The fraction of mercury emissions that leave the regionby atmospheric transport is merely the fraction that has not deposited. Therefore the emissionsadjustment recommended in the HHRAP will not be applied. More accurate modeling ofatmospheric mercury deposition (described below) will directly account for the portion ofmercury emissions that deposit locally vs. those that are transported out of the modeling domain.

Although the HHRAP guidance inappropriately recommends adjusting the modeled emissions ofvapor- and particulate phase mercuric chloride, its assumption that almost all elemental mercuryenters the “global pool” correctly reflects the fact that very little of the emitted elementalmercury will be deposited locally. Since so little deposits locally, elemental mercury emitted bythe Facility will not be carried through the multi-pathway risk assessment calculations asspecified in the HHRAP guidance and algorithms. Because only ionic mercury emissions areincluded in the multi-pathway estimation of mercury concentrations in environmental media(other than air), and because vapor- and particulate-phase mercury behave differently in theatmosphere, it is critical for the distribution of mercury emissions among the various species tobe estimated or measured as accurately as possible.

2.6.2 Distribution of mercury speciesAssumptions regarding the forms of mercury present in boiler stack emissions have an importantbearing on the prediction of mercury’s fate and transport in the environment. This is evident inthe findings of the U.S. EPA’s Mercury Report to Congress (Volume III, page 4-21) in whichdeposition modeling for the model MWC plants was run with two mercury distributions asalternatives to baseline scenario. One alternative distribution assumed a lower fraction ofelemental mercury, and the other a higher fraction. The results of this sensitivity analysisindicated that the predicted total mercury deposition rate is roughly proportional to the fractionof the emissions that is assumed to be vapor-phase ionic mercury (Table 5-19 of the MercuryReport). If the amount of mercury deposited locally (as modeled by the U.S. EPA) is roughlyproportional to the amount of vapor-phase ionic mercury in a facility’s emissions, then modelsthat use these distributions can obtain deposition results that range from essentially zero, to amaximum level obtained from using the HHRAP default values.


Consistent with other aspects of the updated risk assessment, it is preferable to use facility-specific information concerning the distribution of mercury species in boiler stack emissions inorder to reduce the level of uncertainty in the risk assessment. Consequently, data from stacktesting will be examined to determine whether appropriate information exists to determinereliable estimates of mercury speciation. If facility-specific cannot be reliably used, appropriatedefault values will be adopted. These options are further detailed in the following subsections.

2.6.2.1 Measurement-Based SpeciationMercury measurements at the Maine Energy facility use U.S. EPA Reference Method 29. Thecomponents of the sampling train used for Method 29 are shown in Figure 2.2. Although themethod is not explicitly designed for determining the speciation of mercury emissions, the U.S.EPA Report to Congress (U.S. EPA, 1997) notes that the distribution of mercury in the Method29 sampling train can be used to infer the form and speciation of mercury in MWC stack gas. Mercury adsorbed onto particulate matter can be assumed to be collected in the probe and filter;vapor-phase ionic mercury compounds that are soluble in water will be collected in the nitricacid/hydrogen peroxide impingers; and elemental mercury will be collected in the potassiumpermanganate/sulfuric acid impingers.

Unfortunately, because Method 29 is not explicitly designed for measuring speciated mercuryconcentrations, it is possible that the data will not be of sufficient quality to justify its use indetermining facility-specific mercury speciation. For example, it is possible that the levels ofone or more species may be below the detection limit for the testing (e.g., mercury may bedetected in the potassium permanganate/sulfuric acid impingers but none of the other stages). Ifthis is the case, the species may be assumed to be emitted at a concentration of one-half itsdetection limit. If one species’ detection limit is unusually high, it may be impossible to reliablyestimate the concentration of one species. For example, if the detection limit for vapor-phaseionic mercury is unusually high, an inferred speciation value based on the stack test data may bemisleading or uninformative. If the Method 29 stack test data do not provide sufficientinformation to infer a mercury species distribution, default values representative of MWCfacilities will be used, as described in the following subsection.

2.6.2.2 Default Mercury SpeciationThe HHRAP was developed as guidance for performing multi-pathway risk assessments forhazardous waste combustors. It recommends a mercury speciation of 20% as vapor-phaseelemental mercury, 60% as vapor-phase HgCl2 and 20% as particle-bound HgCl2. Thisdistribution is based on the work of Petersen, et al. (1995), which presents mercury speciationdata for modeling mercury deposition in Western Europe. The combustor speciation data is from a German paper by Axenfeld, et al. from 1991 which gives this distribution for the uncontrolledemissions from “waste incinerators.” The science and engineering aimed at both controllingmercury emissions and at measuring the distribution of mercury species in those emissions sincethose data were collected have developed considerably over the intervening years. But evenwhen the HHRAP was written there were available speciation data that were more relevant and


would better describe the well controlled mercury emissions from a municipal waste combustor(MWC) than the HHRAP’s default distribution. Hence, a default distribution of mercury speciesdifferent than that recommended in the HHRAP will be used for modeling the transport and fateof emissions from the Maine Energy facility.

In 1997 the U.S. EPA issued its Mercury Study Report to Congress (U.S. EPA, 1997). Thereport contained two different models to predict the atmospheric dispersion and deposition ofmercury. The regional impacts of anthropogenic sources of mercury were modeled using theRegional Lagrangian Model of Air Pollution (RELMAP). The modeling of atmospherictransport of mercury emissions local to sources (i.e., at distances less than 50 km) was performedusing the Industrial Source Complex Short Term Model (ISCST3), which was the dispersionmodel used in the 1996 risk assessment for the Maine Energy facility. For assessing localmercury impacts, the EPA developed proto-typical model plants that were meant to representclasses of sources. A range of MWCs was represented by a large plant combusting 2,250 tonsper day and a small plant combusting 200 tons per day. The mercury emission rates andspeciation profile for both plants were based on the assumption that they would be subject to theNSPS emission limit of 80 :g/dscm, and that in order to achieve this level the plants wouldemploy activated carbon injection as a control measure. The U.S. EPA noted in developing themodel plant that this control method is very effective at capturing ionic mercury species and thusincreases the fraction of elemental mercury in the emissions. Although the stack size and totalmercury emission rates for these model plants differed, the analysis assumed that both had thesame distribution of mercury species in the emissions of 60% as vapor-phase elemental mercury,30% as vapor-phase ionic mercury, and 10% as particle-bound mercury.

Interestingly, the HHRAP default distribution (20% as vapor-phase elemental mercury, 60% asvapor-phase ionic mercury, and 20% as particle-bound mercury) was used in the U.S. EPA’sregional modeling of mercury emissions (RELMAP) from uncontrolled hazardous wastecombustors. For modeling the emissions from well controlled facilities the EPA selected verydifferent distributions as shown in Table 2.1. For modeling waste combustors that achieve thedegree of mercury control required in the U.S. EPA’s New Source Performance Standards(NSPS), the EPA’s RELMAP model assumes that all of the mercury is emitted in the elementalform. Given that almost no elemental mercury deposits locally, use of the appropriate RELMAPdistribution in the local mercury modeling would result in much less mercury entering thesubsequent portions of the multi-pathway risk assessment than predicted using the baselineISCST3 values. Hence, the default distribution to be used for modeling mercury emissions fromthe Maine Energy facility (60% as vapor-phase elemental, 30% as vapor-phase ionic, and 10% asparticle-bound) is a reasonable yet conservative estimate of mercury speciation, and it will beused in the risk assessment if it is found that the site-specific measurements are unreliable orotherwise unsuitable.


Figure 2.2 EPA Reference Method 29 sampling train for the collection of metals emissions from stationary sources. Mercuryspeciation may be assessed through the separate analysis of the glass fiber filter (particulate bound mercury species),the nitric acid/peroxide impinger solutions (vapor-phase ionic mercury species), and the permanganate/sulfuric acidimpinger (vapor-phase elemental mercury).


Table 2.1 Distributions of mercury emissions from Municipal Waste Combustors among thethree assumed mercury species used for atmospheric dispersion and deposition modeling inthe EPA Mercury Report to Congress (U.S. EPA, 1997).

Model MWC Source type Elemental mercury(%)

Vapor-phase ionicmercury (%)

Particulate-phasemercury (%)

localdepositionmodeling(ISCST3)

sensitivity case A 30 50 20

base-case** 60 30 10

sensitivity case C 90 10 0

regionaldepositionmodeling

(RELMAP)

no control* 20 60 20

50% control 40 45 15

85% control 100 0 0

* This is the HHRAP default distribution.** This is the proposed default distribution for the Maine Energy facility risk assessment.

2.7 Process upset emissionsA waste-to-energy plant does not always operate under normal conditions: the plant goesthrough startups and shutdowns, and may experience upset conditions if a portion of the airpollution control system malfunctions or the combustion control system is disturbed. Emissionsthat occur during these periods will be evaluated in the risk assessment only with respect to thepotential impacts of direct short-term exposures. Although POC mass emission rates duringstartup and shutdowns may be lower than during normal plant operation because of reducedthroughput, it is possible for the maximum ground level POC concentrations to be higher thannormal due to lower than normal dispersion of the emissions. This condition will be evaluatedthrough the use of a special air dispersion modeling run. The potentially higher than normalfacility emissions during system upsets will be evaluated using upset factors developed forspecific types of upset conditions, and then applied to the POCs that would be affected by theseconditions. Because the upset factors will be employed to assess maximum potential one-hourPOC exposures, the factors include the effects of elevated POC emissions caused by the upset,and the duration of the condition. The highest potential short-term emission rates will occurwhen the facility is running at its maximum operating conditions when the upset occurs. Therefore the upset factors will be derived as multipliers to scale from the maximum normal


operating emission rates (as measured in compliance testing, and used in the long-term, multi-pathway emissions modeling) up to the potential maximum one-hour emission rates that mightoccur under upset conditions.

Upset emissions caused by equipment malfunctions in three of the Maine Energy facility’ssystems will be considered:

• upsets to the boilers’ combustion control system that result in incompletecombustion and increased emissions of organic compounds,

• upsets to the baghouses that result in increased emissions of particulate pollutants, and

• upsets to the spray dryer system that result in increased acid gas emissions.

Because there are two of each of these systems at the Maine Energy facility (one on each of thecombustion units) that operate independently, it may reasonably be assumed that only one willexperience upset conditions at any time. These upset conditions are also assumed to be short-lived because once they are detected, waste feed will be stopped to the combustion unitexperiencing the upset. The facility is designed to automatically halt waste feed, as waste feedcutoff is required when the opacity of the visible emission is equal to or greater than 15%.

The effect of process upset conditions will not be included in the multi-pathway risk assessmentcalculations because the effects of upset conditions are not expected to increase long-termemissions above the levels used in these calculations. The stack POC emission rates to be usedin the multi-pathway portions of the risk assessment will be based on actual stack test results,and uncertainty calculations will examine the effect of using high-end, long-term emission rates. These high-end emission rates will already be at levels above the long-term average emissionrates. Section 2.2.1 of the HHRAP states, (U.S. EPA) “. . . expects that emission rates used tocomplete the risk assessment will be (1) long-term average emission rates adjusted for upsets, or(2) reasonable maximum emission rates measured during trial burn conditions in order to assurethat risk assessments are conservative.” In section 2.2.5 of the HHRAP the EPA also notes that“. . . upsets are not generally expected to significantly increase stack emissions over the lifetimeof the facility.” Because the multi-pathway, indirect exposure estimates are based on such along-term time period, and because condition (2) of HHRAP section 2.2.1 cited above is met, theeffects of process upsets will not be included in this part of the risk assessment. The assessmentof upset conditions is thus restricted to short-term effects.

Basically, for the calculation of upset factors it is assumed that a malfunction occurs in one ofthe two units while the other unit operates under non-upset conditions, and that at the time of theupset both units are operating at maximum waste combustion conditions. The upset factor isthus equal to the unit’s increase in the POC emissions averaged over one-hour, added to the non-upset POC emission rates for the other unit, with the sum divided by the normal emission ratesfor both units together. For some of the calculations the normal emission rate is arbitrarily set atunity, and the upset emission rate is greater than one; for other conditions the upset (uncontrolledemission rate) is set at unity and the normal emission rate is lower. For example, if the failure of


a pollution control device allows a POC to be emitted at 10 times the usual level from one of twounits for one-half hour, the upset factor for that condition over a one-hour period would be:

112

102

2325

+ +

= .

The following information about emissions that may occur during upset conditions, and theresulting upset factors, have been developed in conjunction with the Maine Energy facility. Theeffect of using different upset factors in the risk assessment will be discussed in the uncertaintychapter of the report. Based on experience with similar MWC facilities, upset conditionemissions are not expected to have a significant effect on the risk assessment results, especiallyregarding long-term average emission rates. However, additional facility-specific informationwill be developed to determine the potential consequences of upset condition emissions, asdescribed in the following scenarios.

2.7.1 Combustion startup/shutdown upsetsThe conditions that exist during periods of combustor startup and shutdown are sometimesincluded in the estimation of upset factors. Since startup and shutdown procedures includereduced feedrates and result in lower operating temperatures, the only POC stack gasconcentrations likely to increase are those for organic compounds due to incomplete combustionof the feed material. Therefore, all organic POCs will be considered in the startup/shutdownupset scenario. Operating data will be examined to determine appropriate assumptions regardingemissions during startup/shutdown conditions. If facility-specific data are found to beinsufficient, data from other MWCs specifically collected to examine upset conditions will beused. For example, testing completed at a Marion County, Oregon facility during startup andshutdown demonstrated a 3 to 5-fold increase in the emission concentration for totalhydrocarbons (U.S. EPA, 1988). However, due to reduced throughput during these intervals,the hourly mass emission rates are not expected to increase by this amount. In addition, thelower throughput results in a lower gas flow rate at the stack exit which may lead to lessatmospheric dispersion of the emitted POCs and thus potentially higher maximum ground levelconcentrations.

In order to evaluate whether higher ground level organic POC concentrations will occur duringstartup or shutdown operations, a special air dispersion model run will be performed. The POCemission parameters for this run will be based on organic POCs from one combustion unit beingemitted at a concentration that is 5 times above normal, but at a 50% lower total gas throughput. The overall facility mass emission rates will therefore be at 1.75 times normal:

( )1 5 052

175+ ⋅

=.

.


The facility stack emission flow rate will modeled at

( )1 052

0 75+

=.

.

Because this model run will be used only to evaluate the maximum one-hour average directexposure levels, there is no need for POC deposition to be included in the model, nor for theextended modeling receptor grid to be included. These details will be discussed in the airdispersion and deposition modeling section of this protocol.

Information logged by the operators of the Maine Energy facility is expected to be sufficient toderive facility-specific estimates of the frequency and potential importance of startup andshutdown periods. If facility-specific data do not exist, information from similar MWC facilitieswill be used. For example, at the Hempstead, New York Facility operated by American Ref-Fuel during the years 1990–1993, startup and shutdown periods occurred an average of eighttimes per year for a total of six hours (Cambridge Environmental, 1994). In this case, given a limited frequency and modest elevations in potential emissions (as discussed above), startup andshutdown operations are not expected to have a significant effect on annually averagedemissions at the Hempstead facility.

2.7.2 Combustion control upsetsDisturbances of the combustion control system may result in incomplete combustion of organicPOCs. Assuming that such an event were to occur for one hour, facility emissions of organicPOCs may increase. Such disturbances in the combustion control system are typically infrequentand brief, less than one-half of one percent of the operating time at the Hempstead, New YorkFacility during 1992 and 1993 (Cambridge Environmental, 1994). In addition, the efficiency ofthe spray dryer/fabric filter system would preclude any large increases in organic emissions. Forexample, During the testing of the Marion County facility’s startup procedures, the overfire airfan failed for a brief time. Total hydrocarbon emissions during this period were elevated by afactor of 3–5 (U.S. EPA, 1988). Operators of the Maine Energy facility will be consulted toobtain any facility-specific information that may be available, and either this information orgeneric information (in order of preference) will be used to estimate a combustion control upsetfactor. If, for example, data suggest that organic POC concentrations from one of the MaineEnergy units could be increased by 5-fold during a combustion control upset, the facility organicPOC emissions over a one-hour period would be increased by an upset factor of 3:

1 52

3+

=


2.7.3 Baghouse/fabric filter upsetsAlthough total failure of a combustion unit’s entire fabric filter system is not plausible, ruptureof one or more filter bags in the unit’s baghouse system may occur. When this occurs, a portionof the flue gas stream is untreated. Operators quickly isolate the appropriate cell and replace theruptured bags. If such a rupture results in an increase in opacity to a level equal to or greaterthan 10% for 15 minutes, feeding of waste into that unit would automatically cease. Assumingthat the fabric filter bag has a particle mass collection efficiency of 99.5%, a total failure of thebag causes the emission rate through that bag to increase by a factor of 200. If 5% of the unit’sflue gas passes through the ruptured bags and one hour is required to isolate the cell containingthe ruptured bag, the increase in PM emissions from that unit is:

0.95 (flow through intact units) + 200 × 0.05 (flow through ruptured units) = 10.95.

The overall upset factor for such a filter bag rupture is thus:

1 10 952

6+≈

.

2.7.4 Spray dryer absorber upsetsIncreased emissions of hydrogen chloride may result from the malfunction of the spray dryerabsorber system. Most malfunctions of this system are short term, requiring less than about10–15 minutes to address and return to normal operation. In addition, effects of partial or fullspray dryer absorber malfunction are mitigated because residual unreacted lime on the fabricfilter bags will continue to remove acid gases. The assumed upset condition for the spray dryerabsorber system is a malfunction that results in operation for 15 minutes with the emissionsbeing ten times the normal rate. To estimate the overall upset factor, one unit is assumed tooperate normally, while the other operates normally for ¾ of the hour and emits at ten times thenormal rate for the remaining ¼ hour. Taking these three terms in order, the facility massemission rates over a one-hour period would be:

134

104

22 1

+ +

= ..

or a little more than two times greater than the rate under normal operations.


3 Air dispersion and deposition modeling

The 1996 health risk assessment is based on a detailed atmospheric dispersion and depositionmodel for emissions from the Maine Energy facility. The 1996 modeling employs the U.S.EPA’s Industrial Source Complex – Short-Term (ISCST3) model. Two aspects of the 1996modeling study, however, are inadequate to meet the needs of the updated health riskassessment. First, the 1996 modeling study does not include an evaluation of emissions from theodor scrubbing systems. Second, an analysis of wet deposition (pollutant washout from the airthrough rain and snow fall) was not included in the 1996 study.

Since the ISCST3 model is still recommended by the U.S. EPA for refined modelingapplications, the 1996 modeling analysis could be extended to meet the needs of the updated riskassessment. Newer models, however, are emerging that are based on improved scientificknowledge. In particular, a draft version of the AMS/EPA Regulatory Model – AERMOD – hasrecently been issued (U.S. EPA, 2002). AERMOD will likely replace ISCST3 as the preferredgeneral purpose dispersion model in the near future. Developed in a collaborative effort by theAmerican Meteorological Society and the U.S. EPA, AERMOD incorporates a greatly improvedmodel of dispersion due to atmospheric turbulence, and also includes the improved PRIMEalgorithms for simulating the aerodynamic effects of buildings on near-field plume dispersion. AERMOD has recently been used at the Maine Energy facility to investigate the improveddispersion characteristics that would occur from raising the height of the stack vents of the odorscrubbing system. Most recently, dry and wet deposition algorithms have been added toAERMOD enabling its use in multi-pathway risk assessments.

Since AERMOD requires inputs similar to those of the ISCST3 model, much of the informationfrom the 1996 modeling study is transferrable. Air dispersion modeling requires a substantialamount of input data, and preliminary plans and descriptions of the modeling study are detailedin subsequent sections.

3.1 Background and general air modeling descriptionTable 3.1 lists the principal source parameter values which will be used to model the dispersionof pollutant emissions from the Maine Energy facility emission sources. The parameters for theboiler stack are similar to those used in the 1996 modeling study. Table 3.1 also provides modelparameters for the stacks of the odor scrubbing system. These parameters are based oninformation from the 1996 health risk assessment, recent stack test results, and documentsrelated to the odor scrubbing system. The values will be checked with the operators of theMaine Energy facility to ensure that they reflect current operating conditions.


As constructed, the stack vents for the odor scrubbing system are not tall enough to avoid thepotential influence of aerodynamic plume downwash by the boiler building. Consequently, theU.S. EPA’s Building Profile Input Processor (BPIP) program will be used to determine directionspecific building dimensions based on final engineering drawings of the Maine Energy facility.

Table 3.1 Primary source parameters for atmospheric dispersion modeling

ParameterValue(s)

Boiler Stack Odor Scrubbing SystemStacks (3)

Stack-base elevation(above mean sea level) 18.3 m 18.3 m

Stack height 74.4 m 36.6 m

Stack inner (flue) diameter 1.98 m 1.83 m

Stack-gas temperature 295 °F 110 °F

Stack-gas velocity 21.4 m/s 14.3 m/s

Downwash potential? No Yes

3.2 Meteorological data and receptor locationsSimilar to 1996 modeling study, meteorological data for the updated modeling study will beobtained from the SCRAM Bulletin Board maintained by the U.S. EPA's Office of Air QualityPlanning and Standards (U.S. EPA, 2004). Data will be downloaded for the weather stationoperated by the National Weather Service at the Portland International Jetport. A five-yearperiod will be used based on coincidentally available data for both surface and upper air (mixingheight) observations. Hourly precipitation data for the same period will be extracted from asurface observation database compiled by the U.S. Department of Commerce (NCDC, 1993), asthese data are not included in the SCRAM files. The AERMET processor will be used tointegrate the meteorological data files into a format amenable to AERMOD.

The 1996 air modeling study was based on meteorological data over a 1987 to 1991 period. Thistimeframe will need to adjusted slightly to fit into the window of available precipitation data,which ends in 1990 (NCDC, 1993). This anticipated change in the modeling period will likelyhave no significant consequences, as meteorological data averaged over multiple years remainsimilar in their basic character. For example, Figure 3.1 depicts a wind rose of nine years ofmeteorological data (1984 to 1992), and the pattern of observations is quite similar to that of theanalogous wind rose depicted in Figure A.3 of the 1996 risk assessment report (CambridgeEnvironmental, 1996). The greatest frequency of winds originate from the south (slightly morethan 10%), and winds with westerly components are significantly more frequent than winds witheasterly components. The bulk of wind speeds range between 4 and 17 knots.


Figure 3.1 Wind rose observations collected at the Portland Jetport from 1984 through 1992


The receptor locations used in the 1996 dispersion modeling analysis will be maintained in theupdated AERMOD simulations. A standard polar receptor grid will be used to examinepotential impacts over the area within a 15-km radius of the Maine Energy facility. Receptorrings (of constant radius) will consist of 36 receptors spaced at 10 degree intervals. A total of 46receptor rings will be considered, with a higher concentration of receptors near Maine Energyfacility. The network will consist of radii (rings) of 50 m, 100–2500 m at increments of 100 m,2,750–5,000 m at increments of 250 m, and 6–15 km at increments of 1 km. Ground-levelelevations of all receptor locations will be obtained from topographic maps.

3.3 POC deposition parametersThe deposition of POCs from the atmosphere is calculated at each receptor location as part of theAERMOD simulation and the estimation of POC concentrations in environmental media. Forparticles and their associated pollutants, dry deposition parameters are calculated automaticallyby AERMOD based upon meteorologic conditions and particle size properties. Wet depositioncalculations for particles, however, rely on user input for establishing scavenging coefficients. Thus, AERMOD requires both the specification of a particle-size distribution and the explicitspecification of wet scavenging coefficients. The wet deposition of vapor-phase POCs is alsocalculated in the AERMOD modeling based on user specified scavenging coefficients andprecipitation data. Dry deposition of vapor-phase POCs is calculated as part of the modeling ofPOC levels in soils and water bodies based on the POC’s estimated concentration in air and aspecified vapor-phase deposition velocity. The selection of appropriate parameters for each ofthese models is critical for the estimation of POC concentrations in environmental media becausethe deposition parameters define the first step in determining the portions of POCs in air thateventually appear in other media. Uncertainties in the parameter values can therefore havesignificant effects on the uncertainties in the overall risk assessment results. This is especiallytrue for POCs such as mercury for which the risks due to multi-pathway (i.e., foodchain)exposures can be far greater than the risks due to direct inhalation.

The chemical and physical processes that occur during atmospheric deposition are complex andare not easily measured. For the purposes of multi-pathway modeling of the POCs beingconsidered in this risk assessment, several simplifying assumptions will be made in order tomodel atmospheric deposition. Where greater uncertainties exist in the modeling or parameters,the assumptions will tend to err on the side of conservatism, i.e., overestimating the depositionrates. The use of models derived from first principles and recently measured values will beemployed where appropriate and prudent.

3.3.1 Plume depletionPlume depletion options will be used in AERMOD. Use of the depletion options will have littleeffect on predicted concentrations near the facility but will produce more realistic POC estimatesat distant locations.

1 A similar U-shaped tendency is characteristic of dry particle deposition as well.


3.3.2 Particulate-phase POC depositionAs in the 1996 study, a facility-specific particle size distribution measured in 1987 will be usedin the AERMOD calculation of dry and wet particle deposition. Details of the particle size datafor the Maine Energy facility are provided in the 1996 risk assessment report (CambridgeEnvironmental, 1996). Two sets of POC mass fractions are specified based on how the specificPOCs are found in the particles:

• mass-weighted values are for pollutants that are likely to be distributed uniformlythroughout particles in the stack emissions; and

• surface-weighted values are for pollutants that are likely to condense (or form) ontothe surfaces of existing (seed) particles as combustion gases cool prior to their releasefrom the stack.

Information regarding the facility-specific particle size distribution is presented in Table 3.2.

Values for wet scavenging coefficients for particles are a function of particle size, and will beassigned values based on default values in the HHRAP. Scavenging coefficients for frozenprecipitation (snow and ice) are assumed to be one-third as large as the values for liquidprecipitation (rain) also based on recommendations in the HHRAP. The particulate-phase wetscavenging coefficients are listed in Table 3.2 as a function of particle size and are extractedfrom a figure presented in the documentation of the ISCST3 dispersion model (U.S. EPA,1999b).

3.3.3 Vapor-phase POC wet depositionThe atmospheric deposition of vapor-phase compounds is somewhat less well understood thanthe deposition of particles. Little guidance regarding the deposition of gases is provided in theHHRAP, and the limited amount of information that is presented inadequately characterizes thephenomenon. As recommended in the HHRAP, only wet vapor deposition will be explicitlyestimated using AERMOD. Dry vapor deposition will be calculated in subsequent portions ofthe multi-pathway modeling. For modeling wet deposition, the HHRAP suggests that vapors betreated as small particles, which may seem intuitively correct, but is in fact inaccurate from aphysical perspective. Plotted as a function of particle size, wet deposition scavengingcoefficients follow a U-shaped curve that reaches a minimum for particles about a micron indiameter. For large particles (i.e., particles greater than a micron in diameter), scavengingcoefficients decrease as particle diameters decrease in conjunction with a greater ability forparticles to deflect around raindrops (and hence resist scavenging). A reversal occurs, however,for sub-micron sized particles, for which attractive electrostatic effects become large enough toovercome momentum-based forces and cause scavenging coefficients to increase as particle sizedecreases.1 These electrostatic effects do not apply to gases; hence a different approach isrequired.


Table 3.2 Particle size distributions and wet scavenging coefficients for particle-boundPOCs. Based on particle size data presented in the 1996 risk assessment(Cambridge Environmental, 1996).

Particlediameter (:m)

Fraction of particles assigned toparticle diameter

Wet scavenging coefficient(hr/mm-s)

Mass-weighted Surface-weighted

Liquidprecipitation

(rain)

Frozenprecipitation

(ice and snow)

0.5 0.0343 0.2324 5 × 10–5 2 × 10–5

0.815 0.0267 0.1107 5 × 10–5 2 × 10–5

1.125 0.0167 0.0502 6 × 10–5 2 × 10–5

1.625 0.0517 0.1076 1.1 × 10–4 4 × 10–5

2.25 0.0317 0.0476 2.0 × 10–4 7 × 10–5

4.25 0.3670 0.2922 3.2 × 10–4 1.1 × 10–4

8 0.2490 0.1053 5.4 × 10–4 1.8 × 10–4

12.5 0.1400 0.0379 6.6 × 10–4 2.2 × 10–4

17.5 0.0830 0.0161 6.6 × 10–4 2.2 × 10–4

In addition, POC solubility is an important parameter to consider in modeling wet depositionscavenging. To more accurately predict the wet deposition of vapor-phase POCs (other thanionic mercury which is addressed below), a wet scavenging model based on Henry’s Lawpartitioning and mass balance will be used. The model calculates the maximum amount of avapor that could dissolve into a given depth of rainfall within a specified period, based onHenry’s Law and mass conservation. It is assumed that the chemical vapor reaches anequilibrium between vapor and dissolved phases in the air column during a precipitation event. The maximum possible scavenging coefficient for a compound that dissolves into water isderived from this mass balance.

The wet scavenging coefficient model is based on the amount of the chemical that deposits inprecipitation, calculated as:



Cair the average concentration of the vapor in air;Cprecip the average concentration in precipitation;S the precipitation scavenging coefficient;Dmix the atmospheric mixing height;R the rate of precipitation; andJ the time during which precipitation occurs.

The Henry’s Law equilibrium condition requires that:

where H is the Henry’s Law constant. Combining the previous two expressions, the scavengingrate can be estimated as:

A very similar model is presented in the EPA’s Mercury Study Report to Congress (U.S. EPA,1997). If one considers a pollutant that simply dissolves into water, the chemical reaction termsdrop out of the U.S. EPA (1997) model, and one obtains a simple relationship between thewashout ratio W (which equals the concentration of the chemical in rainwater divided by theconcentration of the chemical in air) and the non-dimensional Henry’s Law constant H:

By definition, the scavenging coefficient S is related to the washout ratio W and the atmosphericmixing height Dmix (Seinfeld, 1986):

Combining the above equations, one finds the same relationship proposed for calculating thescavenging coefficient:

Consideration of chemical-specific Henry’s Law constants could conceivably require separateruns of the ISCST3 model for each POC. As an alternative, it is proposed that the POCs be


grouped into three categories on the basis of their Henry’s Law constants (with the exception ofmercury species, as discussed below), and each of these categories be assigned a single set ofwet scavenging coefficients. For high and moderately high H values, equilibrium partitioningbased on a single surrogate value of H will be used, with application of the above equation for S. For chemicals with low Henry’s Law constants (and hence not limited by solubility), the smallparticle default values consistent with examples in the HHRAP guidance will be used. Valuesfor scavenging coefficients are listed in Table 3.3 grouped according to Henry’s Lawcoefficients.

Table 3.3 Gas scavenging coefficients for wet deposition modeling in ISCST3

Range of Hdim, in units ofatm-m3/mol

(non-dimensional Hvalues in parentheses) b

Proposedliquid

scavengingcoefficient (s-

mm/hr)–1

Rationale

Proposedscavenging

coefficient forfrozen

precipitation(s-mm/hr)–1

Rationale

High

Hdim $ 1×10–4

(H $ 4×10–3)


with H = 0.004 (non-dimensional)and Dmix = 750 m a

3 ×10–8

Values based on theassumption that

snow/sleet isroughly a as

efficient atscavenging relative

to rainfall (HHRAP, p. 3-52)

Moderately High

1×10–6 # Hdim < 1×10–4

(4×10–5 # H < 4×10–3)


with H = 0.00004 (non-dimensional) and

Dmix = 750 m a

3 ×10–6

Low

Hdim < 1×10–6

(H < 4×10–5)

5 ×10–5Representative value

for small particlesfrom Table 3-1) c

2 ×10–5

Ionic Hg 4 ×10–5Based on empirical

data described below 1 ×10–5

Notes: a A mixing height of 750 m is assumed (average value for Portland, Maine for 1984–1991 data). b The dimensional and non-dimensional Henry’s Law constants are related by:

where T is temperature and R is the Universal Gas Constant. Assuming a temperature of 25°C (298°K),the product RT is about 0.02445 mol/atm-m3.

c Also corresponds to the value predicted by S =1/(DmixH) with H = 0.0000074 (non-dimensional) and Dmix =750 m.


Vapor-phase ionic mercury has several unique properties that require its wet deposition to bemodeled differently than other compounds. Because the potential health effects related tomercury emissions may dominate the overall non-cancer portion of the risk assessment, it isessential that the first stage of the multi-pathway modeling of ionic mercury is as realistic aspossible.

Mercuric chloride, the form of mercury assumed to comprise all of the ionic mercury in themulti-pathway modeling, has a very low Henry’s Law constant (7.1 × 10–10 atm@m3/mol), and ishighly soluble in water (69,000 mg/l). The Henry’s Law constant for mercuric chloride is wellbelow any of the other POCs that have appreciable vapor fractions (the next lowest Henry’s Lawconstant for a POC with a vapor fraction of greater than 0.01 is 8.36 × 10–7 atm@m3/mol forbenzo(a)pyrene). Because mercuric chloride scavenged into precipitation dissociates rather thansimply partitions from the air, it is not correctly modeled using the Henry’s Law principlesdescribed above. Fortunately mercury concentrations and speciation in air and total mercury inwet deposition have been measured and assessed so that the scavenging coefficient for this POCmay be estimated empirically.

As described above, the washout ratio W is defined as the concentration of a compound inprecipitation divided by its concentration in air, and the scavenging coefficient S is estimatedfrom the washout ratio W by:

where Dmix is the atmospheric mixing height. Atmospheric concentrations of mercuric chloridevapor have been measured in Tennessee and Indiana at levels between 0.050 – 0.200 ng/m3 overa 4-year period from 1992 to 1995 (Lindberg and Stratton, 1998). The mean concentration of the177 samples collected at the Indiana site was 0.104 ng/m3. Total mercury in wet deposition hasbeen measured for several years at locations in Indiana as part of the National AtmosphericDeposition Program/Mercury Deposition Network (MDN, 2004). Table 3.4 presentsmeasurements of the concentration of mercury in precipitation taken at the two Indiana locationsclosest to the ambient measurements of mercuric chloride. Values in Table 3.4 representvolume-weighted averages of weekly samples, which are currently available for three years. Theannual-average mercury concentrations range from 11.1 to 13.2 ng/l. Averaged across calendaryears, values range from 11.3 to 12.2 ng/l at individual sites, and averaged across sites, valuesrange from 11.3 to 12.3 ng/l. The grand average of all mercury concentration values is 11.8 ng/l(weighting each site-year value equally). To estimate the mercuric chloride washout ratio fromthese data, the average deposition concentration (11.8 ng/l) is divided by the averageatmospheric concentration (1.07 × 10–4 ng/l), yielding a unitless washout ratio W of 1.1 × 105.

Application of the washout ratio equation requires an estimate of an average atmospheric mixingheight in the area of eastern Indiana where the concentration and deposition data were collected.Since there are no upper air monitoring stations in Indiana, data from Dayton, Ohio were used to

2 Mixing height data local to Indiana are used in this derivation as to estimate a scavengingcoefficient from a common set of data. The assumption then follows that the cavengingcoefficient is transferrable to any geographic area. In contrast, the generic gas scavengingcoefficients in Table 3.3 for the high and moderately high categories rely on an area-specificmixing height (derived from Portland, ME data) as an integral model parameter.


obtain an average mixing height Dmix of 833 m (U.S. EPA, 2004).2 Converting to the unitsrequired by AERMOD, the liquid scavenging coefficient for mercuric chloride vapor iscalculated as 4 × 10–5 (s-mm/hr)–1. This value is a conservative estimate of the scavengingcoefficient because its derivation assumes that all of the mercury in wet deposition is derivedfrom vapor-phase mercuric chloride when a significant portion of it is actually derived formparticulate-phase mercury species (Keeler et al., 1995), and because it assumes that there is nomercury in the cloud water before precipitation begins.

Table 3.4 Mercury Deposition Network (MDN, 2004) Data for Two Indiana Locations

Monitoring Site

Mercury concentration in precipitation (ng/l)

Calendar YearSite Average

2001 2002 2003

IN20 Roush Lake 11.7 11.2 11.1 11.3

IN21 Clifty Falls State Park 12.2 11.4 13.2 12.3

Calendar Year Average 12.0 11.3 12.2 11.8

A comparison can be made between this proposed wet scavenging coefficient and estimates ofscavenging coefficients derived for nitric acid as presented by Seinfeld (1986). Nitric acid is oneof the few compounds for which there is a significant database of measured values for bothatmospheric and deposition concentrations. It is also used as a surrogate for mercuric chloridebecause their relevant chemical properties are similar (U.S. EPA, 1997 and 1998). Becausemercuric chloride and nitric acid both dissociate in water, the Henry’s Law model isinappropriate to use for estimating their scavenging coefficients. Seinfeld (1986) presents valuesof wet scavenging coefficients for nitric acid under twelve different precipitation scenarios thatrange from 1.3×10–5 to 1.2×10–4 (s-mm/hr)–1. The proposed coefficient for mercuric chloride4×10–5 is well within this range.

As for other vapors, ionic mercury scavenging coefficients for ice/snow will be assigned to beone-third of the values estimated for liquids. Additional discussion and sensitivity calculationsmay be presented in the uncertainty analysis to investigate the importance of the wet depositionmodeling assumptions, especially with regard to ionic mercury vapor.

3 The GDISCDFT dry vapor deposition algorithms have now been incorporated into theISCST3 model. The GDISCDFT modeling as described was developed prior to the release ofthe updated ISCST3 model.


3.3.4 Vapor-phase POC dry depositionAt the time the HHRAP was developed, U.S. EPA dispersion models did not contain algorithmsto calculate dry deposition rates of gases, and consequently dry vapor deposition was insteadincorporated directly in the HHRAP model equations (Appendix B) using a deposition velocityapproach which simply relates the flux of the vapor-phase species to its average ambientconcentration through a multiplicative constant, the deposition velocity. However, little detailedinformation is provided in the HHRAP concerning the estimation of dry gas depositionvelocities. A default deposition velocity of 3 cm/s is suggested in Appendix B of the HHRAP,based on the recommendations in a 1994 draft guidance for screening level risk analyses ofhazardous waste combustion emissions (U.S EPA, 1994). The original database on which thisrecommendation is based contained dry deposition velocities for nitric acid, ozone, and sulfurdioxide. The deposition velocity of 3 cm/s is for nitric acid which was considered the mostsimilar to the constituents covered by the screening level risk analyses. The HHRAP notes(Appendix B, Table B-1-1) that this deposition velocity should be applicable to any organiccompound having a low Henry’s Law constant, but gives no support for the use of nitric acid as asurrogate for such POCs, nor does it give any recommendation for POCs with high Henry’s Lawconstants (nor the value below which the analogy is applicable). In addition, the original sourceof this dry deposition data is not cited by the EPA in either the HHRAP or the 1994 guidance,and is therefore not subject to review.

The U.S EPA’s algorithms for estimating gas deposition velocities were initially incorporatedinto GDISCDFT, a previous, draft version of the ISCST3 model.3 In a previous applicationevaluating emissions from a hazardous waste combusting cement kiln in Indiana, theGDISCDFT model was investigated to better estimate chemical-specific deposition velocities foruse in risk assessment calculations, and also to account for area-specific land use andmeteorologic data (Cambridge Environmental, 2002). The GDISCDFT model predicts averagedeposition velocities significantly lower than the HHRAP’s default recommendation. Based onthe GDISCDFT modeling, a value of 0.36 cm/s was found to be a conservative Vdv value forchemicals of limited solubility and reactivity.

Similar dry deposition algorithms for gases have been incorporated into the draft AERMODsoftware. To maintain consistency with the HHRAP, however, the AERMOD dry depositionoption will not be used for gases, but a more realistic value for the dry deposition velocity willbe used based on consideration of the AERMOD algorithms and values that have beendetermined in studies of dry deposition.

A figure presented by Seinfeld (1986), and referenced to the National Center for AtmosphericResearch (NCAR, 1982) shows experimental data on gas dry deposition velocities rankedapproximately in order of reactivity. The velocities are shown on a logarithmic scale rangingfrom 0.001 cm/s to about 5 cm/s; the gases range from the highly reactive HF to the less reactive

4 CASTNet data are available at: http://www.epa.gov/castnet/data.html, accessed July 2004.


CO, with the more reactive gases having higher deposition velocities. The dry deposition datafor nitric acid, contains 12 values, ranging from 0.06 to 4.5 cm/s; 10 of these are below 3 cm/s. The HHRAP default deposition velocity of 3 cm/s thus almost certainly overestimates thedeposition of gases that are less reactive and less than soluble nitric acid, and is likely tooverestimate the velocity even for species that are as reactive and soluble as nitric acid.

More recent and extensive empirical modeling of dry deposition of common pollutants has beenperformed as part of the U.S. EPA’s Clean Air Status and Trends Network (CASTNet, 2004). Dry deposition is assessed as part of the program using the Multi-Layer Model (MLM) based onmeasured atmospheric concentrations of sulfur and nitrogen based pollutants, andmeteorological, vegetation, and land use data. The MLM simulates dry deposition processes andcalculates deposition velocities (Meyers et al., 1998, and Finkelstein et al., 2000). The MLMhas been evaluated for a limited number of scenarios (summarized by Baumgardner et al., 2002)with the finding that it generally underestimates SO2 dry deposition and has a small positive biasfor HNO3.

CASTNet currently has three sites in Maine that have available data from years ranging from1989 through 20034. Summary data of annual average deposition velocities for four atmosphericspecies at stations in Maine and nationally are given in Table 3.5.

Table 3.5 Deposition velocity estimates from CASTNet (2004) data

Species

Annual average deposition velocities (cm/s)(26 Maine annual summaries, 953 nationwide annual summaries)

Values for Maine stations (nationwide in parentheses)

Minimum Maximum Average

Ozone (O2) 0.15 (0.058) 0.30 (0.33) 0.19 (0.17)

Sulfur dioxide (SO2) 0.23 (0.12) 0.42 (0.54) 0.33 (0.31)

Nitric acid (HNO3) 0.98 (0.52) 1.6 (2.8) 1.4 (1.3)

Particulate matter 0.065 (0.021) 0.15 (0.31) 0.11 (0.11)

The deposition velocities presented are a function of solubility and reactivity, with nitric acidhaving the highest values and particulate matter the lowest. Ozone, though reactive, is relativelyinsoluble, so surface water or moisture inhibits its dry deposition (Seinfeld, 1986). Because drydeposition is also a function of meteorology, vegetation, and land use, the national values cover abroader range than the Maine values. It is also clear from the data that the HHRAP defaultdeposition velocity of 3 cm/s is a significant overestimate for all but the most soluble/reactive


species and under meteorological and geographic conditions that lead to the highest depositionrates.

Although it would be possible to use a different dry deposition velocity in the multi-pathwaymodeling for each vapor-phase POC, the large uncertainties and lack of a well validated modelfor estimating these values (especially for the organic compounds) make this approach difficultto justify. Therefore, based on the dry deposition velocities for nitric acid derived for locationsin Maine as part of the CASTNet program, the risk assessment will employ a vapor-phasedeposition velocity of 1.4 cm/s for all POCs. This value should accurately model the mostcritical compound with respect to dry deposition and estimated risk, mercuric chloride, andshould conservatively model all of the other POCs. Additional discussion and sensitivitycalculations may be presented in the uncertainty analysis to investigate the importance of drydeposition modeling assumptions, especially if the likely overestimation of this parameter resultsin significant risk estimates for POCs less reactive than mercuric chloride.

The air-to-leaf transfer factor is another important deposition-related parameter subject tosubstantial uncertainties. Overall fate-and-transport modeling of PCDD/PCDF congeners hasbeen found to be very sensitive to assumptions regarding air-to-leaf transfer in some studies. U.S. EPA models continue to evolve, as exemplified in a recent paper (Lorber and Pinsky, 2000)that evaluates air-to-leaf models. This study, and possibly more recent literature, will bereviewed with respect to the HHRAP algorithms to ensure that the risk assessment considers anup-to-date scientific understanding of the air-to-leaf transfer factor. Similar to the PAHmetabolism factor and the chromium speciation assumptions, the HHRAP recommendedalgorithms will be used in the baseline risk assessment calculations, and sensitivity calculationsregarding the air-to-leaf transfer factor will be developed in the uncertainty section of the riskassessment.

3.4 Modeling of startup and shutdown emissionsAs described in Section 2.7.1, POC emissions during conditions of unit startup and shutdownwill be modeled in order to evaluate whether maximum, one-hour average, direct POC exposurelevels under these conditions exceed those that occur under normal plant operation. Theemission parameters for this model run will be POC mass flow rates of 1.75 times the normaloperating rates, and stack exit velocity of 0.75 times the normal full operating velocity. Becausethe results of this modeling will only be used for evaluating maximum direct POC exposurelevels, it will not require the modeling of POC deposition rates, nor the use of the large receptorgrid. Therefore only a single, simplified set of modeling runs for a passive tracer species will beneeded.

3.5 Summary of atmospheric dispersion and deposition modelingThe updated atmospheric modeling of POC emissions from the Maine Energy facility will beconducted with AERMOD, a more sophisticated model recently made available by the U.S.EPA. Similar to the 1996 study, the modeling will include a receptor grid extended to a distance


of 15 km from the Facility. Appropriate locations within the modeling domain will be identifiedto evaluate the various exposure scenarios within the human health risk assessment.

The HHRAP guidance suggests the use of three sets of model runs to simulate vapor-phase, andmass- and surface-weighted particle-phase POCs. In order to more accurately model the wetdeposition of critical vapor-phase POCs with differing partitioning and solubility properties,three different runs will be performed for organic vapor-phase POCs, and a separate run will beperformed for vapor-phase ionic mercury. Dispersion and deposition modeling will beconducted for the following POC types:

• mass-weighted particle-bound chemicals (emitted metals except mercury);• surface-weighted particle-bound chemicals (particulate-phase mercuric chloride and

the fraction of organic compounds adsorbed onto particles);• vapors with high Henry’s Law constants (H > 10–4 atm-m3/mol);• vapors with moderate Henry’s Law constants; (10–6 < H < 10–4 atm-m3/mol)• vapors with low Henry’s Law constants (H < 10–6 atm-m3/mol);• vapor-phase ionic mercury.

Each emission type will be assigned a nominal emission rate set to factors of 10 g/s so thatmodel predictions could be scaled easily to POC-specific emission rates. It may be necessary toassign larger nominal emission values in some cases (e.g., cases with low vapor scavengingrates) so that the ISCST3 model provided output with sufficient numbers of significant figures. The results of these modeling runs will then be used as input data to estimate POCconcentrations in other environmental media as discussed in Chapter 5. A single simplified setof modeling runs will also be performed using only the inner receptor grid and with no modelingof POC deposition to estimate maximum, one-hour, direct POC exposure levels under startupand shutdown operating conditions.


4 Exposure scenarios

The multi-pathway exposure assessment builds on the air dispersion and deposition modeling byestimating the concentrations of POCs in a variety of environmental media to which humans andwildlife may be exposed. In order to determine which media need to be evaluated, the pathwayswhich lead to exposures must be defined. The pathways that will be assessed in this riskassessment include the direct inhalation of airborne contaminants, and a variety of indirectpathways that consider the deposition of contaminants to soil, water, and vegetation, withpossible transfer and accumulation in the food-chain. Exposure scenarios are defined as acombination of such exposure pathways evaluated for a receptor at a specific location. Thelocations to be evaluated are those where there is the potential for the reasonable maximum long-term human exposures to emitted POCs to occur through a few specific pathways. Asrecommended in the HHRAP, the following exposure scenarios will be considered for theevaluation of chronic risks:

• Residents (adult and child);• Recreational farmers (adult and child);• Recreational fishers (adult and child); and• Nursing infants.

Children are distinguished from adults because their rates of exposure to chemicals (as expressedper unit body weight) are frequently higher.

Recreational fishers and farmers represent individuals whose diet includes a substantial portionof food that they catch in local waters and raise on local lands. These scenarios have beenredefined from the subsistence fisher and farmer scenarios that are described in the HHRAP tobetter characterize the habits of people living in the Cities of Biddeford and Saco and nearbyareas. The term subsistence suggests that essentially all of a person’s food source derives from asingle source. An examination of the HHRAP’s assumptions reveals that the rates of foodingestion for the subsistence scenarios are well below levels required for sustained existence. Hence, the term subsistence is an inappropriate descriptor for the scenarios characterized in theHHRAP.

In order to avoid the erroneous implications that could be associated with the term subsistence,the updated risk assessment for the Maine Energy facility will use the descriptor “recreational”to refer to high-end exposure scenarios. A recreational fisher is intended to represent a personliving in the Biddeford/Saco area who fishes frequently in local waters and regularly consumes aportion of the catch. Similarly, a recreational farmer is intended to represent a person living


within the area who raises vegetables and livestock to derive a significant portion of their foodsupply.

Allowing for the change in descriptors, the exposure scenarios to be evaluated are essentiallythose recommended in the HHRAP. Table 4.1, reproduced and adapted from the HHRAP,delineates the exposure pathways to be evaluated for each exposure scenario. Evaluation of thesurface water pathway as a source of drinking water will be evaluated based on the Saco River,which serves as the source of municipal water to many area residents.

Table 4.1 Exposure scenarios to be evaluated in the human health risk assessment

Exposure pathwaysExposure ScenariosA

Resident RecreationalFarmer

RecreationalFisher

Inhalation of vapors and particlesB x x x

Incidental ingestion of soil x x x

Ingestion of drinking water x x x

Ingestion of homegrownC produce x x x

Ingestion of homegrown beef x

Ingestion of milk from homegrown cows x

Ingestion of homegrown chickens x

Ingestion of eggs from homegrown chickens x

Ingestion of homegrown pork x

Ingestion of fishC x

Infant ingestion of breast milkD x x xA All of these exposure scenarios will be evaluated for adults and children.B The acute risks of one-hour direct inhalation of POCs will be evaluated at the residential receptorsite.C Ingestion of homegrown produce and livestock as well as fish are evaluated at ingestion rates thatreflect a substantial dietary intake of foods raised or caught locally in the Biddeford/Saco area. D Ingestion of breast milk will be evaluated for dioxin exposure to infants of mothers exposed to POCsin each of the three exposure scenarios

As indicated in Table 4.1, the ingestion of breast milk will be evaluated as a special pathway ofpotential concern independent of the other exposure scenarios, as recommended in the HHRAP. Infants can be exposed to concentrated doses of pollutants that are transferred through their


mother’s milk. The nursing infant pathway is based on the assumption that the mother receivesexposure to contaminant emissions from the Maine Energy facility, and hence is a member of theresident, recreational fishing, and/or recreational farming populations evaluated in the riskassessment.

The first step in the multi-pathway exposure assessment for each of these scenarios involves theinterpretation and use of the atmospheric modeling analysis. Specific receptor locations must beselected to evaluate each exposure pathway, with consideration of differences in the projectedimpacts of sources. For both the boiler stack and odor scrubbing system emissions, themaximum projected impacts might be found some distances beyond the property line at whichthe elevated plume touches down (on average), and the locations for the two sources will likelydiffer. Additionally, the locations of projected maxima may differ for ground-levelconcentrations in air, dry deposition, and wet deposition. Consideration must also be given toland use and the prediction of impacts at specific receptor locations of interest.

The resident receptors will be evaluated at the locations of highest projected facility impactsoutside of the facility property (as there are residential areas fairly close to the facilty). Therecreational fishing scenario will also be evaluated at this worst-case residential location, as it isplausible that any resident can be a recreational fisher. The fate-and-transport modeling,however, will consider the actual locations and characteristics of water bodies in estimatingpollutant levels in fish. The 1996 risk assessment focused on two small ponds because it is morelikely that facility emissions could more substantially affect their water quality. The updatedhealth risk assessment will also consider fish taken in the Saco River, a more significant fishingresource, to test the assumption that the river’s greater dilution volume reduces potential impactsfrom facility emissions. The recreational farming scenario will also be evaluated at the worst-case residential location if zoning and land use support the activities assumed in the scenario. Should the worst-case location be projected in a commercial or densely populated area, the locusof the recreational farming scenario will be shifted to a location at which it is practical to keepand raise a limited amount of livestock (a few chickens, a cow, etc.) to support personal foodconsumption.

In addition to the resident, recreational farmer, and recreational fisher scenarios, an acute riskscenario will also be considered to evaluate the potential for facility emissions to adversely affectnearby residents over short time periods (i.e. one hour) via the inhalation of chemicals ofpotential concern. This scenario will be evaluated at the location of the highest estimated one-hour, off-site ambient air POC concentrations. Indirect exposure analysis will be performed forall chemicals except for those for which it can be demonstrated that indirect exposure pathwaysare of de minimus concern. Complete rationale and documentation will be provided in the riskassessment report to justify the elimination of any chemicals form indirect exposure analysis.

Also, because the updated risk assessment will consider two sources of emissions from theMaine Energy facility released from different heights, there will likely be different worst-caseprojected points of impact. Consequently, the resident, recreational farmer, and recreational


fisher scenarios will be considered at the locus of each of the worst-case projections foremissions from the boiler stack and the odor scrubbing system.


5 Estimation of media concentrations

Following the estimation of average atmospheric POC concentrations and deposition rates, andthe definition of exposure scenarios and pathways, the next step in the risk assessment is thecalculation of POC concentrations in other environmental media. This is performed through theuse of a series of algorithms that model both the transport of POCs from one medium to anotherand the fate of the POCs in each medium. For example, POC concentrations in soil are modeledby considering dry and wet deposition of the POC to the soil, and POC loss from the soil due todegradation, erosion, surface runoff, leaching, and volatilization. The soil POC concentrationsare then used to model POC levels in plants and animals, and to assess human exposures due toincidental ingestion of soil. The estimated POC concentrations in each modeled environmentalmedium will be presented in tabular format within the final risk assessment report.

The detailed, pathway-specific algorithms and equations that make up this portion of the multi-pathway risk assessment are described in the body of the HHRAP guidance and further detailedin the guidance’s Appendix B (U.S. EPA, 1998). The HHRAP fate and transport modelingequations will be used unless site-specific considerations suggest the use of different models andassumptions. The HHRAP algorithms are generally based on previous guidance set forth by theU.S. EPA and other regulatory agencies, but are more comprehensive and detailed than previousguidance, especially with regard to recommendation of chemical-specific parameters. Thealgorithms are given in the body of the HHRAP guidance along with some history of theirderivation and justification for the selection of specific values for the equations. A few of theequations were modified in the 1999 Errata memo (U.S. EPA, 1999a) and some changes arerecommended in the 2000 Peer Review Comments (U.S. EPA, 2000a). Most of the equations inthe body of the document are applied to all of the POCs with the exception of several modifiedalgorithms for the modeling of mercury transport and fate which are documented in the HHRAPAppendix B. The equations are too numerous to be listed or described in detail in this protocol— they will be included in the risk assessment report.

The HHRAP equations require the use of numerous modeling parameters that describe thephysical and chemical properties of each POC, site-specific environmental and land-usecharacteristics, and the uptake and bioaccumulation of the POCs in plants and animals. Defaultvalues for almost all of these parameters are given in the body of the HHRAP guidance and itsAppendix A (U.S. EPA, 1998). The Errata memo (U.S. EPA, 1999a) and 2000 Peer ReviewComments (U.S. EPA, 2000a) contain corrections and updated values for some of theparameters.


In some cases, recent advances in scientific knowledge afford improvements on HHRAPmethods and assumptions. Some examples of these improvements include the detailedconsideration of mercury deposition modeling and topics such as PAH metabolism, chromiumspeciation, and air-to-leaf transfer of PCDD/PCDFs, which are discussed in this protocol. Should additional methods or assumptions become available that would improve the science andaccuracy of the risk assessment, analyses may be added in the uncertainty section of the riskassessment to explore sensitivity of the risk estimates. In such cases, however, baseline riskestimates will be based on the original HHRAP algorithms.

Although it is possible to perform almost all of the risk assessment calculations using only thedefault values for these parameters, the use of site-specific information where available producesrisk estimates that more accurately predict POC concentrations in the media being consideredand should reduce the estimates’ uncertainties. The first chapter of the HHRAP and thedescriptions of many of the default parameters in the HHRAP Appendix B both note thepreference for use of site-specific data when available. However, because such site-specific dataare often either unavailable or require extensive re-evaluation and documentation before they canbe used in a risk assessment, the use of default parameter values may be the only option formany parts of the risk assessment.

Many of the HHRAP default parameters are based on conservative assumptions that are likely toresult in overestimates of POC concentrations. Therefore the use of default parameters may beused as an initial screening approach within the multi-pathway risk assessment to establishwhich POCs and exposure pathways need to be evaluated more carefully. If the use of defaultparameters in the environmental transport calculations produces risk estimates below theappropriate levels of regulatory concern, these values may be used rather than site-specificvalues. The use of site-specific environmental data may only be required for a few POCs andexposure pathways. This approach will greatly simplify the risk assessment calculations, as wellas their reporting and review.

Among the large number of equations and parameters that are included in the HHRAP guidancedocuments, there are a few that have been identified as either being incorrectly derived, or forwhich recently published information provides more realistic estimates. Three such parameterswhich are used in critical POC exposure pathways in the risk assessment calculations aredescribed below. The use of updated, corrected, or more site-specific values for theseparameters addresses significant issues raised by the HHRAP peer review. The generalcomments section of the fate and transport section of the Peer Review Report (U.S. EPA, 2000a)contains the following summary and admonition:

“The major data gaps and limitations associated with fate and transport modeling are identifiedand discussed in this document. The key issues are noted below:


• biotransfer into foodstuffs of POCs with log Kow greater than 5.0;• dioxin bioaccumulation in chicken and eggs;• mercury behavior in watersheds; and• mercury bioaccumulation in fish.

We believe that these data gaps are sufficiently large so that regulatory decisions should not bemade without more detailed evaluations of these issues.” Following the recommendations in thepeer review report, the risk assessment for the Maine Energy facility will employ more accurate,reliable, and/or recently derived values and algorithms to address each of these issues.

The HHRAP guidance for the estimation of POC concentrations in livestock and dairy productsincludes the use of a metabolism factor (MF) that is designed to account for the metabolism ofPOCs in animals and humans. The metabolism factor (MF) represents the estimated amount ofPOCs that remains in fat and muscle. Based on information available at the time the guidancewas published, the HHRAP recommends the use of an MF value different than 1 for only onePOC, bis(2-ethylhexyl)phthalate (BEHP) for which an MF of 0.01 was specified. A recentpublication by Hofelt et al. (2001) identifies the need to apply MFs smaller than one forpolycyclic aromatic hydrocarbons (PAHs), which are readily metabolized by animals. Per therecommendation in Hofelt et al. (2001), an MF value of 0.01 should be applied to all PAHs. TheHHRAP recommends the use of an MF for calculating POC concentrations in beef, milk, andpork. Because the metabolism of PAHs involves enzymes generated by the liver, an MF of 0.01should also be applied in the calculation of POC concentrations in poultry, eggs, and fish (Hofeltet al., 2001), since these animals have livers (or are produced by animals with livers). Asdiscussed in Chapter 2, calculations based on the MF values recommended by Hofelt et al.(2001) will be presented in the uncertainty section of the risk assessment.

The default parameters used to describe the biotransfer of PCDDs and PCDFs to chicken andeggs (Bachicken and Baeggs) were incorrect in the original HHRAP guidance. The values for theseparameters in the HHRAP Appendix Table A-3 were found to have been calculated incorrectlyfrom the original research results (Stephens et al., 1995). The error arose because thebioconcentration factors (BCFs) for chicken and chicken eggs in the original reference weremultiplied by the soil consumption rate of 0.02 kg (DW)/day, when in fact it should have beendivided by the consumption rate. This error was subsequently corrected in the HHRAP Erratamemorandum (U.S. EPA 1999a). However, as noted in the External Peer Review of the HHRAP(U.S. EPA 2000a):

The bioconcentration factors (BCF) presented for eggs and chicken in Table 3 ofStephens et al. (1995) should be applied to the transfer of dioxins/furans from feed, ratherthan soil, since the fraction of feed that is soil is already incorporated in deriving the BCFvalues. In other words, in calculating Ba values for egg and chicken, the BCF values inTable 3 should be divided by the daily feed intake (0.2 kg DW/day), rather than the dailysoil intake (0.02 kg DW/day).


Therefore the values for Bachicken and Baeggs given in the Errata document will be reduced by afactor of 10 for inclusion in the risk assessment calculations.

Even after the correction of the errors in Bachicken and Baegg, there is still significant uncertaintyregarding the biotransfer of PCDDs and PCDFs into chicken and their eggs as examined in detailwithin the Peer Review Report. Three sources of uncertainties that are identified in theextrapolation from Stephens’ (1995) experimental data to the HHRAP’s default parameters aresummarized here. The first source of uncertainty is that the soil intake rate, Qschicken, is based onan untested assumption that 10% of a chicken’s diet is comprised of soil. While this value issimilar to one derived for wild turkeys, it might only be applicable to “free range” chickens. Amore typical value for chickens kept by current-day farmers might be 2 to 3%. The secondsource of uncertainty is that the default Ba values are derived from experimental results forexposures to very high soil concentrations of PCDDs and PCDFs, and with the assumption thatthe transfer characteristics of PCDDs and PCDFs from soil are similar to the transfercharacteristics from grain. Data for more realistic exposure scenarios in the same study and byother researchers produce lower transfer rates. Third, even the use of the corrected HHRAPdefault values for Bachicken and Baegg results in estimated levels of PCDDs and PCDFs in chickensand eggs that are too high in relation to the estimated levels for beef and pork (based on typicallymeasured ratios of PCDD and PCDF concentrations in these foods). The extent that theseuncertainties play a significant role in the overall risk assessment results will be discussed in theuncertainty section of the report.

The bioaccumulation factor (BAF) recommended for methyl mercury, in Appendix Table A-3-140 of the HHRAP is 6.8 ×106 l/kg. This value, according to the guidance in Appendix Table B-4-27, is to be applied to the total of the dissolved-phase concentrations of ionic and methylmercury for estimating methyl mercury levels in trophic level 4 (piscivorous) fish. The referencefor BAF is the 1997 U.S. EPA Mercury Study Report to Congress (U.S. EPA, 1997). This BAFvalue is found specifically in Volume III, Appendix D in section D.3.4.1 “BioaccumulationFactors Directly Estimated from Field Data – Methyl mercury in Piscivorous Fish.” Thedefinition given for the BAF in the original document is: “average Methyl mercuryconcentrations in piscivorous fish (trophic level 4) divided by average dissolved Methyl mercuryconcentrations in water, accumulated by all possible routes of exposure.” This BAF is notderived from the MHg concentration in trophic level 4 fish divided by dissolved total mercuryconcentration in water as described in the HHRAP. Hence the HHRAP-recommended value isinappropriate as used in the guidance, as it should not be applied to the sum of the methyl andionic mercury concentrations in water.

One option for correcting this error would be to apply the HHRAP default BAF to the dissolvedmethyl mercury concentration in the water, as described in the BAF definition in the MercuryStudy Report to Congress (U.S. EPA, 1997). A second approach would be to apply a BAF basedon total mercury levels rather than for methyl mercury levels. Such BAFs are derived in theMercury Study Report to Congress (Volume 3, Appendix D). Finally, the use of site-specificdata to calculate a BAF would remove many of the uncertainties inherent in the use of either theHHRAP default value or a similar value derived from data for different water bodies. If


sufficient data are available, such a BAF may be derived from mercury measurements taken introphic level 4 fish and water from the Saco River or other local water bodies. If only some ofthe data necessary to calculate a site-specific BAF are available or of sufficient quality, the datamay still be used to benchmark the estimated mercury concentrations in either water or fish.

Several factors must be considered in the evaluation of which BAF calculation method to applyfor estimating mercury levels in fish. Because the compound of concern in evaluating healtheffects of mercury in fish is methyl mercury and the modeling estimates a concentration for thisform of mercury in the dissolved-phase, it might seem appropriate to use a BAF based on thesetwo forms. However, the dissolved-phase methyl mercury concentration calculated in themodeling contains too much un-quantified uncertainty to justify this approach.

The transformation of mercury from inorganic forms into methyl mercury at a specific location isaffected not only by the simple physical and chemical properties of the mercury compoundsinvolved, but also by the site-specific watershed, surface water, and sediment chemistry, and bythe various biological species which are present. The transformation rate is affected by severalenvironmental properties, including pH, DOC, anoxia, sulfate concentrations, and water clarity.Many of these dependencies are under investigation by the scientific community. The MercuryStudy Report to Congress (U.S. EPA, 1997) includes five reaction types in three watershedmedia in its description of mercury methylation. The HHRAP algorithms use simple partitioningfactors to model the complex chemical and biological processes that influence the methylation ofinorganic mercury in surface waters. The estimated methyl mercury concentrations are thushighly uncertain.

Empirical data in the Mercury Study Report to Congress on the fraction of methyl mercury aspart of total dissolved mercury range from 4.6% to 15% with a best fit point estimate of 7.8%(U.S. EPA, 1997). A previous application of the HHRAP algorithms to assess mercuryemissions from a hazardous waste combusting cement kiln in Indiana yielded a methyl mercuryfraction of 17% (Cambridge Environmental, 2002), somewhat higher than any values cited in theMercury Study Report to Congress. The generic modeling of mercury methylation andpartitioning as applied in the HHRAP guidance greatly oversimplifies a very complex naturalsituation and is not technically defensible. It is thus proposed that the bioaccumulation ofmercury be modeled using a BAF based on total mercury levels. If it is not possible to calculatea site-specific BAF, this portion of the mercury transport and fate will be modeled using the BAFof 5.0×105 derived in the Mercury Study Report to Congress for total dissolved mercury andtrophic level 4 fish (U.S. EPA, 1997).

Modeling of mercury bioaccumulation based on the total mercury BAF allows easierbenchmarking of estimated waterbody and fish concentrations because these are most oftenmeasured as total mercury rather than methyl mercury. It also allows the quantitative evaluationof the value’s uncertainty because the value is presented in the Mercury Report not only as apoint estimate but also as a distribution of values. As stated previously, if data of sufficientquality and quantity are available, a BAF for mercury will be developed from measurementstaken in local waters. The use of more site-specific data for estimating mercury levels in fish


accounts for some of the variability and uncertainty in modeling the processes of mercurymethylation and bioaccumulation because the effects of local conditions are implicitly includedin the model. Therefore the updated Maine Energy risk assessment will employ a BAF forestimating mercury levels in fish based on total rather than methyl mercury, and preferably basedon site-specific data.


6 Exposure assessment

Exposure assessment builds upon the estimation of POC concentrations in various media bydefining, through various assumptions, rates and frequencies at which receptors might breathe,ingest, and otherwise contact the media to which POCs have migrated. Exposure assumptionsare generally designed to estimate a high-end level of exposure (although not necessarily thehighest potential exposure). The default recommendations discussed in Chapter 6 of theHHRAP regarding exposure assumptions will be followed unless site-specific data are identified.

The parameters that are necessary for estimating exposure rates once the POC concentrations invarious media are calculated include long-term average values for adults and children of:inhalation rates, and ingestion rates for drinking water, soil, homegrown produce and livestock,and locally caught fish. HHRAP default values for these ingestion rates may be modified toaccount for area-specific factors such as recommended limits on fish consumption and the factthat not all locally-derived foods necessarily come from areas substantially impacted by theMaine Energy facility’s emissions. For example, recreational fishers often take fish from avariety of locations, and not just a single water body.

Long-term average body weights are required in the calculations because many of the risk andhazard coefficients are expressed on a per body weight basis (e.g., Reference Doses are given inunits of mg/kg-day). The averaging for exposure by inhalation and ingestion includes factors toaccount for exposure frequency (e.g., days of exposure per week, and weeks of exposure peryear), and an exposure averaging time. For non-carcinogenic effects, the exposure averagingtime is equal to the exposure duration (given below). Because many cancers have a long latencyperiod, and because the metric for assessing cancer risks is the estimated excess lifetime cancerrisk (ELCR), the averaging period for assessing cancer risks is the assumed average lifetime of70 years. A final parameter required for exposure estimation is the assumed duration of theexposure. The HHRAP’s recommended exposure durations are listed in Table 6.1.

Table 6.1 Exposure durations recommended within the HHRAP guidanceExposure scenario receptor Recommended exposure duration Adult resident 30 yearsChild Resident 6 yearsAdult recreational fisher 30 yearsChild recreational fisher 6 yearsAdult recreational farmer 40 yearsChild recreational farmer 6 years


7 Risk characterization

Two categories of potential chronic health effects will be considered in the multi-pathway riskassessment, corresponding to cancer and non-cancer endpoints; potential acute health effects willbe considered in relation to direct exposures only. Dose-response relationships for carcinogensare characterized by unit risk factors and potency slope factors, with the assumption thatexposure to carcinogenic compounds at any level increases an individual’s risk of developingcancer. This increased risk is assumed to be linearly related to the exposure level, with nothreshold for the effect (i.e., there is no assumed exposure level below which there is noincreased risk), and no dependence on the exposure rate. The potential for chronic health effectsto result from exposure to non-carcinogenic POCs is assessed based on the assumption that anexposure threshold exists such that exposures below this level are unlikely to lead to any adverseeffects. These thresholds are the Reference Concentrations (RfCs) and Reference Doses (RfDs)for each POC that may cause chronic non-cancer effects by inhalation and oral exposure,respectively. The reference levels generally include the use of significant safety factors toaccount for uncertainties in their derivation and variability in the exposed population. As such,exposures to levels above the RfCs and RfDs do not necessarily indicate that adverse, non-cancer health effects will occur.

Data to evaluate the chronic toxic effects of the contaminants of concern will be obtainedprincipally from two U.S. EPA databases: the Integrated Risk Information System (IRIS) and theHealth Effects Assessment Summary Tables (HEAST, 1997). Current toxicologic data may notbe available for all of the contaminants of concern (e.g., for tentatively identified compoundsthat are not on standard lists of hazardous air pollutants). In these cases, efforts will be made toidentify relevant data from the literature, including such sources as the Agency for ToxicSubstances and Disease Registry (ATSDR, 2004). The HHRAP itself recommends chemical-specific toxicologic data, some of which derive from older versions of IRIS and HEAST, as wellas other sources.

In some cases, reliable toxicologic data may be available for evaluating oral exposure, but notfor inhalation exposure (or vice versa). If the toxicologic endpoint is plausible via either modeof exposure, data may be extrapolated from one route to the other. Toxicologic data that must bedeveloped for any chemicals of concern that are not contained in IRIS, HEAST, or the HHRAPwill be submitted to the DEP prior to their inclusion and use in the risk assessment.

Certain chemicals, notably PCDD/PCDFs and lead, lack established reference doses for theevaluation of non-cancer risks. For PCDD/PPCDFs, estimated levels of exposure will becompared with typical background levels of exposure to gauge the potential increase in exposure


that might result from facility emissions. Background exposure estimates have been developedin the U.S. EPA draft dioxin reassessment (U.S. EPA, 2000b). For lead, elements of the U.S.EPA’s Integrated Exposure Uptake Biokinetic (IEUBK) Model for Lead in Children will beapplied to estimate the impact of potential exposure to lead on blood-lead concentrations inchildren using the target metric of the percent of children expected to have blood-leadconcentrations greater than the ATSDR action level of 10 :g/dl. The lead calculations will beperformed with and without exposure to facility-related emissions.

Excess (incremental) lifetime carcinogenic risks (ELCRs) will be calculated as the product oflong-term average dose (concentration for inhalation exposure) and carcinogenic potency (unitrisk). The exposure periods listed in Table 6.1 will be used to assess incremental cancer risk. Individual risk estimates will be summed across chemicals and exposure pathways to provide atotal estimate of incremental cancer risk due to emissions from the Maine Energy facility. Overall, individual ELCR levels will be compared with the Superfund criteria for cancer risks inthe range of 10–6 to 10–4 (i.e., 0.000001 to 0.0001, or one-in-one million to one hundred-in-onemillion).

Hazard Quotients (HQs) will be calculated for noncarcinogenic endpoints as the ratio of theestimated dose (or concentration) for each POC to the reference dose (or concentration)identified in the toxicity assessment. An overall hazard level or Hazard Index (HI) will beconstructed as the sum of all hazard ratios calculated for individual exposure routes andchemicals. An estimated HI value less than 1 is generally considered to indicate that theexposure is unlikely to result in adverse non-cancer health effects, and the emissions in questionare therefore acceptably small in this regard. Should the hazard index exceed a value of one, anorgan-specific analysis will be conducted to investigate whether it is appropriate to sum thedifferent types of non-cancer HQs or whether the various effects are unrelated and the HQsshould be evaluated seperately.

In addition to chronic hazard indices, acute hazard ratios will be calculated as the ratio ofmodeled short-term exposure point concentrations in air to Acute Inhalation Exposure Criteria(AIEC), as described in the HHRAP guidance. AIEC are listed for a number of chemicals inAppendix A of the HHRAP. Guidance for updating some AIEC values is available and will beused following the hierarchy described in the HHRAP. As with chronic, non-cancer healtheffects, if the acute exposures are below the exposure criteria levels, it is expected that noadverse effects will occur due to the exposures, and the POC emission rates will therefore beconsidered acceptably small with respect to acute health effects.

The estimated excess lifetime cancer risks and non-cancer hazard quotients for each exposurescenario will be presented in table form within the risk assessment report. The risk indices willbe given for each POC individually and for all POCs together.


8 Uncertainty and sensitivity evaluation

The uncertainty and sensitivity evaluations will include both a qualitative discussion of thefactors that lend uncertainty to the risk estimates (e.g., toxicologic data, assumptions used tomodel exposure point concentrations, etc.), and where applicable, some quantitative sensitivityassessments. Several examples of likely sensitivity analyses are discussed in previous sectionsof the protocol (e.g., non-detects of PCDD/PCDF congeners, PAH metabolism, chromiumspeciation, PCDD/PCDF air-to-leaf transfer). The degree of detail in the uncertainty section willdepend in part on the nature of the findings of the risk assessment. If predicted risks are nearregulatory target levels, the uncertainty section will be more detailed in order to provide moreinformation about risk estimates; if the predicted risk levels are well below regulatory targetlevels, fewer details and sensitivity estimates will be presented. Uncertainties related to POCsthat are responsible for significant portions of the overall estimated risks, and the parameters andequations that describe critical exposure pathways for these POCs will be discussed in greaterdetail. Other factors may also be considered in the uncertainty assessment if they are determinedto be of importance to the calculations and interpretation of the risk characterization.


9 Risk assessment conclusions

The conclusions of the risk assessment will integrate findings and compare them to target risklevels. Aggregate hazard indices will be compared to a value of one. If necessary, hazardindices will be broken down into separate indices based on health-specific endpoints. Incremental cancer risk estimates, summed over all POCs that are known or potentialcarcinogens, will be compared to Superfund criteria for cancer risks in the range of 10–6 to 10–4

(one-in-one million to one hundred-in-one million).


10 References

ATSDR (2004). Toxicological Profiles for many POCs maintained by the Agency for ToxicSubstances and Disease Registry available at: http://www.atsdr.cdc.gov/toxpro2.html.Accessed July 2004.

Axenfeld, F., Münch, J., and Pacyna, J. (1991) Europäische test-emissiondatenbasis vonquecksilberkomponemten für modellrechnueugen. Umweltforschungsplan desBundesministers für Umwelt, Naturshutz und Reaktorsicherheit—Luftreinhaltung—104 02726.

Baumgardner Jr., R.E., Lavery, T.F., Rogers, C.M., and Isil, S.S. (2002). Estimates of theAtmospheric Deposition of Sulfur and Nitrogen Species: Clean Air Status and TrendsNetwork, 1990-2000. Environmental Science and Technology. 36(12):2,614-2,629.

Cambridge Environmental (1994). A Health Risk Assessment for the Capital District IntegratedSolid Waste Management Facility. Prepared for the American Ref-Fuel Company of theCapital District, Village of Green Island. Cambridge Environmental, Cambridge MA,September 1994.

Cambridge Environmental (1996). A Health Risk Assessment for the Maine Energy RecoveryCompany Facility, Biddeford, Maine. Prepared for the Maine Energy Recovery Company Cambridge Environmental, Cambridge MA, October 1996.

Cambridge Environmental (2002). Risk Assessment for the Evaluation of Kiln Stack Emissions andRCRA Fugitive Emissions from the Lone Star Alternative Fuels Facility, GreencastleIndiana. Cambridge Environmental, Cambridge MA, April 2002.

CASTNet (2004). Clean Air Status and Trends Network data is available at:http://www.epa.gov/castnet/data.html, accessed July 2004.

Finkelstein, P.L., Ellestad, T.G., Clarke, J.F., Meyers, T.P., Schwede, D.B., Hebert, E.O., and Neal,J.A. (2000). Ozone and Sulfur Dioxide Dry Deposition to Forests: Observations and ModelEvaluation. Journal of Geophysical Research 105(D12):15,365-377.

HEAST (1997). Health Effects Summary Tables: FY-1997 Update. Washington, DC: Office ofResearch and Development and Office of Emergency and Remedial Response, U.S. EPA. July 1997. EPA 540/R-97-036.


Hofelt, C.S., Honeycutt, M., Torin McCoy, J., and Hawes, L.C. (2001). Development of ametabolism factor for polycyclic aromatic hydrocarbons for use in multipathway riskassessments of hazardous waste combustion facilities. Regulatory Toxicology andPharmacology 33:60–65

IRIS (2004). U.S. EPA, Integrated Risk Information System http://www.epa.gov/ngispgm3/iris/subst/index.html. Accessed July 2004.

Keeler, G., Glinsorn, G., and Pirrone, N. (1995). Particulate mercury in the atmosphere: it'ssignificance, transport, transformation and sources. Water, Air and Soil Pollution 80:159-168.

Lindberg, S.E. and Stratton, W.J. (1998). Atmospheric mercury speciation: Concentrations andbehavior of reactive gaseous mercury in ambient air. Environmental Science & Technology32 (1):49-57.

Lorber, M. And Pinsky, P. (2002). An evaluation of three empirical air-to-leaf models forpolychlorinated dibenzo-p-dioxins and furans. Chemosphere 41:931–941.

MDN (2004). Mercury Deposition Network, Concentration and Deposition Maps, available at:http://nadp.sws.uiuc.edu/mdn/maps. Accessed July 2004.

Meyers, T. P., Finkelstein, P., Clarke, J., Ellestad, T.G., and Sims, P.F. (1998). A Multilayer Modelfor Inferring Dry Deposition Using Standard Meteorological Measurements. Journal ofGeophysical Research 103(D17):22,645-661.

NCAR (1982). National Center for Atmospheric Research, Regional Acid Deposition: Models and

Physical Processes, Boulder CO.

NCDC (1993). Solar and Meteorological Surface Observation Network, 1961 – 1990. U.S.Department of Commerce, National Climatic Data Center.

OEHHA (1998). Technical Support Document for the Determination of Acute Reference ExposureLevels for Airborne Toxicants. California Environmental Protection Agency: Office ofHealth Hazard Assessment.

Petersen, G., Iverfeldt, Ä., and Munthe, J. (1995). Atmospheric mercury species over central andnorther Europe. Model calculations and comparison with observations from the Nordic Airand Precipitation Network for 1987 and 1988. Atmospheric Environment 29:47-67.

Seinfeld, J.H. (1986). Atmospheric Chemistry and Physics of Air Pollution. New York: John Wiley& Sons.

U.S. EPA (1988) Municipal waste combustion multipollutant study. Shutdown/startup emission testreport. Marion County solid waste-to-energy facility. Ogden Martin Systems of Marion, Inc.


Brooks, Oregon. Research Triangle Park, NC: Office of Air Quality Planning and Standards.EMB Report No. 87-MIN-04A.

U.S. EPA (1993). Emission Factor Documentation for AP-42 Section 2.1, Refuse Combustion. U.S.Environmental Protection Agency, Office of Air Quality Planning and Standards. Availableat: http://www.epa.gov/ttn/chief/ap42/ch02/bgdocs/b02s01.pdf

U.S. EPA. (1994). Revised Draft Guidance for Performing Screening Level Risk Analyses atCombustion Facilities Burning Hazardous Wastes. Office of Emergency and RemedialResponse. Office of Solid Waste. December 1994.

U.S. EPA (1997). Mercury Study, Report to Congress. Volume III: Fate and Transport of Mercury

in the Environment. EPA-452/R-97-005.

U.S. EPA (1998). Human health risk assessment protocol for hazardous waste combustion facilities. Peer review draft. Office of Solid Waste and Emergency Response. July 1998. EPA530-D-98-001A, B & C.

U.S. EPA (1999a). Human health risk assessment protocol for hazardous waste combustionfacilities. Peer review draft. Errata—August 2, 1999. Memorandum from Barnes Johnson,Director Economics, Methods, and Risk Analysis Division.

U.S. EPA (1999b). User’s Guide for the Industrial Source Complex (ISC3) Dispersion Models.Volume II – Description of Model Algorithms. June 1999 Addendum. U.S. EnvironmentalProtection Agency, Office of Air Quality Planning and Standards. Available at:http://www.epa.gov/ttn/scram/

U.S. EPA (2000a). External Peer Review-Human Health Risk Assessment Protocol for HazardousWaste Combustion Facilities—Peer Review Comments. TechLaw, Inc. Dallas. May, 2000. RCRA Docket No. F-1998-HHRA-FFFFF.

U.S. EPA (2000b). Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds, Part I: Estimating Exposure to Dioxin-LikeCompounds, Volume 3: Properties, Environmental Levels, and Background Exposures. Draft. U.S. Environmental Protection Agency, Office of Research and Development,National Center for Environmental Assessment - Washington. EPA/600/P-00/001Bc.

U.S. EPA (2002). User's Guide for the AMS/EPA Regulatory Model – AERMOD. U.S.Environmental Protection Agency, Office of Air Quality Planning and Standards. Availableat: http://www.epa.gov/scram001/7thconf/aermod/aermodugb.pdf

U.S. EPA (2004). Meteorological data files available from the Support Center for Regulatory AirModels (SCRAM) website. Homepage: http://www.epa.gov/ttn/scram/

14500 Avion Parkway, Suite 300 Chantilly, Virginia 20151(703) 818-1000(703) 818-8813 FAXwww.techlawinc.com

April 18, 2005

Mr. Brian S. PhinneyEnvironmental Code OfficerCity of Biddeford205 Main StreetBiddeford, ME 04005

Mr. Ken RobbinsMaine Energy Recovery Co./Casella3 Lincoln StreetBiddeford, ME 04005

Reference: MERC Technical Support Contract, Work Assignment No. 06320; TechnicalReview of Risk Assessment Protocol for the Evaluation of Multi-PathwayImpacts of Emissions from the Maine Energy Recovery Company Facility,Biddeford, Maine

Dear Mr. Phinney and Mr. Robbins:

Per our discussion of last week, TechLaw is pleased to provide you with our technical notice ofdeficiency and assessment of the Risk Assessment Protocol for the Evaluation of Multi-PathwayImpacts of Emissions from the Maine Energy Recovery Company Facility, Biddeford, Maine.

I wish to note that in preparation of these comments, TechLaw considered the most widespreadand generally accepted hazardous waste combustion risk assessment guidance documents. Ofcourse, these guidance documents represent conservative, often default-based positions andshould be perceived strictly as guidance, rather than promulgated rule. TechLaw's commentsfocus on many of these conservative and fundamental considerations, however latitude extendedby agreement on risk management may allow for an increase in site-specificity prior to initiationof the human health risk assessment.

Many of the comments as presented may be discussed in a forthcoming conference call, or left tobe addressed within the forthcoming human health risk assessment itself, at your discretion.

TechLaw is providing this assessment formatted in Wordperfect 9.0 and Adobe Acrobat.

TechLaw will be pleased to discuss the importance, ramifications and/or significance of thesecomments at your convenience. Please do not hesitate to contact me if you have any furtherquestions. I may be reached at 518.851.6645 or via email at [email protected].

Sincerely,

Travis R. Kline, MEMManager, Toxciology and Risk Assessment

cc: H. Sellers, TechLawN. Khurd, TechLawM. Smith, TechLawP. Brown-Derocher, TechLaw

TECHNICAL REVIEW OF RISK ASSESSMENT PROTOCOL FOR THE EVALUATION OF MULTI-PATHWAY IMPACTS OF EMISSIONS FROM THE

MAINE ENERGY RECOVERY COMPANY FACILITY, BIDDEFORD, MAINE

Submitted to:

Mr. Brian S. PhinneyEnvironmental Code Officer

City of Biddeford205 Main Street

Biddeford, ME 04005

and

Mr. Ken RobbinsMaine Energy Recovery Co./Casella

3 Lincoln StreetBiddeford, ME 04005

Submitted by:

TechLaw, Inc.14500 Avion Parkway

Suite 300Chantilly, VA 21051-1101

Work Assignment No.: 06320Contract: MERC Technical SupportTechLaw WAM: Travis R. KlineTelephone No.: 518.851.6645

April 18, 2005

1

Risk Assessment Protocol for the Evaluation of Multi-Pathway Impacts of Emissions from the Maine Energy Recovery Company Facility

in Biddeford, Maine

Technical Review Comments

General Comment:

1. Overall, the issue of what is considered a “baseline” analysis in the main body of theproposed risk assessment is problematic as currently described in the Maine EnergyRecovery Company (MERC) protocol. MERC proposes to perform a baseline riskassessment using approaches that are less conservative than those recommended in U.S.EPA’s Human Health Risk Assessment Protocol for Hazardous Waste CombustionFacilities (1998, errata 1999) (HHRAP) document (e.g., average emission values, one-half detection limit values as surrogates in certain emission testing runs, and anabbreviated list of pollutants of concern [POCs]) combined with HHRAP recommendedchromium speciation assumptions and HHRAP recommended algorithms and parameters. MERC further proposes to perform an alternate analysis in the uncertainty section of thereport using high-end emission rates along with a variety of approaches that differ fromthose recommended in the HHRAP document. It is recommended that the baseline riskassessment represent a conservative assessment that is comparable to other baselineassessments performed for other combustion facilities. One course of action that willprovide a conservative risk assessment that is consistent with and comparable to riskassessments performed for other combustion facilities is to perform a baseline riskassessment that substantively follows U.S. EPA’s HHRAP document. The uncertaintysection would then be the appropriate place to evaluate approaches and assumptions thatdiffer from those presented in the HHRAP document such as:

• eliminating all non-detected POCs regardless of whether they are waste streamcomponents,

• using one-half the detection limit as a surrogate emission rate for constituents thatare detected in only some test runs,

• assuming all chromium present is in a trivalent state, • using alternate algorithms or parameter values based on information in the

technical literature, and other proposed technically defensible deviations.

2

Specific Comments:

1. Section 2.1, Basic facility and site description, page 2-1.

The labels and the scale of Figure 2.1, Topographic Map of the Vicinity of the Maine EnergyFacility, are not legible. It is recommend that in the final risk assessment report the MaineEnergy Recovery Facility (MERC) replace the existing Figure 2.1 with a larger scale, morelegible version.

2. Section 2.2, Pollutants of Concern (POCs), page 2-3.

The methodology used to derive the volatile organic (VOC) and semi-volatile (SVOC)compound Pollutants of Concern (POCs) deviates considerably from that outlined in the U.S.EPA’s 1998 Human Health Risk Assessment Protocol for Hazardous Waste CombustionFacilities (HHRAP). The MERC protocol (protocol) proposes to include only the SVOCs thatwere detected in at least one run of the recent stack testing performed at the facility. TheHHRAP guidance, however, recommends a more conservative approach which include not onlyVOCs and SVOCs that are detected in at least one stack test run, but inclusion of all non-detected VOCs and SVOCs that may be present in the waste stream or formed as products ofincomplete combustion (PICs), consideration of the 30 largest tentatively identified compounds(TICs), and consideration of any constituents that may be of particular concern to the localcommunity. At a minimum, this suggests that the additional organic compounds detected in theodor scrubbing system testing be included in the POC list for the boiler stack, as well as anyother constituents that are known to be present in the waste stream or potentially formed as PICs(e.g., polynuclear aromatic hydrocarbons). The protocol should provide further information onthe potential chemical composition of the waste stream burned as fuel, identify whether anywaste stream testing has been conducted, and if so, discuss the results of that testing. It isrecommended that the list of POCs be expanded to include additional constituents of potentialconcern as detailed in the HHRAP guidance. Alternatively, compelling evidence for limiting thePOCs to those currently listed in the protocol should be provided.

3. Section 2.3, POC Emission Rates, page 2-4.

The MERC protocol states that emission rates will be derived from recent stack testing. Further,the data collected during boiler stack tests conducted in the past four years will be “considered.” Additional information is necessary to more fully describe the proposed development of POCemission rates for the risk assessment. It is recommended that the protocol clarify whetherrecent stack testing was conducted as a trial burn, a risk burn, or as part of some othercompliance test program. The conditions under which the testing was performed should bedescribed (e.g., stressed operations with representative waste). Furthermore, it is recommendedthat the protocol be revised to include the methodology to be followed when considering datafrom previous boiler stack tests. Finally, the protocol should describe how information from alldata sources will be integrated into a final data set from which the risk assessment emission rateswill be derived.

3

The protocol states that a baseline risk assessment will be performed using emission rates basedon averages over the emission test runs. Both EPA’s 1998 HHRAP guidance and 2001 RiskBurn Guidance for Hazardous Waste Combustion Facilities recommend use of the average valueplus two standard deviations as the emission rate for the risk assessment. It is recommended thatthe more conservative methodology for deriving emission rates outlined in the documentsreferenced above be used in the baseline risk assessment (i.e., the lower of either the maximumdetected emission rate or the average emission rate plus two standard deviations). The alternateassessment using the average of the emissions test results, as proposed in the current protocol,should be performed as part of the uncertainty analysis.

4. Section 2.4, Procedure for Non-Detected Compounds, page 2-5.

U.S. EPA’s HHRAP document recommends the use of the full detection limit (MDL-derivedRDL for non-isotope dilution methods and the EDL for isotope dilution methods) as a surrogateemission rate for the risk assessment. The MERC protocol indicates that a value of one-half thedetection limit will be used. It is recommended that the more conservative full detection limitvalue be used in the baseline risk assessment. Then, if necessary, an alternate assessment using avalue of one-half the detection limit, as proposed in the current protocol, maybe performed aspart of the uncertainty analysis.

Additionally, the protocol should clarify what detection limits are being referred to in Section2.4. It is recommended that the protocol clearly state that the emission rates for non-detectedPOCs will be calculated by assuming that their concentration is equivalent to the MDL-derivedRDL for non-isotope dilution methods, or the method-defined EDL for isotope dilution methods. Alternatively, if MERC proposes to use other types of detection limits in the risk assessment toaddress non-detect issues, the type of detection limit should be identified and its use justified. Also, the impact on the risk assessment due to use of other types of detection limits should becompared to the results if the detection limits recommended in the HHRAP were used.

5. Section 2.5, Chromium Speciation, page 2-5.

Section 2.3.8.1 of the U.S. EPA HHRAP document states that unless speciation data exist forchromium, all chromium should be conservatively considered to be in its hexavalent form. Thedocument further states that if chromium is determined to be a risk driver, then the risks shouldbe recalculated in the uncertainty section assuming that chromium is in its trivalent form forindirect exposure pathways. Therefore, in the absence of site-specific chromium speciation data,it is recommended that the baseline risk assessment be conducted assuming all chromium is in itshexavalent form as recommended in the HHRAP document. Then, if necessary, an alternateassessment assuming chromium is present only in its trivalent form should be performed forindirect exposure pathways as part of the uncertainty assessment.

6. Section 2.6.2.2, Default Mercury Speciation, page 2-8.

Mercury speciation in the risk assessment for the MERC facility is discussed in Section 2.6 of

4

the protocol. Specifically, Section 2.6.2.2 proposes to employ a distribution of mercury speciestaken from the Mercury Study Report to Congress if measurement-based speciation data cannotbe developed from analysis of mercury samples taken at the facility. The proposed distribution,60% vapor-phase elemental mercury, 30% vapor-phase ionic mercury, and 10% particle-boundmercury, differs from the distribution presented in the 1998 HHRAP (20% vapor-phaseelemental mercury (Hg0), 60% vapor-phase ionic mercury (Hg2+), and 20% particle-boundmercury (HgP)).

The case study referenced in the MERC protocol that uses 60% Hg0, 30% Hg2+, and 10%HgPspeciation ratios taken from the EPA’s 1997 Mercury Study Report to Congress is based onthe assumption that the example municipal waste incinerator uses activated carbon injection inthe pollution control system. Since activated carbon effectively captures Hg2+, the result is thatthe percentage of Hg0 as a fraction of total mercury increases. The MERC municipal wasteincinerator does not employ activated carbon injection in the air pollution control system. TheMercury Study Report to Congress (section C.2.1.2) cites studies in the literature that municipalwaste incinerators using spray dryers and fabric filters (such as those at the MERC facility)result in mercury control ranging between 0 and 50 percent, and when activated carbon injectionis added, mercury control exceeding 90 percent can be achieved. The Mercury Study Report toCongress (section C.2.1.2) further cites three other studies in the literature indicating thatmunicipal waste incinerators predominantly emit Hg2+, with mercury speciation ratios of 10%vapor-phase elemental mercury, 85% vapor-phase ionic mercury, and 5% particle-boundmercury specifically cited in two of those papers. This is considerably different than thespeciation ratios proposed in the MERC protocol and would result in much greater calculatedlevels of deposited mercury and bioaccumulated mercury.

It is strongly recommended that, in the absence of site-specific mercury speciation of adequatedata quality, the baseline risk assessment be conducted using the mercury speciation ratios givenin the U.S. EPA HHRAP document. The mercury speciation ratios proposed in the protocol maybe evaluated and presented for comparison purposes in the uncertainty section of the riskassessment. The alternate evaluation, if conducted and presented in the risk assessment report,should justify the use of specific mercury speciation ratios utilized in the analysis. Because theMERC facility does not employ an air pollution control technology capable of capturingsignificant portions of divalent mercury, it may not be justifiable to utilize a higher ratio forelemental mercury in the risk assessment.

7. Section 2.7, Process Upset Emissions, page 2-11.

The application of process upset factor(s) as presented in the MERC protocol is different fromthe recommended approach presented in the U.S. EPA HHRAP document. The MERC proposalappears to be for an acute analysis rather than the development of process upset factors asdefined in the HHRAP document. Sections 2.7.1 through 2.7.4 of the MERC protocol presentsample calculations for the proposed process upset factors that represent upset conditions duringplant startup/shutdown operations and three (3) equipment malfunction scenarios. Thecalculation methods for the process upset factors appear technically adequate. Section 2.7.1

5

states that POCs will be emitted at 5 times their normal concentration during combustionstartup/shutdown upsets. In addition, it will be assumed that the total gas throughput will be50% lower. It is recommended that MERC revise the protocol to describe how these valueswere determined. It is further recommended that the risk assessment report provide the data usedto calculate the process upset factors proposed in Sections 2.7.2 through 2.7.4 of the protocol aswell as an example calculation for each factor.

The MERC protocol indicates that surrogate operating data from similar municipal wastecombustion facilities will be used to develop process upset factors for an acute analysis if site-specific operations data are not sufficient to derive facility-specific upset factors. As part of theprotocol document, MERC should present and evaluate any available historic site-specificoperations data available and make a determination as to whether it is sufficient to derive site-specific upset factors. Note that factors such as standard operating procedures and employeetraining unique to each facility may influence the frequency and duration of upset events. Eventhough two facilities may manage the same waste and have similar equipment and process, thefrequency of their process upset conditions may be considerably different. It is recommendedthat the MERC protocol be revised to include a description of how site-specific data will beevaluated to determine if it is suitable for developing process upset factors for application in theacute analysis. Further, it is recommended that MERC revise the protocol to outline the criteriathat will be applied to determine if potential sources of surrogate operating data are suitable fordeveloping process upset factors for the MERC facility acute analysis.

Sections 2.7.1 through 2.7.4 use assumptions in developing the proposed process upset factors. These assumptions should be supported by site-specific equipment and operations data. Theprotocol assumes that any of the potential upset conditions would not lead to increased metalemissions. One possible scenario that might lead to increased metals emissions would be anuncontrolled increase in combustion temperature thereby volatilizing metals. A rupture of bagsin the baghouse could result in the failure to capture particulate metal emissions. In addition, theprotocol assumes that only one of the discussed potential upset conditions would occur at anygiven time. This assumption is not adequately justified in the protocol. It is recommended thatMERC revise the protocol to include information in support of the assumption that metalsemissions are not affected by process upsets. MERC should also provide information supportingthe claim that only one unit will experience a process upset at a time.

In general, it is recommended that site-specific equipment and operations data be used tocalculate the process upset factors for organic and metal emissions. The U.S. EPA HHRAPdocument recommends multiplication of process upset factors and the reasonable maximumemission rates to derive emission rate estimates that account for increased emissions duringupset conditions. The HHRAP document suggests use of 95th percentile or maximum emissionrates obtained under trial burn (stressed equipment) conditions as the reasonable maximumemission rates. The MERC protocol does not clearly identify or state the type of stack testingthat will be used to develop the emission rate estimates. Furthermore, the HHRAP documentsuggests that the increased emission rates, that account for the process upset conditions, be usedas part of the long-term risk assessment. It is recommended that the protocol be revised to

6

demonstrate that MERC will be using reasonable maximum emission rates based on trial burntesting data. Additionally, since MERC has proposed not to use the process upset factors as partof the long-term risk assessment, it is recommended that MERC demonstrate that equipment andprocedures are in place to prevent process upsets (e.g., automatic waste feed cutoff (AWFCO)system(s) that operates right at the reasonable maximum emission rates). Alternatively, MERCshould derive and apply site-specific process upset factors in the long-term risk assessment.

Process upset factors that can be applied to reasonable maximum emission rates on a long-termbasis can be derived using historic operations data. A simple methodology would be to utilizehistoric operations data to determine the annual average operating time (Tn); the annual averagetime when the process is under upset conditions including both startup/shutdown and equipmentmalfunctions (Tu); average emissions during non-upset conditions (En); and average emissionsduring upset conditions (Eu). The process upset factor can be calculated using the followingformula:

PUF = [N% (1.0) + U % (EI)]/100

where:PUF = Process upset factor (unit-less)N% = Time process operates in non-upset condition (1-Tu/Tn × 100)U% = Time process operates in upset condition (Tu/Tn × 100)

Data from the continuous emissions monitors can be used to determine emissions during historicupset conditions. For example, carbon monoxide data may be used to calculate an upset factorfor organic emissions and particulate matter data may be used to calculate an upset factor formetal emissions. The estimated annual average stack emission rates should be multiplied by theappropriate organic or metal site-specific process upset factor. Alternatively, MERC may wantto use the default upset factors presented in the HHRAP document.

8. Section 3.2, Meteorological Data and Receptor Locations, age 3-4.

The protocol does not present information on site-specific micrometeorological parametersrequired for air modeling. It is recommended that the protocol be revised to include, at aminimum, sector-specific surface roughness, noon-time albedo and bowen ratio values.

The MERC protocol does not include any information on the special sub-populations located inthe assessment area. It is recommended that the protocol be revised to specifically identify thelocations of any special sub-populations (schools, hospitals, nursing homes, day car centers,parks, community activity centers, etc.) located in the assessment area. The modeling ofemissions impacts at these locations should be addressed in the protocol as well.

The protocol indicates that the assessment area will be modeled to examine the potential impactsof facility emissions using a polar grid. Based on the protocol, it is not clear that the proposedpolar grid will capture the impact points of interest in the area of highest grid point density.

7

Revise the protocol to demonstrate that the points of impact of interest in the risk assessment willfall in areas of high grid point density and that refined modeling will not be needed to identifythose impact points. This demonstration can be based on a discussion of the results achieved inprevious MERC risk assessments that employed the same receptor grid methodology.

Additional details should be provided on the polar receptor grid proposed for the air dispersionmodeling analysis. The risk assessment protocol does not indicate whether elevation data will beused in conjunction with the modeled receptor locations. It is recommended that the protocol berevised to state that elevation data will be used in the air dispersion modeling. The method ofassigning elevations to the grid nodes of the polar grid, including any methods of interpolationbetween known elevation values, should be identified. Further, a discussion should bepresented that explains how the results achieved with the polar grid will be applied to determinethe area average deposition rates over the waterbodies and watersheds addressed in the riskassessment.

9. Section 3.3.3, Vapor-Phase POC Wet Deposition, page 3-5.

The approach for determining scavenging coefficients for POC wet deposition proposed byMERC in Section 3.3.3 of the risk assessment protocol was reviewed and appears technicallysound. Further, this approach has been subjected to technical review, approved, and used in ahazardous waste combustion risk assessment by U.S. EPA Region 5. No response necessary.

10. Section 3.3.4, Vapor-Phase POC Dry Deposition, page 3-11.

MERC has proposed a vapor-phase dry deposition velocity of 1.4 cm/s for all POCs addressed inthe risk assessment. Based on the information contained in Section 3.3.4 of the MERC riskassessment protocol, it is not clear that 1.4 cm/s is the best vapor-phase deposition velocity forall POCs addressed in the risk assessment. It is recommended that the MERC risk assessmentprotocol be revised to include a discussion of the applicability of the proposed value in thecontext of the solubility and reactivity of each POC. An alternate value (e.g., the HHRAPrecommended value of 3 cm/s) for each POC that is not conservatively modeled using thedeposition velocity of 1.4 cm/s should be proposed.

Page 3-13 of the protocol briefly mentions that alternate air-to-leaf transfer assumptions fordioxins/furans may be employed and cites a particular scientific paper. Section 3.3.4 states that“...the HHRAP recommended algorithms will be used in the baseline risk assessment...andsensitivity calculations regarding the air-to-leaf transfer factor will be developed in theuncertainty section of the risk assessment.” Therefore, MERC’s proposed approach is deemedacceptable. It is recommended, however, that the specific alternate assumptions related to air-to-leaf transfer of dioxins/furans be presented and discussed in the protocol for review in advanceof performing the risk assessment.

11. Section 3.4, Modeling of Startup and Shutdown Emissions, page 3-13.

8

Section 2.7.1 of the MERC protocol indicates that the facility’s upset history will be reviewed todetermine whether or not a facility-specific upset factor can be calculated. Section 3.4, however,commits to using factors derived from surrogate or unknown sources in modeling startup andshutdown emissions. This discrepancy should be resolved. Also see comment “Section 2.7,Process Upset Emissions, page 2-11.”

12. Section 4, Exposure Scenarios, page 4-3.

The second to last paragraph of page 4-3 of the protocol states that “Indirect exposure analysiswill be performed for all chemicals except for those for which it can be demonstrated thatindirect exposure pathways are of de minimus concern.” The protocol does not make clear whatcriteria will be used to identify those constituents in indirect exposure pathways that may bedropped from the risk assessment and how issues such as the potential for bioaccumulation willbe addressed in a screening procedure. The protocol also does not address the potentialcumulative impact that eliminating multiple constituents from the risk assessment may have onthe final risk results. The U.S. EPA HHRAP document does not advocate any screeningprocedures and recommends that all constituents of potential concern be carried through the riskassessment. It is recommended, therefore, that the specific methodology that will be used toscreen out constituents from the risk assessment be presented for review in advance ofconducting the risk assessment.

13. Section 5, Estimation of Media Concentrations, pages 5-1 through 5-6

Application of MF for PAHs: The MERC protocol proposes to apply a metabolism factor (MF)in the calculation of PAH uptake. Because MERC has proposed to conduct the baseline riskassessment without applying the MF in the calculation of PAH uptake and apply the MF to thePAH uptake calculation in the uncertainty section, TechLaw believes that the proposed approachis acceptable.

Error is calculating mercury concentration in fish: The MERC protocol identifies an error in theHHRAP guidance regarding calculation of mercury concentration in fish wherein total dissolvedmercury water concentrations (both mercuric chloride and methyl mercury) are multiplied withthe BAF for methyl mercury. Corrections suggested in the protocol to address this error include:(1) multiplying the dissolved methyl mercury water concentration by the BAF for methylmercury, or (2) multiplying the total dissolved mercury water concentration by a BAF for totalmercury. The protocol then selects approach number 2, above, on the basis that the methylationof mercury is complex and the simplified modeling in the HHRAP document is not technicallydefensible. It is acknowledged that mercury modeling is very complex and mercury methylationis influenced by numerous watershed-specific variables. However, it is recommended that theapproach providing the most conservative risk estimates (and the one that focuses on methylmercury - one of the most toxic forms of mercury and a form that is readily accumulated in theaquatic food chain), be selected for use in the baseline risk assessment.

A paper presented by staff in EPA’s Region 6 Center for Combustion Science and Engineering

9

accounts for the error noted in the protocol. That paper (and its associated example calculationsfor two watersheds) separately calculate fish concentrations for mercuric chloride (Hg2+) andmethyl mercury (MHg), which are then subsequently added together for a total mercuric fishconcentration. However, since no BAF exists for Hg2+ the fish concentration due to mercuricchloride is zero, and the total fish concentration essentially amounts to multiplying the dissolvedmethyl mercury water concentration by the BAF for methyl mercury. This is the same ascorrection approach (1) suggested by MERC. Using the example watershed variables in thesupporting calculations to the EPA Region 6 paper, the fish mercury concentration using theBAF for total mercury is approximately 10 times lower than the fish mercury concentration thatis calculated using the BAF for methyl mercury. The EPA Region 6 paper and examplecalculations may be found at www.epa.gov/region6/6pd/rcra_c/pd-o/mercury.htm. In theinterests of protecting the human health and the environment from mercury exposure, it isrecommended that the more conservative approach advocated by EPA using the BAF for methylmercury be used in the baseline risk assessment. The alternate approach using the BAF for totalmercury could be presented and discussed in the uncertainty section of the risk assessment.

The protocol proposes to use environmental sampling to measure mercury levels in trophic level4 fish and water from the Saco River or other water bodies in order to develop a site-specificBAF for methyl mercury. It is unclear how sample representativeness will be assured in thedevelopment of this site-specific value, given such issues as sampling location variability forsame body of water, variations in mercury concentrations given fish age/size/species, potentialseasonal variability, etc. It is recommended that the protocol be expanded to discuss in greaterdetail the proposed program for collecting fish and water samples in the vicinity of the MERCfacility.

14. Section 7, Risk Characterization, page 7-1.

The protocol states that toxicity criteria for the risk assessment will be gathered from USEPA’sIntegrated Risk Information System (IRIS) database and the Health Effects AssessmentSummary Tables (HEAST). In December 2003, EPA issued OSWER Directive 9285.7-53 thatrevised the hierarchy of human health toxicity values generally recommended for use in riskassessments. Under the new hierarchy, the preferred sources of toxicity criteria in the followingorder are recommended: IRIS data, Provisional Peer Reviewed Toxicity Values (PPRTVs) whichcan be found at http://hhpprtv.ornl.gov/index.shtml, and other toxicity information sources (e.g.,

10

HEAST, other EPA sources, and non-EPA sources). It is recommended that the MERC protocolbe revised to follow this preferred hierarchy of toxicity criteria information sources.

15. Other Issues not Addressed in the Protocol

Modeling Fugitive Emissions: Fugitive emissions are not addressed in the MERC protocol. Allpotential sources of fugitive emissions at MERC cannot be identified as the risk assessmentprotocol does not include a detailed description of the complete boiler system and/or a figureillustrating all system components. It is recommended that the risk assessment protocol berevised to identify sources and assess the potential for fugitive emissions from these sources. For example, the potential for fugitive dust emissions should be assessed for the cyclone asshould the potential for emissions from handling caked material and spent bags at the baghouse. For each potential source, the waste stream(s) should be identified as should any equipment orprocedures in place to control fugitive emissions. Suggested guidance on assessing fugitiveemissions at combustion facilities is provided in Section 2.2.6, RCRA Fugitive Emissions, andSection 3.10, Modeling Fugitive Emissions, of the U.S. EPA HHRAP document.

Total Organic Emissions (TOE) Evaluation: The MERC protocol does not indicate whetherTotal Organic Emissions (TOE) data were collected or will be collected during stack emissionstesting. Section 2.2.1.3 of the U.S. EPA HHRAP document discusses calculation of a TOEfactor as a way of evaluating the proportion of the emissions that may be uncharacterized in thelaboratory analytical testing. It is recommended that the protocol be revised to address thisissue.

Acute Exposure Scenario: The HHRAP document recommends evaluating an acute exposurescenario, in which the air model computes the highest 1-hour average air concentration for eachsource using five years of meteorological data. In the acute assessment, emission rates are notpresumed to increase, rather the air model identifies the combination of meteorological andtopographic conditions that result in the highest short-term (1-hour) air concentrations of bothorganics and inorganics. In contrast, the MERC protocol’s short-term assessment assumesstartup/shutdown emissions rates of organic constituents only will be elevated and gas flowthroughput reduced. The MERC short-term assessment also proposes only to investigate theorganic constituent air concentrations at the location of the residential receptor. Section 4.2.7 ofthe HHRAP document states that the acute exposures should not be limited to those scenariosevaluated in the long-term risk assessment. For example, workers at nearby facilities orrecreational users of other off-site areas may be impacted during the acute 1-hour time period. For this reason the acute risk at the maximum off-site location should be evaluated (unlessexposure at this point can be demonstrated to be inconceivable). In light of these issues, it isrecommended that MERC augment the proposed acute analysis to evaluate organic andinorganic constituents at the maximum off-site location as suggested in the U.S. EPA HHRAPdocument.

11

Typographical Errors Noted:

Page 3-8, title for Table 3.3: change “... modeling in ISCST3” to “... modeling in AERMOD”

Page 3-14, last paragraph, second sentence: change “...ISCST3 model provided...” to “AERMODmodel provides...”


MEMORANDUM

To: Jim Secunde, Dixon Pike: MERC; Travis Kline: TechLaw

From: Michael Ames, Steve Zemba: Cambridge Environmental

Subject: Responses to Technical Review Comments on Risk Assessment Protocol for theEvaluation of Multi-Pathway Impacts of Emissions from the Maine EnergyRecovery Company Facility in Biddeford, Maine

Date: July 15, 2005

Background:

The Maine Energy Recovery Company (MERC) operates a facility in the City of Biddeford,Maine that processes municipal solid waste to produce refuse-derived fuel (RDF). The RDF iscombusted at the facility to produce electricity. In 1996, Cambridge Environmental conducted ahuman health risk assessment of air pollutants emitted from the facility and found that theseemissions posed no significant risks to human health. Cambridge Environmental has proposed aprotocol for updating the 1996 risk assessment to account for(1) updated information regardingthe facility’s air pollution emissions and operating conditions, (2) the development of newregulatory guidance and models for conducting risk assessments, and (3) the enactment ofregulations by the City of Biddeford designed to evaluate emissions of facilities that releasepotentially hazardous air pollutants. The protocol was submitted to MERC for review inNovember 2004 and subsequently provided to the City of Biddeford . A technical review of theprotocol was conducted on behalf of the City of Biddeford by Tech Law Inc. On April 18, 2005TechLaw Inc. submitted their written comments on the protocol to Mr. Brian Phinney of the Cityof Biddeford and Mr. Ken Robbins of MERC. Cambridge Environmental considered thecomments and on May 25, 2005 participated in a conference call with the protocol’s reviewersfrom TechLaw, as well as representatives of MERC and the City of Biddeford. Thismemorandum contains Cambridge Environmental’s responses to each of TechLaw’s commentsas discussed and agreed upon during the May 25 conference call, following the outline ofTechLaw’s April 18, 2005 comments.

In general, these responses serve as an account of the May 25 discussion of issues raised in thecomments, to clarify portions of the protocol, or to correct errors in the protocol. The riskassessment will proceed following the protocol as amended by these responses to TechLaw’scomments. Should further changes to the protocol become necessary in developing the riskassessment, Cambridge Environmental may either (1) notify MERC, the City of Biddeford, andTechLaw to allow for review of these changes, and/or (2) directly incorporate the changes intothe risk assessment along with justification and a discussion of them on the overall riskestimates.

Page 2July 15, 2005


General Comments:

As stated in the protocol, the risk assessment is to be based on the overall methods and detailedequations contained in the U.S. EPA’s Human Health Risk Assessment Protocol (HHRAP) forHazardous Waste Combustion Facilities (1998, plus the 1999 EPA errata document, and the2000 peer review comments). However, because the HHRAP was developed to assess thepotential risks from hazardous waste combustion facilities to comply with specific EPArequirements (see HHRAP pages 1-2 and 1-3), there are portions of the HHRAP that are notstrictly applicable to a risk assessment of the MERC facility. The primary difference betweenthe MERC facility and those for which the HHRAP was developed is that MERC does nothandle wastes that are a priori hazardous. The selection of pollutants of concern (POCs) for theMERC risk assessment is thus not driven by the presence of hazardous compounds in thefacility’s input waste stream. Additionally, emissions from solid waste combustors have beencharacterized through many evaluations to develop a well-established list of compounds ofconcern in the past of municipal waste combustion risk assessments. Stack testing at MERC isnot designed to verify that hazardous materials entering the facility are destroyed and removed ata required efficiency, but rather to assess the emissions of POCs that have previously beenidentified as being emitted from municipal waste combustors.

The HHRAP is biased to conservatively overestimate potential risks. In some cases, the degreeof likely overprediction is so great that the risk estimates are likely misleading anduninformative. Because the risk assessment for the MERC facility will be widely read, we feelthat the use of excessive conservatism will mislead, and hence we intend to introduce some morerealistic assumptions (as described in the protocol) so the POC and risk estimates are still healthprotective, but are more in line with actual POC levels and potential risks. As an example of theHHRAP’s tendency to overestimate POC levels, we note a paper written by EPA Region 6 andcited by TechLaw in their comments which includes an example calculation of a multipathwayrisk assessment for mercury using all of the HHRAP default parameters (protocol review item13, page 9; available at: www.epa.gov/region6/6pd/rcra_c/pd-o/mercury.htm). The examplecalculations highlight the extent to which the full use of HHRAP default assumptions leads to asignificant overestimation of POC concentrations in environmental media and hence to estimatedrisks. The source modeled in the calculations is relatively small, emitting about 1.5 pounds ofmercury per year, yet the calculations predict that mercury from this source alone would lead tomercury concentrations in fish of 1.2 mg/kg. While this mercury concentration is in the typicalupper range of actual mercury levels measured in fish, actual fish are affected by many moresources, and thus the estimated increment to the mercury levels cause by this one small source isclearly a significant overestimate. Furthermore, there are large combustion sources that emithundreds to thousands of times more mercury than this small source and, if the HHRAP were

Page 3July 15, 2005


applied to these sources, the resulting mercury concentration estimates would be far above anylevel measured in fish.

While each of the individual HHRAP default modeling parameters may be reasonablyconservative estimates of uncertain POC or environmental properties, when they are all includedin a multipathway risk assessment, their conservatisms are multiplied together, it can easilyresult in gross overestimates on POC levels and potential risk. Therefore, to produce POC andrisk estimates that are as realistic as possible, yet are still conservative and health protective,wherever justifiable the MERC risk assessment will employ facility- and site-specific modelingparameters rather than HHRAP default values.

Specific Comments:

1. The risk assessment will include a more legible figure depicting the area surrounding theMERC facility.

2. The list of POCs contained in the risk assessment protocol (pages 2-3 and 2-4) was based onpast U.S. EPA data on pollutants released by waste-to-energy facilities, and data from recentMERC boiler stack testing and odor scrubber system testing. Compounds that have beendetected in any of the boiler stack, or odor scrubber system tests will be included as POCs. Because the MERC facility does not process hazardous waste (which would be required to beanalyzed itself), and because the municipal solid waste that it does process is not homogenous, itis not feasible to sample the waste stream for potential POCs in the manner recommended by theHHRAP. As a surrogate for a waste stream analysis, to help define the list of POCs, the MERCfacility risk assessment include as POCs compounds that have been detected in the inlet to theodor control system. Odor handling POCs will also be considered as part of the boiler stackemissions with an appropriate destruction and removal efficiency because the combustion aircomes from inside the MERC waste storage, handling and processing buildings.

3. The POC emission rates used in the risk assessment will be based on the most recentlycollected data for the boiler stack and odor scrubbing system unless unusual results are noted. For example, a chemical detected at constant levels in historic stack tests will not be assigned alower emission rate based on potentially anomalous test results. Conditions under which thestack and scrubber testing are performed will be included in the risk assessment report. ThePOC emission test results from older sampling efforts will be used to establish the full list ofPOCs as described above, and to determine whether there has been any significant trends in theemission rates of any POCs. Based on the stated ideal that the MERC risk assessment primarilyprovide conservative best-estimates of the likely impacts of the facility, the baseline riskassessment will use average POC emission rates based on the of the most recent test results.

Page 4July 15, 2005


Recent and historical maximum (or average plus two standard deviations) measured emissionrates will be considered as part of the uncertainty portion of the report. This will allow aseparate evaluation of the sensitivity of the risk results to changes in the assumed POC emissionrates.

4. The estimation of POC emission rates for POCs that are not consistently detected in theboiler stack or scrubber emission tests can be a source of uncertainty in a risk assessment. Toproduce estimates of the emission rates for these POCs, two different methodologies will beapplied. For those POCs that have not been detected in the recent stack or scrubber tests (buthave been detected in older tests), the assumed baseline emission rates will be taken as one-halfthe detection limit of the most recent testing program. For those POCs that have been detectedin some but not all of the most recent tests, the test results in which the POC is not detected willbe averaged with the detected results at the full detection limit. The use of other methodologiesfor estimating emission rates of non-detected POCs will be addressed in the uncertainty sectionof the risk assessment with special mention of non-detected POCs that are estimated to lead to asignificant portion of the overall risk estimate.

The specific detection limit for each POC and test result that is used in emission ratescalculations will be dependent on the data that are available for each testing program. The goalsfor this portion of the risk assessment are to use as much data as is available and to not introduceoverly conservative methodologies to compensate for uncertainty. The detection limits used toestimate concentrations of non-detected POCs will be the maximum concentration level forwhich the POC would not be indicated as a detected compound. Therefore, if method detectionlimits (MDLs) are given, and POCs present at levels just above the MDL would be shown asbeing detected, the MDL value will be used as the detection limit. If POC concentrations arereported in the test results at just above MDLs (perhaps with a qualifier indicating an estimatedconcentration), the value will be used as given (consistent with the treatment of estimated valuesin the Superfund program). In this case, the use of the HHRAP recommended MDL-derivedreliable detection limit (RDL) values for non-detected POCs could result in test results with non-detects being averaged into the emission calculations at higher concentrations than detected tests. Use of an MDL-derived RDL will only be considered when test results indicate considerableuncertainty (such as widely varying results or detection limits). 5. A review of available speciation data for chromium emissions from municipal wastecombustors indicates that the fraction of chromium present in the boiler stack emissions in thehexavalent form is likely to be on the order of a few percent, far below the 100% that theHHRAP recommends as a worst-case assumption. Because of the large differences in cancerand non-cancer toxicities between hexavalent and trivalent chromium, assuming that all of thechromium is hexavalent can lead to substantial overestimates of risks. Therefore, in the absence

Page 5July 15, 2005


of site-specific data, the fraction of chromium in the boiler stack emissions that is present in thehexavalent form will be taken as the 95% upper confidence limit of the average hexavalentchromium fraction as found in available data for municipal combustors firing refuse derived fuel(the maximum will be used if it is exceeded by the 95% upper confidence limit). The HHRAPdoes provide for this option as stated in HHRAP section 2.3.8.1, allowing the use of “process-specific data” for estimating the valence speciation of chromium. This will provide a realisticand health protective estimate of hexavalent chromium concentrations and risks.

6. The speciation of emitted mercury among vapor-phase elemental, vapor-phase divalent, andparticulate-phase (or particulate-bound) divalent forms has a very significant effect on mercuryconcentrations in environmental media due to the different behavior of these mercury forms inthe atmosphere. However, the physical and chemical behavior of mercury in combustion andpollution control systems is not well enough understood to adequately predict mercury speciationbased on a facility’s operating conditions. It is also the case that a wide range of speciationprofiles have been measured at nominally similar combustion facilities. Therefore, to producethe most realistic estimates of potential environmental media and health impacts of the MERCfacility’s mercury emissions, the use of site-specific data is preferred to employing assumed ordefault speciation profiles. Previously collected (and future planned) mercury concentrationmeasurements of the MERC facility’s boiler stack emissions have been made using EPA’spromulgated Test Method 29. Although this method is not specifically designed for speciatedmeasurements, mercury speciation will be inferred for purposes of the risk assessment byexamining the detailed results from the various portions of the sampling train as measured in themost recent boiler stack tests. The front portion of the train (containers 1 and 2 of the method 29analysis) that includes the glass filter will used to assess particulate mercury emissions; materialfrom the first set of impingers (5%HNO3 / 10%H2O2, container 4 of the analysis) will be used toassess vapor-phase divalent mercury emissions; and material from the second set of impingers(4%KMNO4 / 10%H2SO4, containers 5a,b, and c of the analysis) will be used to assess vapor-phase elemental mercury emissions. The protocol review comments correctly note that thespeciation for municipal waste combustors found in the Mercury Study Report to Congress isbased on the assumption that these facilities use activated carbon injection as a mercury controlmethod. Because the MERC facility does not operate a carbon injection system, the speciationprofile given in this report for municipal waste combustors should not be applied. If the dataavailable from the MERC facility’s boiler stack tests prove to be unusable for mercury speciationestimates, the HHRAP default distribution will be used. The use of other mercury speciationprofiles for the MERC facility boiler stack emissions will be examined in the uncertainty sectionof the risk assessment.

7. Process upset conditions are evaluated in a risk assessment for two purposes: to assesswhether the upset conditions could lead to short-term health risks, and to assess the extent that

Page 6July 15, 2005


the occurrence of upset conditions affects long-term emission rates. The MERC protocol statesthat only the former analysis will be performed in the risk assessment because the effects ofupset conditions are not expected to increase long-term emissions. The protocol review notesthat the latter evaluation should also be performed using site-specific, historic operations data todevelop a process upset factor (PUF) to account for the effect of upsets on long-term averageemission levels. Based on a recent review of the MERC facility’s boiler start-up, shut-down, andoutage records for the past three years, it is clear that, over the long-term, periods when either orboth or the MERC boilers are offline (and hence there are no stack emissions for that boiler)more than offset the potentially increased emission levels the occur during system upsets. Facility-specific details will be included in the risk assessment to document upset conditionevaluation methods, emission levels, durations, and frequencies in support of the acute riskassessment modeling parameters and the exclusion of process upset factors from the long-termrisk assessment calculations. Process upset conditions that could lead to elevated boiler stackemissions of metals will be included in the baghouse/fabric filter upset scenario for which allparticulate POCs will assessed.

8. The site-specific air modeling details mentioned in the protocol review (surface roughness,albedo, bowen ratios, elevation data, deposition averaging methods) will be included in the airmodeling section of the risk assessment. The locations of special sub-populations (e.g. schoolshospitals, etc.) will be identified in the description of the area surrounding the MERC facility. The air quality impacts at these locations will also be discussed. However, because the riskassessment calculations will be performed using estimated POC concentrations at the maximumimpact locations, and using toxicological data derived to protect the health of sensitive sub-populations, no special risk calculations will be performed for the sub-populations describedabove, as they will by definition be included in the consideration of the maximum impactlocations. The areas of maximum POC impact will be modeled using a finely-spaced (100m)receptor grid. Results form Cambridge Environmental’s previous dispersion modeling of theMERC facility will be employed to help develop the receptor grid for the current analysis.

9. No response necessary.

10. As described in the protocol and the comments, the HHRAP recommends an atmosphericdry deposition velocity of 3 cm/s in for all vapor-phase POCs. When the HHRAP was written,limitations in the air dispersion models and in available data prompted the use of a single,conservative default deposition velocity for all POCs based on concentration and deposition ratedata available for nitric acid. However, dry deposition velocities are dependent on the propertiesof both the compound in question and the surfaces to which the deposition is occurring. Theselection of nitric acid as a surrogate for all POCs with respect to dry deposition velocities wasdue to the availability of data, the desire to have a conservative, upper estimate of dry deposition,

Page 7July 15, 2005


and on nitric acid’s high reactivity and solubility (properties that increase dry deposition rates). However, a deposition velocity of 3 cm/s is an upper estimate even for nitric acid. Furthermore,there are POCs which very likely have lower deposition velocities than nitric acid, but whichwill be modeled conservatively, using the nitric acid value. One such POC for which theestimated media concentrations are especially sensitive to the assumed deposition velocity isvapor-phase divalent mercury. The GDISCDFT model (described in the protocol) containsalgorithms to estimate vapor-phase compound dry deposition velocities based on variousproperties. In order for the vapor deposition velocity of HgCl2 to be 3 cm/s, the reactivityparameter in this algorithm would need to be set 800, which a far higher than the maximumvalue listed in the GDISCDFT documentation, which value is 18 for nitric acid. Thus the use ofthe nitric acid dry deposition velocity as a surrogate for all POCs can significantly overestimatedry deposition rates.

Because dry deposition is a function not only of the properties of the POC but also of the localenvironment, the use of deposition velocities calculated from Maine-based datasets (as describedin the protocol) is preferable to velocities based on national data. As shown in Table 3.5 of theprotocol, more recent, and Maine-specific data suggest that a lower value provides a morerealistic value for nitric acid’s deposition velocity. Cambridge Environmental feels that the useof more representative and site-specific data (rather than default values) for the vapor-phase drydeposition velocity will produce POC concentrations and risk estimates that more accuratelyreflect actual conditions, yet which remain health protective. Based on these factors, which willbe included and expanded in the risk assessment, a dry deposition velocity of 1.4 cm/s will beused for vapor-phase POCs.

11. Facility startup and shutdown emissions will be modeled as described in protocol section2.7.1 using available facility-specific data as described above in response to review comment 7.

12. The screening analyses referred to in the protocol’s section 4 will be applied only toestimating POC concentrations in the Saco River for evaluation of the drinking water and fishingestion pathways. Simplified worst-case dilution models will be employed to estimate POClevels in the Saco if all of the emitted POCs entered the river. Because it is clear that not all ofthe emitted POCs will enter the Saco (some will be blown out to the ocean), this is a veryconservative screening analysis. This analysis will preclude the need to model air dispersion anddeposition over the entire Saco River watershed which extends beyond the distance for whichAERMOD has been validated (about 120km vs. 50 km), and will preclude the use of thewatershed transport models over a large area comprised of diverse land types for which therewould be a very great deal of modeling uncertainty. No other pathways or POCs will beexcluded from the multipathway risk assessment based on screening level calculations.

Page 8July 15, 2005


13. The methylation and bioaccumulation of mercury in aquatic ecosystems is one of the mostcomplex portions of the actual transport of this POC through the environment to a place where itis available for human exposure. Application of the default HHRAP modeling parameters toestimate the methyl mercury levels in trophic level 4 fish greatly oversimplifies these processesand ignores any site-specific dependence of the factors governing methylation andbioaccumulation. Because these processes are dependent on local water and watershedchemistry and the presence of methylating micro-organisms, the extent to which the processesoccur is strongly site-specific. The HHRAP default bioaccumulation factor (BAF) of 6.8 × 106 isbased on the a value for the methylmercury concentrations in piscivorous fish divided bydissolved methylmercury concentrations in water given in the EPA’s Mercury Report toCongress (Volume 3, Appendix D). Aside from the fact that the HHRAP incorrectly applies thisvalue to dissolved total mercury concentrations in water, the value of the BAF is derived fromfour sets of water bodies (Onondaga Lake, NY; four lakes in Manitoba, Canada; Clear Lake, CA;and Lake Michigan) that are very different than those near the MERC facility. To produce morerealistic estimates of mercury levels in fish around the MERC facility, the risk assessment willuse BAFs derived from fish and water measurements taken in small lakes in Vermont, NewHampshire, and Maine. BAFs based on total mercury measurements in water will be usedpreferentially in the baseline calculations because these tend to be more robust with respect totheir sampling and analytical procedures, and because these measurements are more numerous. BAFs based on methylmercury measurements in water will be included in the risk assessment’suncertainty section to help address the range of values that may be selected for this critical, yetoften poorly understood parameter. No mercury sampling programs were proposed in theprotocol and none are planned as part of the development of the risk assessment. Only data thathas already been collected by state or other agencies, or by non-governmental researchers will beused in developing a BAF for the risk assessment.

14. The revised hierarchy suggested in the protocol review for toxicity data will be used in therisk assessment.

15. The risk assessment will include a detailed description of the MERC facilities, with allsources of stack and fugitive emissions identified. Because the buildings at MERC aremaintained at negative pressure relative to ambient air, the potential for significant fugitiveemissions is low. An assessment of fugitive emissions from the facility was completed inFebruary 2003 and submitted to the City of Biddeford. Copies of these assessments will beincluded as appendices to the risk assessment. Potential risks due to fugitive emissions will bebased on these previous analyses.

The risk assessment will include data on total VOC and speciated organic emissions from theMERC boiler stack, as well as data on total organics, non-methane hydrocarbons, and speciated

Page 9July 15, 2005


organics from the odor scrubber systems. The potential risks due to portions of the emissionsthat are unidentified in the speciated measurements will be addressed in the uncertainty sectionof the risk assessment.

As stated in response to comment 7, metallic POCs will be evaluated for acute exposures underupset conditions. Short-term risks will be evaluated at the maximally impacted off-site receptorlocation.

Appendix II Compounds of Potential Concern(COPC) Properties Tables

The tables in this Appendix include all of the physical, chemical, and toxicological properties forthe COPCs evaluated in the risk assessment. The column labeled ‘HHRAP’ indicates whetherthe compound is listed in HHRAP Appendix A, Tables A-3. Physical and chemical propertiesfor compounds not listed in HHRAP Appendix A were derived form the U.S. EPA Office of AirQuality Planning and Standards’ WATER9 software (U.S. EPA 2001a), and the National Libraryof Medicine’s Hazardous Substances Databank (HSDB, 2001).

The preferred database for toxicological data is the Integrated Risk Information System (IRIS,available at: http://www.epa.gov/ngispgm3/iris/subst/index.html), followed by the ProvisionalPeer Reviewed Toxicity Values (PPRTVs, http://hhpprtv.ornl.gov/index.shtml) and HealthEffects Assessment Summary Tables (HEAST, 1997). Some additional toxicological data hasalso been derived from the U.S. EPA Region III’s Risk-Based Concentration Table (U.S. EPA2001b). The HHRAP itself recommends compound-specific toxicologic data that are derivedfrom data in IRIS, HEAST, and other sources, and toxicological data that has been extrapolatedfrom one route of exposure to another (e.g., an ingestion potency derived from inhalation data).

MW Tm Vp S H Da Dw Kow Koc Kdsg/mol deg K atm mg/L atm-m3/mol cm2/s cm2/s ml/g ml/g

MetalsArsenic 74.92 1091 0 0 0 0.107 1.24E-05 0 NA 27.73684Beryllium 9.01 1560 0 0 0 0.439 5.08E-05 0 NA 547.7895Cadmium 112.41 594.1 0 0 0 0.0816 9.45E-06 0 NA 56.05263Chromium (total) 52 2173.1 0 0 0 0.101 4.63E-05 0 NA 1231958Chromium (hexavalent) 52 2173.1 0 0 0 0.136 1.58E-05 0 NA 22.78947Copper 63.55 1356.15 0 0 0 0.119 1.38E-05 0 NA 6854.737Lead 207.2 600.5 0 0 0 0.0543 6.28E-06 0 NA 900Mercury (elemental) 200.59 234.23 2.63E-06 0.0562 0.0071 0.0109 3.01E-05 0 NA 1000Mercuric chloride 271.52 550.1 0.00012 69000 7.1E-10 0.0453 5.25E-06 0.61 NA 58000Methyl mercury 216 NA NA NA 4.7E-07 0.0528 6.11E-06 0 ND 7000Nickel 58.69 1828 0 0 0 0.126 1.46E-05 0 NA 49.52632Selenium 78.96 490.1 0 0 0 0.103 0.000012 0 NA 9.105263Silver 107.87 1233.6 0 0 0 0.0838 9.71E-06 0 NA 5.710526Tin 118.69 505.06 0 0 0 0.07867 9.11E-06 0 NA 250Vanadium 50.94 3707 0 0 0 0.138266 1.6E-05 0 NA 1000Zinc 65.38 692.6 0 0 0 0.117 1.36E-05 0 NA 62

Hydrogen chloride 36.47 158.9 46 673000 0.002493 0.173 0.00002 0 NA NA

Organic compoundsacetone 58.08 179.1 0.299 604000 2.88E-05 0.187 1.15E-05 0.6 0.95051281 0.009505benzene 78.11 278.6 0.125 0.0018 0.00549 0.117 1.02E-05 137 65.7116001 0.657116benzoic acid 122.12 395.5 8.57E-06 3130 3.34E-07 0.0536 8.8E-06 76 41.4987105 0.0055benzyl alcohol 108.13 288.29 0.00014 40000 3.78E-07 0.0689 9.38E-06 12.6 10.2161915 0.102162bis(2-ethylhexyl)phthalate 390.54 218.2 2.63E-10 0.4 1.46E-05 0.0351 3.66E-06 200000 111686.092 1116.861bromomethane 94.94 179.6 2.09 900 0.00686 0.0728 1.21E-05 12.6 10.2161915 0.102162butanol, n- 74.12 183.7 0.00875 77000 7.69E-06 0.08 9.3E-06 6.76 6.28576909 0.062858butanine, 2- (methyl ethyl ketone) 72.1 187.1 0.12 0.000024 3.61E-05 0.135 1.03E-05 1.91 2.34534117 0.023453carbon disulfide 76.14 161.5 0.447 0.00267 0.0127 0.104 1.29E-05 100 51.4043652 0.514044chloroform 119.39 209.6 0.269 7960 0.00403 0.0517 1.09E-05 89 53 0.53chloromethane (methyl chloride) 50.49 176.1 5.68 6340 0.0452 0.213 1.39E-05 8 6 0.06cyclohexane 84.2 279.5 0.127652 55 0.195424 0.098904 1.15E-05 2754.229 682.652995 6.82653

II-1


Organic compounds (continued)di-n-butylphthalate 278.34 238.1 5.55E-08 10.8 1.43E-06 0.0438 7.86E-06 52500 30517.8915 305.1789dichlorobenzene, 1,2- 147.01 256.1 0.00179 125 0.00211 0.0411 8.93E-06 2790 379 3.79dichlorobenzene, 1,3- 147.01 297.86 0.00303 68.8 0.006474 0.0414 8.85E-06 3390 803 8.03dichlorobenzene, 1,4- 147.01 326.6 0.00139 73 0.0028 0.0414 8.85E-06 2580 616 6.16diethyl phthalate 222.24 232.6 2.17E-06 880 5.48E-07 0.0256 6.35E-06 27300 82 0.82ethanol 46.07 159 0.0776 100000 5.26E-06 0.123 0.000013 0.479 0.79737332 0.007974ethylbenzene 106.16 178.1 0.0126 173 0.00773 0.0765 8.49E-06 1330 386.904945 3.869049freon 11 (trichlorofluoromethane) 137.38 162.1 1.1 1100 0.137 0.0427 0.00001 340 134 1.34freon 12 (dichlorodifluoromethane) 120.92 115.1 6.4 300 2.58 0.0777 0.000009 144 6.85 0.685heptane 100.2 182.7 0.061 3.0561 2 0.088073 1.02E-05 45708.82 6106.6074 61.06607hexane 86.17 177.7 0.197368 22.15 0.768 0.2 1.12E-05 5000 1086.91756 10.86918methane 16.04 90.4 45.35884 38.65 18.82421 0.298734 3.46E-05 724.44 240.880636 2.408806methanol 32.04 175.3 0.13 29000 0.000144 0.458 1.67E-05 0.195 0.39557332 0.003956methylene chloride 84.94 178.1 0.487 17400 0.00238 0.0869 1.25E-05 18 13.4931253 0.134931methylnaphthalene, 2- 142.2 307.8 7.24E-05 24.6 0.00052 0.069741 8.08E-06 7240 4466.28476 44.66285methyl phenol, 2- (o-cresol) 108.13 284.1 0.00019 23000 8.93E-07 0.0693 9.3E-06 91 47.7586768 0.477587methyl phenol, 3- (m-cresol) 108.13 303.1 0.000416 27700 1.62E-06 0.0688 9.41E-06 105 53.3983273 0.533983methyl phenol, 4- (p-cresol) 108.13 308.6 0.00017 23000 7.99E-07 0.0693 9.3E-06 87 46.1131741 0.461132naphthalene 128.16 353.3 0.000117 31.1 0.000482 0.0526 8.92E-06 2360 1505.65213 15.05652phenol 94.11 314 0.000574 90800 5.95E-07 0.0827 1.03E-05 30 20.0980804 0.200981propane 44.1 85.3 9.412 587.2 0.7067 0.152216 1.76E-05 229.0868 98.1295935 0.981296propanol, 2- (isopropyl alcohol) 60.09 184.7 0.0563 100000 7.69E-06 0.098 1.04E-05 0.692 1.06238701 0.010624styrene 104.14 242.5 0.00821 257 0.0026 0.0773 8.77E-06 849 272.613902 2.726139tetrachloroethene 165.85 251.1 0.0242 232 0.0173 0.072 8.2E-06 351 136.87986 1.368799toluene 92.13 178.1 0.0371 558 0.00613 0.0972 9.23E-06 465 170.456397 1.704564trichloroethane, 1,1,1- 133.42 242.7 0.163 1170 0.0186 0.0466 9.56E-06 264 109.610223 1.096102trimethylbenzene, 1,2,4- 120.19 229.4 0.00276 57 0.00616 0.078014 9.03E-06 4270 961.022913 9.610229vinyl chloride 62.5 119.3 3.68 730 0.315 0.158 1.19E-05 14 11.1 0.111xylene, m- 106.16 225.7 0.0106 186 0.00605 0.0769 8.49E-06 1590 444.72317 4.447232xylene, o- 106.16 248.1 0.0106 186 0.00605 0.0769 8.44E-06 1350 391.435617 3.914356xylene, p- 106.16 286.1 0.0106 186 0.00605 0.0761 8.5E-06 1480 420.536928 4.205369

II-2


Polychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 321.98 578.1 9.74E-15 1.93E-05 0.000016 0.0127 6.81E-06 4370000 2690000 269001,2,3,7,8-PCDD 356.42 513.1 1.25E-12 0.00012 2.6E-06 0.0121 4.38E-06 4370000 2690000 269001,2,3,4,7,8-HxCDD 390.87 546.1 1.33E-13 4.4E-06 0.000012 0.0115 4.12E-06 61700000 38000000 3800001,2,3,6,7,8-HxCDD 390.87 558.1 4.74E-14 4.4E-06 0.000012 0.0115 4.12E-06 17800000 11000000 1100001,2,3,7,8,9-HxCDD 390.87 516.1 6.45E-14 4.4E-06 0.000012 0.0115 4.12E-06 17800000 11000000 1100001,2,3,4,6,7,8-HpCDD 425.31 537.1 4.22E-14 2.4E-06 7.5E-06 0.0111 3.89E-06 1.58E+08 97700000 977000OCDD 460.76 598.1 1.09E-15 7.4E-08 7E-09 0.0106 3.69E-07 38900000 24000000 2400002,3,7,8-TCDF 305.98 500.1 1.17E-11 0.000419 8.6E-06 0.0179 4.85E-06 3390000 2090000 209001,2,3,7,8-PCDF 340.42 498.1 3.58E-12 0.00024 6.2E-06 0.017 4.51E-06 6170000 3800000 380002,3,4,7,8-PCDF 340.42 469.1 4.33E-12 0.000236 6.2E-06 0.017 4.51E-06 8320000 5130000 513001,2,3,4,7,8-HxCDF 374.87 498.6 3.16E-13 8.25E-06 0.000014 0.0162 4.23E-06 17800000 11000000 1100001,2,3,6,7,8-HxCDF 374.87 505.1 2.89E-13 1.77E-05 6.1E-06 0.0162 4.23E-06 17800000 11000000 1100002,3,4,6,7,8-HxCDF 374.87 512.1 2.63E-13 0.000013 0.00001 0.0162 4.23E-06 17800000 11000000 1100001,2,3,7,8,9-HxCDF 374.87 519.1 2.37E-13 0.000013 0.00001 0.0162 4.23E-06 17800000 11000000 1100001,2,3,4,6,7,8-HpCDF 409.31 509.1 1.76E-13 1.35E-06 0.000053 0.0155 3.99E-06 83200000 51300000 5130001,2,3,4,7,8,9-HpCDF 409.31 494.1 1.41E-13 1.4E-06 0.000053 0.0155 3.99E-06 83200000 51300000 513000OCDF 444.76 531.1 4.93E-15 1.2E-06 1.9E-06 0.0148 3.78E-06 6.03E+08 372000000 3720000

PCB Aroclor 1248 327 283.1 1.16E-07 0.0515 0.000737 0.04 4.64E-06 1610000 99800 983

II-3

MetalsArsenicBerylliumCadmiumChromium (total)Chromium (hexavalent)CopperLeadMercury (elemental)Mercuric chlorideMethyl mercuryNickelSeleniumSilverTinVanadiumZinc

Hydrogen chloride

Organic compoundsacetonebenzenebenzoic acidbenzyl alcoholbis(2-ethylhexyl)phthalatebromomethanebutanol, n-butanine, 2- (methyl ethyl ketone)carbon disulfidechloroformchloromethane (methyl chloride)cyclohexane

Kdsw Kdbs ksg Fv RCF Br(rootveg) Br(agfruit) Br(agveg) Br(forage) Br(grain)ml/g ml/g 1/yr mL/g unitless unitless unitless unitless unitless

27.73684 27.73684 0 0 0.221895 0.008 0.00633 0.00633 0.036 0.004547.7895 547.7895 0 0 0.821684 0.0015 0.00258 0.00258 0.01 0.001556.05263 56.05263 0 0 3.587368 0.064 0.125 0.125 0.364 0.0621231958 1231958 0 0 5543.811 0.0045 0.00488 0.00488 0.0075 0.004522.78947 22.78947 0 0 0.102553 0.0045 0.00488 0.00488 0.0075 0.00456854.737 6854.737 0 0 1713.684 0.25 0.25 0.25 0.25 0.25

900 900 0 0 8.1 0.009 0.0136 0.0136 0.045 0.0091000 3000 0 1 0 0 0 0 0 0

100000 50000 0 0 2088 0.036 0.0145 0.0145 0100000 3000 0 0 693 0.099 0.0294 0.0294 0

49.52632 49.52632 0 0 0.396211 0.008 0.00931 0.00931 0.032 0.0069.105263 9.105263 0 0 0.200316 0.022 0.0195 0.0195 0.016 0.0025.710526 5.710526 0 0 0.571053 0.1 0.138 0.138 0.4 0.1

250 250 0 0 1.5 0.006 0.006 0.006 0.03 0.0061000 1000 0 0 3 0.003 0.003 0.003 0.003 0.003

62 62 0 0 2.728 0.044 0.072 0.097 0.25 0.054

ND ND 0 1 0 0 0 0 0 0

0.071288 0.038021 36.1 1 6.46 680 52 52 52 524.92837 2.628464 3.89 1 16.6 26.7 2.25 2.25 2.25 2.250.0413 0.022 126 1 12.8 2330 3.17 3.17 3.17 3.17

0.766214 0.408648 0 1 7.94 77.7 8.95 8.95 8.95 8.958376.457 4467.444 11 1 365.4002 0.327167 0.03342 0.03342 0.03342 0.033420.766214 0.408648 0 1 1.032464 10.10615 8.953355 8.953355 8.953355 8.9533550.471433 0.251431 36.1 1 0.95154 15.13801 12.8319 12.8319 12.8319 12.83190.175901 0.093814 36.1 1 6.69 286 26.7 26.7 26.7 26.73.855327 2.056175 0 1 14.4 27.9 2.7 2.7 2.7 2.7

3.975 2.12 1.41 1 13.7 25.8 2.89 2.89 2.89 2.890.45 0.24 9.03 1 7.46 124 11.6 11.6 11.6 11.6

51.19897 27.30612 0 1 14.27241 2.090726 0.397814 0.397814 0.397814 0.397814

II-4

Organic compounds (continued)di-n-butylphthalatedichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-diethyl phthalateethanolethylbenzenefreon 11 (trichlorofluoromethane)freon 12 (dichlorodifluoromethane)heptanehexanemethanemethanolmethylene chloridemethylnaphthalene, 2-methyl phenol, 2- (o-cresol)methyl phenol, 3- (m-cresol)methyl phenol, 4- (p-cresol)naphthalenephenolpropanepropanol, 2- (isopropyl alcohol)styrenetetrachloroethenetoluenetrichloroethane, 1,1,1-trimethylbenzene, 1,2,4-vinyl chloridexylene, m-xylene, o-xylene, p-


2288.842 1220.716 11.1 0.989 1010 64.3 0.0724 0.0724 0.0724 0.072428.4 15.2 1.41 1 111 29.2 39.5 39.5 39.5 39.560.2 32.1 1.41 1 128 15.9 0.353 0.353 0.353 0.35342.6 24.6 1.41 1 105 17 0.413 0.413 0.413 0.4136.15 3.28 4.52 1 612 746 0.106 0.106 0.106 0.106

0.059803 0.031895 253 1 0.837134 104.9865 59.2606 59.2606 59.2606 59.260629.01787 15.4762 25.3 1 65.1 32 0.607 0.607 0.607 0.607

10 5.34 0.703 1 27 2.02 1.33 1.33 1.33 1.335.14 2.74 1.41 1 17 24.8 2.19 2.19 2.19 2.19

457.9956 244.2643 0 1 117.8238 1.929448 0.078437 0.078437 0.078437 0.07843781.51882 43.4767 9 1 22.1 2.03 0.282 0.282 0.282 0.28218.06605 9.635225 0 1 5.630629 2.337518 0.860832 0.860832 0.860832 0.8608320.029668 0.015823 36.1 1 6.37 1610 99.6 99.6 99.6 99.61.011984 0.539725 9.03 1 8.46 84.6 7.29 7.29 7.29 7.29334.9714 178.6514 0 1 29.13383 0.652306 0.227547 0.227547 0.227547 0.2275473.581901 1.910347 8.72 1 13.8 28.9 2.86 2.86 2.86 2.864.004875 2.135933 36.1 1 14.7 27.5 2.63 2.63 2.63 2.633.458488 1.844527 379 1 13.5 29.4 2.93 2.93 2.93 2.93112.9239 60.22609 5.27 1 98.1 8.23 0.435 0.435 0.435 0.4351.507356 0.803923 25.3 1 9.5 43.2 5.42 5.42 5.42 5.427.35972 3.925184 0 1 2.80244 2.855856 1.674634 1.674634 1.674634 1.674634

0.079679 0.042495 9.04 1 0.842745 79.32559 47.90917 47.90917 47.90917 47.9091720.44604 10.90456 9.03 1 48.1 5.28 0.785 0.785 0.785 0.78510.26599 5.475194 0.703 1 27.5 10.4 1.31 1.31 1.31 1.3112.78423 6.818256 11.5 1 32.6 23.3 1.11 1.11 1.11 1.118.220767 4.384409 0.926 1 23.3 0.0173 1.54 1.54 1.54 1.5472.07672 38.44092 9.04 1 19.67513 2.047311 0.308754 0.308754 0.308754 0.308754

0.832 0.444 1.41 1 8.08 72.9 8.42 8.42 8.42 8.4233.35424 17.78893 9.03 1 74.1 37.8 0.547 0.547 0.547 0.54729.35767 15.65742 9.03 1 66.1 27.4 0.601 0.601 0.601 0.60131.54027 16.82148 9.03 1 70.5 22.7 0.57 0.57 0.57 0.57

II-5

Polychlorinated dibenzo(p)dioxins a2,3,7,8-TCDD1,2,3,7,8-PCDD1,2,3,4,7,8-HxCDD1,2,3,6,7,8-HxCDD1,2,3,7,8,9-HxCDD1,2,3,4,6,7,8-HpCDDOCDD2,3,7,8-TCDF1,2,3,7,8-PCDF2,3,4,7,8-PCDF1,2,3,4,7,8-HxCDF1,2,3,6,7,8-HxCDF2,3,4,6,7,8-HxCDF1,2,3,7,8,9-HxCDF1,2,3,4,6,7,8-HpCDF1,2,3,4,7,8,9-HpCDFOCDF

PCB Aroclor 1248


202000 108000 0.0693 0.490154 30100 1.12 0.00562 0.00562 0.00562 0.00562202000 108000 0.0693 0.219 30100 1.12 0.00562 0.00562 0.00562 0.00562

2850000 1520000 0.0693 0.0596 231000 0.609 0.00122 0.00122 0.00122 0.00122822000 439000 0.0693 0.0289 88800 0.81 0.0025 0.0025 0.0025 0.0025822000 439000 0.0693 0.0153 88800 0.81 0.0025 0.0025 0.0025 0.0025

7330000 3910000 0.0693 0.0162 479000 0.49 0.000705 0.000705 0.000705 0.0007051800000 960000 0.0693 0.001694 162000 0.677 0.00159 0.00159 0.00159 0.00159157000 83600 0.0693 0.663449 24800 1.19 0.00651 0.00651 0.00651 0.00651285000 152000 0.0693 0.364 39300 1.03 0.00461 0.00461 0.00461 0.00461385000 205000 0.0693 0.263 49500 0.965 0.00387 0.00387 0.00387 0.00387822000 439000 0.0693 0.0486 88800 0.81 0.0025 0.0025 0.0025 0.0025822000 439000 0.0693 0.0515 88800 0.81 0.0025 0.0025 0.0025 0.0025822000 439000 0.0693 0.0547 88800 0.81 0.0025 0.0025 0.0025 0.0025822000 439000 0.0693 0.0576 88800 0.81 0.0025 0.0025 0.0025 0.0025

3850000 2050000 0.0693 0.0347 291000 0.568 0.00102 0.00102 0.00102 0.001023850000 2050000 0.0693 0.0201 291000 0.568 0.00102 0.00102 0.00102 0.0010227900000 14900000 0.0693 0.00167 1340000 0.36 0.000326 0.000326 0.000326 0.000326

7370 3930 5.06 0.993 14000 14.2 0.01 0.01 0.01 0.01

II-6


Hydrogen chloride


Bv(ag) Bv(forage) Ba(milk) Ba(beef) Ba(pork) Ba(egg) Ba(chicken) BCF(fish) BAF(fish) BSAF(fish)unitless unitless d/kg fw d/kg fw d/kg fw d/kg fw d/kg fw l/kg fw l/kg fw unitless

0 0 0.00006 0.002 0 0 0 200 0 9E-07 0.001 0 0 0 620 0 6.5E-06 0.00012 0.000191 0.0025 0.106 2500 0 0.0015 0.0055 0 0 0 1900 0 0.0015 0.0055 0 0 0 30 0 0.0015 0.01 0 0 00 0 0.00025 0.0003 0.00036 0 0 80 0 0 0 0 0 0 0

1800 1800 0.00226 0.00522 3.39E-05 0.0239 0.02390 0 0.000338 0.00078 5.07E-06 0.00358 0.00358 820000 0 0.001 0.006 0 0 0 780 0 0.00586 0.00227 0.188 1.13 1.13 1290 0 0.02 0.003 0 0 0 2040 0 0.001 0.08 0 0 00 0 0.00002 0.0025 0 0 00 0 3.25E-05 0.00009 0.000128 0.00875 0.00875 2060

ad fisher HI 0.088816 0.07220260 0 0 0 0 0 0 0

0.00113 0.00113 4.77E-09 1.51E-08 1.82E-08 4.77E-06 1.19E-08 0.1030.00192 0.00192 1.09E-06 3.44E-06 4.17E-06 0.00109 2.72E-06 24.8

16.8 16.8 6.04E-07 1.91E-06 2.31E-06 0.000604 1.51E-06 15.82.19 2.19 1E-07 3.16E-07 3.83E-07 0.0001 2.5E-07 4.04

1692.473 1692.473 0.001589 0.005024 0.006081 1.588656 0.003966 30220.060.000121 0.000121 1E-07 3.16E-07 3.83E-07 0.0001 2.5E-07 4.0390720.055622 0.055622 5.37E-08 1.7E-07 2.06E-07 5.37E-05 1.34E-07 2.5162830.00308 0.00308 1.51E-08 4.79E-08 5.79E-08 1.51E-05 3.78E-08 0.961

0.000592 0.000592 7.94E-07 2.51E-06 3.04E-06 0.000794 1.98E-06 19.50.00165 0.00165 7.07E-07 2.23E-06 2.71E-06 0.000707 1.76E-06 3.591.13E-05 1.13E-05 6.36E-08 2.01E-07 2.43E-07 6.35E-05 1.59E-07 2.860.001318 0.001318 2.19E-05 6.92E-05 8.37E-05 0.021878 5.46E-05 242.326

II-7



4160 4160 0.000417 0.00132 0.0016 0.417 0.00104 55800.124 0.124 2.21E-05 0.00007 8.48E-05 0.0221 5.53E-05 245

0.0802 0.0802 2.69E-05 8.52E-05 0.000103 0.0269 6.72E-05 2840.086 0.086 2.05E-05 6.49E-05 7.86E-05 0.0205 5.12E-05 2315420 5420 0.000217 0.000687 0.000831 0.217 0.000542 2450

0.004851 0.004851 3.8E-09 1.2E-08 1.46E-08 3.8E-06 9.5E-09 0.3365540.0153 0.0153 1.05E-05 3.33E-05 4.03E-05 0.0105 2.63E-05 139

0.000202 0.000202 2.7E-06 8.54E-06 1.03E-05 0.0027 6.74E-06 49.44.33E-06 4.33E-06 1.15E-06 3.63E-06 4.4E-06 0.00115 2.87E-06 25.80.002565 0.002565 0.000363 0.001148 0.00139 0.363078 0.000906 9842.662

0.0634 0.0634 3.97E-05 0.000126 0.000151 0.0397 0.000101 3813.3E-06 3.3E-06 5.75E-06 1.82E-05 2.2E-05 0.005754 1.44E-05 87.82176.82E-05 0.000682 1.3E-09 4.3E-09 5.21E-09 1.55E-06 3.39E-09 0.170.000511 0.000511 1.43E-07 4.52E-07 5.47E-07 0.000143 3.57E-07 5.31.386424 1.386424 5.75E-05 0.000182 0.00022 0.057509 0.000144 505.1278

7.64 7.64 7.23E-07 2.29E-06 2.77E-06 0.000723 1.86E-06 18.14.89 4.89 8.34E-07 2.64E-06 3.19E-06 0.000834 2.08E-06 20.28.13 8.13 6.91E-07 2.19E-06 2.65E-06 0.000691 1.73E-06 17.50.452 0.452 1.87E-05 5.92E-05 7.16E-05 0.0187 4.67E-05 2153.52 3.52 2.38E-07 7.54E-07 9.12E-07 0.000238 5.95E-07 7.81

2.58E-05 2.58E-05 1.82E-06 5.75E-06 6.97E-06 0.00182 4.54E-06 36.610020.490981 0.490981 5.5E-09 1.74E-08 2.1E-08 5.5E-06 1.37E-08 0.445124

0.0221 0.0221 6.74E-06 2.13E-05 2.58E-05 0.00674 1.68E-05 99.10.00166 0.00166 2.79E-06 8.82E-06 1.07E-05 0.00279 6.96E-06 50.60.00633 0.00633 3.69E-06 1.17E-05 1.41E-05 0.00369 9.22E-06 62.70.00114 0.00114 2.1E-06 6.63E-06 8.03E-06 0.0021 5.24E-06 40.8

0.066696 0.066696 3.39E-05 0.000107 0.00013 0.033918 8.47E-05 338.16232.95E-06 2.95E-06 1.11E-07 3.52E-07 4.26E-07 0.000111 2.78E-07 1.810.0237 0.0237 1.26E-05 3.99E-05 4.83E-05 0.0126 3.15E-05 1600.0199 0.0199 1.07E-05 3.39E-05 0.000041 0.0107 2.68E-05 1410.022 0.022 1.18E-05 3.72E-05 0.000045 0.0118 2.93E-05 151

II-8


PCB Aroclor 1248


see comment below65500 65500 0.01 0.0543 0.0657 12.3 15.1 0.09239000 239000 0.01 0.0543 0.0657 9.73 11.4 0.09520000 520000 0.006 0.0326 0.0394 9.36 8.32 0.04520000 520000 0.005 0.0271 0.0329 7.64 5.32 0.04520000 520000 0.005 0.0271 0.0329 4.82 2.86 0.04910000 910000 0.001 0.0054 0.00657 5.27 1.77 0.005

2360000 2360000 0.001 0.00543 0.00657 2.05 0.227 0.000145700 45700 0.003 0.0163 0.0197 7.45 11.6 0.0997500 97500 0.002 0.0109 0.0131 11.6 14.9 0.0997500 97500 0.009 0.0489 0.0591 11.6 14.9 0.09162000 162000 0.007 0.038 0.046 9.32 7.18 0.04162000 162000 0.006 0.0326 0.0394 9.36 7.36 0.04162000 162000 0.005 0.0271 0.0329 5.59 3.59 0.04162000 162000 0.006 0.0326 0.0394 7.871084 5.745999 0.04830000 830000 0.001 0.00543 0.00657 4.32 1.45 0.005830000 830000 0.003 0.0163 0.0197 5 2.18 0.005

2280000 2280000 0.001 0.00543 0.00657 1.64 0.0909 0.0001

309 309 0.0128 0.0405 0.049 12.8 0.0319 2

II-9


Hydrogen chloride


RfD OralCSF RfC RfDinhal URF Inhal. CSF 24-hr AAL Annual AAL AIECmg/kg-day kg-day/mg mg/m3 mg/kg-d m3/ug kg-d/mg ug/m3 ug/m3 mg/m3

0.20.0003 1.5 0.0011 0.000314 0.0043 15 0.036 0.024 0.000190.002 8.4 0.02 0.005714 0.0024 8.4 0.02 0.02 0.00995

0.0005 6.3 0.0002 5.71E-05 0.0018 6.3 0.036 0.024 0.02991.5 0 5.25 1.5 0 0 1.786 1.19 1.49

0.003 42 0.00014 0.00004 0.012 42 0.036 0.024 0.150.04 0.0024 0.04 0 0 0.1

0 0 0 0 0 0 0.179 0.119 0.03810.000086 0 0.0003 8.57E-05 0 0 0.3 0.3 0.0018

0.0003 0 0.0011 0.000314 0 0 0.3 0.3 0.00180.0001 0 0.00035 0.0001 0 0 0.3 0.3

0.02 0 0.0702 0.020057 0.00024 0.84 0.357 0.238 0.0060.005 0 0.018 0.005143 0 0 0.714 0.476 0.002940.005 0 0.018 0.005143 0 0 0.3

0.6 0 2.1 0.6 0 0 0.1340.009 0 0 0 0 0.03

0.3 0 1.1 0.314286 0 0

0.0057 0 0.02 0.005714 0 0 27 20 2.1

0.1 0 0.35 0.1 0 00.017 0.029 0.06 0.017143 8.3E-06 0.029 5.714 3.81 1.3

4 0 14 4 0 00.3 0 1.1 0.314286 0 0 66.3

0.02 0.014 0.07 0.02 0.000004 0.0140.0014 0 0.005 0.001429 0 0 58.3

0.1 0 0 0 00.6 0 1 0.285714 0 0 1000 1000 0.0590.1 0 0.7 0.2 0 0 700 700 3.11

0.01 0.0061 0.035 0.01 0.000023 0.081 175 117 0.3560.086 0.013 0.3 0.085714 1.8E-06 0.0063 368 245 207

0 0 6 1.714286 0 0

II-10



0.1 0 0.35 0.1 0 00.09 0 0.2 0.057143 0 0 301

0.0009 0 0.00315 0.0009 0 00.03 0.024 0.8 0.228571 6.9E-06 0.024 6610.8 0 2.8 0.8 0 0 15

0 0 0 00.1 0 1 0.285714 0 0 1000 1000 5430.3 0 0.7 0.2 0 0 28100.2 0 0.2 0.057143 0 0 14800

0 0 00.06 0 0.2 0.057143 0 0 885 200

0 0 00.5 0 1.8 0.514286 0 0 1318 24 2.8

0.06 0.0075 3 0.857143 4.7E-07 0.0016 621 414 6950.004 0 0 0 00.05 0 0.18 0.051429 0 0 111 74 66.30.05 0 0.18 0.051429 0 0 111 74 66.30.005 0 0.18 0.051429 0 0 111 74 66.30.02 0 0.003 0.000857 0 0 186 3 78.60.6 0 2.1 0.6 0 0 68 45 38.5

0 0 00 7 2 0 0 3.2

0.2 0 1 0.285714 0 0 2130.01 0.052 0.4 0.114286 5.8E-07 0.002 6780.2 0 0.4 0.114286 0 0 671 400 188

0.035 0 0.123 0.035143 0 0 680.05 0 0.006 0.001714 0 00.003 1.9 0.1 0.028571 0.000084 0.3 100 100 207

2 0 7 2 0 0 1550 1033 222 0 7 2 0 0 1550 1033 222 0 7 2 0 0 1550 1033 22

II-11


PCB Aroclor 1248


150000 0 33 150000 0.001 0.00175000 0 7500015000 0 1500015000 0 1500015000 0 150001500 0 1500150 0 150

15000 0 150007500 0 7500

75000 0 7500015000 0 1500015000 0 1500015000 0 1500015000 0 150001500 0 15001500 0 1500150 0 150

0.00002 2 0.00007 0.00002 2 0.1 0.1

II-12

Appendix III Data Used to Calculate COPC EmissionRates

Data in the tables that follow were used to calculate COPC emission rates from the MaineEnergy combustion stack and odor control system exhaust during average normal operations,maximum normal operations, and off-normal upset conditions.

Data used to estimate emission rates from the Maine Energy combustion system stack

EPA Method 29 Trace Metal Lab Results MERC 2002 Air Toxics Test Program -- Final Report Appendix BMercury splits from Appendix F-2

Sample date 8/1/2002 8/1/2002 8/1/2002 8/1/2002MDL Run1 Run1 dup Run2 Run3ug ug ug ug ug

Arsenic 0.4 0.59 0.59 0.57Beryllium 0.1 0.1 0.1Cadmium 0.1 0.63 0.64 0.53 0.55Chromium (total) 0.3 5.4 5.4 5.1 3.1Copper 0.5 19 19 27 14Lead 0.2 13 13 18 14Mercury (total) 5.87 7.07 7.64Nickel 0.3 7.7 7.9 3.9 5Selenium 1 1.5 1Silver 0.2 0.49 0.46 0.51 0.24Tin 0.6 23 23 22 22Vanadium 0.2 0.74 1 0.79 0.51Zinc 0.8 71 71 110 67

8/1/2002 8/1/2002 8/1/200209:00-11:2512:10-14:2815:15-17:32Run1 Run2 Run3 Run1 Run2 Run3 mean max mean+2std min of 2lb/hr lb/hr lb/hr g/s g/s g/s g/s g/s g/s g/s

Arsenic 9.04E-05 8.35E-05 5.82E-05 1.14E-05 1.05E-05 7.33E-06 9.75E-06 1.14E-05 1.40E-05 1.14E-05Beryllium 1.53E-05 1.46E-05 1.46E-05 1.93E-06 1.84E-06 1.83E-06 1.87E-06 1.93E-06 1.98E-06 1.93E-06Cadmium 9.65E-05 7.76E-05 8.00E-05 1.22E-05 9.78E-06 1.01E-05 1.07E-05 1.22E-05 1.33E-05 1.22E-05Chromium (total) 8.27E-04 7.47E-04 4.51E-04 1.04E-04 9.41E-05 5.68E-05 8.50E-05 1.04E-04 1.35E-04 1.04E-04Copper 2.91E-03 3.95E-03 2.04E-03 3.67E-04 4.98E-04 2.57E-04 3.74E-04 4.98E-04 6.16E-04 4.98E-04Lead 1.99E-03 2.64E-03 2.04E-03 2.51E-04 3.32E-04 2.57E-04 2.80E-04 3.32E-04 3.70E-04 3.32E-04Mercury (total) 8.99E-04 1.04E-03 1.11E-03 1.13E-04 1.31E-04 1.40E-04 1.28E-04 1.40E-04 1.55E-04 1.40E-04Nickel 1.18E-03 5.71E-04 7.27E-04 1.49E-04 7.19E-05 9.16E-05 1.04E-04 1.49E-04 1.84E-04 1.49E-04Selenium 1.53E-04 2.20E-04 1.46E-04 1.93E-05 2.77E-05 1.83E-05 2.18E-05 2.77E-05 3.20E-05 2.77E-05Silver 7.51E-05 7.47E-05 3.49E-05 9.46E-06 9.41E-06 4.40E-06 7.76E-06 9.46E-06 1.36E-05 9.46E-06Tin 3.52E-03 3.22E-03 3.20E-03 4.44E-04 4.06E-04 4.03E-04 4.18E-04 4.44E-04 4.63E-04 4.44E-04Vanadium 1.13E-04 1.16E-04 7.42E-05 1.42E-05 1.46E-05 9.35E-06 1.27E-05 1.46E-05 1.86E-05 1.46E-05Zinc 1.09E-02 1.61E-02 4.16E-02 1.37E-03 2.03E-03 5.24E-03 2.88E-03 5.24E-03 7.02E-03 5.24E-03

III-1

dscfm 82938 76675 812757/22/2003 7/23/2003 7/24/2003

10:57-14:0213:32-16:1508:15-10:52Run1 Run2 Run3 Run1 Run2 Run3 mean max mean+2std min of 2mg/dscm @mg/dscm @mg/dscm @7%O2 g/s g/s g/s g/s g/s g/s g/s

Arsenic 5.00E-04 5.00E-04 6.00E-04 1.96E-05 1.81E-05 2.30E-05 2.02E-05 2.30E-05 2.53E-05 2.30E-05Cadmium 4.40E-04 8.00E-05 1.72E-05 2.89E-06 1.01E-05 1.72E-05 3.03E-05 1.72E-05Chromium (total) 4.90E-03 3.40E-03 2.90E-03 1.92E-04 1.23E-04 1.11E-04 1.42E-04 1.92E-04 2.29E-04 1.92E-04Lead 2.10E-03 1.40E-03 1.60E-03 8.22E-05 5.07E-05 6.14E-05 6.47E-05 8.22E-05 9.68E-05 8.22E-05Mercury (total) 2.30E-03 3.30E-03 2.50E-03 9.00E-05 1.19E-04 9.59E-05 1.02E-04 1.19E-04 1.33E-04 1.19E-04Nickel 7.60E-03 4.10E-03 3.90E-03 2.97E-04 1.48E-04 1.50E-04 1.98E-04 2.97E-04 3.70E-04 2.97E-04

Stack flow (d 90340 95055 921208/3/2004 8/3/2004 8/3/2004

10:56-13:4916:10-18:5722:24-00:28Run1 Run2 Run3 Run1 Run2 Run3 mean max mean+2std min of 2mg/dscm @mg/dscm @mg/dscm @7% O2 g/s g/s g/s g/s g/s g/s g/s

Cadmium 0.0027 0.001 0.0014 1.15E-04 4.49E-05 6.09E-05 7.36E-05 1.15E-04 1.47E-04 1.15E-04Lead 0.0893 0.024 0.0312 3.81E-03 1.08E-03 1.36E-03 2.08E-03 3.81E-03 5.09E-03 3.81E-03Mercury (total) 0.001 0.0008 0.0007 4.26E-05 3.59E-05 3.04E-05 3.63E-05 4.26E-05 4.86E-05 4.26E-05

OVERALL FOR MODELINGmean max mean+2stde min of 2g/s g/s g/s g/s

Arsenic 1.50E-05 2.30E-05 2.72E-05 2.30E-05Beryllium 1.87E-06 1.93E-06 1.98E-06 1.93E-06Cadmium 3.41E-05 1.15E-04 1.11E-04 1.11E-04Chromium (total) 1.14E-04 1.92E-04 2.03E-04 1.92E-04Copper 3.74E-04 4.98E-04 6.16E-04 4.98E-04Lead 8.08E-04 3.81E-03 3.24E-03 3.24E-03Mercury (total) 8.87E-05 1.40E-04 1.73E-04 1.40E-04Nickel 1.51E-04 2.97E-04 3.09E-04 2.97E-04Selenium 2.18E-05 2.77E-05 3.20E-05 2.77E-05Silver 7.76E-06 9.46E-06 1.36E-05 9.46E-06Tin 4.18E-04 4.44E-04 4.63E-04 4.44E-04Vanadium 1.27E-05 1.46E-05 1.86E-05 1.46E-05Zinc 2.88E-03 5.24E-03 7.02E-03 5.24E-03

III-2

8/1/2002 8/1/2002 8/1/2002MDL Run1 Run2 Run3 With ever detects at ND=DL, never detects at ND=DL/2ug ug ug ug ug ug ug fractions fractions fractions

Mercury 1B 0.03 0.053 0.081 0.043 0.053 0.081 0.043 0.01 0.01 0.01Mercury 2B 0.01 5.8 6.7 7.3 5.8 6.7 7.3 0.96 0.95 0.96Mercury 3A 0.01 0.028 0.043 0.033 0.028 0.028 0.028 0.00 0.00 0.00Mercury 3B 0.05 0.025 0.025 0.025 0.00 0.00 0.00Mercury 3C 0.05 0.14 0.2 0.21 0.14 0.2 0.21 0.02 0.03 0.03

sum 6.046 7.034 7.606

average fractions fractions for stackMercury 1B 0.01 Hg2 Particul 0.01Mercury 2B 0.96 Hg2 Vapor 0.96Mercury 3A 0.00 Hg0 Vapor 0.03Mercury 3B 0.00Mercury 3C 0.03

8/3/2004 8/3/2004 8/3/200410:56-13:4916:10-18:57 22:24-00:28Run1 Run2 Run3 With ever detects at ND=DL, never detects at ND=DL/2

MDL ug ug ug ug ug ug fractions fractions fractionsMercury 1B 0.19 0.29 0.286 0.19 0.29 0.286 0.11 0.16 0.17Mercury 2B 1.26 1.37 1.25 1.26 1.37 1.25 0.71 0.75 0.74Mercury 3A 0.02 0.01 0.01 0.01 0.01 0.01 0.01Mercury 3B 0.1 0.05 0.05 0.05 0.03 0.03 0.03Mercury 3C 0.1 0.26 0.26 0.1 0.1 0.15 0.05 0.06

sum 1.77 1.82 1.696OVERALL FOR MODELINGaverage fractions fractions for stack

Mercury 1B 0.15 Hg2 Particul 0.15Mercury 2B 0.73 Hg2 Vapor 0.74Mercury 3A 0.01 Hg0 Vapor 0.12Mercury 3B 0.03Mercury 3C 0.09

III-3

Hydrogen Chloride 7/22/2003 7/23/2003 7/24/200315:01-16:0115:22-16:2311:54-12:54Run1 Run2 Run3 Run1 Run2 Run3ppm @ 7%Oppm @ 7%Oppm @ 7%O2 g/s g/s g/s

8.61 21.21 21.74 5.03E-01 1.14E+00 1.24E+00

Boiler A 8/6/2004 8/6/2004 8/6/200407:58-09:0609:28-10:3110:46-10:53lb/hr lb/hr lb/hr g/s g/s g/s

1.86 1.25 0.69 2.34E-01 1.57E-01 8.69E-02

Boiler A 8/6/2004 8/6/2004 8/6/200407:58-09:0609:28-10:3110:46-10:53lb/hr lb/hr lb/hr g/s g/s g/s

0.67 0.89 1.09 8.44E-02 1.12E-01 1.37E-01g/s g/s g/s

sum 3.19E-01 2.70E-01 2.24E-01

OVERALL FOR MODELINGmean max mean+2stde min of 2g/s g/s g/s g/s

2.71E-01 3.19E-01 3.65E-01 3.19E-01

III-4

MERC 1\2002 Air Toxics Test Proggram Final Report E-1SOME DETECTS MULTIPIER 1NEVER DETECT MULTIPIER 0.5

detects scrubber detects or protocol8/6/2002 8/6/2002 8/6/2002

VOCs TO-15 MRL (ug.m3 Result value for calcMRL (ug.m3Result value for ca MRL (ug.m3 Result value for calcsacetone x x 10 210 210 5 300 300 5 240 240benzene x x 10 10 5 63 63 5 83 83bromodichloromethane 10 5 5bromoform 10 5 5bromomethane x x 10 10 5 5.7 5.7 5 5butanone, 2- (methyl ehyl ketonx x 10 11 11 5 21 21 5 18 18carbon disulfide x x 10 41 41 5 40 40 5 26 26carbon tetrachloride 10 5 5chlorobenzene 10 5 5chloroethane 10 5 5chloroform x 10 5 5 2.5 5 2.5chloromethane x x 10 10 5 20 20 5 13 13dibromochloromethane 10 5 5dibromoethane, 1,2- 10 5 5dichlorobenzene, 1,2- x 10 5 5 2.5 5 2.5dichlorobenzene, 1,3- x 10 5 5 2.5 5 2.5dichlorobenzene, 1,4- x 10 5 5 2.5 5 2.5dichloroethane, 1,1- 10 5 5dichloroethane, 1,2- 10 5 5dichloroethene, 1,1- 10 5 5dichloroethene, trans-1,2- 10 5 5dichloropropane, 1,2- 10 5 5dichloropropene, cis-1,3- 10 5 5dichloropropene, trans-1,3- 10 5 5ethylbenzene x 10 5 5 2.5 5 2.5hexanone, 2- 10 5 5methyl tert-butyl ether 10 5 5methyl-2-pentanon, 4- 10 5 5methylene chloride x x 10 86 86 5 77 77 5 60 60styrene x x 10 10 5 11 11 5 5tetrachloroethane, 1,1,2,2- 10 5 5tetrachloroethene x x 10 10 5 5.6 5.6 5 6 6toluene x x 10 76 76 5 82 82 5 68 68trichloroethane, 1,1,1- x 10 5 5 2.5 5 2.5trichloroethane, 1,1,2- 10 5 5trichloroethene 10 5 5trichlorofluoromethane 10 5 5trichlorotrifluoroethane 10 5 5vinyl acetate 10 5 5vinyl chloride x x 10 10 5 5 5 5xylene, o- x 10 5 5 2.5 5 2.5xylenes, m,p- x x 10 10 5 5 5 5 5

III-5

8/6/2002 8/6/2002 8/6/2002MRL (ug.m3) Result

value for calcs

MRL (ug.m3) Result

value for calcs

MRL (ug.m3) Result

value for calcs

acetone x x 5 220 220 5 190 190 5 190 190benzene x x 5 150 150 5 520 520 5 100 100bromodichloromethane 5 5 5bromoform 5 5 5bromomethane x x 5 5 5 32 32 5 5butanone, 2- (methyl ehyl ketonx x 5 15 15 5 11 11 5 10 10carbon disulfide x x 5 19 19 5 15 15 5 12 12carbon tetrachloride 5 5 5chlorobenzene 5 5 5chloroethane 5 5 5chloroform x 5 2.5 5 2.5 5 2.5chloromethane x x 5 8.1 8.1 5 93 93 5 5.7 5.7dibromochloromethane 5 5 5dibromoethane, 1,2- 5 5 5dichlorobenzene, 1,2- x 5 2.5 5 2.5 5 2.5dichlorobenzene, 1,3- x 5 2.5 5 2.5 5 2.5dichlorobenzene, 1,4- x 5 2.5 5 2.5 5 2.5dichloroethane, 1,1- 5 5 5dichloroethane, 1,2- 5 5 5dichloroethene, 1,1- 5 5 5dichloroethene, trans-1,2- 5 5 5dichloropropane, 1,2- 5 5 5dichloropropene, cis-1,3- 5 5 5dichloropropene, trans-1,3- 5 5 5ethylbenzene x 5 2.5 5 2.5 5 2.5hexanone, 2- 5 5 5methyl tert-butyl ether 5 5 5methyl-2-pentanon, 4- 5 5 5methylene chloride x x 5 57 57 5 42 42 5 39 39styrene x x 5 5.4 5.4 5 5 5 5tetrachloroethane, 1,1,2,2- 5 5 5tetrachloroethene x x 5 7.4 7.4 5 12 12 5 5toluene x x 5 67 67 5 58 58 5 48 48trichloroethane, 1,1,1- x 5 2.5 5 2.5 5 2.5trichloroethane, 1,1,2- 5 5 5trichloroethene 5 5 5trichlorofluoromethane 5 5 5trichlorotrifluoroethane 5 5 5vinyl acetate 5 5 5vinyl chloride x x 5 5 5 13 13 5 5xylene, o- x 5 2.5 5 2.5 5 2.5xylenes, m,p- x x 5 5 5 5 5 5

III-6

STACK FLOW for VOC emissionsO2% 10 9.1 9.6dscfh 5230493 5473533 5241083

7% O2 correction 1.2264706m^3/s 41.811619 OVERALL FOR MODELING

mean stack max mean stack maxmean max stdev mean +2std calc max ug/m3 ug/m3 g/s g/s

acetone 225 300 41.352146 307.70429 300 acetone 225 300 1.15E-02 1.54E-02benzene 154.33333 520 184.90286 524.13905 520 benzene 154.33333 520 7.91E-03 2.67E-02bromodichloromethane bromomethane 10.45 31.92138 5.36E-04 1.64E-03bromoform butanone, 2- (methyl eh 14.333333 21 7.35E-04 1.08E-03bromomethane 10.45 32 10.735688 31.921376 31.921376 carbon disulfide 25.5 41 1.31E-03 2.10E-03butanone, 2- (methyl ehyl keton 14.333333 21 4.4572039 23.247741 21 chloroform 2.9166667 4.957908 1.50E-04 2.54E-04carbon disulfide 25.5 41 12.533954 50.567908 41 chloromethane 24.966667 92.35268 1.28E-03 4.74E-03carbon tetrachloride dichlorobenzene, 1,2- 2.9166667 4.957908 1.50E-04 2.54E-04chlorobenzene dichlorobenzene, 1,3- 2.9166667 4.957908 1.50E-04 2.54E-04chloroethane dichlorobenzene, 1,4- 2.9166667 4.957908 1.50E-04 2.54E-04chloroform 2.9166667 5 1.0206207 4.9579081 4.9579081 ethylbenzene 2.9166667 4.957908 1.50E-04 2.54E-04chloromethane 24.966667 93 33.693006 92.352679 92.352679 methylene chloride 60.166667 86 3.09E-03 4.41E-03dibromochloromethane styrene 6.9 11 3.54E-04 5.64E-04dibromoethane, 1,2- tetrachloroethene 7.6666667 12 3.93E-04 6.15E-04dichlorobenzene, 1,2- 2.9166667 5 1.0206207 4.9579081 4.9579081 toluene 66.5 82 3.41E-03 4.21E-03dichlorobenzene, 1,3- 2.9166667 5 1.0206207 4.9579081 4.9579081 trichloroethane, 1,1,1- 2.9166667 4.957908 1.50E-04 2.54E-04dichlorobenzene, 1,4- 2.9166667 5 1.0206207 4.9579081 4.9579081 vinyl chloride 7.1666667 13 3.68E-04 6.67E-04dichloroethane, 1,1- xylene, m- 2.9166667 4.957908 1.50E-04 2.54E-04dichloroethane, 1,2- xylene, o- 2.9166667 4.957908 1.50E-04 2.54E-04dichloroethene, 1,1- xylene, p- 2.9166667 4.957908 1.50E-04 2.54E-04dichloroethene, trans-1,2-dichloropropane, 1,2- xylenes, m,p- 5.8333333 9.915816dichloropropene, cis-1,3-dichloropropene, trans-1,3-ethylbenzene 2.9166667 5 1.0206207 4.9579081 4.9579081hexanone, 2-methyl tert-butyl ethermethyl-2-pentanon, 4-methylene chloride 60.166667 86 18.648503 97.463673 86styrene 6.9 11 2.8106939 12.521388 11tetrachloroethane, 1,1,2,2-tetrachloroethene 7.6666667 12 2.7732051 13.213077 12toluene 66.5 82 12.227019 90.954039 82trichloroethane, 1,1,1- 2.9166667 5 1.0206207 4.9579081 4.9579081trichloroethane, 1,1,2-trichloroethenetrichlorofluoromethanetrichlorotrifluoroethanevinyl acetatevinyl chloride 7.1666667 13 3.4880749 14.142817 13xylene, o- 2.9166667 5 1.0206207 4.9579081 4.9579081xylenes, m,p- 5.8333333 10 2.0412415 9.9158162 9.9158162

III-7

MERC 2002 Air Toxics Test Proggram Final Report C-1SVOCs 7/30/2002 7/30/2002 7/31/2002 7/31/2002

15:00-19:0315:00-19:118:20/10:30-18:20/10:30-14:321ALL IN lb/hr lb/hr lb/hr lb/hrbenzoic acid 7.90E-03 5.15E-03 1.01E-02 2.87E-04benzyl alcohol 1.13E-03 6.25E-04 6.00E-04 4.30E-04bis(2-ethylhexyl)phthalate 7.52E-04 5.88E-04 7.19E-04 2.04E-02diethyl phthalate 2.60E-04 1.62E-04 1.58E-04 1.58E-04di-n-butylphthalate 2.37E-04 1.62E-04 1.58E-04 1.58E-04methylnapthalene, 2- 6.02E-04 2.65E-04 7.19E-04 2.58E-04methylphenol, 2- 4.14E-03 2.65E-04 2.59E-04 2.58E-04methylphenol, 3&4 2.07E-03 5.15E-04 5.03E-04 5.01E-04

naphthalene 1.58E-03 1.47E-04 8.63E-04 2.04E-04phenol 2.75E-02 5.52E-04 3.06E-04 2.69E-04

OVERALL FOR MODELINGmean max mean+2stde min of 2

g/s g/s g/s g/s g/s g/s g/s g/sbenzoic acid 9.95E-04 6.49E-04 1.27E-03 3.62E-05 7.38E-04 1.27E-03 1.80E-03 1.27E-03benzyl alcohol 1.42E-04 7.87E-05 7.56E-05 5.42E-05 8.77E-05 1.42E-04 1.64E-04 1.42E-04bis(2-ethylhexyl)phthalate 9.47E-05 7.41E-05 9.06E-05 2.57E-03 7.07E-04 2.57E-03 3.19E-03 2.57E-03diethyl phthalate 3.28E-05 2.04E-05 1.99E-05 1.99E-05 2.32E-05 3.28E-05 3.59E-05 3.28E-05di-n-butyl phthalate 2.99E-05 2.04E-05 1.99E-05 1.99E-05 2.25E-05 2.99E-05 3.23E-05 2.99E-05methylnapthalene, 2- 7.59E-05 3.34E-05 9.06E-05 3.25E-05 5.81E-05 9.06E-05 1.17E-04 9.06E-05methylphenol, 2- 5.22E-04 3.34E-05 3.26E-05 3.25E-05 1.55E-04 5.22E-04 6.44E-04 5.22E-04methylphenol, 3- 1.30E-04 3.24E-05 3.17E-05 3.16E-05 5.65E-05 1.30E-04 1.55E-04 1.30E-04methylphenol, 4- 1.30E-04 3.24E-05 3.17E-05 3.16E-05 5.65E-05 1.30E-04 1.55E-04 1.30E-04naphthalene 1.99E-04 1.85E-05 1.09E-04 2.57E-05 8.80E-05 1.99E-04 2.57E-04 1.99E-04phenol 3.46E-03 6.95E-05 3.86E-05 3.39E-05 9.00E-04 3.46E-03 4.31E-03 3.46E-03

7/30/2002 7/30/2002 7/31/2002 7/31/2002PCBs 15:00-19:0315:00-19:118:20/10:30-18:20/10:30-14:321

lb/hr lb/hr lb/hr lb/hrAroclor-1248 5.27E-06 3.95E-06 1.84E-06 1.90E-06 Overall for modeling

mean max mean+2stdemin of 2g/s g/s g/s g/s g/s g/s g/s g/s

6.64E-07 4.98E-07 2.32E-07 2.39E-07 4.08E-07 6.64E-07 8.29E-07 6.64E-07

III-8

Data used to estimate emission rates from the Maine Energy combustion system stackPolychlorinated dibenzo(p)dioxins and furans

2002 SAMPLESA and B are boilers were sampled seperately

7/30/2002 7/30/2002 7/30/2002 7/30/2002 7/31/2002 7/31/2002Run 1A Run 1B Run 2A Run 2B Run 3A Run 3Bpg pg pg pg pg pg

2,3,7,8-TCDD -9.2 14 -7.8 -9.5 -7.6 -8.21,2,3,7,8-PCDD 17 31 19 29 18 241,2,3,4,7,8-HxCDD 15 23 12 20 13 191,2,3,6,7,8-HxCDD 31 48 27 46 29 381,2,3,7,8,9-HxCDD 31 54 34 50 32 401,2,3,4,6,7,8-HpCDD 190 270 190 270 190 230OCDD 240 330 260 320 240 2702,3,7,8-TCDF -180 -260 -170 -260 -170 -1801,2,3,7,8-PCDF 59 82 59 81 60 672,3,4,7,8-PCDF 73 110 69 110 76 831,2,3,4,7,8-HxCDF 140 200 130 200 130 1501,2,3,6,7,8-HxCDF 71 100 69 97 67 782,3,4,6,7,8-HxCDF 85 120 69 120 73 811,2,3,7,8,9-HxCDF 4.5 6.9 5.5 7.8 4.2 4.51,2,3,4,6,7,8-HpCDF 270 300 230 300 230 2301,2,3,4,7,8,9-HpCDF 24 39 23 34 19 21OCDF 70 110 72 120 64 75

NDs 2 1 2 2 2 2Dets 15 16 15 15 15 15

Run 1A Run 1B Run 2A Run 2B Run 3A Run 3Bg/s g/s g/s g/s g/s g/s

2,3,7,8-TCDD 4.87E-11 6.45E-11 4.50E-11 5.10E-11 3.94E-11 4.35E-111,2,3,7,8-PCDD 9.00E-11 1.43E-10 1.10E-10 1.56E-10 9.34E-11 1.27E-101,2,3,4,7,8-HxCDD 7.94E-11 1.06E-10 6.92E-11 1.07E-10 6.75E-11 1.01E-101,2,3,6,7,8-HxCDD 1.64E-10 2.21E-10 1.56E-10 2.47E-10 1.50E-10 2.02E-101,2,3,7,8,9-HxCDD 1.64E-10 2.49E-10 1.96E-10 2.69E-10 1.66E-10 2.12E-101,2,3,4,6,7,8-HpCDD 1.01E-09 1.24E-09 1.10E-09 1.45E-09 9.86E-10 1.22E-09OCDD 1.27E-09 1.52E-09 1.50E-09 1.72E-09 1.25E-09 1.43E-092,3,7,8-TCDF 9.53E-10 1.20E-09 9.81E-10 1.40E-09 8.82E-10 9.55E-101,2,3,7,8-PCDF 3.12E-10 3.78E-10 3.40E-10 4.35E-10 3.11E-10 3.56E-102,3,4,7,8-PCDF 3.86E-10 5.07E-10 3.98E-10 5.91E-10 3.94E-10 4.41E-101,2,3,4,7,8-HxCDF 7.41E-10 9.22E-10 7.50E-10 1.07E-09 6.75E-10 7.96E-101,2,3,6,7,8-HxCDF 3.76E-10 4.61E-10 3.98E-10 5.21E-10 3.48E-10 4.14E-102,3,4,6,7,8-HxCDF 4.50E-10 5.53E-10 3.98E-10 6.45E-10 3.79E-10 4.30E-101,2,3,7,8,9-HxCDF 2.38E-11 3.18E-11 3.17E-11 4.19E-11 2.18E-11 2.39E-111,2,3,4,6,7,8-HpCDF 1.43E-09 1.38E-09 1.33E-09 1.61E-09 1.19E-09 1.22E-091,2,3,4,7,8,9-HpCDF 1.27E-10 1.80E-10 1.33E-10 1.83E-10 9.86E-11 1.11E-10OCDF 3.71E-10 5.07E-10 4.15E-10 6.45E-10 3.32E-10 3.98E-10

Run 1 Run 2 Run 3 mean max mean+2stdmin of 2g/s g/s g/s g/s g/s g/s g/s

2,3,7,8-TCDD 1.13E-10 9.60E-11 8.30E-11 9.74E-11 1.13E-10 1.28E-10 1.13E-101,2,3,7,8-PCDD 2.33E-10 2.65E-10 2.21E-10 2.40E-10 2.65E-10 2.86E-10 2.65E-101,2,3,4,7,8-HxCDD 1.85E-10 1.77E-10 1.68E-10 1.77E-10 1.85E-10 1.94E-10 1.85E-101,2,3,6,7,8-HxCDD 3.85E-10 4.03E-10 3.52E-10 3.80E-10 4.03E-10 4.32E-10 4.03E-101,2,3,7,8,9-HxCDD 4.13E-10 4.65E-10 3.78E-10 4.19E-10 4.65E-10 5.06E-10 4.65E-101,2,3,4,6,7,8-HpCDD 2.25E-09 2.55E-09 2.21E-09 2.33E-09 2.55E-09 2.70E-09 2.55E-09OCDD 2.79E-09 3.22E-09 2.68E-09 2.90E-09 3.22E-09 3.47E-09 3.22E-092,3,7,8-TCDF 2.15E-09 2.38E-09 1.84E-09 2.12E-09 2.38E-09 2.66E-09 2.38E-091,2,3,7,8-PCDF 6.90E-10 7.76E-10 6.67E-10 7.11E-10 7.76E-10 8.25E-10 7.76E-102,3,4,7,8-PCDF 8.93E-10 9.89E-10 8.35E-10 9.06E-10 9.89E-10 1.06E-09 9.89E-101,2,3,4,7,8-HxCDF 1.66E-09 1.82E-09 1.47E-09 1.65E-09 1.82E-09 2.01E-09 1.82E-091,2,3,6,7,8-HxCDF 8.37E-10 9.19E-10 7.62E-10 8.39E-10 9.19E-10 9.97E-10 9.19E-102,3,4,6,7,8-HxCDF 1.00E-09 1.04E-09 8.09E-10 9.52E-10 1.04E-09 1.20E-09 1.04E-091,2,3,7,8,9-HxCDF 5.56E-11 7.36E-11 4.57E-11 5.83E-11 7.36E-11 8.67E-11 7.36E-111,2,3,4,6,7,8-HpCDF 2.81E-09 2.94E-09 2.41E-09 2.72E-09 2.94E-09 3.27E-09 2.94E-091,2,3,4,7,8,9-HpCDF 3.07E-10 3.15E-10 2.10E-10 2.77E-10 3.15E-10 3.94E-10 3.15E-10OCDF 8.78E-10 1.06E-09 7.30E-10 8.89E-10 1.06E-09 1.22E-09 1.06E-09

III-9

2004 SAMPLESSample Vol (dscm) 4.48 4.28 4.29Flowrate(dscfm) 93071 88575 92905O2% 9.2 8.6 8.54corr to 7% O2 1.19 1.13 1.12

Test 1 Test 2 Test 38/3/2004 8/3/2004 8/5/2004

09:12-15:30 16:59-23:34 11:00-15:26 Test 1 Test 2 Test 3pg ng/dscm pg ng/dscm pg ng/dscm g/s g/s g/s

2,3,7,8-TCDD 27.5 0.0061 27.6 0.0064 28.5 0.0066 3.20E-10 3.04E-10 3.27E-101,2,3,7,8-PCDD 94.9 0.0212 49.5 0.0116 92.3 0.0215 1.10E-09 5.46E-10 1.06E-091,2,3,4,7,8-HxCDD 83.8 0.0187 36.2 0.0085 95 0.0221 9.75E-10 3.99E-10 1.09E-091,2,3,6,7,8-HxCDD 96.2 0.0215 48.5 0.0113 95.9 0.0224 1.12E-09 5.35E-10 1.10E-091,2,3,7,8,9-HxCDD 157 0.0350 65.8 0.0154 146 0.0340 1.83E-09 7.26E-10 1.68E-091,2,3,4,6,7,8-HpCDD 663 0.1480 228 0.0533 676 0.1576 7.71E-09 2.51E-09 7.76E-09OCDD 943 0.2105 319 0.0745 1210 0.2821 1.10E-08 3.52E-09 1.39E-082,3,7,8-TCDF 76.6 0.0171 62.7 0.0146 66.2 0.0154 8.91E-10 6.91E-10 7.60E-101,2,3,7,8-PCDF 201 0.0449 165 0.0386 164 0.0382 2.34E-09 1.82E-09 1.88E-092,3,4,7,8-PCDF 221 0.0493 190 0.0444 205 0.0478 2.57E-09 2.10E-09 2.35E-091,2,3,4,7,8-HxCDF 466 0.1040 333 0.0778 440 0.1026 5.42E-09 3.67E-09 5.05E-091,2,3,6,7,8-HxCDF 243 0.0542 167 0.0390 223 0.0520 2.83E-09 1.84E-09 2.56E-092,3,4,6,7,8-HxCDF 220 0.0491 132 0.0308 199 0.0464 2.56E-09 1.46E-09 2.29E-091,2,3,7,8,9-HxCDF -17.7 -0.0040 -19.7 -0.0046 25.7 0.0060 2.06E-10 2.17E-10 2.95E-101,2,3,4,6,7,8-HpCDF 595 0.1328 315 0.0736 586 0.1366 6.92E-09 3.47E-09 6.73E-091,2,3,4,7,8,9-HpCDF 70 0.0156 43.3 0.0101 81.5 0.0190 8.14E-10 4.77E-10 9.36E-10OCDF 210 0.0469 114 0.0266 315 0.0734 2.44E-09 1.26E-09 3.62E-09

0 0 0NDs 1 1 0Dets 16 16 17

2004 TESTS OVERALL FOR MODELINGmean max mean+2stdevmin of 2 mean max mean+2stdmin of 2g/s g/s g/s g/s g/s g/s g/s g/s

2,3,7,8-TCDD 3.17E-10 3.27E-10 3.41E-10 3.27E-10 2.07E-10 3.27E-10 4.49E-10 3.27E-101,2,3,7,8-PCDD 9.03E-10 1.10E-09 1.52E-09 1.10E-09 5.71E-10 1.10E-09 1.40E-09 1.10E-091,2,3,4,7,8-HxCDD 8.22E-10 1.09E-09 1.56E-09 1.09E-09 4.99E-10 1.09E-09 1.35E-09 1.09E-091,2,3,6,7,8-HxCDD 9.18E-10 1.12E-09 1.58E-09 1.12E-09 6.49E-10 1.12E-09 1.37E-09 1.12E-091,2,3,7,8,9-HxCDD 1.41E-09 1.83E-09 2.60E-09 1.83E-09 9.14E-10 1.83E-09 2.24E-09 1.83E-091,2,3,4,6,7,8-HpCDD 6.00E-09 7.76E-09 1.20E-08 7.76E-09 4.17E-09 7.76E-09 9.71E-09 7.76E-09OCDD 9.46E-09 1.39E-08 2.02E-08 1.39E-08 6.18E-09 1.39E-08 1.61E-08 1.39E-082,3,7,8-TCDF 7.81E-10 8.91E-10 9.84E-10 8.91E-10 1.45E-09 2.38E-09 2.97E-09 2.38E-091,2,3,7,8-PCDF 2.01E-09 2.34E-09 2.58E-09 2.34E-09 1.36E-09 2.34E-09 2.84E-09 2.34E-092,3,4,7,8-PCDF 2.34E-09 2.57E-09 2.82E-09 2.57E-09 1.62E-09 2.57E-09 3.23E-09 2.57E-091,2,3,4,7,8-HxCDF 4.72E-09 5.42E-09 6.56E-09 5.42E-09 3.18E-09 5.42E-09 6.74E-09 5.42E-091,2,3,6,7,8-HxCDF 2.41E-09 2.83E-09 3.43E-09 2.83E-09 1.62E-09 2.83E-09 3.46E-09 2.83E-092,3,4,6,7,8-HxCDF 2.10E-09 2.56E-09 3.25E-09 2.56E-09 1.53E-09 2.56E-09 2.99E-09 2.56E-091,2,3,7,8,9-HxCDF 2.39E-10 2.95E-10 3.37E-10 2.95E-10 1.49E-10 2.95E-10 3.57E-10 2.95E-101,2,3,4,6,7,8-HpCDF 5.71E-09 6.92E-09 9.58E-09 6.92E-09 4.21E-09 6.92E-09 8.32E-09 6.92E-091,2,3,4,7,8,9-HpCDF 7.43E-10 9.36E-10 1.22E-09 9.36E-10 5.10E-10 9.36E-10 1.11E-09 9.36E-10OCDF 2.44E-09 3.62E-09 4.80E-09 3.62E-09 1.66E-09 3.62E-09 3.93E-09 3.62E-09

III-10

Data used to estimate emission rates of organic compounds from the MERC odor control system

VOC (EPA TO-15) Concentration data from Air Toxics LTD. Detailed data sheets.Data from APCC August 2003 report "Emission testing from three scrubbers at MERC

Blanks are ND's 8/11/03 1140-1240 8/15/03 0208-0308mean flow (m3/s) 29.97 29.97max flow (m3/s) 32.01 32.01

S-1 Inlet A S-1 Inlet B

BOLD IN PROTOCOL POCs Rpt. Limit Rpt. Limit Amount AmountAmt for calcs Rpt. Limit Rpt. Limit Amount Amount

Amt for calcs

ppbv ug/m3 ppbv ug/m3 ug/m3 ppbv ug/m3 ppbv ug/m3 ug/m3acetone 54 250 600 600.0 62 510 1200 1200.0alpha-chlorotoluene 13 16benzene 13 41.5 16 51.1bromodichloromethane 13 16bromoform 54 62bromomethane 13 25.2 16 31.1butadiene, 1,3 13 16butanone, 2- (Methyl Ethyl Ketone 54 440 1300 1300.0 62 540 1600 1600.0carbon disulfide 54 84.1 62 96.5carbon tetrachloride 13 16chlorobenzene 13 16chloroethane 13 16chloroform 13 31.7 16 39.1chloromethane 54 55.8 62 64.0cumene 13 16cyclohexane 13 44.7 16 17 59 59.0dibromochloromethane 13 16dibromoethane, 1,2- 13 16dichlorobenzene, 1,2- 13 39.1 16 48.1dichlorobenzene, 1,3- 13 39.1 16 48.1dichlorobenzene, 1,4- 13 78.2 16 16 96 96.0dichloroethane, 1,1- 13 16dichloroethane, 1,2- 13 16dichloroethene, 1,1- 13 16dichloroethene, cis-1,2- 13 16dichloroethene, trans-1,2- 54 62dichloropropane, 1,2- 13 16dichloropropene, cis-a,3- 13 16dichlororpropene, trans-1,3- 13 16dioxane, 1,4- 54 62ethanol 54 17000 33000 33000.0 62 27000 51000 51000.0ethylbenzene 13 15 67 67.0 16 28 130 130.0ethyltoluene, 4- 54 62freon 113 13 16freon 114 13 16freon 12 13 64.3 16 18 92 92.0freon11 13 73.0 16 89.9heptane 13 15 64 64.0 16 20 84 84.0hexachlorobutadiene 54 62hexane 13 39 140 140.0 16 38 140 140.0hexanone, 2- 54 62methyl tert-butyl ether 54 62methyl-2-pentanone, 4- 54 62methylene chloride 13 45.2 16 42 150 150.0propanol, 2- 54 310 780 780.0 62 300 750 750.0propylbenzene 13 16styrene 13 17 73 73.0 16 22 98 98.0tetrachloroethane, 1,1,2,2- 13 16tetrachloroethene 13 88.2 16 21 150 150.0tetrahydofuran 54 62toluene 13 77 300 300.0 16 140 540 540.0trichlorobenzene, 1,2,4- 54 62trichloroethane, 1,1,1- 13 70.9 16 20 110 110.0trichloroethane, 1,1,2- 13 16trichloroethene 13 16trimethylbenzene, 1,2,4- 13 14 68 68.0 16 25 120 120.0trimethylbenzene, 1,3,5- 13 16vinyl acetate 54 62vinyl chloride 13 16.6 16 20.4xylene, m,p- 13 40 170 170.0 16 99 440 440.0xylene, o- 13 56.5 16 30 130 130.0

TICSButane 180 180.0 180.0 300 713 713.1Acetaldehyde 190 342 342.3 300 540 540.5Pentane 98 289 289.2 120 354 354.1Butane, 2-methyl- 320 944 944.3 360 1062 1062.3Pentane, 2-methyl- 75 264 264.4 0.0Cyclopentane, methyl- 0.0 0.01-Propanol 0.0 120 295 295.02-Butanol 460 1394 1394.5 200 606 606.3Alpha-Pinene 88 490 490.3 0.0Acetic acid, butyl ester 0.0 0.0Limonene 220 1226 1225.8 280 1560 1560.1Decane 0.0 0.0

III-11

Blanks are ND'smean flow (m3/s)max flow (m3/s)

BOLD IN PROTOCOL POCs

acetonealpha-chlorotoluenebenzenebromodichloromethanebromoformbromomethanebutadiene, 1,3butanone, 2- (Methyl Ethyl Ketonecarbon disulfidecarbon tetrachloridechlorobenzenechloroethanechloroformchloromethanecumenecyclohexanedibromochloromethanedibromoethane, 1,2-dichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-dichloroethane, 1,1-dichloroethane, 1,2-dichloroethene, 1,1-dichloroethene, cis-1,2-dichloroethene, trans-1,2-dichloropropane, 1,2-dichloropropene, cis-a,3-dichlororpropene, trans-1,3-dioxane, 1,4-ethanolethylbenzeneethyltoluene, 4-freon 113freon 114freon 12freon11heptanehexachlorobutadienehexanehexanone, 2-methyl tert-butyl ethermethyl-2-pentanone, 4-methylene chloridepropanol, 2-propylbenzenestyrenetetrachloroethane, 1,1,2,2-tetrachloroethenetetrahydofurantoluenetrichlorobenzene, 1,2,4-trichloroethane, 1,1,1-trichloroethane, 1,1,2-trichloroethenetrimethylbenzene, 1,2,4-trimethylbenzene, 1,3,5-vinyl acetatevinyl chloridexylene, m,p-xylene, o-

TICSButaneAcetaldehydePentaneButane, 2-methyl-Pentane, 2-methyl-Cyclopentane, methyl-1-Propanol2-ButanolAlpha-PineneAcetic acid, butyl esterLimoneneDecane

8/11/03 1644-1744 8/14/03 2038-213829.74 29.7431.41 31.41


Rpt. Limit Rpt. Limit Amount AmountAmt for calcs Rpt. Limit Rpt. Limit Amount Amount

Amt for calcs

ppbv ug/m3 ppbv ug/m3 ug/m3 ppbv ug/m3 ppbv ug/m3 ug/m365 330 810 810.0 30 270 660 660.016 7.516 51.1 7.5 8 26 26.016 7.565 3016 31.1 7.5 14.616 7.565 370 1100 1100.0 30 290 860 860.065 101.2 30 46.716 7.516 7.516 7.516 39.1 7.5 18.365 67.1 30 31.016 7.516 55.1 7.5 15 54 54.016 7.516 7.516 48.1 7.5 22.516 48.1 7.5 22.516 96.2 7.5 12 73 73.016 7.516 7.516 7.516 7.565 3016 7.516 7.516 7.565 3065 26000 50000 50000.0 30 13000 24000 24000.016 28 120 120.0 7.5 13 57 57.065 3016 7.516 7.516 27 130 130.0 7.5 14 68 68.016 89.9 7.5 8.5 48 48.016 39 160 160.0 7.5 18 73 73.065 3016 32 120 120.0 7.5 13 46 46.065 3065 3065 3016 17 61 61.0 7.5 18 62 62.065 230 570 570.0 30 160 400 400.016 7.516 49 210 210.0 7.5 8.9 39 39.016 7.516 108.5 7.5 9.4 65 65.065 3016 160 600 600.0 7.5 61 230 230.065 3016 17 96 96.0 7.5 11 62 62.016 7.516 7.516 25 120 120.0 7.5 9.3 47 47.016 7.565 3016 20.4 7.5 9.616 78 340 340.0 7.5 49 220 220.016 25 110 110.0 7.5 14 62 62.0

330 784 784.4 180 428 427.9330 595 594.5 150 270 270.210 30 29.5 49 145 144.6

340 1003 1003.3 150 443 442.6100 352 352.5 0.0

0.0 0.0220 541 540.8 73 179 179.4160 485 485.0 64 194 194.0

0.0 0.083 394 394.3 0.0

240 1337 1337.2 57 318 317.60.0 0.0

III-12





8/12/03 0215-0315 8/14/03 0215-031530.25 30.2531.89 31.89



Amt for calcs

ppbv ug/m3 ppbv ug/m3 ug/m3 ppbv ug/m3 ppbv ug/m3 ug/m376 260 640 640.0 75 160 390 390.019 1919 60.7 19 60.719 1976 7519 36.9 19 36.919 1976 390 1200 1200.0 75 560 1700 1700.076 118.3 75 116.819 1919 1919 1919 46.4 19 46.476 78.5 75 77.419 1919 65.4 19 65.419 1919 1919 57.1 19 57.119 57.1 19 57.119 114.2 19 114.219 1919 1919 1919 1976 7519 1919 1919 1976 7576 20000 38000 38000.0 75 24000 45000 45000.019 82.5 19 82.576 7519 1919 1919 30 150 150.0 19 94.019 106.7 19 106.719 77.9 19 77.976 7519 20 72 72.0 19 67.076 7576 7576 7519 22 78 78.0 19 66.076 210 530 530.0 75 130 330 330.019 1919 31 130 130.0 19 80.919 1919 128.9 19 128.976 7519 62 240 240.0 19 46 180 180.076 7519 103.7 19 103.719 1919 1919 93.4 19 93.419 1976 7519 24.3 19 24.319 38 160 160.0 19 27 120 120.019 82.5 19 82.5

0.0 310 737 736.9240 432 432.4 270 486 486.4

0.0 110 325 324.60.0 300 885 885.30.0 0.00.0 0.00.0 0.0

200 606 606.3 760 2304 2303.90.0 0.00.0 0.0

170 947 947.2 110 613 612.90.0 0.0

III-13





OVERALL SYSTEM INLET RESULTS FOR MODELING

Detects

mean max stdev mean+2stdev min of 2ug/m3 ug/m3 ug/m3 ug/m3 ug/m3

6 7.17E-04 1.20E-03 2.73E-04 1.26E-03 1.20E-0301 4.85E-05 6.07E-05 1.32E-05 7.48E-05 6.07E-05000 2.93E-05 3.69E-05 8.43E-06 4.61E-05 3.69E-0506 1.29E-03 1.70E-03 3.14E-04 1.92E-03 1.70E-030 9.39E-05 1.18E-04 2.65E-05 1.47E-04 1.18E-040000 3.68E-05 4.64E-05 1.06E-05 5.80E-05 4.64E-050 6.23E-05 7.85E-05 1.76E-05 9.74E-05 7.85E-0502 5.73E-05 6.54E-05 7.84E-06 7.30E-05 6.54E-05000 4.53E-05 5.71E-05 1.30E-05 7.14E-05 5.71E-050 4.53E-05 5.71E-05 1.30E-05 7.14E-05 5.71E-052 9.53E-05 1.14E-04 1.74E-05 1.30E-04 1.14E-040000000006 4.02E-02 5.10E-02 1.05E-02 6.12E-02 5.10E-024 8.98E-05 1.30E-04 2.91E-05 1.48E-04 1.30E-040004 9.97E-05 1.50E-04 3.41E-05 1.68E-04 1.50E-041 8.57E-05 1.07E-04 2.24E-05 1.30E-04 1.07E-044 8.95E-05 1.60E-04 3.52E-05 1.60E-04 1.60E-0405 9.75E-05 1.40E-04 4.09E-05 1.79E-04 1.40E-040004 7.70E-05 1.50E-04 3.73E-05 1.52E-04 1.50E-046 5.60E-04 7.80E-04 1.81E-04 9.22E-04 7.80E-0405 1.05E-04 2.10E-04 5.94E-05 2.24E-04 2.10E-0402 1.12E-04 1.50E-04 3.10E-05 1.74E-04 1.50E-0406 3.48E-04 6.00E-04 1.77E-04 7.02E-04 6.00E-0403 9.10E-05 1.10E-04 1.98E-05 1.31E-04 1.10E-04004 9.03E-05 1.20E-04 2.88E-05 1.48E-04 1.20E-04000 1.93E-05 2.43E-05 5.55E-06 3.04E-05 2.43E-056 2.42E-04 4.40E-04 1.23E-04 4.88E-04 4.40E-043 8.72E-05 1.30E-04 2.82E-05 1.44E-04 1.30E-04

5 1.42E-02 2.46E-02 1.04E-02 3.50E-02 2.46E-026 1.33E-02 1.87E-02 3.86E-03 2.11E-02 1.87E-025 5.71E-03 1.13E-02 4.94E-03 1.56E-02 1.13E-025 2.17E-02 3.40E-02 1.33E-02 4.83E-02 3.40E-022 3.07E-03 1.11E-02 5.11E-03 1.33E-02 1.11E-020 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+003 5.04E-03 1.70E-02 6.90E-03 1.88E-02 1.70E-026 2.80E-02 7.35E-02 2.50E-02 7.80E-02 7.35E-021 2.45E-03 1.57E-02 6.41E-03 1.53E-02 1.53E-0216 3.00E-02 4.99E-02 1.49E-02 5.99E-02 4.99E-02

0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

III-14





8/11/03 1140-1240 8/15/03 0208-030829.97 29.9732.01 32.01

S-1 Outlet A S-1 Outlet B


Amt for calcs

ppbv ug/m3 ppbv ug/m3 ug/m3 ppbv ug/m3 ppbv ug/m3 ug/m341 350 850 850.0 61 430 1000 1000.010 1510 31.9 15 47.910 1541 6110 19.4 15 29.110 1541 500 1500 1500.0 61 550 1600 1600.041 63.8 61 95.010 1510 1510 1510 24.4 15 36.641 42.3 61 63.010 1510 34.4 15 18 62 62.010 1510 1510 30.1 15 45.110 30.1 15 45.110 60.1 15 90.210 1510 1510 1510 1541 6110 1510 1510 1541 6141 18000 35000 35000.0 61 23000 44000 44000.010 17 74 74.0 15 26 110 110.041 6110 1510 1510 10 53 53.0 15 74.210 56.2 15 84.310 18 75 75.0 15 16 68 68.041 6110 40 140 140.0 15 30 110 110.041 6141 6141 6110 15 53 53.0 15 34 120 120.041 340 860 860.0 61 240 610 610.010 1510 19 81 81.0 15 19 84 84.010 1510 67.8 15 18 120 120.041 6110 84 320 320.0 15 120 450 450.041 6110 54.6 15 81.810 1510 1510 16 79 79.0 15 22 110 110.010 1541 6110 12.8 15 19.210 41 180 180.0 15 80 350 350.010 13 58 58.0 15 23 100 100.0

190 452 451.6 240 571 570.5220 396 396.4 440 793 792.7100 295 295.1 130 384 383.6340 1003 1003.3 340 1003 1003.378 275 274.9 0.069 238 237.5 0.0

0.0 140 344 344.1520 1576 1576.4 280 849 848.885 474 473.6 130 724 724.3

0.0 0.0210 1170 1170.1 240 1337 1337.2

0.0 0.0

III-15





8/11/03 1644-1744 8/14/03 2038-213829.74 29.7431.41 31.41



Amt for calcs

ppbv ug/m3 ppbv ug/m3 ug/m3 ppbv ug/m3 ppbv ug/m3 ug/m350 290 700 700.0 73 550 1300 1300.012 1812 38.3 18 57.512 1850 7312 23.3 18 34.912 1850 270 820 820.0 73 570 1700 1700.050 77.9 73 113.712 1812 1812 1812 29.3 18 43.950 51.6 73 75.412 1812 41.3 18 37 130 130.012 1812 1812 36.1 18 54.112 36.1 18 54.112 72.1 18 24 140 140.012 1812 1812 1812 1850 7312 1812 1812 1850 7350 21000 40000 40000.0 73 29000 55000 55000.012 20 90 90.0 18 30 130 130.050 7312 1812 1812 20 99 99.0 18 24 120 120.012 67.4 18 18 100 100.012 29 120 120.0 18 38 160 160.050 7312 25 89 89.0 18 27 98 98.050 7350 7350 7312 14 50 50.0 18 41 140 140.050 180 460 460.0 73 330 830 830.012 1812 35 150 150.0 18 76.712 1812 81.4 18 122.150 7312 120 450 450.0 18 140 530 530.050 7312 13 75 75.0 18 22 120 120.012 1812 1812 18 89 89.0 18 22 110 110.012 1850 7312 15.3 18 23.012 54 240 240.0 18 110 470 470.012 17 76 76.0 18 30 130 130.0

0.0 350 832 832.0230 414 414.4 330 595 594.568 201 200.7 120 354 354.1

230 679 678.7 330 974 973.868 240 239.7 0.0

0.0 0.00.0 160 393 393.3

110 333 333.5 170 515 515.40.0 0.00.0 0.0

130 724 724.3 250 1393 1392.90.0 0.0

III-16





8/12/03 0215-0315 8/14/03 0215-031530.25 30.2531.89 31.89



Amt for calcs

ppbv ug/m3 ppbv ug/m3 ug/m3 ppbv ug/m3 ppbv ug/m3 ug/m361 310 760 760.0 75 150 370 370.015 1915 47.9 19 60.715 1961 7515 29.1 19 36.915 1961 370 1100 1100.0 75 600 1800 1800.061 95.0 75 116.815 1915 1915 1915 36.6 19 46.461 63.0 75 77.415 1915 51.6 19 65.415 1915 1915 45.1 19 57.115 45.1 19 57.115 90.2 19 114.215 1915 1915 1915 1961 7515 1915 1915 1961 7561 20000 37000 37000.0 75 26000 49000 49000.015 15 67 67.0 19 82.561 7515 1915 1915 29 140 140.0 19 94.015 84.3 19 21 120 120.015 61.5 19 77.961 7515 19 68 68.0 19 67.061 7561 7561 7515 26 93 93.0 19 66.061 230 570 570.0 75 150 380 380.015 1915 30 130 130.0 19 80.915 1915 101.7 19 128.961 7515 73 280 280.0 19 52 200 200.061 7515 81.8 19 103.715 1915 1915 15 76 76.0 19 93.415 1961 7515 19.2 19 24.315 45 200 200.0 19 30 130 130.015 65.1 19 82.5

0.0 360 856 855.8400 721 720.7 300 540 540.5

0.0 120 354 354.1220 649 649.2 340 1003 1003.3

0.0 0.00.0 0.00.0 0.0

190 576 576.0 780 2365 2364.694 524 523.7 0.0

0.0 0.0190 1059 1058.6 0.0

0.0 130 756 756.5

III-17





OVERALL SYSTEM OUTLET RESULTS FOR MODELINGOverall scrubber flow (m^3/s)mean 89.95max 95.31outlet detected

mean max stdevmean+2stdev min of 2

g/s g/s g/s g/s g/s6 7.45E-02 9.71E-02 1.55E-02 1.05E-01 9.71E-0200 4.26E-03 5.28E-03 5.93E-04 5.45E-03 5.28E-03000 2.59E-03 3.21E-03 3.60E-04 3.31E-03 3.21E-0306 1.28E-01 1.62E-01 2.39E-02 1.76E-01 1.62E-010 8.43E-03 1.03E-02 1.10E-03 1.06E-02 1.03E-020000 3.26E-03 4.03E-03 4.53E-04 4.17E-03 4.03E-030 5.59E-03 6.85E-03 7.32E-04 7.05E-03 6.85E-0302 5.76E-03 8.15E-03 1.98E-03 9.71E-03 8.15E-03000 4.01E-03 4.96E-03 5.58E-04 5.13E-03 4.96E-030 4.01E-03 4.96E-03 5.58E-04 5.13E-03 4.96E-031 8.50E-03 1.09E-02 1.65E-03 1.18E-02 1.09E-020000000006 3.90E+00 4.70E+00 4.49E-01 4.80E+00 4.70E+005 8.29E-03 1.02E-02 1.18E-03 1.07E-02 1.02E-020004 8.70E-03 1.06E-02 1.17E-03 1.10E-02 1.06E-022 7.68E-03 9.67E-03 1.19E-03 1.01E-02 9.67E-034 8.41E-03 9.91E-03 9.23E-04 1.03E-02 9.91E-0305 8.57E-03 9.73E-03 6.64E-04 9.90E-03 9.73E-030005 7.82E-03 1.12E-02 2.44E-03 1.27E-02 1.12E-026 5.56E-02 7.18E-02 1.03E-02 7.61E-02 7.18E-0204 9.03E-03 1.15E-02 1.87E-03 1.28E-02 1.15E-0201 9.33E-03 1.18E-02 1.51E-03 1.24E-02 1.18E-0206 3.34E-02 4.00E-02 3.65E-03 4.07E-02 4.00E-0202 7.75E-03 9.69E-03 1.20E-03 1.02E-02 9.69E-03005 8.35E-03 9.95E-03 8.75E-04 1.01E-02 9.95E-03000 1.71E-03 2.11E-03 2.37E-04 2.18E-03 2.11E-036 2.35E-02 3.23E-02 6.21E-03 3.59E-02 3.23E-024 7.66E-03 9.92E-03 1.49E-03 1.06E-02 9.92E-03

1.35E-02 2.73E-02 1.21E-02 3.78E-02 2.73E-021.73E-02 2.54E-02 5.15E-03 2.76E-02 2.54E-027.92E-03 1.23E-02 4.62E-03 1.72E-02 1.23E-022.65E-02 3.21E-02 5.56E-03 3.77E-02 3.21E-022.56E-03 8.80E-03 4.24E-03 1.10E-02 8.80E-031.19E-03 7.60E-03 3.10E-03 7.39E-03 7.39E-033.67E-03 1.24E-02 6.05E-03 1.58E-02 1.24E-023.11E-02 7.54E-02 2.51E-02 8.13E-02 7.54E-028.62E-03 2.32E-02 1.04E-02 2.94E-02 2.32E-02

2.84E-02 4.38E-02 1.66E-02 6.15E-02 4.38E-023.81E-03 2.41E-02 9.85E-03 2.35E-02 2.35E-02

III-18

Data used to estimate emission rates of fugitive metals from the Maine Energy odor control system

Ash fugitive emissions from Jim Secunde sent to Biddeford, revised 2/10/03Calendar 2003 ash produced

46322.32 tons1.5 lbs/ton AP42 emission factor used for CaO

69483.48 lbs/yr of uncontrolled ash emission 80% conditioning control90% enclosure control

1389.6696 lbs/yr of controled ash emission0.019974277 g/s of controled ash emission

89.95 Overall scrubber flow (m^3/s)

Ash compositionThis data is from 2002-2004 MERC Annual Solid Waste Reports

2002 2002 2002 2002 2002 2002 2002 2002

1 Qtr 2 Qtr 3 Qtr 4 Qtr avg maxavg + 2stdev

min of max's

Arsenic 64 38 49 36 46.75 64 72.43398 64Cadmium 39 44 40 71 48.5 71 78.80951 71Chromium (total) 387 62 83 88 155 387 465.1527 387Chromium (hexavalent) 1 0.8 1.3 1.1 1.05 1.3 1.466333 1.3Copper 739 628 1950 773 1022.5 1950 2265.351 1950Lead 2020 1600 1430 2740 1947.5 2740 3114.762 2740Mercury 7.2 5.55 3.84 10.6 6.7975 10.6 12.56223 10.6Nickel 152 118 89 190 137.25 190 224.4184 190Selenium 1.5 1.4 1.9 1.7 1.625 1.9 2.068471 1.9Silver 11 13 10 13 11.75 13 14.75 13Vanadium 30 40 80 50 50 80 93.20494 80Zinc 6320 2900 7440 5240 5475 7440 9349.894 7440

2003 2003 2003 2003 2003 2003 2003 2003


min of max's

Arsenic 35 33 50 40 39.5 50 54.68771 50Cadmium 30 22.6 80 34 41.65 80 93.64833 80Chromium (total) 52 56 70 67 61.25 70 78.48369 70Chromium (hexavalent) 1 1 1 1 1 1 1 1Copper 761 1200 537 1421 979.75 1421 1785.637 1421Lead 1217 1510 3100 1750 1894.25 3100 3559.966 3100Mercury 7.6 6.78 11 3.78 7.29 11 13.2275 11Nickel 145 123 137 78 120.75 145 180.5803 145Selenium 1.5 1.6 0.5 3 1.65 3 3.705886 3Silver 13 12 13 8 11.5 13 16.26095 13Vanadium 30 40 10 70 37.5 70 87.5 70Zinc 4160 4030 6450 4410 4762.5 6450 7034.496 6450

III-19

2004 2004 2004 2004 2004 2004 2004 2004


min of max's

Arsenic 29 27 40 55 37.75 55 63.43398 55Cadmium 15.2 28 23 64 32.55 64 75.78625 64Chromium (total) 92 59 45 51 61.75 92 103.6825 92Chromium (hexavalent)Copper 5675 6950 990 4538.333 6950 10815.09 6950Lead 511 1172 1185 2600 1367 2600 3127.369 2600Mercury 5.98 6.77 5.17 11.8 7.43 11.8 13.40133 11.8Nickel 206 127 93 142 206 257.9483 206Selenium 1.9 1.6 1.6 1.9 1.75 1.9 2.09641 1.9Silver 12 12 6 14 11 14 17.9282 14Vanadium 60 20 20 30 32.5 60 70.35939 60Zinc 4410 3090 3150 3550 4410 5040.772 4410

Ash composition OVERALL FOR MODELINGmean max average maxmg/kg mg/kg g/s g/s

Arsenic 41.3 72.4 8.26E-07 1.45E-06Beryllium 3.04E-08 9.35E-08Cadmium 40.9 93.6 8.17E-07 1.87E-06Chromium (total) 92.7 465.2 1.85E-06 9.29E-06Chromium (hexavalent) 1.0 1.5 2.05E-08 2.93E-08Copper 2180.2 2265.4 4.35E-05 4.52E-05Lead 1736.3 3560.0 3.47E-05 7.11E-05Mercury 7.2 13.2 1.43E-07 2.64E-07Nickel 133.3 224.4 2.66E-06 4.48E-06Selenium 1.7 3.7 3.35E-08 7.40E-08Silver 11.4 16.3 2.28E-07 3.25E-07Tin 1.79E-05 9.73E-06Vanadium 40.0 93.2 7.99E-07 1.86E-06Zinc 4595.8 9349.9 9.18E-05 1.87E-04

Beryllium and Tin were not measured in the ashBeryllium is ratioed to Chromium using stack data (both are LVM for MACT purposes)Tin is ratioed to Lead using stack data (similar T(m)s )

III-20

Data used to calculate upset factors from CEMS measurements at Maine Energy

Upset start hour

Upset end hour

Duration (hours) Cause CEMS data

average concentrations

Date Start hour End hour hours low high ratio min max meanSPRAY DRYER UPSETS

11/1/2002 3 5 2 atomizer SO2 14 34.5 2.5 2.2 2.5 2.37/14/2004 5 6 1 atomizer SO22/20/2005 10 19 9 atomizer SO2 14.25 31.5 2.2

COMBUSTION CONTROL UPSETS10/1/2003 11 21 10 grates CO 2.3 3.9 2.9

10/15/2003 5 24 19 grates CO10/16/2003 0 10.5 10.5 grates CO11/5/2003 19 24 5 grates CO11/6/2003 0 2 2 grates CO4/6/2004 1 24 23 grates CO

4/20/2004 20 24 4 grates CO 123 306 2.54/21/2004 0 20 20 grates CO4/22/2004 0 17 17 grates CO4/25/2004 13 24 11 grates CO 62 220 3.54/26/2004 0 5 5 grates CO8/4/2004 8 24 16 grates CO 67 204 3.08/5/2004 0 9 9 grates CO 88 204 2.3

8/12/2004 7 24 17 grates CO 73 282 3.98/13/2004 0 6 6 grates CO 80 250 3.18/15/2004 0 20 20 grates CO8/19/2004 0 24 24 grates CO 65 217 3.38/20/2004 0 13 13 grates CO 87 222 2.69/9/2004 11 24 13 grates CO 110 250 2.3

9/10/2004 0 3 3 grates CO 187 464 2.59/26/2004 16 24 8 grates CO 165 520 3.29/27/2004 0 2 2 grates CO 175 453 2.6

III-21

Appendix IV Air Dispersion and Deposition Modelingand Data Files

This Appendix consists of a CD-ROM and the following brief explanation of the files that arestored on it. The files are those used to conduct the air dispersion modeling study of the MaineEnergy facility with the AERMOD and ISCST3 atmospheric dispersion and deposition models. More detailed explanations of the modeling study and the files can be found in Chapter 3 of therisk assessment report. The boldfaced sections refer to directories of files contained on the CD-ROM. Three main directories are on the CD-ROM: “Model Input and Output Files,”“Meteorological Data Files,” and “Receptor Files.”

Model Input and Output Files

The main directory “Model Input and Output Files” contains subdirectories of input and outputfiles for each of the emission sources and COPC groups modeled. The subdirectory namesdescribe the source (“Boiler Stack” or “Odor Control System”), and the type of COPC modeled(either vapors classified by Henry’s Law constant; vapor-phase divalent mercury; or mass-, orsurface-weighted particulate-phase COPCs). Emissions from the facility’s boiler stack weremodeled for two different flow rates: the primary modeling runs were used to assess typicaloperating conditions, those labeled as “startup” model runs were used to assess potential effectsthat might occur during short periods of reduced stack flowrates.

Three types of files are included in each of these subdirectories:

1. Modeling input files for the AERMOD and ISCST3 model runs. Five input filesare included in each subdirectory corresponding to each of the five years ofmeteorological data used in the modeling (1986–1990). The year ofmeteorological data used is identified in the file name as two digits (‘86’ through‘90’), or as four digits (‘1986’ through ‘1990’).

2. Primary modeling output files with the file extension “.out” are the full outputfiles generated by the AERMOD and ISCST3 models. The modeled year isidentified as for the input files.

3. Data only output files with file extensions of either “.txt” (ISCST3 runs) or “.plt”(AERMOD runs) are plotfiles containing the maximum concentration anddeposition results for each receptor location averaged over the period identified atthe end of the file name as: ‘_1 ’ for one-hour maximum levels, ‘24 ’ or ‘_24 ’ for24-hour maximum average levels, and ‘PER’ or ‘_yr’ for maximum annualaverages. The modeled year is again identified as for the input files.

Meteorological Data Files

Two subdirectories of meteorological data files are included: AERMET (for AERMOD), andPCRAMMET (for ISCST3).

The files in the AERMET subdirectory include:1. Meteorological data files: surface files (14764_86.dat through 14764_90.dat) in

SAMSON format, upper air data (14764_86.ua through 14764_90.ua) in TD6201-VB format;

2. Stage 1, 2, and 3 AERMET program input files (PORT_861.INP, port_862.INP,and port_863.inp through PORT_901.INP, port_902.INP, and port_903.inp);

3. various intermediate files used in the progression of AERMET programs (fileswith ‘.mrg’, ‘.msg’, ‘.rpt’, and other ‘.dat’ extensions); and

4. the final AERMET output files for surface (‘.sfc’) and profile (‘.pfl’) data for usein the AERMOD dispersion models.

The files in the PCRAMMET subdirectory include:1. meteorological surface data files for the Portland International Jetport,

downloaded from the EPA SCRAM Bulletin Board (14764_86.sam through14764_90.sam),

2. mixing height data files also for the Portland International Jetport, downloadedfrom the EPA SCRAM Bulletin Board (14764_86.txt through 14764_90.txt)

3. PCRAMMET program input files (pcr86.inp through pcr90.inp), and4. PCRAMMET program output files that were used in the ISCST3 modeling

(port1986.met through port1990.met ).

Receptor Files

Files in the directory “Receptor Files” include the files used to determine the ground levelelevations of all receptor locations for both the AERMOD and ISCST3 dispersion modeling, andthe “HILL” receptor input required for the AERMOD dispersion modeling. The files include:

1. AERMAP input files for the three sets of receptors (files ‘merc1map.txt’ through‘merc3map.txt’),

2. AERMAP output files for the three sets of receptors (files ‘mer1grid.out’ through‘mer3grid.out’), and

3. the Digital Elevation Model (.dem) files of gridded topographic elevationsdeveloped by the U.S. Geological Survey used by AERMAP.

Appendix V Air Dispersion and Deposition ModelingResults Figures

The following figures depict the modeled atmospheric dispersion and deposition patterns foreach type of COPC emitted from the Maine Energy combustion stack and odor control systemexhaust. The concentrations and deposition fluxes are show for nominal modeled emission rates(e.g., 1 gram per second or 300 grams per second). Actual modeled COPC concentrations anddeposition fluxes are calculated by multiplying the modeled COPC emission rates by themodeled normalized concentration and deposition values.


V-1

Figure V.1 Maximum 1-hour concentration, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-2

Figure V.2 Maximum 24-hour concentration, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-3

Figure V.3 Annual average concentration, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-4

Figure V.4 Annual average wet deposition, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-5

Figure V.5 Annual average dry deposition, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-6

Figure V.6 Annual average total deposition, ISCST3 modeling of boiler stack emissions of volume(mass) weighted particles (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-7

Figure V.7 Maximum 1-hour concentration, ISCST3 modeling of boiler stack emissions of surface-weighted particles (normalized to 1 g/s emission rate). Top projection depicts entiremodeling domain, lower projection a 6-km by 6-km region around the Maine Energyfacility. Color-coded legend indicates relative values. Cross indicates facility location,and black outlines pond watersheds.


V-8

Figure V.8 Maximum 24-hour concentration, ISCST3 modeling of boiler stack emissions of surface-weighted particles (normalized to 1 g/s emission rate). Top projection depicts entiremodeling domain, lower projection a 6-km by 6-km region around the Maine Energyfacility. Color-coded legend indicates relative values. Cross indicates facility location,and black outlines pond watersheds.


V-9

Figure V.9 Annual average concentration, ISCST3 modeling of boiler stack emissions of surface-weighted particles (normalized to 1 g/s emission rate). Top projection depicts entiremodeling domain, lower projection a 6-km by 6-km region around the Maine Energyfacility. Color-coded legend indicates relative values. Cross indicates facility location,and black outlines pond watersheds.


V-10

Figure V.10 Annual average wet deposition, ISCST3 modeling of boiler stack emissions of surface-weighted particles (normalized to 1 g/s emission rate). Top projection depicts entiremodeling domain, lower projection a 6-km by 6-km region around the Maine Energyfacility. Color-coded legend indicates relative values. Cross indicates facility location,and black outlines pond watersheds.


V-11

Figure V.11 Annual average dry deposition, ISCST3 modeling of boiler stack emissions of surface-weighted particles (normalized to 1 g/s emission rate). Top projection depicts entiremodeling domain, lower projection a 6-km by 6-km region around the Maine Energyfacility. Color-coded legend indicates relative values. Cross indicates facility location,and black outlines pond watersheds.


V-12

Figure V.12 Annual average total deposition, ISCST3 modeling of boiler stack emissions of surface-weighted particles (normalized to 1 g/s emission rate). Top projection depicts entiremodeling domain, lower projection a 6-km by 6-km region around the Maine Energyfacility. Color-coded legend indicates relative values. Cross indicates facility location,and black outlines pond watersheds.


V-13

Figure V.13 Maximum 1-hour concentration, ISCST3 modeling of boiler stack emissions of vaporswith low Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-14

Figure V.14 Maximum 24-hour concentration, ISCST3 modeling of boiler stack emissions of vaporswith low Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-15

Figure V.15 Annual average concentration, ISCST3 modeling of boiler stack emissions of vapors withlow Henry’s Law constants (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-16

Figure V.16 Annual average wet deposition, ISCST3 modeling of boiler stack emissions of vaporswith low Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-17

Figure V.17 Maximum 1-hour concentration, ISCST3 modeling of boiler stack emissions of vaporswith medium Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-18

Figure V.18 Maximum 24-hour concentration, ISCST3 modeling of boiler stack emissions of vaporswith medium Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-19

Figure V.19 Annual average concentration, ISCST3 modeling of boiler stack emissions of vapors withmedium Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-20

Figure V.20 Annual average wet deposition, ISCST3 modeling of boiler stack emissions of vaporswith medium Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-21

Figure V.21 Maximum 1-hour concentration, ISCST3 modeling of boiler stack emissions of vaporswith high Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-22

Figure V.22 Maximum 24-hour concentration, ISCST3 modeling of boiler stack emissions of vaporswith high Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-23

Figure V.23 Annual average concentration, ISCST3 modeling of boiler stack emissions of vapors withhigh Henry’s Law constants (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-24

Figure V.24 Annual average wet deposition, ISCST3 modeling of boiler stack emissions of vaporswith high Henry’s Law constants (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-25

Figure V.25 Maximum 1-hour concentration, ISCST3 modeling of boiler stack emissions of mercuricchloride (HgCl2) vapors (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-26

Figure V.26 Maximum 24-hour concentration, ISCST3 modeling of boiler stack emissions ofmercuric chloride (HgCl2) vapors (normalized to 1 g/s emission rate). Top projectiondepicts entire modeling domain, lower projection a 6-km by 6-km region around theMaine Energy facility. Color-coded legend indicates relative values. Cross indicatesfacility location, and black outlines pond watersheds.


V-27

Figure V.27 Annual average concentration, ISCST3 modeling of boiler stack emissions of mercuricchloride (HgCl2) vapors (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-28

Figure V.28 Annual average wet deposition, ISCST3 modeling of boiler stack emissions of mercuricchloride (HgCl2) vapors (normalized to 1 g/s emission rate). Top projection depictsentire modeling domain, lower projection a 6-km by 6-km region around the MaineEnergy facility. Color-coded legend indicates relative values. Cross indicates facilitylocation, and black outlines pond watersheds.


V-29

Figure V.29 Maximum 1-hour concentration, AERMOD modeling of odor scrubbing systememissions of small particles and vapors with low Henry’s Law constants (normalized to300 g/s emission rate). Top projection depicts entire modeling domain, lower projectiona 6-km by 6-km region around the Maine Energy facility. Color-coded legend indicatesrelative values. Cross indicates facility location, and black outlines pond watersheds.


V-30

Figure V.30 Maximum 24-hour concentration, AERMOD modeling of odor scrubbing systememissions of small particles and vapors with low Henry’s Law constants (normalized to300 g/s emission rate). Top projection depicts entire modeling domain, lower projectiona 6-km by 6-km region around the Maine Energy facility. Color-coded legend indicatesrelative values. Cross indicates facility location, and black outlines pond watersheds.


V-31

Figure V.31 Annual average concentration, AERMOD modeling of odor scrubbing system emissionsof small particles and vapors with low Henry’s Law constants (normalized to 300 g/semission rate). Top projection depicts entire modeling domain, lower projection a 6-kmby 6-km region around the Maine Energy facility. Color-coded legend indicates relativevalues. Cross indicates facility location, and black outlines pond watersheds.


V-32

Figure V.32 Annual average wet deposition, AERMOD modeling of odor scrubbing system emissionsof small particles and vapors with low Henry’s Law constants (normalized to 300 g/semission rate). Top projection depicts entire modeling domain, lower projection a 6-kmby 6-km region around the Maine Energy facility. Color-coded legend indicates relativevalues. Cross indicates facility location, and black outlines pond watersheds.


V-33

Figure V.33 Annual average dry deposition, AERMOD modeling of odor scrubbing system emissionsof small particles and vapors with low Henry’s Law constants (normalized to 300 g/semission rate). Top projection depicts entire modeling domain, lower projection a 6-kmby 6-km region around the Maine Energy facility. Color-coded legend indicates relativevalues. Cross indicates facility location, and black outlines pond watersheds.


V-34

Figure V.34 Annual average total deposition, AERMOD modeling of odor scrubbing systememissions of small particles and vapors with low Henry’s Law constants (normalized to300 g/s emission rate). Top projection depicts entire modeling domain, lower projectiona 6-km by 6-km region around the Maine Energy facility. Color-coded legend indicatesrelative values. Cross indicates facility location, and black outlines pond watersheds.


V-35

Figure V.35 Maximum 1-hour concentration, AERMOD modeling of odor scrubbing systememissions of vapors with medium Henry’s Law constants (normalized to 300 g/semission rate). Top projection depicts entire modeling domain, lower projection a 6-kmby 6-km region around the Maine Energy facility. Color-coded legend indicates relativevalues. Cross indicates facility location, and black outlines pond watersheds.


V-36

Figure V.36 Maximum 24-hour concentration, AERMOD modeling of odor scrubbing systememissions of vapors with medium Henry’s Law constants (normalized to 300 g/semission rate). Top projection depicts entire modeling domain, lower projection a 6-kmby 6-km region around the Maine Energy facility. Color-coded legend indicates relativevalues. Cross indicates facility location, and black outlines pond watersheds.


V-37

Figure V.37 Annual average concentration, AERMOD modeling of odor scrubbing system emissionsof vapors with medium Henry’s Law constants (normalized to 300 g/s emission rate). Top projection depicts entire modeling domain, lower projection a 6-km by 6-km regionaround the Maine Energy facility. Color-coded legend indicates relative values. Crossindicates facility location, and black outlines pond watersheds.


V-38

Figure V.38 Annual average wet deposition, AERMOD modeling of odor scrubbing system emissionsof vapors with medium Henry’s Law constants (normalized to 300 g/s emission rate). Top projection depicts entire modeling domain, lower projection a 6-km by 6-km regionaround the Maine Energy facility. Color-coded legend indicates relative values. Crossindicates facility location, and black outlines pond watersheds.


V-39

Figure V.39 Maximum 1-hour concentration, AERMOD modeling of odor scrubbing systememissions of vapors with high Henry’s Law constants (normalized to 300 g/s emissionrate). Top projection depicts entire modeling domain, lower projection a 6-km by 6-kmregion around the Maine Energy facility. Color-coded legend indicates relative values. Cross indicates facility location, and black outlines pond watersheds.


V-40

Figure V.40 Maximum 24-hour concentration, AERMOD modeling of odor scrubbing systememissions of vapors with high Henry’s Law constants (normalized to 300 g/s emissionrate). Top projection depicts entire modeling domain, lower projection a 6-km by 6-kmregion around the Maine Energy facility. Color-coded legend indicates relative values. Cross indicates facility location, and black outlines pond watersheds.


V-41

Figure V.41 Annual average concentration, AERMOD modeling of odor scrubbing system emissionsof vapors with high Henry’s Law constants (normalized to 300 g/s emission rate). Topprojection depicts entire modeling domain, lower projection a 6-km by 6-km regionaround the Maine Energy facility. Color-coded legend indicates relative values. Crossindicates facility location, and black outlines pond watersheds.


V-42

Figure V.42 Annual average wet deposition, AERMOD modeling of odor scrubbing system emissionsof vapors with high Henry’s Law constants (normalized to 300 g/s emission rate). Topprojection depicts entire modeling domain, lower projection a 6-km by 6-km regionaround the Maine Energy facility. Color-coded legend indicates relative values. Crossindicates facility location, and black outlines pond watersheds.

Appendix VII Calculated Concentrations ofCompounds of Potential Concern(COPC) inEnvironmental Media

The tables in this Appendix contain the COPC concentrations calculated to be present in theenvironmental media evaluated in the risk assessment.

The first of these tables gives the unitized air concentrations (:g-s/g-m3, for vapor phase COPCsonly) and wet and dry deposition rates (s/m2-yr). These values may be multiplied by the COPC’semission rate (g/s) to determine the estimated vapor phase concentrations (:g/m3), and thedeposition rates (g/m2-yr). The dry deposition rate of vapor phase COPCs is estimated bymultiplying the air concentration by a deposition velocity (m/s). Zeros are shown for phases ofeach COPC that are not present from that source, or that are not modeled in that medium (e.g.,elemental mercury is only modeled for direct exposure, but not in other media). VOCs may haveparticle phase values listed for stack emissions even if none of that compound is present as aparticle; this is accounted for through the use of the COPC vapor fraction parameter Fv. Theabbreviations for the unitized values indicate:

Cyv vapor phase air concentration, maximum impact locationDywv vapor phase wet deposition, maximum impact locationDydp particle phase dry deposition, maximum impact locationDywp particle phase dry deposition, maximum impact locationCywv vapor phase air concentration, watershed averageDywwv vapor phase wet deposition, watershed averageDytwp particle phase total deposition, watershed average

In the tables for soil and subsequent media concentrations listed under ‘cancer’ are based onconcentrations averaged over the exposure duration (HHRAP equation 5-1C); those listed under‘non-cancer’ are maximum one year average concentrations estimated at the end of the facility’soperating life (HHRAP equation 5-1E). Tilled soil is assumed to have a mixing depth of 20 cmand untilled soil is assumed o have a mixing depth of 1 cm based on HHRAP guidance. Valuesgiven for COPC concentrations in the Saco River, and fish in the Saco River are based onbounding estimates described in Section 5.4.4.

annual average unitized deposition and concentrationwatershed average

Cyv Dywv Dydp Dywp Cywv Dywwv Dytwp(ug-s/g-m3) (s/m2-yr) (s/m2-yr) (s/m2-yr) (ug-s/g-m3) (s/m2-yr) (s/m2-yr)

Stack emissionsMetalsArsenic 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Beryllium 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Cadmium 0.00E+00 0.00E+00 3.33E-02 8.39E-01 0.00E+00 0.00E+00 2.08E-02Chromium (total) 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Chromium (hexavalent) 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Copper 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Lead 0.00E+00 0.00E+00 3.33E-02 8.39E-01 0.00E+00 0.00E+00 2.08E-02Mercuric chloride (particle) 0.00E+00 0.00E+00 3.33E-02 8.39E-01 0.00E+00 0.00E+00 2.08E-02Mercuric chloride (vapor) 3.02E-02 1.48E-01 0.00E+00 0.00E+00 1.90E-02 1.12E-03 0.00E+00Mercury 3.11E-02 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Methyl mercury 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Nickel 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Selenium 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Silver 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Tin 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Vanadium 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Zinc 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02

Hydrogen chloride 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00

Organic compoundsacetone 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00benzene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00benzoic acid 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00benzyl alcohol 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00bis(2-ethylhexyl)phthalate 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00bromomethane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00butanol, n- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00butanone, 2- methyl ethyl ketone 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00carbon disulfide 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00chloroform 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00chloromethane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00cyclohexane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00di-n-butylphthalate 3.08E-02 3.27E-02 0.00E+00 0.00E+00 1.95E-02 2.66E-04 2.29E-04dichlorobenzene, 1,2- 3.03E-02 3.36E-04 3.67E-04 9.23E-03 1.90E-02 2.73E-06 0.00E+00dichlorobenzene, 1,3- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00dichlorobenzene, 1,4- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00diethyl phthalate 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00ethanol 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00ethylbenzene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00freon 11 (trichlorofluoromethane) 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00freon 12 (dichlorodifluoromethane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00heptane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00hexane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00methane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00methanol 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00methylene chloride 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00methylnaphthalene, 2- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00methyl phenol, 2- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00methyl phenol, 3- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00methyl phenol, 4- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00naphthalene 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00phenol 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00propane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00propanol, 2- (isopropyl alcohol) 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00styrene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00tetrachloroethene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00toluene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00trichloroethane, 1,1,1- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00trimethylbenzene, 1,2,4- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00vinyl chloride 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00xylene, m- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00xylene, o- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00xylene, p- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00

VI-1



Stack emissionsPolychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 1.52E-02 1.62E-02 1.70E-02 4.28E-01 9.68E-03 1.32E-04 1.06E-021,2,3,7,8-PCDD 6.81E-03 7.24E-03 2.60E-02 6.55E-01 4.33E-03 5.88E-05 1.63E-021,2,3,4,7,8-HxCDD 1.85E-03 1.97E-03 3.13E-02 7.89E-01 1.18E-03 1.60E-05 1.96E-021,2,3,6,7,8-HxCDD 8.99E-04 9.56E-04 3.24E-02 8.15E-01 5.71E-04 7.76E-06 2.02E-021,2,3,7,8,9-HxCDD 4.76E-04 5.06E-04 3.28E-02 8.26E-01 3.02E-04 4.11E-06 2.05E-021,2,3,4,6,7,8-HpCDD 5.04E-04 5.36E-04 3.28E-02 8.25E-01 3.20E-04 4.35E-06 2.05E-02OCDD 5.11E-05 3.16E-04 3.33E-02 8.38E-01 3.22E-05 2.35E-06 2.08E-022,3,7,8-TCDF 2.06E-02 2.19E-02 1.12E-02 2.82E-01 1.31E-02 1.78E-04 7.01E-031,2,3,7,8-PCDF 1.13E-02 1.20E-02 2.12E-02 5.34E-01 7.19E-03 9.77E-05 1.32E-022,3,4,7,8-PCDF 8.18E-03 8.70E-03 2.46E-02 6.18E-01 5.20E-03 7.06E-05 1.53E-021,2,3,4,7,8-HxCDF 1.51E-03 1.61E-03 3.17E-02 7.98E-01 9.60E-04 1.30E-05 1.98E-021,2,3,6,7,8-HxCDF 1.60E-03 1.70E-03 3.16E-02 7.96E-01 1.02E-03 1.38E-05 1.97E-022,3,4,6,7,8-HxCDF 1.70E-03 1.81E-03 3.15E-02 7.93E-01 1.08E-03 1.47E-05 1.97E-021,2,3,7,8,9-HxCDF 1.79E-03 1.90E-03 3.14E-02 7.91E-01 1.14E-03 1.55E-05 1.96E-021,2,3,4,6,7,8-HpCDF 1.08E-03 1.15E-03 3.22E-02 8.10E-01 6.85E-04 9.32E-06 2.01E-021,2,3,4,7,8,9-HpCDF 6.25E-04 6.65E-04 3.27E-02 8.22E-01 3.97E-04 5.40E-06 2.04E-02OCDF 5.19E-05 5.52E-05 3.33E-02 8.38E-01 3.30E-05 4.48E-07 2.08E-02

PCB Aroclor 1248 3.09E-02 3.28E-02 2.33E-04 5.87E-03 1.96E-02 2.67E-04 1.46E-04

VI-2



Scrubber emissionsMetalsArsenic 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Beryllium 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Cadmium 0.00E+00 0.00E+00 3.33E-02 8.39E-01 0.00E+00 0.00E+00 2.08E-02Chromium (total) 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Chromium (hexavalent) 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Copper 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Lead 0.00E+00 0.00E+00 3.33E-02 8.39E-01 0.00E+00 0.00E+00 2.08E-02Mercury (elemental) 0.00E+00 0.00E+00 3.33E-02 8.39E-01 0.00E+00 0.00E+00 2.08E-02Mercuric chloride (vapor) 3.02E-02 1.48E-01 0.00E+00 0.00E+00 1.90E-02 1.12E-03 0.00E+00Mercuric chloride (particle) 3.11E-02 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Methyl mercury 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Nickel 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Selenium 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Silver 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Tin 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Vanadium 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02Zinc 0.00E+00 0.00E+00 6.67E-02 1.52E+00 0.00E+00 0.00E+00 4.05E-02

Hydrogen chloride 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00

Organic compoundsacetone 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00benzene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00benzoic acid 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00benzyl alcohol 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00bis(2-ethylhexyl)phthalate 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00bromomethane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00butanol, n- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00butanone, 2- methyl ethyl ketone 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00carbon disulfide 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00chloroform 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00chloromethane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00cyclohexane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00di-n-butylphthalate 3.08E-02 3.27E-02 0.00E+00 0.00E+00 1.95E-02 2.66E-04 2.29E-04dichlorobenzene, 1,2- 3.03E-02 3.36E-04 3.67E-04 9.23E-03 1.90E-02 2.73E-06 0.00E+00dichlorobenzene, 1,3- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00dichlorobenzene, 1,4- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00diethyl phthalate 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00ethanol 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00ethylbenzene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00freon 11 (trichlorofluoromethane) 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00freon 12 (dichlorodifluoromethane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00heptane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00hexane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00methane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00methanol 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00methylene chloride 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00methylnaphthalene, 2- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00methyl phenol, 2- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00methyl phenol, 4- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00methyl phenol, 4- 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00naphthalene 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00phenol 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00propane 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00propanol, 2- (isopropyl alcohol) 3.11E-02 3.31E-02 0.00E+00 0.00E+00 1.98E-02 2.69E-04 0.00E+00styrene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00tetrachloroethene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00toluene 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00trichloroethane, 1,1,1- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00trimethylbenzene, 1,2,4- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00vinyl chloride 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00xylene, m- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00xylene, o- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00xylene, p- 3.03E-02 3.36E-04 0.00E+00 0.00E+00 1.90E-02 2.73E-06 0.00E+00

VI-3



Scrubber emissionsPolychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 1.52E-02 1.62E-02 1.70E-02 4.28E-01 9.68E-03 1.32E-04 1.06E-021,2,3,7,8-PCDD 6.81E-03 7.24E-03 2.60E-02 6.55E-01 4.33E-03 5.88E-05 1.63E-021,2,3,4,7,8-HxCDD 1.85E-03 1.97E-03 3.13E-02 7.89E-01 1.18E-03 1.60E-05 1.96E-021,2,3,6,7,8-HxCDD 8.99E-04 9.56E-04 3.24E-02 8.15E-01 5.71E-04 7.76E-06 2.02E-021,2,3,7,8,9-HxCDD 4.76E-04 5.06E-04 3.28E-02 8.26E-01 3.02E-04 4.11E-06 2.05E-021,2,3,4,6,7,8-HpCDD 5.04E-04 5.36E-04 3.28E-02 8.25E-01 3.20E-04 4.35E-06 2.05E-02OCDD 5.11E-05 3.16E-04 3.33E-02 8.38E-01 3.22E-05 2.35E-06 2.08E-022,3,7,8-TCDF 2.06E-02 2.19E-02 1.12E-02 2.82E-01 1.31E-02 1.78E-04 7.01E-031,2,3,7,8-PCDF 1.13E-02 1.20E-02 2.12E-02 5.34E-01 7.19E-03 9.77E-05 1.32E-022,3,4,7,8-PCDF 8.18E-03 8.70E-03 2.46E-02 6.18E-01 5.20E-03 7.06E-05 1.53E-021,2,3,4,7,8-HxCDF 1.51E-03 1.61E-03 3.17E-02 7.98E-01 9.60E-04 1.30E-05 1.98E-021,2,3,6,7,8-HxCDF 1.60E-03 1.70E-03 3.16E-02 7.96E-01 1.02E-03 1.38E-05 1.97E-022,3,4,6,7,8-HxCDF 1.70E-03 1.81E-03 3.15E-02 7.93E-01 1.08E-03 1.47E-05 1.97E-021,2,3,7,8,9-HxCDF 1.79E-03 1.90E-03 3.14E-02 7.91E-01 1.14E-03 1.55E-05 1.96E-021,2,3,4,6,7,8-HpCDF 1.08E-03 1.15E-03 3.22E-02 8.10E-01 6.85E-04 9.32E-06 2.01E-021,2,3,4,7,8,9-HpCDF 6.25E-04 6.65E-04 3.27E-02 8.22E-01 3.97E-04 5.40E-06 2.04E-02OCDF 5.19E-05 5.52E-05 3.33E-02 8.38E-01 3.30E-05 4.48E-07 2.08E-02

PCB Aroclor 1248 0.030887 3.28E-02 2.33E-04 5.87E-03 1.96E-02 2.67E-04 1.46E-04

VI-4

normalLong-term average

24-hour maximum

1-hour maximum

24-hour maximum

1-hour maximum

Stack emissionsMetalsArsenic 2.15E-07 2.93E-05 3.64E-04 2.93E-05 3.64E-04Beryllium 2.68E-08 2.46E-06 3.06E-05 2.46E-06 3.06E-05Cadmium 6.75E-07 1.91E-04 1.95E-03 1.91E-04 1.95E-03Chromium (total) 1.63E-06 2.44E-04 3.04E-03 2.44E-04 3.04E-03Chromium (hexavalent) 3.26E-08 4.88E-06 6.07E-05 1.22E-05 1.52E-04Copper 5.37E-06 6.34E-04 7.89E-03 6.34E-04 7.89E-03Lead 1.80E-05 5.88E-03 5.98E-02 5.88E-03 5.98E-02Mercuric chloride (particle) 3.18E-07 6.66E-06 5.28E-05 6.66E-06 5.28E-05Mercuric chloride (vapor) 1.98E-06 4.27E-05 3.39E-04 4.27E-05 3.39E-04Mercury 2.86E-07 3.68E-05 3.74E-04 3.68E-05 3.74E-04Methyl mercury 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Nickel 2.17E-06 3.78E-04 4.71E-03 3.78E-04 4.71E-03Selenium 3.13E-07 3.52E-05 4.38E-04 3.52E-05 4.38E-04Silver 1.11E-07 1.20E-05 1.50E-04 1.20E-05 1.50E-04Tin 6.00E-06 5.65E-04 7.03E-03 5.65E-04 7.03E-03Vanadium 1.83E-07 1.85E-05 2.31E-04 1.85E-05 2.31E-04Zinc 4.14E-05 6.67E-03 8.30E-02 6.67E-03 8.30E-02

Hydrogen chloride

Organic compoundsacetone 3.59E-04 1.65E-02 1.46E-01 1.65E-02 1.46E-01benzene 2.39E-04 3.19E-02 2.53E-01 3.19E-02 2.53E-01benzoic acid 2.30E-05 1.37E-03 1.21E-02 1.37E-03 1.21E-02benzyl alcohol 2.73E-06 1.53E-04 1.35E-03 1.53E-04 1.35E-03bis(2-ethylhexyl)phthalate 2.20E-05 2.76E-03 2.44E-02 2.76E-03 2.44E-02bromomethane 1.62E-05 1.96E-03 1.55E-02 1.96E-03 1.55E-02butanol, n- 3.31E-05 2.40E-03 2.12E-02 9.24E-02 8.16E-01butanone, 2- methyl ethyl ketone 2.29E-05 1.16E-03 1.02E-02 1.16E-03 1.02E-02carbon disulfide 3.96E-05 2.52E-03 1.99E-02 2.52E-03 1.99E-02chloroform 4.53E-06 3.04E-04 2.41E-03 3.04E-04 2.41E-03chloromethane 3.87E-05 5.67E-03 4.49E-02 5.67E-03 4.49E-02cyclohexane 4.50E-11 2.03E-09 1.61E-08 7.83E-08 6.20E-07di-n-butylphthalate 6.98E-07 3.21E-05 2.83E-04 3.21E-05 2.83E-04dichlorobenzene, 1,2- 3.56E-11 1.77E-09 1.41E-08 6.84E-08 5.42E-07dichlorobenzene, 1,3- 3.56E-11 1.77E-09 1.41E-08 6.84E-08 5.42E-07dichlorobenzene, 1,4- 7.49E-11 3.55E-09 2.81E-08 1.37E-07 1.08E-06diethyl phthalate 7.23E-07 3.52E-05 3.11E-04 3.52E-05 3.11E-04ethanol 3.24E-08 1.42E-06 1.26E-05 5.48E-05 4.84E-04ethylbenzene 7.06E-11 4.04E-09 3.20E-08 1.56E-07 1.23E-06freon 11 (trichlorofluoromethane) 7.06E-11 4.04E-09 3.20E-08 1.56E-07 1.23E-06freon 12 (dichlorodifluoromethane) 7.83E-11 4.66E-09 3.69E-08 1.80E-07 1.42E-06heptane 7.03E-11 4.97E-09 3.94E-08 1.91E-07 1.52E-06hexane 7.66E-11 4.35E-09 3.45E-08 1.68E-07 1.33E-06

Concentrations in air (ug/m3)upset conditions

startupupset conditions

normal

VI-5


24-hour maximum

1-hour maximum

24-hour maximum

1-hour maximum



normal

methane 7.21E-07 4.06E-05 3.21E-04 1.56E-03 1.24E-02Stack emissionsmethanol 4.71E-06 3.01E-04 2.66E-03 1.16E-02 1.02E-01methylene chloride 9.34E-05 5.28E-03 4.18E-02 5.28E-03 4.18E-02methylnaphthalene, 2- 1.81E-06 9.73E-05 8.59E-04 9.73E-05 8.59E-04methyl phenol, 2- 4.82E-06 5.61E-04 4.95E-03 5.61E-04 4.95E-03methyl phenol, 3- 1.76E-06 1.40E-04 1.24E-03 1.40E-04 1.24E-03methyl phenol, 4- 1.76E-06 1.40E-04 1.24E-03 1.40E-04 1.24E-03naphthalene 2.74E-06 2.14E-04 1.89E-03 2.14E-04 1.89E-03phenol 2.80E-05 3.72E-03 3.28E-02 3.72E-03 3.28E-02propane 1.61E-06 2.34E-04 1.85E-03 9.01E-03 7.14E-02propanol, 2- (isopropyl alcohol) 4.52E-10 2.18E-08 1.92E-07 8.38E-07 7.40E-06styrene 1.07E-05 6.75E-04 5.35E-03 6.75E-04 5.35E-03tetrachloroethene 1.19E-05 7.36E-04 5.84E-03 7.36E-04 5.84E-03toluene 1.03E-04 5.03E-03 3.99E-02 5.03E-03 3.99E-02trichloroethane, 1,1,1- 7.15E-11 3.42E-09 2.71E-08 1.32E-07 1.04E-06trimethylbenzene, 1,2,4- 7.09E-11 3.73E-09 2.96E-08 1.44E-07 1.14E-06vinyl chloride 1.11E-05 7.98E-04 6.32E-03 7.98E-04 6.32E-03xylene, m- 4.53E-06 3.04E-04 2.41E-03 3.04E-04 2.41E-03xylene, o- 4.53E-06 3.04E-04 2.41E-03 3.04E-04 2.41E-03xylene, p- 4.53E-06 3.04E-04 2.41E-03 3.04E-04 2.41E-03

Polychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 5.51E-12 3.71E-10 3.28E-09 3.71E-10 3.28E-091,2,3,7,8-PCDD 1.38E-11 1.92E-09 1.69E-08 1.92E-09 1.69E-081,2,3,4,7,8-HxCDD 1.14E-11 2.28E-09 2.01E-08 2.28E-09 2.01E-081,2,3,6,7,8-HxCDD 1.46E-11 2.42E-09 2.13E-08 2.42E-09 2.13E-081,2,3,7,8,9-HxCDD 2.05E-11 4.00E-09 3.53E-08 4.00E-09 3.53E-081,2,3,4,6,7,8-HpCDD 9.33E-11 1.70E-08 1.50E-07 1.70E-08 1.50E-07OCDD 1.38E-10 3.43E-08 2.72E-07 3.43E-08 2.72E-072,3,7,8-TCDF 4.08E-11 1.78E-09 1.57E-08 1.78E-09 1.57E-081,2,3,7,8-PCDF 3.47E-11 3.31E-09 2.92E-08 3.31E-09 2.92E-082,3,4,7,8-PCDF 3.99E-11 4.21E-09 3.72E-08 4.21E-09 3.72E-081,2,3,4,7,8-HxCDF 7.22E-11 1.15E-08 1.01E-07 1.15E-08 1.01E-071,2,3,6,7,8-HxCDF 3.69E-11 5.96E-09 5.26E-08 5.96E-09 5.26E-082,3,4,6,7,8-HxCDF 3.47E-11 5.38E-09 4.75E-08 5.38E-09 4.75E-081,2,3,7,8,9-HxCDF 3.39E-12 6.18E-10 5.46E-09 6.18E-10 5.46E-091,2,3,4,6,7,8-HpCDF 9.51E-11 1.49E-08 1.31E-07 1.49E-08 1.31E-071,2,3,4,7,8,9-HpCDF 1.14E-11 2.04E-09 1.80E-08 2.04E-09 1.80E-08OCDF 3.70E-11 8.03E-09 7.09E-08 8.03E-09 7.09E-08

PCB Aroclor 1248 1.27E-08 7.14E-07 6.30E-06 7.14E-07 6.30E-06

VI-6


24-hour maximum

1-hour maximum

24-hour maximum

1-hour maximum



normal

Scrubber emissionsMetalsArsenic 1.19E-08 3.68E-07 4.72E-05 3.68E-07 4.72E-05Beryllium 4.37E-10 2.38E-08 3.05E-06 2.38E-08 3.05E-06Cadmium 1.82E-08 6.78E-07 6.10E-05 6.78E-07 6.10E-05Chromium (total) 2.66E-08 2.36E-06 3.03E-04 2.36E-06 3.03E-04Chromium (hexavalent) 2.94E-10 7.45E-09 9.55E-07 7.45E-09 9.55E-07Copper 6.25E-07 1.15E-05 1.48E-03 1.15E-05 1.48E-03Lead 7.71E-07 2.58E-05 2.32E-03 2.58E-05 2.32E-03Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (particle) 3.19E-09 9.58E-08 8.61E-06 9.58E-08 8.61E-06Methyl mercury 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Nickel 3.82E-08 1.14E-06 1.46E-04 1.14E-06 1.46E-04Selenium 4.80E-10 1.88E-08 2.41E-06 1.88E-08 2.41E-06Silver 3.27E-09 8.26E-08 1.06E-05 8.26E-08 1.06E-05Tin 2.57E-07 2.48E-06 3.17E-04 2.48E-06 3.17E-04Vanadium 1.15E-08 4.74E-07 6.07E-05 4.74E-07 6.07E-05Zinc 1.32E-06 4.75E-05 6.09E-03 4.75E-05 6.09E-03

Hydrogen chloride

Organic compoundsacetone 2.32E-03 4.32E-02 3.16E+00 4.32E-02 3.16E+00benzene 1.29E-04 2.61E-03 1.72E-01 2.61E-03 1.72E-01benzoic acid 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00benzyl alcohol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bis(2-ethylhexyl)phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bromomethane 7.84E-05 1.59E-03 1.05E-01 1.59E-03 1.05E-01butanol, n- 1.15E-01 3.65E+00 2.67E+02 3.65E+00 2.67E+02butanone, 2- methyl ethyl ketone 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00carbon disulfide 2.55E-04 5.12E-03 3.37E-01 5.12E-03 3.37E-01chloroform 9.86E-05 2.00E-03 1.31E-01 2.00E-03 1.31E-01chloromethane 1.69E-04 3.39E-03 2.23E-01 3.39E-03 2.23E-01cyclohexane 1.74E-04 4.04E-03 2.66E-01 4.04E-03 2.66E-01di-n-butylphthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00dichlorobenzene, 1,2- 1.21E-04 2.46E-03 1.62E-01 2.46E-03 1.62E-01dichlorobenzene, 1,3- 1.21E-04 2.46E-03 1.62E-01 2.46E-03 1.62E-01dichlorobenzene, 1,4- 2.57E-04 5.41E-03 3.56E-01 5.41E-03 3.56E-01diethyl phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00ethanol 1.21E-01 2.09E+00 1.53E+02 2.09E+00 1.53E+02ethylbenzene 2.51E-04 5.07E-03 3.34E-01 5.07E-03 3.34E-01freon 11 (trichlorofluoromethane) 2.32E-04 4.79E-03 3.15E-01 4.79E-03 3.15E-01freon 12 (dichlorodifluoromethane) 2.63E-04 5.25E-03 3.46E-01 5.25E-03 3.46E-01heptane 2.55E-04 4.91E-03 3.23E-01 4.91E-03 3.23E-01hexane 2.59E-04 4.82E-03 3.17E-01 4.82E-03 3.17E-01

VI-7


24-hour maximum

1-hour maximum

24-hour maximum

1-hour maximum



normal

methane 2.50E-03 6.16E-02 4.06E+00 6.16E-02 4.06E+00Scrubber emissionsmethanol 1.63E-02 4.57E-01 3.35E+01 4.57E-01 3.35E+01methylene chloride 2.37E-04 5.55E-03 3.65E-01 5.55E-03 3.65E-01methylnaphthalene, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00naphthalene 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00phenol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00propane 5.59E-03 3.55E-01 2.34E+01 3.55E-01 2.34E+01propanol, 2- (isopropyl alcohol) 1.73E-03 3.19E-02 2.34E+00 3.19E-02 2.34E+00styrene 2.73E-04 5.72E-03 3.76E-01 5.72E-03 3.76E-01tetrachloroethene 2.82E-04 5.84E-03 3.84E-01 5.84E-03 3.84E-01toluene 1.01E-03 1.98E-02 1.30E+00 1.98E-02 1.30E+00trichloroethane, 1,1,1- 2.34E-04 4.80E-03 3.16E-01 4.80E-03 3.16E-01trimethylbenzene, 1,2,4- 2.53E-04 4.93E-03 3.25E-01 4.93E-03 3.25E-01vinyl chloride 5.16E-05 1.05E-03 6.88E-02 1.05E-03 6.88E-02xylene, m- 3.55E-04 8.01E-03 5.27E-01 8.01E-03 5.27E-01xylene, o- 2.32E-04 4.91E-03 3.23E-01 4.91E-03 3.23E-01xylene, p- 3.55E-04 8.01E-03 5.27E-01 8.01E-03 5.27E-01


PCB Aroclor 1248 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

VI-8

tilled soil untilled soil

Stack emissions cancernon-

cancer cancer non-cancer cancernon-

cancerMetalsArsenic 1.09E-03 1.30E-03 1.29E-03 1.30E-03 3.28E-05 3.31E-05Beryllium 4.48E-04 8.52E-04 2.68E-03 3.19E-03 6.44E-05 7.57E-05Cadmium 2.00E-03 2.77E-03 2.87E-03 2.92E-03 6.79E-05 6.91E-05Chromium (total) 3.01E-02 6.02E-02 6.02E-01 1.20E+00 1.33E-02 2.46E-02Chromium (hexavalent) 1.41E-04 1.62E-04 1.61E-04 1.62E-04 4.10E-06 4.12E-06Copper 9.83E-02 1.96E-01 1.69E+00 3.13E+00 3.77E-02 6.52E-02Lead 1.10E-01 2.14E-01 9.23E-01 1.22E+00 2.03E-02 2.61E-02Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 1.60E-03 3.20E-03 3.14E-02 6.22E-02 1.60E-03 2.95E-03Mercuric chloride (particle) 1.69E-03 3.39E-03 3.33E-02 6.59E-02 6.87E-04 1.27E-03Methyl mercury 6.67E-05 1.33E-04 1.13E-03 2.06E-03 4.03E-05 6.91E-05Nickel 1.68E-02 2.27E-02 2.31E-02 2.34E-02 5.85E-04 5.93E-04Selenium 5.94E-04 6.28E-04 6.26E-04 6.28E-04 1.59E-05 1.60E-05Silver 1.37E-04 1.41E-04 1.41E-04 1.41E-04 3.59E-06 3.60E-06Tin 8.94E-02 1.61E-01 3.02E-01 3.26E-01 7.46E-03 8.04E-03Vanadium 3.19E-03 6.21E-03 2.84E-02 3.84E-02 6.66E-04 8.73E-04Zinc 3.68E-01 5.22E-01 5.48E-01 5.59E-01 1.39E-02 1.41E-02

Hydrogen chloride 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Organic compoundsacetone 5.21E-06 5.21E-06 3.02E-07 3.02E-07 5.79E-08 5.79E-08benzene 6.95E-07 6.95E-07 3.52E-08 3.52E-08 2.16E-08 2.16E-08benzoic acid 8.23E-07 8.23E-07 2.18E-06 2.18E-06 4.19E-07 4.19E-07benzyl alcohol 1.86E-06 1.86E-06 1.38E-06 1.38E-06 2.66E-07 2.66E-07bis(2-ethylhexyl)phthalate 1.00E-05 1.00E-05 1.98E-04 1.98E-04 3.80E-05 3.81E-05bromomethane 9.50E-09 9.50E-09 4.76E-10 4.76E-10 2.92E-10 2.92E-10butanol, n- 3.32E-06 3.33E-06 1.46E-06 1.46E-06 2.81E-07 2.81E-07butanone, 2- methyl ethyl keto 7.34E-07 7.34E-07 5.22E-08 5.22E-08 1.00E-08 1.00E-08carbon disulfide 4.41E-08 4.41E-08 2.21E-09 2.21E-09 1.36E-09 1.36E-09chloroform 3.24E-08 3.24E-08 1.65E-09 1.65E-09 1.01E-09 1.01E-09chloromethane 6.93E-10 6.93E-10 3.47E-11 3.47E-11 2.13E-11 2.13E-11cyclohexane 4.56E-14 4.56E-14 2.28E-15 2.28E-15 1.40E-15 1.40E-15di-n-butylphthalate 3.10E-07 3.10E-07 6.12E-06 6.12E-06 1.17E-06 1.17E-06dichlorobenzene, 1,2- 3.87E-12 3.87E-12 2.23E-13 2.23E-13 1.37E-13 1.37E-13dichlorobenzene, 1,3- 2.80E-12 2.80E-12 1.53E-13 1.53E-13 9.39E-14 9.39E-14dichlorobenzene, 1,4- 9.75E-12 9.76E-12 5.70E-13 5.70E-13 3.50E-13 3.50E-13diethyl phthalate 5.74E-07 5.74E-07 1.66E-06 1.66E-06 3.18E-07 3.18E-07ethanol 5.29E-10 5.29E-10 1.85E-10 1.85E-10 3.56E-11 3.56E-11ethylbenzene 1.00E-12 1.00E-12 6.62E-14 6.62E-14 4.06E-14 4.06E-14freon 11 (trichlorofluoromethan 4.64E-14 4.64E-14 2.32E-15 2.32E-15 1.42E-15 1.42E-15freon 12 (dichlorodifluorometh 7.68E-16 7.68E-16 3.84E-17 3.84E-17 2.36E-17 2.36E-17heptane 6.99E-14 6.99E-14 3.50E-15 3.50E-15 2.15E-15 2.15E-15hexane 1.55E-14 1.55E-14 7.78E-16 7.78E-16 4.77E-16 4.77E-16

untilled soil

Goosefare watershed average

Concentrations in soil (mg/kg)

VI-9



methane 8.86E-13 8.86E-13 4.43E-14 4.43E-14 2.72E-14 2.72E-14methanol 2.68E-09 2.68E-09 1.35E-10 1.35E-10 2.59E-11 2.59E-11Stack emissionsmethylene chloride 1.72E-07 1.72E-07 8.74E-09 8.74E-09 5.36E-09 5.36E-09methylnaphthalene, 2- 1.91E-05 1.95E-05 1.06E-06 1.06E-06 2.03E-07 2.03E-07methyl phenol, 2- 2.09E-06 2.09E-06 5.28E-06 5.28E-06 1.01E-06 1.01E-06methyl phenol, 4- 2.27E-07 2.27E-07 1.35E-06 1.35E-06 2.59E-07 2.59E-07methyl phenol, 4- 2.31E-08 2.31E-08 3.82E-07 3.82E-07 7.34E-08 7.34E-08naphthalene 2.19E-06 2.19E-06 7.60E-07 7.60E-07 1.46E-07 1.46E-07phenol 4.60E-06 4.60E-06 1.57E-05 1.57E-05 3.02E-06 3.02E-06propane 4.22E-11 4.22E-11 2.11E-12 2.11E-12 1.30E-12 1.30E-12propanol, 2- (isopropyl alcohol 3.90E-11 3.90E-11 2.99E-12 2.99E-12 5.75E-13 5.75E-13styrene 3.34E-07 3.34E-07 2.08E-08 2.08E-08 1.28E-08 1.28E-08tetrachloroethene 3.74E-08 3.74E-08 1.88E-09 1.88E-09 1.15E-09 1.15E-09toluene 7.94E-07 7.94E-07 4.24E-08 4.24E-08 2.60E-08 2.60E-08trichloroethane, 1,1,1- 2.58E-13 2.58E-13 1.30E-14 1.30E-14 7.97E-15 7.97E-15trimethylbenzene, 1,2,4- 3.01E-12 3.02E-12 2.03E-13 2.03E-13 1.25E-13 1.25E-13vinyl chloride 7.12E-11 7.12E-11 3.56E-12 3.56E-12 2.18E-12 2.18E-12xylene, m- 1.06E-07 1.06E-07 6.21E-09 6.21E-09 3.81E-09 3.81E-09xylene, o- 9.49E-08 9.50E-08 5.46E-09 5.46E-09 3.35E-09 3.35E-09xylene, p- 1.02E-07 1.02E-07 5.93E-09 5.93E-09 3.64E-09 3.64E-09

Polychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 2.03E-09 2.37E-09 3.93E-08 4.56E-08 1.08E-09 1.22E-091,2,3,7,8-PCDD 1.26E-08 1.47E-08 2.47E-07 2.87E-07 5.23E-09 5.93E-091,2,3,4,7,8-HxCDD 1.59E-08 1.85E-08 3.17E-07 3.69E-07 6.50E-09 7.39E-091,2,3,6,7,8-HxCDD 2.20E-08 2.57E-08 4.37E-07 5.09E-07 8.97E-09 1.02E-081,2,3,7,8,9-HxCDD 3.18E-08 3.71E-08 6.32E-07 7.37E-07 1.30E-08 1.47E-081,2,3,4,6,7,8-HpCDD 1.45E-07 1.69E-07 2.89E-06 3.38E-06 5.93E-08 6.75E-08OCDD 2.21E-07 2.58E-07 4.42E-06 5.15E-06 9.05E-08 1.03E-072,3,7,8-TCDF 7.13E-09 8.32E-09 1.37E-07 1.59E-07 6.28E-09 7.10E-091,2,3,7,8-PCDF 2.01E-08 2.35E-08 3.96E-07 4.60E-07 9.12E-09 1.03E-082,3,4,7,8-PCDF 3.19E-08 3.72E-08 6.29E-07 7.33E-07 1.35E-08 1.54E-081,2,3,4,7,8-HxCDF 1.03E-07 1.21E-07 2.05E-06 2.39E-06 4.22E-08 4.79E-081,2,3,6,7,8-HxCDF 5.25E-08 6.13E-08 1.04E-06 1.22E-06 2.14E-08 2.44E-082,3,4,6,7,8-HxCDF 4.90E-08 5.72E-08 9.72E-07 1.13E-06 2.00E-08 2.27E-081,2,3,7,8,9-HxCDF 4.75E-09 5.54E-09 9.43E-08 1.10E-07 1.94E-09 2.20E-091,2,3,4,6,7,8-HpCDF 1.41E-07 1.65E-07 2.81E-06 3.27E-06 5.76E-08 6.55E-081,2,3,4,7,8,9-HpCDF 1.76E-08 2.05E-08 3.50E-07 4.08E-07 7.18E-09 8.16E-09OCDF 5.96E-08 6.95E-08 1.19E-06 1.39E-06 2.44E-08 2.78E-08

PCB Aroclor 1248 1.24E-08 1.24E-08 1.10E-07 1.10E-07 2.11E-08 2.11E-08

VI-10



Scrubber emissionsMetalsArsenic 6.01E-05 7.17E-05 7.12E-05 7.18E-05 1.81E-06 1.82E-06Beryllium 7.30E-06 1.39E-05 4.37E-05 5.20E-05 1.05E-06 1.23E-06Cadmium 5.38E-05 7.47E-05 7.72E-05 7.85E-05 1.83E-06 1.86E-06Chromium (total) 4.91E-04 9.82E-04 9.81E-03 1.96E-02 2.16E-04 4.02E-04Chromium (hexavalent) 1.27E-06 1.46E-06 1.45E-06 1.46E-06 3.69E-08 3.72E-08Copper 1.15E-02 2.28E-02 1.97E-01 3.64E-01 4.39E-03 7.60E-03Lead 4.74E-03 9.19E-03 3.96E-02 5.22E-02 8.73E-04 1.12E-03Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (particle) 2.04E-05 4.08E-05 4.00E-04 7.93E-04 8.28E-06 1.53E-05Methyl mercury 4.13E-07 8.23E-07 6.97E-06 1.28E-05 1.46E-07 2.50E-07Nickel 2.96E-04 3.99E-04 4.07E-04 4.13E-04 1.03E-05 1.04E-05Selenium 9.12E-07 9.65E-07 9.62E-07 9.65E-07 2.45E-08 2.45E-08Silver 4.02E-06 4.16E-06 4.15E-06 4.16E-06 1.06E-07 1.06E-07Tin 3.84E-03 6.90E-03 1.30E-02 1.40E-02 3.20E-04 3.45E-04Vanadium 2.00E-04 3.90E-04 1.78E-03 2.41E-03 4.18E-05 5.49E-05Zinc 1.17E-02 1.66E-02 1.75E-02 1.78E-02 4.41E-04 4.50E-04

Hydrogen chloride 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Organic compoundsacetone 3.36E-05 3.36E-05 1.95E-06 1.95E-06 3.74E-07 3.74E-07benzene 3.75E-07 3.75E-07 1.89E-08 1.89E-08 1.16E-08 1.16E-08benzoic acid 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00benzyl alcohol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bis(2-ethylhexyl)phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bromomethane 4.59E-08 4.59E-08 2.30E-09 2.30E-09 1.41E-09 1.41E-09butanol, n- 1.15E-02 1.15E-02 5.07E-03 5.07E-03 9.75E-04 9.75E-04butanone, 2- methyl ethyl keto 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00carbon disulfide 2.84E-07 2.84E-07 1.42E-08 1.42E-08 8.74E-09 8.74E-09chloroform 7.07E-07 7.07E-07 3.60E-08 3.60E-08 2.21E-08 2.21E-08chloromethane 3.03E-09 3.03E-09 1.51E-10 1.51E-10 9.29E-11 9.29E-11cyclohexane 1.77E-07 1.77E-07 8.84E-09 8.84E-09 5.42E-09 5.42E-09di-n-butylphthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00dichlorobenzene, 1,2- 1.32E-05 1.32E-05 7.60E-07 7.60E-07 4.67E-07 4.67E-07dichlorobenzene, 1,3- 9.56E-06 9.56E-06 5.22E-07 5.22E-07 3.20E-07 3.20E-07dichlorobenzene, 1,4- 3.35E-05 3.35E-05 1.96E-06 1.96E-06 1.20E-06 1.20E-06diethyl phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00ethanol 1.98E-03 1.98E-03 6.93E-04 6.93E-04 1.33E-04 1.33E-04ethylbenzene 3.57E-06 3.57E-06 2.35E-07 2.35E-07 1.44E-07 1.44E-07freon 11 (trichlorofluoromethan 1.53E-07 1.53E-07 7.64E-09 7.64E-09 4.69E-09 4.69E-09freon 12 (dichlorodifluorometh 2.58E-09 2.58E-09 1.29E-10 1.29E-10 7.92E-11 7.92E-11heptane 2.53E-07 2.53E-07 1.27E-08 1.27E-08 7.77E-09 7.77E-09hexane 5.26E-08 5.26E-08 2.63E-09 2.63E-09 1.62E-09 1.62E-09methane 3.07E-09 3.07E-09 1.54E-10 1.54E-10 9.42E-11 9.42E-11methanol 9.28E-06 9.28E-06 4.67E-07 4.67E-07 8.96E-08 8.96E-08

VI-11



methylene chloride 4.35E-07 4.35E-07 2.22E-08 2.22E-08 1.36E-08 1.36E-08methylnaphthalene, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Scrubber emissionsmethyl phenol, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00naphthalene 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00phenol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00propane 1.46E-07 1.46E-07 7.32E-09 7.32E-09 4.49E-09 4.49E-09propanol, 2- (isopropyl alcohol 1.49E-04 1.49E-04 1.14E-05 1.14E-05 2.20E-06 2.20E-06styrene 8.52E-06 8.53E-06 5.31E-07 5.31E-07 3.26E-07 3.26E-07tetrachloroethene 8.87E-07 8.87E-07 4.45E-08 4.45E-08 2.73E-08 2.73E-08toluene 7.77E-06 7.77E-06 4.14E-07 4.14E-07 2.54E-07 2.54E-07trichloroethane, 1,1,1- 8.47E-07 8.47E-07 4.26E-08 4.26E-08 2.61E-08 2.61E-08trimethylbenzene, 1,2,4- 1.07E-05 1.07E-05 7.25E-07 7.25E-07 4.45E-07 4.45E-07vinyl chloride 3.31E-10 3.31E-10 1.65E-11 1.65E-11 1.01E-11 1.01E-11xylene, m- 8.33E-06 8.33E-06 4.87E-07 4.87E-07 2.99E-07 2.99E-07xylene, o- 4.86E-06 4.87E-06 2.80E-07 2.80E-07 1.72E-07 1.72E-07xylene, p- 8.01E-06 8.01E-06 4.66E-07 4.66E-07 2.86E-07 2.86E-07

Polychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 1.76E-11 2.05E-11 3.40E-10 3.94E-10 9.32E-12 1.06E-111,2,3,7,8-PCDD 2.22E-10 2.59E-10 4.36E-09 5.08E-09 9.23E-11 1.05E-101,2,3,4,7,8-HxCDD 8.38E-11 9.78E-11 1.67E-09 1.95E-09 3.43E-11 3.90E-111,2,3,6,7,8-HxCDD 1.28E-10 1.50E-10 2.55E-09 2.97E-09 5.23E-11 5.94E-111,2,3,7,8,9-HxCDD 1.30E-10 1.52E-10 2.59E-09 3.01E-09 5.31E-11 6.03E-111,2,3,4,6,7,8-HpCDD 7.76E-10 9.05E-10 1.55E-08 1.81E-08 3.18E-10 3.61E-10OCDD 1.50E-09 1.75E-09 2.99E-08 3.49E-08 6.13E-10 6.97E-102,3,7,8-TCDF 4.92E-11 5.75E-11 9.50E-10 1.10E-09 4.34E-11 4.91E-111,2,3,7,8-PCDF 2.02E-10 2.35E-10 3.97E-09 4.61E-09 9.14E-11 1.04E-102,3,4,7,8-PCDF 2.75E-10 3.21E-10 5.43E-09 6.33E-09 1.17E-10 1.33E-101,2,3,4,7,8-HxCDF 3.76E-10 4.39E-10 7.45E-09 8.68E-09 1.53E-10 1.74E-101,2,3,6,7,8-HxCDF 4.57E-10 5.33E-10 9.08E-09 1.06E-08 1.87E-10 2.12E-102,3,4,6,7,8-HxCDF 3.63E-10 4.23E-10 7.20E-09 8.40E-09 1.48E-10 1.68E-101,2,3,7,8,9-HxCDF 9.22E-11 1.08E-10 1.83E-09 2.13E-09 3.76E-11 4.28E-111,2,3,4,6,7,8-HpCDF 9.45E-10 1.10E-09 1.88E-08 2.19E-08 3.86E-10 4.39E-101,2,3,4,7,8,9-HpCDF 1.25E-10 1.45E-10 2.48E-09 2.89E-09 5.09E-11 5.78E-11OCDF 3.72E-10 4.34E-10 7.43E-09 8.67E-09 1.52E-10 1.73E-10

PCB Aroclor 1248 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

VI-12

Concentrations in vegetation (mg/kg)cancer

above ground produce

forage silage root vegetables grains

Stack emissionsMetalsArsenic 1.42E-04 1.55E-03 4.83E-04 8.72E-06 4.36E-06Beryllium 1.80E-05 1.92E-04 5.98E-05 6.72E-07 6.72E-07Cadmium 3.99E-04 2.39E-03 1.22E-03 1.28E-04 1.24E-04Chromium (total) 1.17E-03 1.16E-02 3.59E-03 1.36E-04 1.36E-04Chromium (hexavalent) 2.11E-05 2.29E-04 6.83E-05 6.32E-07 6.32E-07Copper 2.79E-02 6.22E-02 3.56E-02 2.46E-02 2.46E-02Lead 5.48E-03 4.94E-02 1.81E-02 9.94E-04 9.94E-04Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 2.53E-05 2.14E-06 1.07E-06 5.76E-05 0.00E+00Mercuric chloride (particle) 7.02E-05 5.10E-04 1.50E-04 6.10E-05 0.00E+00Methyl mercury 1.54E-05 1.44E-04 4.27E-05 6.61E-06 0.00E+00Nickel 1.52E-03 1.57E-02 5.02E-03 1.35E-04 1.01E-04Selenium 2.07E-04 2.20E-03 6.54E-04 1.31E-05 1.19E-06Silver 8.86E-05 8.34E-04 2.84E-04 1.37E-05 1.37E-05Tin 4.30E-03 4.47E-02 1.50E-02 5.37E-04 5.37E-04Vanadium 1.24E-04 1.29E-03 3.86E-04 9.57E-06 9.57E-06Zinc 5.24E-02 3.81E-01 1.77E-01 1.62E-02 1.99E-02

Hydrogen chloride 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Organic compoundsacetone 2.71E-04 2.71E-04 2.71E-04 3.54E-03 2.71E-04benzene 1.56E-06 1.56E-06 1.56E-06 1.76E-05 1.56E-06benzoic acid 2.93E-06 2.93E-06 2.77E-06 1.91E-03 2.61E-06benzyl alcohol 1.66E-05 1.66E-05 1.66E-05 1.44E-04 1.66E-05bis(2-ethylhexyl)phthalate 6.45E-07 3.14E-05 1.59E-05 3.28E-08 3.35E-07bromomethane 8.50E-08 8.50E-08 8.50E-08 9.60E-08 8.50E-08butanol, n- 4.27E-05 4.27E-05 4.27E-05 5.03E-05 4.27E-05butanone, 2- methyl ethyl keto 1.96E-05 1.96E-05 1.96E-05 2.09E-04 1.96E-05carbon disulfide 1.19E-07 1.19E-07 1.19E-07 1.24E-06 1.19E-07chloroform 9.37E-08 9.37E-08 9.37E-08 8.38E-07 9.37E-08chloromethane 8.04E-09 8.04E-09 8.04E-09 8.62E-08 8.04E-09cyclohexane 1.82E-14 1.82E-14 1.82E-14 9.54E-14 1.81E-14di-n-butylphthalate 5.96E-08 2.55E-06 1.25E-06 1.03E-08 2.24E-08dichlorobenzene, 1,2- 1.53E-10 1.53E-10 1.53E-10 1.13E-10 1.53E-10dichlorobenzene, 1,3- 9.92E-13 9.92E-13 9.91E-13 4.47E-11 9.90E-13dichlorobenzene, 1,4- 4.03E-12 4.03E-12 4.03E-12 1.66E-10 4.03E-12diethyl phthalate 9.35E-08 3.33E-06 1.69E-06 4.28E-06 6.08E-08ethanol 3.13E-08 3.13E-08 3.13E-08 5.55E-08 3.13E-08ethylbenzene 6.10E-13 6.10E-13 6.10E-13 1.69E-11 6.09E-13freon 11 (trichlorofluoromethan 6.17E-14 6.17E-14 6.17E-14 9.34E-13 6.17E-14freon 12 (dichlorodifluorometh 1.68E-15 1.68E-15 1.68E-15 1.91E-14 1.68E-15heptane 5.49E-15 5.64E-15 5.56E-15 1.35E-15 5.49E-15hexane 8.43E-15 8.43E-15 6.41E-15 3.16E-14 4.38E-15

VI-13




methane 7.65E-13 7.65E-13 7.64E-13 2.07E-12 7.63E-13Stack emissionsmethanol 2.67E-07 2.67E-07 2.67E-07 4.31E-06 2.67E-07methylene chloride 1.25E-06 1.25E-06 1.25E-06 1.08E-05 1.25E-06methylnaphthalene, 2- 4.34E-06 4.34E-06 4.34E-06 1.24E-05 4.34E-06methyl phenol, 2- 6.00E-06 6.00E-06 5.99E-06 6.03E-05 5.97E-06methyl phenol, 4- 6.05E-07 6.05E-07 6.02E-07 6.26E-06 5.98E-07methyl phenol, 4- 7.96E-08 7.96E-08 7.36E-08 6.76E-07 6.76E-08naphthalene 9.52E-07 9.52E-07 9.52E-07 1.43E-05 9.51E-07phenol 2.50E-05 2.50E-05 2.50E-05 2.18E-04 2.49E-05propane 7.08E-11 7.08E-11 7.07E-11 1.21E-10 7.07E-11propanol, 2- (isopropyl alcohol 1.87E-09 1.87E-09 1.87E-09 3.09E-09 1.87E-09styrene 2.62E-07 2.62E-07 2.62E-07 5.89E-06 2.62E-07tetrachloroethene 4.90E-08 4.90E-08 4.90E-08 7.51E-07 4.90E-08toluene 8.82E-07 8.82E-07 8.81E-07 1.52E-05 8.81E-07trichloroethane, 1,1,1- 3.98E-13 3.98E-13 3.98E-13 5.49E-12 3.98E-13trimethylbenzene, 1,2,4- 9.35E-13 9.35E-13 9.33E-13 6.17E-12 9.31E-13vinyl chloride 6.00E-10 6.00E-10 6.00E-10 5.18E-09 6.00E-10xylene, m- 5.81E-08 5.81E-08 5.81E-08 1.77E-06 5.80E-08xylene, o- 5.71E-08 5.71E-08 5.71E-08 1.60E-06 5.71E-08xylene, p- 5.82E-08 5.82E-08 5.82E-08 1.71E-06 5.81E-08



VI-14




Scrubber emissionsMetalsArsenic 7.81E-06 8.51E-05 2.66E-05 4.81E-07 2.40E-07Beryllium 2.93E-07 3.13E-06 9.74E-07 1.10E-08 1.10E-08Cadmium 1.07E-05 6.45E-05 3.28E-05 3.44E-06 3.34E-06Chromium (total) 1.91E-05 1.90E-04 5.85E-05 2.21E-06 2.21E-06Chromium (hexavalent) 1.90E-07 2.07E-06 6.16E-07 5.70E-09 5.70E-09Copper 3.26E-03 7.24E-03 4.15E-03 2.86E-03 2.86E-03Lead 2.35E-04 2.12E-03 7.75E-04 4.27E-05 4.27E-05Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (particle) 8.04E-07 5.68E-06 1.67E-06 7.34E-07 0.00E+00Methyl mercury 1.56E-07 1.60E-06 4.72E-07 4.09E-08 0.00E+00Nickel 2.67E-05 2.77E-04 8.83E-05 2.37E-06 1.78E-06Selenium 3.19E-07 3.38E-06 1.00E-06 2.01E-08 1.82E-09Silver 2.61E-06 2.45E-05 8.36E-06 4.02E-07 4.02E-07Tin 1.84E-04 1.92E-03 6.46E-04 2.30E-05 2.30E-05Vanadium 7.79E-06 8.09E-05 2.42E-05 6.01E-07 6.01E-07Zinc 1.67E-03 1.22E-02 5.65E-03 5.16E-04 6.33E-04


Organic compoundsacetone 1.75E-03 1.75E-03 1.75E-03 2.29E-02 1.75E-03benzene 8.43E-07 8.43E-07 8.43E-07 9.46E-06 8.43E-07benzoic acid 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00benzyl alcohol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bis(2-ethylhexyl)phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bromomethane 4.11E-07 4.11E-07 4.11E-07 4.64E-07 4.11E-07butanol, n- 1.48E-01 1.48E-01 1.48E-01 1.74E-01 1.48E-01butanone, 2- methyl ethyl keto 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00carbon disulfide 7.68E-07 7.68E-07 7.68E-07 7.97E-06 7.68E-07chloroform 2.04E-06 2.04E-06 2.04E-06 1.83E-05 2.04E-06chloromethane 3.51E-08 3.51E-08 3.51E-08 3.76E-07 3.51E-08cyclohexane 7.05E-08 7.05E-08 7.04E-08 3.70E-07 7.03E-08di-n-butylphthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00dichlorobenzene, 1,2- 5.21E-04 5.21E-04 5.21E-04 3.87E-04 5.21E-04dichlorobenzene, 1,3- 3.38E-06 3.38E-06 3.38E-06 1.52E-04 3.37E-06dichlorobenzene, 1,4- 1.39E-05 1.39E-05 1.38E-05 5.71E-04 1.38E-05diethyl phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00ethanol 1.17E-01 1.17E-01 1.17E-01 2.07E-01 1.17E-01ethylbenzene 2.17E-06 2.17E-06 2.17E-06 6.00E-05 2.17E-06freon 11 (trichlorofluoromethan 2.03E-07 2.03E-07 2.03E-07 3.08E-06 2.03E-07freon 12 (dichlorodifluorometh 5.66E-09 5.66E-09 5.66E-09 6.41E-08 5.66E-09heptane 1.99E-08 2.04E-08 2.01E-08 4.89E-09 1.99E-08

VI-15




hexane 2.85E-08 2.85E-08 2.17E-08 1.07E-07 1.48E-08Scrubber emissionsmethane 2.65E-09 2.65E-09 2.65E-09 7.18E-09 2.64E-09methanol 9.25E-04 9.25E-04 9.25E-04 1.49E-02 9.25E-04methylene chloride 3.17E-06 3.17E-06 3.17E-06 2.73E-05 3.17E-06methylnaphthalene, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00naphthalene 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00phenol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00propane 2.45E-07 2.45E-07 2.45E-07 4.18E-07 2.45E-07propanol, 2- (isopropyl alcohol 7.14E-03 7.14E-03 7.14E-03 1.18E-02 7.14E-03styrene 6.70E-06 6.70E-06 6.69E-06 1.50E-04 6.69E-06tetrachloroethene 1.16E-06 1.16E-06 1.16E-06 1.78E-05 1.16E-06toluene 8.63E-06 8.63E-06 8.62E-06 1.49E-04 8.62E-06trichloroethane, 1,1,1- 1.30E-06 1.30E-06 1.30E-06 1.80E-05 1.30E-06trimethylbenzene, 1,2,4- 3.33E-06 3.33E-06 3.32E-06 2.20E-05 3.32E-06vinyl chloride 2.78E-09 2.78E-09 2.78E-09 2.41E-08 2.78E-09xylene, m- 4.56E-06 4.56E-06 4.56E-06 1.39E-04 4.56E-06xylene, o- 2.93E-06 2.93E-06 2.93E-06 8.21E-05 2.92E-06xylene, p- 4.57E-06 4.57E-06 4.57E-06 1.34E-04 4.56E-06



VI-16

Stack emissionsMetalsArsenicBerylliumCadmiumChromium (total)Chromium (hexavalent)CopperLeadMercury (elemental)Mercuric chloride (vapor)Mercuric chloride (particle)Methyl mercuryNickelSeleniumSilverTinVanadiumZinc

Hydrogen chloride

Organic compoundsacetonebenzenebenzoic acidbenzyl alcoholbis(2-ethylhexyl)phthalatebromomethanebutanol, n-butanone, 2- methyl ethyl ketocarbon disulfidechloroformchloromethanecyclohexanedi-n-butylphthalatedichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-diethyl phthalateethanolethylbenzenefreon 11 (trichlorofluoromethanfreon 12 (dichlorodifluoromethheptanehexane

non-cancerabove ground produce


1.43E-04 1.55E-03 4.90E-04 1.04E-05 5.20E-061.90E-05 1.96E-04 6.38E-05 1.28E-06 1.28E-064.96E-04 2.68E-03 1.50E-03 1.78E-04 1.72E-041.32E-03 1.19E-02 3.81E-03 2.71E-04 2.71E-042.12E-05 2.29E-04 6.84E-05 7.31E-07 7.31E-075.23E-02 8.65E-02 6.00E-02 4.90E-02 4.90E-026.89E-03 5.41E-02 2.27E-02 1.93E-03 1.93E-030.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+004.85E-05 2.14E-06 1.07E-06 1.15E-04 0.00E+009.48E-05 5.10E-04 1.50E-04 1.22E-04 0.00E+001.74E-05 1.44E-04 4.27E-05 1.32E-05 0.00E+001.57E-03 1.59E-02 5.20E-03 1.81E-04 1.36E-042.08E-04 2.20E-03 6.54E-04 1.38E-05 1.26E-068.93E-05 8.36E-04 2.86E-04 1.41E-05 1.41E-054.72E-03 4.68E-02 1.72E-02 9.65E-04 9.65E-041.33E-04 1.30E-03 3.95E-04 1.86E-05 1.86E-056.35E-02 4.20E-01 2.16E-01 2.30E-02 2.82E-02

0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

2.71E-04 2.71E-04 2.71E-04 3.54E-03 2.71E-041.56E-06 1.56E-06 1.56E-06 1.76E-05 1.56E-062.93E-06 2.93E-06 2.77E-06 1.91E-03 2.61E-061.67E-05 1.67E-05 1.67E-05 1.45E-04 1.67E-056.46E-07 3.14E-05 1.59E-05 3.28E-08 3.35E-078.50E-08 8.50E-08 8.50E-08 9.60E-08 8.50E-084.27E-05 4.27E-05 4.27E-05 5.03E-05 4.27E-051.96E-05 1.96E-05 1.96E-05 2.09E-04 1.96E-051.19E-07 1.19E-07 1.19E-07 1.24E-06 1.19E-079.37E-08 9.37E-08 9.37E-08 8.38E-07 9.37E-088.04E-09 8.04E-09 8.04E-09 8.62E-08 8.04E-091.82E-14 1.82E-14 1.82E-14 9.54E-14 1.81E-145.96E-08 2.55E-06 1.25E-06 1.03E-08 2.25E-081.53E-10 1.53E-10 1.53E-10 1.13E-10 1.53E-109.92E-13 9.92E-13 9.91E-13 4.47E-11 9.90E-134.04E-12 4.04E-12 4.03E-12 1.66E-10 4.03E-129.36E-08 3.33E-06 1.69E-06 4.29E-06 6.09E-083.13E-08 3.13E-08 3.13E-08 5.55E-08 3.13E-086.10E-13 6.10E-13 6.10E-13 1.69E-11 6.09E-136.17E-14 6.17E-14 6.17E-14 9.34E-13 6.17E-141.68E-15 1.68E-15 1.68E-15 1.91E-14 1.68E-155.49E-15 5.64E-15 5.56E-15 1.35E-15 5.49E-158.43E-15 8.43E-15 6.41E-15 3.16E-14 4.38E-15

Concentrations in vegetation (mg/kg)

VI-17

methaneStack emissionsmethanolmethylene chloridemethylnaphthalene, 2-methyl phenol, 2-methyl phenol, 4-methyl phenol, 4-naphthalenephenolpropanepropanol, 2- (isopropyl alcoholstyrenetetrachloroethenetoluenetrichloroethane, 1,1,1-trimethylbenzene, 1,2,4-vinyl chloridexylene, m-xylene, o-xylene, p-

Polychlorinated dibenzo(p)diox2,3,7,8-TCDD1,2,3,7,8-PCDD1,2,3,4,7,8-HxCDD1,2,3,6,7,8-HxCDD1,2,3,7,8,9-HxCDD1,2,3,4,6,7,8-HpCDDOCDD2,3,7,8-TCDF1,2,3,7,8-PCDF2,3,4,7,8-PCDF1,2,3,4,7,8-HxCDF1,2,3,6,7,8-HxCDF2,3,4,6,7,8-HxCDF1,2,3,7,8,9-HxCDF1,2,3,4,6,7,8-HpCDF1,2,3,4,7,8,9-HpCDFOCDF

PCB Aroclor 1248




7.65E-13 7.65E-13 7.64E-13 2.07E-12 7.63E-13

2.67E-07 2.67E-07 2.67E-07 4.31E-06 2.67E-071.25E-06 1.25E-06 1.25E-06 1.08E-05 1.25E-064.44E-06 4.44E-06 4.44E-06 1.27E-05 4.44E-066.01E-06 6.01E-06 5.99E-06 6.04E-05 5.98E-066.05E-07 6.05E-07 6.02E-07 6.26E-06 5.98E-077.96E-08 7.96E-08 7.36E-08 6.76E-07 6.76E-089.54E-07 9.54E-07 9.53E-07 1.43E-05 9.53E-072.50E-05 2.50E-05 2.50E-05 2.18E-04 2.49E-057.08E-11 7.08E-11 7.07E-11 1.21E-10 7.07E-111.87E-09 1.87E-09 1.87E-09 3.09E-09 1.87E-092.62E-07 2.62E-07 2.62E-07 5.89E-06 2.62E-074.90E-08 4.90E-08 4.90E-08 7.51E-07 4.90E-088.82E-07 8.82E-07 8.81E-07 1.52E-05 8.81E-073.98E-13 3.98E-13 3.98E-13 5.49E-12 3.98E-139.35E-13 9.35E-13 9.33E-13 6.17E-12 9.31E-136.00E-10 6.00E-10 6.00E-10 5.18E-09 6.00E-105.81E-08 5.81E-08 5.81E-08 1.77E-06 5.80E-085.71E-08 5.71E-08 5.71E-08 1.60E-06 5.71E-085.82E-08 5.82E-08 5.82E-08 1.71E-06 5.81E-08

2.79E-10 3.06E-09 9.28E-10 2.65E-11 1.33E-111.80E-09 1.94E-08 5.81E-09 1.64E-10 8.24E-112.20E-09 2.43E-08 7.18E-09 1.13E-10 2.26E-113.08E-09 3.37E-08 9.98E-09 2.07E-10 6.42E-114.45E-09 4.88E-08 1.44E-08 3.00E-10 9.29E-112.00E-08 2.22E-07 6.54E-08 8.29E-10 1.19E-103.07E-08 3.39E-07 1.00E-07 1.74E-09 4.10E-108.71E-10 9.85E-09 3.09E-09 9.87E-11 5.42E-112.82E-09 3.08E-08 9.25E-09 2.43E-10 1.08E-104.48E-09 4.89E-08 1.46E-08 3.59E-10 1.44E-101.45E-08 1.59E-07 4.70E-08 9.75E-10 3.02E-107.34E-09 8.05E-08 2.38E-08 4.95E-10 1.53E-106.85E-09 7.51E-08 2.22E-08 4.61E-10 1.43E-106.64E-10 7.28E-09 2.15E-09 4.47E-11 1.39E-111.95E-08 2.16E-07 6.38E-08 9.34E-10 1.68E-102.43E-09 2.69E-08 7.95E-09 1.16E-10 2.09E-118.18E-09 9.12E-08 2.69E-08 2.50E-10 2.27E-11

2.54E-10 4.45E-09 2.06E-09 1.76E-09 1.24E-10

VI-18

Scrubber emissionsMetalsArsenicBerylliumCadmiumChromium (total)Chromium (hexavalent)CopperLeadMercury (elemental)Mercuric chloride (vapor)Mercuric chloride (particle)Methyl mercuryNickelSeleniumSilverTinVanadiumZinc

Hydrogen chloride

Organic compoundsacetonebenzenebenzoic acidbenzyl alcoholbis(2-ethylhexyl)phthalatebromomethanebutanol, n-butanone, 2- methyl ethyl ketocarbon disulfidechloroformchloromethanecyclohexanedi-n-butylphthalatedichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-diethyl phthalateethanolethylbenzenefreon 11 (trichlorofluoromethanfreon 12 (dichlorodifluoromethheptane




7.88E-06 8.56E-05 2.70E-05 5.73E-07 2.87E-073.10E-07 3.20E-06 1.04E-06 2.08E-08 2.08E-081.34E-05 7.21E-05 4.04E-05 4.78E-06 4.63E-062.14E-05 1.93E-04 6.22E-05 4.42E-06 4.42E-061.91E-07 2.07E-06 6.17E-07 6.59E-09 6.59E-096.10E-03 1.01E-02 6.99E-03 5.71E-03 5.71E-032.96E-04 2.32E-03 9.75E-04 8.27E-05 8.27E-050.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+001.10E-06 5.68E-06 1.67E-06 1.47E-06 0.00E+001.68E-07 1.60E-06 4.72E-07 8.15E-08 0.00E+002.77E-05 2.80E-04 9.16E-05 3.19E-06 2.40E-063.20E-07 3.38E-06 1.01E-06 2.12E-08 1.93E-092.63E-06 2.46E-05 8.41E-06 4.16E-07 4.16E-072.03E-04 2.01E-03 7.37E-04 4.14E-05 4.14E-058.36E-06 8.15E-05 2.48E-05 1.17E-06 1.17E-062.02E-03 1.34E-02 6.88E-03 7.32E-04 8.99E-04

0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

1.75E-03 1.75E-03 1.75E-03 2.29E-02 1.75E-038.43E-07 8.43E-07 8.43E-07 9.46E-06 8.43E-070.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+004.11E-07 4.11E-07 4.11E-07 4.64E-07 4.11E-071.48E-01 1.48E-01 1.48E-01 1.74E-01 1.48E-010.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+007.68E-07 7.68E-07 7.68E-07 7.97E-06 7.68E-072.04E-06 2.04E-06 2.04E-06 1.83E-05 2.04E-063.51E-08 3.51E-08 3.51E-08 3.76E-07 3.51E-087.05E-08 7.05E-08 7.04E-08 3.70E-07 7.03E-080.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+005.22E-04 5.22E-04 5.22E-04 3.87E-04 5.22E-043.38E-06 3.38E-06 3.38E-06 1.52E-04 3.38E-061.39E-05 1.39E-05 1.39E-05 5.72E-04 1.38E-050.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+001.17E-01 1.17E-01 1.17E-01 2.07E-01 1.17E-012.17E-06 2.17E-06 2.17E-06 6.00E-05 2.17E-062.03E-07 2.03E-07 2.03E-07 3.08E-06 2.03E-075.66E-09 5.66E-09 5.66E-09 6.41E-08 5.66E-091.99E-08 2.04E-08 2.01E-08 4.89E-09 1.99E-08

VI-19

hexaneScrubber emissionsmethanemethanolmethylene chloridemethylnaphthalene, 2-methyl phenol, 2-methyl phenol, 4-methyl phenol, 4-naphthalenephenolpropanepropanol, 2- (isopropyl alcoholstyrenetetrachloroethenetoluenetrichloroethane, 1,1,1-trimethylbenzene, 1,2,4-vinyl chloridexylene, m-xylene, o-xylene, p-


PCB Aroclor 1248




2.85E-08 2.85E-08 2.17E-08 1.07E-07 1.48E-08

2.65E-09 2.65E-09 2.65E-09 7.18E-09 2.64E-099.25E-04 9.25E-04 9.25E-04 1.49E-02 9.25E-043.17E-06 3.17E-06 3.17E-06 2.73E-05 3.17E-060.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+002.45E-07 2.45E-07 2.45E-07 4.18E-07 2.45E-077.15E-03 7.15E-03 7.15E-03 1.18E-02 7.15E-036.70E-06 6.70E-06 6.70E-06 1.50E-04 6.69E-061.16E-06 1.16E-06 1.16E-06 1.78E-05 1.16E-068.63E-06 8.63E-06 8.62E-06 1.49E-04 8.62E-061.30E-06 1.30E-06 1.30E-06 1.80E-05 1.30E-063.33E-06 3.33E-06 3.32E-06 2.20E-05 3.32E-062.78E-09 2.78E-09 2.78E-09 2.41E-08 2.78E-094.56E-06 4.56E-06 4.56E-06 1.39E-04 4.56E-062.93E-06 2.93E-06 2.93E-06 8.22E-05 2.92E-064.57E-06 4.57E-06 4.57E-06 1.34E-04 4.56E-06


0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

VI-20

total water body

water column

dissolved phase

benthic sediments

Stack emissionsMetalsArsenic 1.55E-07 8.89E-08 1.55E-07 2.46E-06Beryllium 1.93E-08 1.22E-09 1.93E-08 6.65E-07Cadmium 3.14E-07 1.25E-07 3.14E-07 6.99E-06Chromium (total) 1.18E-06 2.64E-10 1.56E-07 4.31E-05Chromium (hexavalent) 2.35E-08 1.46E-08 2.35E-08 3.33E-07Copper 3.87E-06 2.13E-08 3.73E-06 1.41E-04Lead 8.37E-06 3.29E-07 8.33E-06 2.95E-04Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 6.79E-07 7.61E-10 4.43E-07 2.49E-05Mercuric chloride (particle) 1.33E-07 1.49E-10 8.70E-08 4.88E-06Methyl mercury 8.12E-07 1.49E-08 5.30E-07 2.97E-05Nickel 1.57E-06 6.69E-07 1.57E-06 3.31E-05Selenium 2.25E-07 1.82E-07 2.25E-07 1.66E-06Silver 8.03E-08 7.01E-08 8.03E-08 4.00E-07Tin 4.32E-06 5.54E-07 4.32E-06 1.38E-04Vanadium 1.32E-07 4.68E-09 1.31E-07 4.66E-06Zinc 2.98E-05 1.11E-05 2.98E-05 6.90E-04

Hydrogen chloride 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Organic compoundsacetone 1.19E-04 1.21E-04 1.19E-04 4.59E-06benzene 8.19E-05 7.72E-05 8.19E-05 2.03E-04benzoic acid 7.64E-06 7.72E-06 7.64E-06 1.70E-07benzyl alcohol 9.08E-07 9.08E-07 9.08E-07 3.71E-07bis(2-ethylhexyl)phthalate 7.32E-06 6.23E-08 7.01E-06 2.66E-04bromomethane 5.55E-06 5.55E-06 5.55E-06 2.27E-06butanol, n- 1.10E-05 1.11E-05 1.10E-05 2.78E-06butanone, 2- methyl ethyl keto 7.61E-06 7.67E-06 7.61E-06 7.20E-07carbon disulfide 1.35E-05 1.30E-05 1.35E-05 2.66E-05chloroform 1.55E-06 1.48E-06 1.55E-06 3.14E-06chloromethane 1.33E-05 1.33E-05 1.33E-05 3.19E-06cyclohexane 1.54E-11 8.88E-12 1.54E-11 2.42E-10di-n-butylphthalate 2.33E-07 6.88E-09 2.30E-07 8.30E-06dichlorobenzene, 1,2- 1.22E-11 8.68E-12 1.22E-11 1.32E-10dichlorobenzene, 1,3- 1.22E-11 6.54E-12 1.22E-11 2.10E-10dichlorobenzene, 1,4- 2.56E-11 1.54E-11 2.56E-11 3.79E-10diethyl phthalate 2.41E-07 2.23E-07 2.41E-07 7.32E-07ethanol 1.08E-08 1.09E-08 1.08E-08 3.48E-10ethylbenzene 2.41E-11 1.71E-11 2.41E-11 2.65E-10freon 11 (trichlorofluoromethan 2.41E-11 2.13E-11 2.41E-11 1.14E-10

bounding estimatesConcentrations in surface water (mg/L or mg/kg)

Saco river

VI-21

total water body

water column

dissolved phase

benthic sediments


Saco river

freon 12 (dichlorodifluorometh 2.68E-11 2.52E-11 2.68E-11 6.90E-11Stack emissionsheptane 2.40E-11 3.15E-12 2.40E-11 7.67E-10hexane 2.62E-11 1.21E-11 2.62E-11 5.24E-10methane 2.47E-07 1.97E-07 2.47E-07 1.90E-06methanol 1.57E-06 1.58E-06 1.57E-06 2.50E-08methylene chloride 3.19E-05 3.18E-05 3.19E-05 1.72E-05methylnaphthalene, 2- 6.01E-07 1.03E-07 6.00E-07 1.83E-05methyl phenol, 2- 1.60E-06 1.54E-06 1.60E-06 2.94E-06methyl phenol, 4- 5.85E-07 5.59E-07 5.85E-07 1.19E-06methyl phenol, 4- 5.85E-07 5.63E-07 5.85E-07 1.04E-06naphthalene 9.11E-07 3.46E-07 9.11E-07 2.08E-05phenol 9.32E-06 9.22E-06 9.32E-06 7.41E-06propane 5.52E-07 5.03E-07 5.52E-07 1.98E-06propanol, 2- (isopropyl alcohol 1.50E-10 1.52E-10 1.50E-10 6.46E-12styrene 3.66E-06 2.85E-06 3.66E-06 3.10E-05tetrachloroethene 4.07E-06 3.58E-06 4.07E-06 1.96E-05toluene 3.53E-05 3.00E-05 3.53E-05 2.05E-04trichloroethane, 1,1,1- 2.45E-11 2.21E-11 2.45E-11 9.68E-11trimethylbenzene, 1,2,4- 2.43E-11 1.19E-11 2.43E-11 4.58E-10vinyl chloride 3.80E-06 3.80E-06 3.80E-06 1.69E-06xylene, m- 1.55E-06 1.05E-06 1.55E-06 1.87E-05xylene, o- 1.55E-06 1.09E-06 1.55E-06 1.71E-05xylene, p- 1.55E-06 1.07E-06 1.55E-06 1.80E-05

Polychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 2.15E-12 1.51E-15 1.04E-12 7.86E-111,2,3,7,8-PCDD 5.92E-12 4.16E-15 2.85E-12 2.17E-101,2,3,4,7,8-HxCDD 5.17E-12 2.01E-15 3.20E-13 1.89E-101,2,3,6,7,8-HxCDD 6.72E-12 3.01E-15 1.25E-12 2.46E-101,2,3,7,8,9-HxCDD 9.46E-12 4.24E-15 1.76E-12 3.47E-101,2,3,4,6,7,8-HpCDD 4.31E-11 1.61E-14 1.08E-12 1.58E-09OCDD 6.40E-11 2.58E-14 6.06E-12 2.34E-092,3,7,8-TCDF 1.50E-11 1.21E-14 8.20E-12 5.51E-101,2,3,7,8-PCDF 1.41E-11 8.54E-15 5.61E-12 5.17E-102,3,4,7,8-PCDF 1.68E-11 9.14E-15 5.52E-12 6.16E-101,2,3,4,7,8-HxCDF 3.30E-11 1.48E-14 6.14E-12 1.21E-091,2,3,6,7,8-HxCDF 1.68E-11 7.53E-15 3.13E-12 6.16E-102,3,4,6,7,8-HxCDF 1.58E-11 7.07E-15 2.94E-12 5.79E-101,2,3,7,8,9-HxCDF 1.54E-12 6.90E-16 2.87E-13 5.65E-111,2,3,4,6,7,8-HpCDF 4.36E-11 1.67E-14 2.04E-12 1.60E-091,2,3,4,7,8,9-HpCDF 5.28E-12 2.02E-15 2.46E-13 1.94E-10OCDF 1.72E-11 6.32E-15 1.16E-13 6.31E-10

PCB Aroclor 1248 4.23E-09 3.38E-09 4.07E-09 3.45E-08

VI-22

total water body

water column

dissolved phase

benthic sediments


Saco river

Scrubber emissionsMetalsArsenic 8.55E-09 4.90E-09 8.55E-09 1.36E-07Beryllium 3.15E-10 1.98E-11 3.14E-10 1.08E-08Cadmium 8.46E-09 3.36E-09 8.45E-09 1.88E-07Chromium (total) 1.92E-08 4.30E-12 2.54E-09 7.02E-07Chromium (hexavalent) 2.12E-10 1.32E-10 2.12E-10 3.00E-09Copper 4.51E-07 2.49E-09 4.35E-07 1.64E-05Lead 3.59E-07 1.41E-08 3.57E-07 1.27E-05Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (particle) 1.48E-09 1.66E-12 9.69E-10 5.43E-08Methyl mercury 0.00E+00 0.00E+00 0.00E+00 0.00E+00Nickel 2.76E-08 1.18E-08 2.76E-08 5.84E-07Selenium 3.46E-10 2.80E-10 3.46E-10 2.55E-09Silver 2.36E-09 2.06E-09 2.36E-09 1.18E-08Tin 1.86E-07 2.38E-08 1.85E-07 5.94E-06Vanadium 8.27E-09 2.94E-10 8.23E-09 2.93E-07Zinc 9.50E-07 3.55E-07 9.50E-07 2.20E-05

Hydrogen chloride 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Organic compoundsacetone 7.72E-04 7.79E-04 7.72E-04 2.96E-05benzene 4.41E-05 4.16E-05 4.41E-05 1.09E-04benzoic acid 0.00E+00 0.00E+00 0.00E+00 0.00E+00benzyl alcohol 0.00E+00 0.00E+00 0.00E+00 0.00E+00bis(2-ethylhexyl)phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00bromomethane 2.68E-05 2.68E-05 2.68E-05 1.10E-05butanol, n- 3.82E-02 3.83E-02 3.82E-02 9.64E-03butanone, 2- methyl ethyl keto 0.00E+00 0.00E+00 0.00E+00 0.00E+00carbon disulfide 8.73E-05 8.35E-05 8.73E-05 1.72E-04chloroform 3.37E-05 3.22E-05 3.37E-05 6.83E-05chloromethane 5.79E-05 5.81E-05 5.79E-05 1.39E-05cyclohexane 5.96E-05 3.44E-05 5.96E-05 9.39E-04di-n-butylphthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00dichlorobenzene, 1,2- 4.15E-05 2.96E-05 4.15E-05 4.50E-04dichlorobenzene, 1,3- 4.15E-05 2.23E-05 4.15E-05 7.15E-04dichlorobenzene, 1,4- 8.80E-05 5.30E-05 8.80E-05 1.30E-03diethyl phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00ethanol 4.03E-02 4.07E-02 4.03E-02 1.30E-03ethylbenzene 8.58E-05 6.08E-05 8.58E-05 9.41E-04freon 11 (trichlorofluoromethan 7.95E-05 7.01E-05 7.95E-05 3.74E-04freon 12 (dichlorodifluorometh 9.01E-05 8.47E-05 9.01E-05 2.32E-04Scrubber emissions

VI-23

total water body

water column

dissolved phase

benthic sediments


Saco river

heptane 8.71E-05 1.14E-05 8.69E-05 2.78E-03hexane 8.87E-05 4.08E-05 8.87E-05 1.77E-03methane 8.54E-04 6.83E-04 8.54E-04 6.58E-03methanol 5.43E-03 5.48E-03 5.43E-03 8.68E-05methylene chloride 8.10E-05 8.07E-05 8.10E-05 4.35E-05methylnaphthalene, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00naphthalene 0.00E+00 0.00E+00 0.00E+00 0.00E+00phenol 0.00E+00 0.00E+00 0.00E+00 0.00E+00propane 1.91E-03 1.74E-03 1.91E-03 6.85E-03propanol, 2- (isopropyl alcohol 5.75E-04 5.81E-04 5.75E-04 2.47E-05styrene 9.35E-05 7.27E-05 9.35E-05 7.93E-04tetrachloroethene 9.66E-05 8.48E-05 9.66E-05 4.64E-04toluene 3.45E-04 2.94E-04 3.45E-04 2.00E-03trichloroethane, 1,1,1- 8.02E-05 7.24E-05 8.02E-05 3.17E-04trimethylbenzene, 1,2,4- 8.65E-05 4.24E-05 8.64E-05 1.63E-03vinyl chloride 1.77E-05 1.76E-05 1.77E-05 7.83E-06xylene, m- 1.22E-04 8.25E-05 1.22E-04 1.47E-03xylene, o- 7.93E-05 5.60E-05 7.93E-05 8.77E-04xylene, p- 1.22E-04 8.40E-05 1.22E-04 1.41E-03

Polychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 0.00E+00 0.00E+00 0.00E+00 0.00E+001,2,3,7,8-PCDD 1.86E-14 1.30E-17 8.95E-15 6.80E-131,2,3,4,7,8-HxCDD 1.05E-13 4.07E-17 6.48E-15 3.83E-121,2,3,6,7,8-HxCDD 2.73E-14 1.22E-17 5.09E-15 1.00E-121,2,3,7,8,9-HxCDD 3.92E-14 1.76E-17 7.31E-15 1.44E-121,2,3,4,6,7,8-HpCDD 3.87E-14 1.45E-17 9.69E-16 1.42E-12OCDD 2.31E-13 9.31E-17 2.19E-14 8.47E-122,3,7,8-TCDF 4.33E-13 3.48E-16 2.36E-13 1.59E-111,2,3,7,8-PCDF 1.04E-13 6.29E-17 4.13E-14 3.80E-122,3,4,7,8-PCDF 1.41E-13 7.69E-17 4.64E-14 5.18E-121,2,3,4,7,8-HxCDF 1.45E-13 6.50E-17 2.70E-14 5.32E-121,2,3,6,7,8-HxCDF 1.20E-13 5.36E-17 2.23E-14 4.39E-122,3,4,6,7,8-HxCDF 1.46E-13 6.55E-17 2.73E-14 5.36E-121,2,3,7,8,9-HxCDF 1.17E-13 5.24E-17 2.18E-14 4.29E-121,2,3,4,6,7,8-HpCDF 2.99E-14 1.15E-17 1.40E-15 1.10E-121,2,3,4,7,8,9-HpCDF 2.92E-13 1.12E-16 1.36E-14 1.07E-11OCDF 3.74E-14 1.37E-17 2.51E-16 1.37E-12

PCB Aroclor 1248 0.00E+00 0.00E+00 0.00E+00 0.00E+00

VI-24


Hydrogen chloride

Organic compoundsacetonebenzenebenzoic acidbenzyl alcoholbis(2-ethylhexyl)phthalatebromomethanebutanol, n-butanone, 2- methyl ethyl ketocarbon disulfidechloroformchloromethanecyclohexanedi-n-butylphthalatedichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-diethyl phthalateethanolethylbenzenefreon 11 (trichlorofluoromethan

total water body

water column

dissolved phase

benthic sediments

1.15E-06 6.60E-07 6.59E-07 1.83E-051.08E-06 6.82E-08 6.80E-08 3.73E-051.71E-06 6.79E-07 6.79E-07 3.80E-053.87E-04 8.68E-08 1.15E-08 1.42E-021.61E-07 1.00E-07 1.00E-07 2.28E-067.56E-04 4.17E-06 4.02E-06 2.76E-023.41E-04 1.34E-05 1.33E-05 1.20E-020.00E+00 0.00E+00 0.00E+00 0.00E+003.20E-05 3.58E-08 2.34E-08 1.17E-031.43E-05 1.61E-08 1.05E-08 5.25E-041.67E-06 3.07E-08 2.00E-08 6.01E-051.55E-05 6.61E-06 6.60E-06 3.27E-041.19E-06 9.64E-07 9.64E-07 8.78E-063.94E-07 3.44E-07 3.44E-07 1.96E-061.32E-04 1.70E-05 1.70E-05 4.24E-031.12E-05 3.97E-07 3.95E-07 3.95E-043.36E-04 1.25E-04 1.25E-04 7.76E-03

0.00E+00 0.00E+00 0.00E+00 0.00E+00

2.31E-07 2.33E-07 2.33E-07 8.87E-097.44E-09 7.02E-09 7.02E-09 1.84E-081.63E-06 1.64E-06 1.64E-06 3.62E-085.97E-07 5.97E-07 5.97E-07 2.44E-072.81E-06 2.38E-08 2.28E-08 1.02E-043.07E-10 3.07E-10 3.07E-10 1.26E-105.20E-07 5.22E-07 5.22E-07 1.31E-072.32E-08 2.34E-08 2.34E-08 2.20E-095.30E-10 5.07E-10 5.07E-10 1.04E-093.84E-10 3.66E-10 3.66E-10 7.77E-105.48E-11 5.50E-11 5.50E-11 1.32E-111.34E-16 7.75E-17 7.75E-17 2.12E-159.61E-08 2.84E-09 2.80E-09 3.42E-061.25E-14 8.88E-15 8.88E-15 1.35E-135.51E-15 2.95E-15 2.95E-15 9.48E-142.36E-14 1.42E-14 1.42E-14 3.50E-131.92E-07 1.78E-07 1.78E-07 5.84E-071.24E-10 1.26E-10 1.26E-10 4.01E-123.82E-15 2.71E-15 2.70E-15 4.19E-143.23E-16 2.84E-16 2.84E-16 1.52E-15

cancerConcentrations in surface water (mg/L or mg/kg)

Goosefare Brook

VI-25

freon 12 (dichlorodifluoromethStack emissionsheptanehexanemethanemethanolmethylene chloridemethylnaphthalene, 2-methyl phenol, 2-methyl phenol, 4-methyl phenol, 4-naphthalenephenolpropanepropanol, 2- (isopropyl alcoholstyrenetetrachloroethenetoluenetrichloroethane, 1,1,1-trimethylbenzene, 1,2,4-vinyl chloridexylene, m-xylene, o-xylene, p-


PCB Aroclor 1248

total water body

water column

dissolved phase

benthic sediments


Goosefare Brook

6.84E-17 6.43E-17 6.43E-17 1.76E-16

4.37E-16 5.72E-17 5.70E-17 1.39E-141.35E-16 6.20E-17 6.20E-17 2.69E-153.66E-13 2.92E-13 2.92E-13 2.81E-126.20E-10 6.26E-10 6.26E-10 9.91E-124.82E-09 4.81E-09 4.81E-09 2.59E-097.93E-09 1.35E-09 1.35E-09 2.42E-078.66E-07 8.32E-07 8.32E-07 1.59E-061.91E-07 1.83E-07 1.83E-07 3.90E-076.77E-08 6.52E-08 6.52E-08 1.20E-077.03E-09 2.67E-09 2.67E-09 1.61E-074.70E-06 4.65E-06 4.65E-06 3.74E-061.24E-12 1.14E-12 1.14E-12 4.46E-121.71E-12 1.73E-12 1.73E-12 7.35E-141.50E-09 1.16E-09 1.16E-09 1.27E-082.41E-10 2.11E-10 2.11E-10 1.16E-094.35E-09 3.70E-09 3.70E-09 2.52E-081.84E-15 1.66E-15 1.66E-15 7.26E-156.79E-15 3.33E-15 3.33E-15 1.28E-139.59E-12 9.58E-12 9.58E-12 4.25E-123.25E-10 2.21E-10 2.21E-10 3.93E-093.12E-10 2.20E-10 2.20E-10 3.45E-093.22E-10 2.22E-10 2.22E-10 3.74E-09

8.35E-11 5.87E-14 2.83E-14 3.06E-094.27E-10 3.00E-13 1.45E-13 1.56E-085.51E-10 2.14E-13 1.33E-14 2.02E-087.52E-10 3.37E-13 6.28E-14 2.76E-081.09E-09 4.87E-13 9.08E-14 3.99E-085.05E-09 1.89E-12 4.73E-14 1.85E-077.68E-09 3.10E-12 2.93E-13 2.82E-074.70E-10 3.78E-13 2.06E-13 1.72E-087.39E-10 4.48E-13 1.78E-13 2.71E-081.11E-09 6.07E-13 1.99E-13 4.08E-083.53E-09 1.58E-12 2.95E-13 1.29E-071.80E-09 8.06E-13 1.50E-13 6.60E-081.67E-09 7.50E-13 1.40E-13 6.14E-081.62E-10 7.27E-14 1.36E-14 5.95E-094.88E-09 1.87E-12 8.73E-14 1.79E-076.09E-10 2.33E-13 1.09E-14 2.23E-082.08E-09 7.63E-13 5.12E-15 7.62E-08

1.34E-11 1.07E-11 1.03E-11 1.09E-10

VI-26


Hydrogen chloride

Organic compoundsacetonebenzenebenzoic acidbenzyl alcoholbis(2-ethylhexyl)phthalatebromomethanebutanol, n-butanone, 2- methyl ethyl ketocarbon disulfidechloroformchloromethanecyclohexanedi-n-butylphthalatedichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-diethyl phthalateethanolethylbenzenefreon 11 (trichlorofluoromethanfreon 12 (dichlorodifluoromethScrubber emissions

total water body

water column

dissolved phase

benthic sediments


Goosefare Brook

6.34E-08 3.63E-08 3.63E-08 1.01E-061.77E-08 1.11E-09 1.11E-09 6.07E-074.60E-08 1.83E-08 1.83E-08 1.02E-066.31E-06 1.42E-09 1.88E-10 2.31E-041.45E-09 9.03E-10 9.03E-10 2.06E-088.81E-05 4.86E-07 4.69E-07 3.21E-031.46E-05 5.75E-07 5.72E-07 5.15E-040.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+001.72E-07 1.93E-10 1.26E-10 6.29E-066.16E-09 1.13E-10 7.40E-11 2.22E-072.72E-07 1.16E-07 1.16E-07 5.76E-061.83E-09 1.48E-09 1.48E-09 1.35E-081.16E-08 1.01E-08 1.01E-08 5.78E-085.68E-06 7.28E-07 7.27E-07 1.82E-047.01E-07 2.49E-08 2.48E-08 2.48E-051.07E-05 3.99E-06 3.99E-06 2.47E-040.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+001.78E-06 1.80E-06 1.80E-06 6.84E-088.81E-09 8.30E-09 8.30E-09 2.18E-080.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+003.43E-09 3.43E-09 3.43E-09 1.40E-092.74E-03 2.75E-03 2.75E-03 6.92E-040.00E+00 0.00E+00 0.00E+00 0.00E+008.20E-09 7.84E-09 7.84E-09 1.61E-081.93E-08 1.85E-08 1.85E-08 3.92E-085.34E-10 5.37E-10 5.37E-10 1.29E-101.23E-09 7.10E-10 7.09E-10 1.94E-080.00E+00 0.00E+00 0.00E+00 0.00E+009.21E-08 6.56E-08 6.56E-08 9.98E-074.06E-08 2.18E-08 2.18E-08 6.99E-071.75E-07 1.06E-07 1.06E-07 2.60E-060.00E+00 0.00E+00 0.00E+00 0.00E+005.32E-04 5.37E-04 5.37E-04 1.71E-052.86E-08 2.03E-08 2.03E-08 3.14E-072.41E-09 2.13E-09 2.13E-09 1.14E-085.08E-10 4.77E-10 4.77E-10 1.31E-09

VI-27

heptanehexanemethanemethanolmethylene chloridemethylnaphthalene, 2-methyl phenol, 2-methyl phenol, 4-methyl phenol, 4-naphthalenephenolpropanepropanol, 2- (isopropyl alcoholstyrenetetrachloroethenetoluenetrichloroethane, 1,1,1-trimethylbenzene, 1,2,4-vinyl chloridexylene, m-xylene, o-xylene, p-


PCB Aroclor 1248

total water body

water column

dissolved phase

benthic sediments


Goosefare Brook

3.62E-09 4.74E-10 4.73E-10 1.15E-071.08E-09 4.97E-10 4.97E-10 2.16E-085.06E-09 4.04E-09 4.04E-09 3.89E-082.85E-06 2.88E-06 2.88E-06 4.55E-082.84E-08 2.83E-08 2.83E-08 1.53E-080.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+001.23E-08 1.12E-08 1.12E-08 4.40E-088.58E-06 8.67E-06 8.67E-06 3.68E-078.13E-08 6.32E-08 6.32E-08 6.89E-071.19E-08 1.05E-08 1.05E-08 5.73E-089.14E-08 7.78E-08 7.78E-08 5.30E-071.34E-08 1.21E-08 1.21E-08 5.29E-085.20E-08 2.55E-08 2.55E-08 9.82E-071.06E-10 1.06E-10 1.06E-10 4.71E-115.38E-08 3.65E-08 3.65E-08 6.49E-073.36E-08 2.37E-08 2.37E-08 3.71E-075.33E-08 3.68E-08 3.68E-08 6.19E-07


0.00E+00 0.00E+00 0.00E+00 0.00E+00

VI-28


Hydrogen chloride

Organic compoundsacetonebenzenebenzoic acidbenzyl alcoholbis(2-ethylhexyl)phthalatebromomethanebutanol, n-butanone, 2- methyl ethyl ketocarbon disulfidechloroformchloromethanecyclohexanedi-n-butylphthalatedichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-diethyl phthalateethanolethylbenzenefreon 11 (trichlorofluoromethan

total water body

water column

dissolved phase

benthic sediments

1.16E-06 6.65E-07 6.65E-07 1.84E-051.27E-06 7.99E-08 7.97E-08 4.37E-051.74E-06 6.90E-07 6.90E-07 3.87E-056.94E-04 1.56E-07 2.06E-08 2.54E-021.62E-07 1.01E-07 1.01E-07 2.30E-061.28E-03 7.08E-06 6.83E-06 4.68E-024.36E-04 1.71E-05 1.71E-05 1.54E-020.00E+00 0.00E+00 0.00E+00 0.00E+005.81E-05 6.52E-08 4.26E-08 2.13E-032.56E-05 2.87E-08 1.87E-08 9.37E-042.99E-06 5.49E-08 3.59E-08 1.08E-041.57E-05 6.70E-06 6.70E-06 3.32E-041.20E-06 9.67E-07 9.67E-07 8.80E-063.94E-07 3.45E-07 3.45E-07 1.97E-061.42E-04 1.83E-05 1.82E-05 4.56E-031.46E-05 5.18E-07 5.16E-07 5.16E-043.42E-04 1.28E-04 1.27E-04 7.90E-03

0.00E+00 0.00E+00 0.00E+00 0.00E+00

2.31E-07 2.33E-07 2.33E-07 8.87E-097.44E-09 7.02E-09 7.02E-09 1.84E-081.63E-06 1.64E-06 1.64E-06 3.62E-085.97E-07 5.97E-07 5.97E-07 2.44E-072.81E-06 2.39E-08 2.28E-08 1.02E-043.07E-10 3.07E-10 3.07E-10 1.26E-105.20E-07 5.22E-07 5.22E-07 1.31E-072.32E-08 2.34E-08 2.34E-08 2.20E-095.30E-10 5.07E-10 5.07E-10 1.04E-093.84E-10 3.66E-10 3.66E-10 7.77E-105.48E-11 5.50E-11 5.50E-11 1.32E-111.34E-16 7.75E-17 7.75E-17 2.12E-159.62E-08 2.84E-09 2.80E-09 3.42E-061.25E-14 8.88E-15 8.88E-15 1.35E-135.51E-15 2.95E-15 2.95E-15 9.48E-142.36E-14 1.42E-14 1.42E-14 3.50E-131.92E-07 1.78E-07 1.78E-07 5.84E-071.24E-10 1.26E-10 1.26E-10 4.01E-123.82E-15 2.71E-15 2.70E-15 4.19E-143.23E-16 2.84E-16 2.84E-16 1.52E-15

Concentrations in surface water (mg/L or mg/kg)

Goosefare Brooknon-cancer

VI-29

freon 12 (dichlorodifluoromethStack emissionsheptanehexanemethanemethanolmethylene chloridemethylnaphthalene, 2-methyl phenol, 2-methyl phenol, 4-methyl phenol, 4-naphthalenephenolpropanepropanol, 2- (isopropyl alcoholstyrenetetrachloroethenetoluenetrichloroethane, 1,1,1-trimethylbenzene, 1,2,4-vinyl chloridexylene, m-xylene, o-xylene, p-


PCB Aroclor 1248

total water body

water column

dissolved phase

benthic sediments



6.84E-17 6.43E-17 6.43E-17 1.76E-16

4.37E-16 5.72E-17 5.70E-17 1.39E-141.35E-16 6.20E-17 6.20E-17 2.69E-153.66E-13 2.92E-13 2.92E-13 2.81E-126.20E-10 6.26E-10 6.26E-10 9.91E-124.82E-09 4.81E-09 4.81E-09 2.59E-097.93E-09 1.35E-09 1.35E-09 2.42E-078.66E-07 8.32E-07 8.32E-07 1.59E-061.91E-07 1.83E-07 1.83E-07 3.90E-076.77E-08 6.52E-08 6.52E-08 1.20E-077.03E-09 2.67E-09 2.67E-09 1.61E-074.70E-06 4.65E-06 4.65E-06 3.74E-061.24E-12 1.14E-12 1.14E-12 4.46E-121.71E-12 1.73E-12 1.73E-12 7.35E-141.50E-09 1.16E-09 1.16E-09 1.27E-082.41E-10 2.11E-10 2.11E-10 1.16E-094.35E-09 3.70E-09 3.70E-09 2.52E-081.84E-15 1.66E-15 1.66E-15 7.26E-156.79E-15 3.33E-15 3.33E-15 1.28E-139.59E-12 9.58E-12 9.58E-12 4.25E-123.25E-10 2.21E-10 2.21E-10 3.93E-093.12E-10 2.20E-10 2.20E-10 3.45E-093.22E-10 2.22E-10 2.22E-10 3.74E-09


1.34E-11 1.07E-11 1.07E-11 1.09E-10

VI-30


Hydrogen chloride

Organic compoundsacetonebenzenebenzoic acidbenzyl alcoholbis(2-ethylhexyl)phthalatebromomethanebutanol, n-butanone, 2- methyl ethyl ketocarbon disulfidechloroformchloromethanecyclohexanedi-n-butylphthalatedichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-diethyl phthalateethanolethylbenzenefreon 11 (trichlorofluoromethanfreon 12 (dichlorodifluoromethScrubber emissions

total water body

water column

dissolved phase

benthic sediments



6.39E-08 3.66E-08 3.66E-08 1.02E-062.07E-08 1.30E-09 1.30E-09 7.12E-074.68E-08 1.86E-08 1.86E-08 1.04E-061.13E-05 2.54E-09 3.37E-10 4.15E-041.46E-09 9.09E-10 9.09E-10 2.07E-081.50E-04 8.25E-07 7.96E-07 5.45E-031.87E-05 7.35E-07 7.32E-07 6.59E-040.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+003.07E-07 3.44E-10 2.25E-10 1.12E-051.09E-08 2.01E-10 1.31E-10 3.94E-072.76E-07 1.18E-07 1.18E-07 5.84E-061.84E-09 1.49E-09 1.49E-09 1.35E-081.16E-08 1.01E-08 1.01E-08 5.79E-086.11E-06 7.83E-07 7.82E-07 1.96E-049.15E-07 3.26E-08 3.24E-08 3.24E-051.09E-05 4.06E-06 4.06E-06 2.52E-040.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+001.78E-06 1.80E-06 1.80E-06 6.84E-088.81E-09 8.30E-09 8.30E-09 2.18E-080.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+003.43E-09 3.43E-09 3.43E-09 1.40E-092.74E-03 2.75E-03 2.75E-03 6.92E-040.00E+00 0.00E+00 0.00E+00 0.00E+008.20E-09 7.84E-09 7.84E-09 1.61E-081.93E-08 1.85E-08 1.85E-08 3.92E-085.34E-10 5.37E-10 5.37E-10 1.29E-101.23E-09 7.10E-10 7.09E-10 1.94E-080.00E+00 0.00E+00 0.00E+00 0.00E+009.21E-08 6.56E-08 6.56E-08 9.98E-074.06E-08 2.18E-08 2.18E-08 6.99E-071.75E-07 1.06E-07 1.06E-07 2.60E-060.00E+00 0.00E+00 0.00E+00 0.00E+005.32E-04 5.37E-04 5.37E-04 1.71E-052.86E-08 2.03E-08 2.03E-08 3.14E-072.41E-09 2.13E-09 2.13E-09 1.14E-085.08E-10 4.77E-10 4.77E-10 1.31E-09

VI-31

heptanehexanemethanemethanolmethylene chloridemethylnaphthalene, 2-methyl phenol, 2-methyl phenol, 4-methyl phenol, 4-naphthalenephenolpropanepropanol, 2- (isopropyl alcoholstyrenetetrachloroethenetoluenetrichloroethane, 1,1,1-trimethylbenzene, 1,2,4-vinyl chloridexylene, m-xylene, o-xylene, p-


PCB Aroclor 1248

total water body

water column

dissolved phase

benthic sediments



3.62E-09 4.74E-10 4.73E-10 1.15E-071.08E-09 4.97E-10 4.97E-10 2.16E-085.06E-09 4.04E-09 4.04E-09 3.89E-082.85E-06 2.88E-06 2.88E-06 4.55E-082.84E-08 2.83E-08 2.83E-08 1.53E-080.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+001.23E-08 1.12E-08 1.12E-08 4.40E-088.58E-06 8.67E-06 8.67E-06 3.68E-078.13E-08 6.32E-08 6.32E-08 6.89E-071.19E-08 1.05E-08 1.05E-08 5.73E-089.14E-08 7.78E-08 7.78E-08 5.30E-071.34E-08 1.21E-08 1.21E-08 5.29E-085.20E-08 2.55E-08 2.55E-08 9.82E-071.06E-10 1.06E-10 1.06E-10 4.71E-115.38E-08 3.65E-08 3.65E-08 6.49E-073.36E-08 2.37E-08 2.37E-08 3.71E-075.33E-08 3.68E-08 3.68E-08 6.19E-07


0.00E+00 0.00E+00 0.00E+00 0.00E+00

VI-32

Saco

cancer non-cancer cancernon-

cancerbounding estimate

Stack emissionsMetalsArsenic 1.32E-05 1.33E-05 1.01E-05 1.02E-05 3.41E-07Beryllium 4.22E-06 4.96E-06 3.22E-06 3.78E-06 1.31E-07Cadmium 1.70E-04 1.72E-04 1.35E-04 1.37E-04 8.63E-06Chromium (total) 2.19E-06 4.83E-06 1.67E-06 3.74E-06 3.26E-06Chromium (hexavalent) 3.00E-07 3.02E-07 2.30E-07 2.32E-07 7.76E-09Copper 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Lead 1.07E-04 1.36E-04 8.44E-05 1.07E-04 7.33E-06Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (particle) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Methyl mercury 6.77E-03 6.86E-03 5.27E-03 5.40E-03 4.79E-03Nickel 5.15E-04 5.23E-04 3.95E-04 4.01E-04 1.34E-05Selenium 1.24E-04 1.25E-04 9.54E-05 9.57E-05 3.20E-06Silver 7.02E-05 7.03E-05 5.38E-05 5.39E-05 1.80E-06Tin 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Vanadium 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Zinc 2.58E-01 2.63E-01 1.98E-01 2.01E-01 6.76E-03


Organic compoundsacetone 2.40E-08 2.40E-08 1.86E-08 1.86E-08 1.35E-06benzene 1.74E-07 1.74E-07 8.08E-08 8.08E-08 2.23E-04benzoic acid 2.60E-05 2.60E-05 1.88E-05 1.88E-05 1.33E-05benzyl alcohol 2.41E-06 2.41E-06 1.68E-06 1.68E-06 4.04E-07bis(2-ethylhexyl)phthalate 6.90E-04 6.90E-04 5.83E-04 5.83E-04 2.33E-02bromomethane 1.24E-09 1.24E-09 5.88E-10 5.88E-10 2.46E-06butanol, n- 1.31E-06 1.31E-06 6.70E-07 6.70E-07 3.05E-06butanone, 2- methyl ethyl keto 2.25E-08 2.25E-08 1.37E-08 1.37E-08 8.04E-07carbon disulfide 9.88E-09 9.88E-09 4.71E-09 4.71E-09 2.90E-05chloroform 1.32E-09 1.32E-09 5.63E-10 5.63E-10 6.11E-07chloromethane 1.57E-10 1.57E-10 1.40E-10 1.40E-10 4.17E-06cyclohexane 1.88E-14 1.88E-14 1.48E-14 1.48E-14 4.10E-10di-n-butylphthalate 1.56E-05 1.56E-05 1.46E-05 1.46E-05 1.41E-04dichlorobenzene, 1,2- 2.18E-12 2.18E-12 9.31E-13 9.31E-13 3.28E-10dichlorobenzene, 1,3- 8.39E-13 8.39E-13 3.64E-13 3.64E-13 3.81E-10dichlorobenzene, 1,4- 3.28E-12 3.28E-12 1.41E-12 1.41E-12 6.51E-10diethyl phthalate 4.36E-04 4.36E-04 3.06E-04 3.06E-04 6.49E-05ethanol 4.23E-11 4.23E-11 2.92E-11 2.92E-11 4.00E-10ethylbenzene 3.76E-13 3.76E-13 1.71E-13 1.71E-13 3.69E-10freon 11 (trichlorofluoromethan 1.40E-14 1.40E-14 8.27E-15 8.27E-15 1.31E-10freon 12 (dichlorodifluorometh 1.66E-15 1.66E-15 2.16E-15 2.16E-15 7.60E-11heptane 5.62E-13 5.62E-13 7.01E-13 7.01E-13 2.60E-08hexane 2.36E-14 2.36E-14 2.87E-14 2.87E-14 1.10E-09

WilcoxGoosefareConcentrations in fish (mg/kg)

VI-33

Saco




methane 2.56E-11 2.56E-11 3.10E-11 3.10E-11 2.38E-06methanol 1.06E-10 1.06E-10 1.10E-10 1.10E-10 2.93E-08Stack emissionsmethylene chloride 2.55E-08 2.55E-08 1.16E-08 1.16E-08 1.86E-05methylnaphthalene, 2- 6.83E-07 6.83E-07 3.56E-07 3.56E-07 3.34E-05methyl phenol, 2- 1.51E-05 1.51E-05 9.77E-06 9.77E-06 3.20E-06methyl phenol, 4- 3.69E-06 3.69E-06 2.24E-06 2.24E-06 1.30E-06methyl phenol, 4- 1.14E-06 1.14E-06 7.94E-07 7.94E-07 1.13E-06naphthalene 5.74E-07 5.74E-07 2.80E-07 2.80E-07 2.15E-05phenol 3.63E-05 3.63E-05 2.43E-05 2.43E-05 8.01E-06propane 4.16E-11 4.16E-11 4.64E-11 4.64E-11 2.22E-06propanol, 2- (isopropyl alcohol 7.70E-13 7.70E-13 4.82E-13 4.82E-13 7.37E-12styrene 1.15E-07 1.15E-07 5.09E-08 5.09E-08 3.99E-05tetrachloroethene 1.07E-08 1.07E-08 5.13E-09 5.13E-09 2.27E-05toluene 2.32E-07 2.32E-07 1.06E-07 1.06E-07 2.43E-04trichloroethane, 1,1,1- 6.76E-14 6.76E-14 3.06E-14 3.06E-14 1.10E-10trimethylbenzene, 1,2,4- 1.13E-12 1.13E-12 5.05E-13 5.05E-13 9.02E-10vinyl chloride 1.73E-11 1.73E-11 2.00E-11 2.00E-11 7.57E-07xylene, m- 3.53E-08 3.53E-08 1.59E-08 1.59E-08 2.72E-05xylene, o- 3.11E-08 3.11E-08 1.40E-08 1.40E-08 2.40E-05xylene, p- 3.36E-08 3.36E-08 1.51E-08 1.51E-08 2.57E-05



VI-34

Saco




Scrubber emissionsMetalsArsenic 7.27E-07 7.32E-07 5.57E-07 5.62E-07 1.88E-08Beryllium 6.88E-08 8.09E-08 5.25E-08 6.17E-08 2.14E-09Cadmium 4.57E-06 4.64E-06 3.63E-06 3.69E-06 2.32E-07Chromium (total) 3.57E-08 7.87E-08 2.72E-08 6.10E-08 5.31E-08Chromium (hexavalent) 2.71E-09 2.73E-09 2.08E-09 2.09E-09 6.99E-11Copper 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Lead 4.58E-06 5.85E-06 3.62E-06 4.60E-06 3.14E-07Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (particle) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Methyl mercury 2.51E-05 4.47E-05 1.85E-05 3.22E-05 0.00E+00Nickel 9.07E-06 9.20E-06 6.95E-06 7.05E-06 2.36E-07Selenium 1.91E-07 1.92E-07 1.47E-07 1.47E-07 4.91E-09Silver 2.06E-06 2.07E-06 1.58E-06 1.59E-06 5.30E-08Tin 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Vanadium 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Zinc 8.22E-03 8.37E-03 6.30E-03 6.41E-03 2.15E-04


Organic compoundsacetone 1.85E-07 1.85E-07 2.02E-07 2.02E-07 8.74E-06benzene 2.06E-07 2.06E-07 1.65E-07 1.65E-07 1.20E-04benzoic acid 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00benzyl alcohol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bis(2-ethylhexyl)phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bromomethane 1.38E-08 1.38E-08 1.14E-08 1.14E-08 1.19E-05butanol, n- 6.92E-03 6.92E-03 5.16E-03 5.16E-03 1.06E-02butanone, 2- methyl ethyl keto 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00carbon disulfide 1.53E-07 1.53E-07 1.30E-07 1.30E-07 1.87E-04chloroform 6.63E-08 6.63E-08 5.11E-08 5.11E-08 1.33E-05chloromethane 1.54E-09 1.54E-09 2.58E-09 2.58E-09 1.82E-05cyclohexane 1.72E-07 1.72E-07 2.54E-07 2.54E-07 1.59E-03di-n-butylphthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00dichlorobenzene, 1,2- 1.61E-05 1.61E-05 1.22E-05 1.22E-05 1.12E-03dichlorobenzene, 1,3- 6.19E-06 6.19E-06 4.77E-06 4.77E-06 1.30E-03dichlorobenzene, 1,4- 2.44E-05 2.44E-05 1.86E-05 1.86E-05 2.23E-03diethyl phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00ethanol 1.81E-04 1.81E-04 1.44E-04 1.44E-04 1.49E-03ethylbenzene 2.82E-06 2.82E-06 2.23E-06 2.23E-06 1.31E-03freon 11 (trichlorofluoromethan 1.05E-07 1.05E-07 1.13E-07 1.13E-07 4.32E-04freon 12 (dichlorodifluorometh 1.23E-08 1.23E-08 2.93E-08 2.93E-08 2.56E-04heptane 4.65E-06 4.65E-06 1.07E-05 1.07E-05 9.41E-02hexane 1.89E-07 1.89E-07 4.33E-07 4.33E-07 3.72E-03

VI-35

Saco




methane 3.55E-07 3.55E-07 9.13E-07 9.13E-07 8.25E-03methanol 4.89E-07 4.89E-07 1.13E-06 1.13E-06 1.01E-04Scrubber emissionsmethylene chloride 1.50E-07 1.50E-07 1.17E-07 1.17E-07 4.72E-05methylnaphthalene, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00naphthalene 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00phenol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00propane 4.11E-07 4.11E-07 9.12E-07 9.12E-07 7.70E-03propanol, 2- (isopropyl alcohol 3.86E-06 3.86E-06 3.04E-06 3.04E-06 2.82E-05styrene 6.26E-06 6.26E-06 4.80E-06 4.80E-06 1.02E-03tetrachloroethene 5.29E-07 5.29E-07 4.41E-07 4.41E-07 5.37E-04toluene 4.88E-06 4.88E-06 3.86E-06 3.86E-06 2.38E-03trichloroethane, 1,1,1- 4.92E-07 4.92E-07 3.99E-07 3.99E-07 3.60E-04trimethylbenzene, 1,2,4- 8.64E-06 8.64E-06 6.77E-06 6.77E-06 3.22E-03vinyl chloride 1.92E-10 1.92E-10 4.20E-10 4.20E-10 3.52E-06xylene, m- 5.84E-06 5.84E-06 4.57E-06 4.57E-06 2.14E-03xylene, o- 3.35E-06 3.35E-06 2.62E-06 2.62E-06 1.23E-03xylene, p- 5.56E-06 5.56E-06 4.35E-06 4.35E-06 2.02E-03

Polychlorinated dibenzo(p)dioxins and furans2,3,7,8-TCDD 4.34E-12 5.65E-12 3.48E-12 4.64E-12 0.00E+001,2,3,7,8-PCDD 4.39E-11 5.72E-11 3.61E-11 4.80E-11 1.18E-141,2,3,4,7,8-HxCDD 7.49E-12 9.88E-12 6.16E-12 8.31E-12 2.95E-141,2,3,6,7,8-HxCDD 1.13E-11 1.49E-11 9.34E-12 1.25E-11 7.70E-151,2,3,7,8,9-HxCDD 1.15E-11 1.51E-11 9.47E-12 1.27E-11 1.11E-141,2,3,4,6,7,8-HpCDD 8.68E-12 1.15E-11 7.14E-12 9.63E-12 1.37E-15OCDD 3.34E-13 4.40E-13 2.75E-13 3.70E-13 1.63E-162,3,7,8-TCDF 1.94E-11 2.53E-11 1.50E-11 2.02E-11 2.75E-131,2,3,7,8-PCDF 4.35E-11 5.69E-11 3.54E-11 4.74E-11 6.59E-142,3,4,7,8-PCDF 5.63E-11 7.37E-11 4.61E-11 6.18E-11 8.97E-141,2,3,4,7,8-HxCDF 3.32E-11 4.36E-11 2.73E-11 3.67E-11 4.09E-141,2,3,6,7,8-HxCDF 4.05E-11 5.32E-11 3.33E-11 4.47E-11 3.38E-142,3,4,6,7,8-HxCDF 3.21E-11 4.22E-11 2.64E-11 3.55E-11 4.13E-141,2,3,7,8,9-HxCDF 8.16E-12 1.07E-11 6.72E-12 9.03E-12 3.30E-141,2,3,4,6,7,8-HpCDF 1.05E-11 1.39E-11 8.67E-12 1.17E-11 1.06E-151,2,3,4,7,8,9-HpCDF 1.39E-12 1.83E-12 1.14E-12 1.54E-12 1.03E-14OCDF 8.32E-14 1.10E-13 6.85E-14 9.24E-14 2.64E-17


VI-36

Concentrations in farm animals and animal products (mg/kg)cancer

beef milk pork poultry eggsStack emissionsMetalsArsenic 3.19E-06 1.42E-07 0.00E+00 0.00E+00 0.00E+00Beryllium 2.13E-07 2.45E-10 0.00E+00 0.00E+00 0.00E+00Cadmium 4.82E-07 3.90E-08 8.11E-08 1.13E-06 2.67E-08Chromium (total) 1.65E-04 4.72E-05 0.00E+00 0.00E+00 0.00E+00Chromium (hexavalent) 1.20E-06 4.91E-07 0.00E+00 0.00E+00 0.00E+00Copper 8.75E-04 1.56E-04 0.00E+00 0.00E+00 0.00E+00Lead 4.41E-05 4.50E-05 1.75E-05 0.00E+00 0.00E+00Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 3.57E-06 1.25E-06 1.70E-08 7.10E-07 7.10E-07Mercuric chloride (particle) 2.79E-06 1.23E-06 9.62E-09 3.93E-07 3.93E-07Methyl mercury 5.18E-08 2.95E-08 7.95E-11 2.88E-09 2.88E-09Nickel 9.65E-05 2.38E-05 0.00E+00 0.00E+00 0.00E+00Selenium 3.75E-06 1.46E-05 1.57E-05 8.30E-07 8.30E-07Silver 1.85E-06 1.86E-05 0.00E+00 0.00E+00 0.00E+00Tin 3.26E-03 5.61E-05 0.00E+00 0.00E+00 0.00E+00Vanadium 4.26E-06 4.09E-08 0.00E+00 0.00E+00 0.00E+00Zinc 2.57E-05 1.38E-05 3.86E-06 7.35E-06 7.35E-06


Volatile organic compounds (VOCs)acetone 1.44E-11 7.82E-12 6.91E-12 1.92E-13 7.70E-11benzene 5.96E-11 3.26E-11 2.89E-11 8.02E-13 3.21E-10benzoic acid 2.41E-11 1.26E-11 9.51E-12 2.57E-13 1.03E-10benzyl alcohol 1.85E-11 1.01E-11 8.99E-12 2.50E-13 1.00E-10bis(2-ethylhexyl)phthalate 1.68E-06 7.70E-07 2.64E-07 5.24E-09 2.10E-06bromomethane 2.98E-13 1.62E-13 1.44E-13 4.00E-15 1.60E-12butanol, n- 2.55E-10 1.39E-10 1.23E-10 3.43E-12 1.37E-09butanone, 2- methyl ethyl keto 3.30E-12 1.79E-12 1.59E-12 4.42E-14 1.77E-11carbon disulfide 3.31E-12 1.81E-12 1.60E-12 4.44E-14 1.78E-11chloroform 2.31E-12 1.26E-12 1.12E-12 3.11E-14 1.25E-11chloromethane 1.79E-14 9.76E-15 8.63E-15 2.40E-16 9.60E-14cyclohexane 1.40E-16 7.61E-17 6.78E-17 1.89E-18 7.57E-16di-n-butylphthalate 3.20E-08 1.51E-08 3.72E-09 4.30E-11 1.73E-08dichlorobenzene, 1,2- 1.18E-12 6.45E-13 5.73E-13 1.59E-14 6.36E-12dichlorobenzene, 1,3- 0.00E+00 0.00E+00 0.00E+00 1.27E-16 5.09E-14dichlorobenzene, 1,4- 0.00E+00 0.00E+00 0.00E+00 3.94E-16 1.58E-13diethyl phthalate 2.22E-08 1.06E-08 2.07E-09 7.86E-12 3.15E-09ethanol 1.32E-14 7.22E-15 6.40E-15 1.78E-16 7.12E-14ethylbenzene 2.26E-15 1.22E-15 1.09E-15 3.05E-17 1.22E-14freon 11 (trichlorofluoromethan 5.84E-17 3.18E-17 2.81E-17 7.85E-19 3.14E-16freon 12 (dichlorodifluorometh 6.76E-21 3.69E-21 3.28E-21 9.10E-21 3.65E-18heptane 7.32E-16 3.93E-16 3.55E-16 1.00E-17 4.01E-15hexane 1.11E-16 5.69E-17 3.38E-17 8.48E-19 3.33E-16

VI-37


beef milk pork poultry eggsmethane 1.54E-15 8.40E-16 7.46E-16 2.07E-17 8.31E-15methanol 4.03E-14 2.10E-14 1.95E-14 5.40E-16 2.47E-13Stack emissionsmethylene chloride 6.26E-12 3.41E-12 3.02E-12 8.40E-14 3.37E-11methylnaphthalene, 2- 2.80E-09 1.52E-09 1.37E-09 3.82E-11 1.53E-08methyl phenol, 2- 5.05E-11 2.69E-11 2.49E-11 7.27E-13 2.83E-10methyl phenol, 4- 6.26E-12 3.24E-12 3.16E-12 9.26E-14 3.71E-11methyl phenol, 4- 8.99E-13 4.36E-13 3.85E-13 1.13E-14 4.52E-12naphthalene 2.05E-10 1.10E-10 1.02E-10 2.88E-12 1.15E-09phenol 6.84E-11 3.67E-11 3.35E-11 9.47E-13 3.79E-10propane 4.51E-14 2.46E-14 2.18E-14 6.06E-16 2.43E-13propanol, 2- (isopropyl alcohol 1.14E-15 6.22E-16 5.51E-16 1.53E-17 6.13E-15styrene 6.20E-11 3.38E-11 3.01E-11 8.35E-13 3.35E-10tetrachloroethene 4.79E-12 2.61E-12 2.32E-12 6.44E-14 2.58E-11toluene 1.14E-10 6.21E-11 5.51E-11 1.54E-12 6.14E-10trichloroethane, 1,1,1- 2.92E-16 1.59E-16 1.41E-16 3.93E-18 1.58E-15trimethylbenzene, 1,2,4- 1.12E-14 6.07E-15 5.43E-15 1.52E-16 6.08E-14vinyl chloride 2.34E-15 1.27E-15 1.13E-15 3.14E-17 1.25E-14xylene, m- 2.58E-11 1.40E-11 1.25E-11 3.48E-13 1.39E-10xylene, o- 2.15E-11 1.17E-11 1.04E-11 2.90E-13 1.16E-10xylene, p- 2.41E-11 1.31E-11 1.16E-11 3.24E-13 1.30E-10



VI-38


beef milk pork poultry eggsScrubber emissionsMetalsArsenic 1.30E-07 5.82E-09 0.00E+00 0.00E+00 0.00E+00Beryllium 2.83E-09 3.25E-12 0.00E+00 0.00E+00 0.00E+00Cadmium 5.35E-09 4.33E-10 9.00E-10 1.25E-08 2.96E-10Chromium (total) 2.19E-06 6.28E-07 0.00E+00 0.00E+00 0.00E+00Chromium (hexavalent) 8.68E-09 3.54E-09 0.00E+00 0.00E+00 0.00E+00Copper 1.02E-04 1.82E-05 0.00E+00 0.00E+00 0.00E+00Lead 7.35E-07 7.51E-07 2.92E-07 0.00E+00 0.00E+00Mercury (elemental) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (vapor) 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00Mercuric chloride (particle) 7.31E-08 3.17E-08 2.57E-10 1.05E-08 1.05E-08Methyl mercury 1.01E-09 6.21E-10 9.00E-13 2.75E-11 2.75E-11Nickel 1.30E-06 3.19E-07 0.00E+00 0.00E+00 0.00E+00Selenium 5.77E-09 2.24E-08 2.41E-08 1.27E-09 1.27E-09Silver 5.45E-08 5.48E-07 0.00E+00 0.00E+00 0.00E+00Tin 5.44E-05 9.36E-07 0.00E+00 0.00E+00 0.00E+00Vanadium 2.67E-07 2.57E-09 0.00E+00 0.00E+00 0.00E+00Zinc 8.18E-07 4.39E-07 1.23E-07 2.34E-07 2.34E-07


Volatile organic compounds (VOCs)acetone 3.09E-11 1.68E-11 1.49E-11 4.14E-13 1.66E-10benzene 1.07E-11 5.85E-12 5.18E-12 1.44E-13 5.77E-11benzoic acid 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00benzyl alcohol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bis(2-ethylhexyl)phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00bromomethane 4.80E-13 2.62E-13 2.32E-13 6.44E-15 2.58E-12butanol, n- 2.95E-08 1.61E-08 1.43E-08 3.96E-10 1.59E-07butanone, 2- methyl ethyl keto 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00carbon disulfide 7.12E-12 3.88E-12 3.44E-12 9.55E-14 3.83E-11chloroform 1.81E-11 9.83E-12 8.76E-12 2.44E-13 9.77E-11chloromethane 2.60E-14 1.42E-14 1.26E-14 3.50E-16 1.40E-13cyclohexane 1.81E-11 9.83E-12 8.76E-12 2.44E-13 9.77E-11di-n-butylphthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00dichlorobenzene, 1,2- 1.35E-07 7.33E-08 6.51E-08 1.81E-09 7.22E-07dichlorobenzene, 1,3- 0.00E+00 0.00E+00 0.00E+00 1.44E-11 5.78E-09dichlorobenzene, 1,4- 0.00E+00 0.00E+00 0.00E+00 4.51E-11 1.81E-08diethyl phthalate 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00ethanol 1.65E-09 8.99E-10 7.97E-10 2.21E-11 8.86E-09ethylbenzene 2.68E-10 1.45E-10 1.30E-10 3.61E-12 1.44E-09freon 11 (trichlorofluoromethan 6.41E-12 3.49E-12 3.09E-12 8.62E-14 3.45E-11freon 12 (dichlorodifluorometh 7.58E-16 4.14E-16 3.67E-16 1.02E-15 4.09E-13heptane 8.84E-11 4.74E-11 4.29E-11 1.21E-12 4.84E-10hexane 1.25E-11 6.42E-12 3.81E-12 9.57E-14 3.76E-11

VI-39


beef milk pork poultry eggsmethane 1.79E-13 9.72E-14 8.63E-14 2.40E-15 9.61E-13methanol 4.66E-12 2.43E-12 2.25E-12 6.24E-14 2.85E-11methylene chloride 5.29E-12 2.88E-12 2.56E-12 7.10E-14 2.84E-11Scrubber emissionsmethylnaphthalene, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 2- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00methyl phenol, 4- 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00naphthalene 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00phenol 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00propane 5.22E-12 2.84E-12 2.52E-12 7.01E-14 2.81E-11propanol, 2- (isopropyl alcohol 1.45E-10 7.93E-11 7.03E-11 1.95E-12 7.81E-10styrene 5.28E-10 2.87E-10 2.56E-10 7.11E-12 2.85E-09tetrachloroethene 3.79E-11 2.06E-11 1.84E-11 5.09E-13 2.04E-10toluene 3.73E-10 2.03E-10 1.80E-10 5.01E-12 2.00E-09trichloroethane, 1,1,1- 3.19E-11 1.74E-11 1.55E-11 4.30E-13 1.72E-10trimethylbenzene, 1,2,4- 1.33E-09 7.21E-10 6.45E-10 1.80E-11 7.22E-09vinyl chloride 3.61E-15 1.97E-15 1.75E-15 4.85E-17 1.94E-14xylene, m- 6.74E-10 3.66E-10 3.27E-10 9.10E-12 3.64E-09xylene, o- 3.67E-10 2.00E-10 1.78E-10 4.96E-12 1.98E-09xylene, p- 6.30E-10 3.44E-10 3.05E-10 8.47E-12 3.41E-09



VI-40


Hydrogen chloride

Volatile organic compounds (Vacetonebenzenebenzoic acidbenzyl alcoholbis(2-ethylhexyl)phthalatebromomethanebutanol, n-butanone, 2- methyl ethyl ketocarbon disulfidechloroformchloromethanecyclohexanedi-n-butylphthalatedichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-diethyl phthalateethanolethylbenzenefreon 11 (trichlorofluoromethanfreon 12 (dichlorodifluoromethheptanehexane

Concentrations in farm animals and animal products (mg/kg)

non-cancerbeef milk pork poultry eggs

3.20E-06 1.43E-07 0.00E+00 0.00E+00 0.00E+002.29E-07 2.58E-10 0.00E+00 0.00E+00 0.00E+005.29E-07 4.30E-08 9.44E-08 1.27E-06 2.99E-082.72E-04 7.08E-05 0.00E+00 0.00E+00 0.00E+001.20E-06 4.91E-07 0.00E+00 0.00E+00 0.00E+001.40E-03 2.40E-04 0.00E+00 0.00E+00 0.00E+005.18E-05 5.15E-05 2.30E-05 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+007.03E-06 2.45E-06 3.36E-08 1.41E-06 1.41E-064.71E-06 1.89E-06 1.88E-08 7.79E-07 7.79E-076.36E-08 3.36E-08 1.36E-10 5.27E-09 5.27E-099.75E-05 2.40E-05 0.00E+00 0.00E+00 0.00E+003.75E-06 1.46E-05 1.57E-05 8.33E-07 8.33E-071.86E-06 1.87E-05 0.00E+00 0.00E+00 0.00E+003.42E-03 5.86E-05 0.00E+00 0.00E+00 0.00E+004.93E-06 4.53E-08 0.00E+00 0.00E+00 0.00E+002.78E-05 1.50E-05 4.43E-06 8.22E-06 8.22E-06

0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

1.44E-11 7.82E-12 6.91E-12 1.92E-13 7.70E-115.96E-11 3.26E-11 2.89E-11 8.02E-13 3.21E-102.41E-11 1.26E-11 9.51E-12 2.57E-13 1.03E-101.86E-11 1.01E-11 9.00E-12 2.51E-13 1.00E-101.68E-06 7.70E-07 2.64E-07 5.24E-09 2.10E-062.98E-13 1.62E-13 1.44E-13 4.00E-15 1.60E-122.55E-10 1.39E-10 1.23E-10 3.43E-12 1.37E-093.30E-12 1.79E-12 1.59E-12 4.42E-14 1.77E-113.31E-12 1.81E-12 1.60E-12 4.44E-14 1.78E-112.31E-12 1.26E-12 1.12E-12 3.11E-14 1.25E-111.79E-14 9.76E-15 8.63E-15 2.40E-16 9.60E-141.40E-16 7.61E-17 6.78E-17 1.89E-18 7.57E-163.20E-08 1.51E-08 3.72E-09 4.31E-11 1.73E-081.19E-12 6.45E-13 5.73E-13 1.59E-14 6.36E-120.00E+00 0.00E+00 0.00E+00 1.27E-16 5.09E-140.00E+00 0.00E+00 0.00E+00 3.94E-16 1.58E-132.22E-08 1.06E-08 2.07E-09 7.86E-12 3.15E-091.32E-14 7.22E-15 6.40E-15 1.78E-16 7.12E-142.26E-15 1.22E-15 1.09E-15 3.05E-17 1.22E-145.84E-17 3.18E-17 2.81E-17 7.85E-19 3.14E-166.76E-21 3.69E-21 3.28E-21 9.10E-21 3.65E-187.32E-16 3.93E-16 3.55E-16 1.00E-17 4.01E-151.11E-16 5.69E-17 3.38E-17 8.48E-19 3.33E-16

VI-41

methanemethanolStack emissionsmethylene chloridemethylnaphthalene, 2-methyl phenol, 2-methyl phenol, 4-methyl phenol, 4-naphthalenephenolpropanepropanol, 2- (isopropyl alcoholstyrenetetrachloroethenetoluenetrichloroethane, 1,1,1-trimethylbenzene, 1,2,4-vinyl chloridexylene, m-xylene, o-xylene, p-


PCB Aroclor 1248



1.54E-15 8.40E-16 7.46E-16 2.07E-17 8.31E-154.03E-14 2.10E-14 1.95E-14 5.40E-16 2.47E-13

6.26E-12 3.41E-12 3.02E-12 8.40E-14 3.37E-112.87E-09 1.55E-09 1.40E-09 3.90E-11 1.56E-085.06E-11 2.70E-11 2.49E-11 7.28E-13 2.83E-106.26E-12 3.24E-12 3.17E-12 9.26E-14 3.71E-118.99E-13 4.36E-13 3.85E-13 1.13E-14 4.52E-122.05E-10 1.10E-10 1.02E-10 2.89E-12 1.16E-096.84E-11 3.67E-11 3.35E-11 9.47E-13 3.79E-104.51E-14 2.46E-14 2.18E-14 6.06E-16 2.43E-131.14E-15 6.22E-16 5.52E-16 1.53E-17 6.13E-156.20E-11 3.38E-11 3.01E-11 8.35E-13 3.35E-104.79E-12 2.61E-12 2.32E-12 6.44E-14 2.58E-111.14E-10 6.21E-11 5.51E-11 1.54E-12 6.14E-102.92E-16 1.59E-16 1.41E-16 3.93E-18 1.58E-151.12E-14 6.07E-15 5.43E-15 1.52E-16 6.08E-142.34E-15 1.27E-15 1.13E-15 3.14E-17 1.25E-142.58E-11 1.40E-11 1.25E-11 3.48E-13 1.39E-102.15E-11 1.17E-11 1.04E-11 2.91E-13 1.16E-102.41E-11 1.31E-11 1.17E-11 3.24E-13 1.30E-10


1.99E-09 8.04E-10 7.13E-10 2.33E-11 9.35E-09

VI-42


Hydrogen chloride

Volatile organic compounds (Vacetonebenzenebenzoic acidbenzyl alcoholbis(2-ethylhexyl)phthalatebromomethanebutanol, n-butanone, 2- methyl ethyl ketocarbon disulfidechloroformchloromethanecyclohexanedi-n-butylphthalatedichlorobenzene, 1,2-dichlorobenzene, 1,3-dichlorobenzene, 1,4-diethyl phthalateethanolethylbenzenefreon 11 (trichlorofluoromethanfreon 12 (dichlorodifluoromethheptanehexane



1.31E-07 5.84E-09 0.00E+00 0.00E+00 0.00E+003.04E-09 3.42E-12 0.00E+00 0.00E+00 0.00E+005.87E-09 4.77E-10 1.05E-09 1.41E-08 3.32E-103.61E-06 9.42E-07 0.00E+00 0.00E+00 0.00E+008.68E-09 3.54E-09 0.00E+00 0.00E+00 0.00E+001.63E-04 2.80E-05 0.00E+00 0.00E+00 0.00E+008.63E-07 8.59E-07 3.84E-07 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+001.24E-07 4.95E-08 5.03E-10 2.08E-08 2.08E-081.13E-09 6.60E-10 1.44E-12 5.02E-11 5.02E-111.31E-06 3.22E-07 0.00E+00 0.00E+00 0.00E+005.77E-09 2.24E-08 2.42E-08 1.28E-09 1.28E-095.46E-08 5.49E-07 0.00E+00 0.00E+00 0.00E+005.70E-05 9.78E-07 0.00E+00 0.00E+00 0.00E+003.09E-07 2.84E-09 0.00E+00 0.00E+00 0.00E+008.85E-07 4.77E-07 1.41E-07 2.62E-07 2.62E-07

0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

3.09E-11 1.68E-11 1.49E-11 4.14E-13 1.66E-101.07E-11 5.85E-12 5.18E-12 1.44E-13 5.77E-110.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+004.80E-13 2.62E-13 2.32E-13 6.44E-15 2.58E-122.95E-08 1.61E-08 1.43E-08 3.96E-10 1.59E-070.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+007.12E-12 3.88E-12 3.44E-12 9.55E-14 3.83E-111.81E-11 9.83E-12 8.76E-12 2.44E-13 9.77E-112.60E-14 1.42E-14 1.26E-14 3.50E-16 1.40E-131.81E-11 9.83E-12 8.76E-12 2.44E-13 9.77E-110.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+001.35E-07 7.33E-08 6.52E-08 1.81E-09 7.23E-070.00E+00 0.00E+00 0.00E+00 1.45E-11 5.79E-090.00E+00 0.00E+00 0.00E+00 4.51E-11 1.81E-080.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+001.65E-09 8.99E-10 7.97E-10 2.21E-11 8.86E-092.68E-10 1.45E-10 1.30E-10 3.61E-12 1.44E-096.41E-12 3.49E-12 3.09E-12 8.62E-14 3.45E-117.58E-16 4.14E-16 3.67E-16 1.02E-15 4.09E-138.84E-11 4.74E-11 4.29E-11 1.21E-12 4.84E-101.25E-11 6.42E-12 3.81E-12 9.57E-14 3.76E-11

VI-43

methanemethanolmethylene chlorideScrubber emissionsmethylnaphthalene, 2-methyl phenol, 2-methyl phenol, 4-methyl phenol, 4-naphthalenephenolpropanepropanol, 2- (isopropyl alcoholstyrenetetrachloroethenetoluenetrichloroethane, 1,1,1-trimethylbenzene, 1,2,4-vinyl chloridexylene, m-xylene, o-xylene, p-


PCB Aroclor 1248



1.79E-13 9.72E-14 8.63E-14 2.40E-15 9.61E-134.66E-12 2.43E-12 2.25E-12 6.24E-14 2.85E-115.29E-12 2.88E-12 2.56E-12 7.10E-14 2.84E-11

0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+000.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+005.22E-12 2.84E-12 2.52E-12 7.01E-14 2.81E-111.45E-10 7.93E-11 7.03E-11 1.95E-12 7.81E-105.28E-10 2.88E-10 2.56E-10 7.11E-12 2.85E-093.79E-11 2.06E-11 1.84E-11 5.09E-13 2.04E-103.73E-10 2.03E-10 1.80E-10 5.01E-12 2.00E-093.19E-11 1.74E-11 1.55E-11 4.30E-13 1.72E-101.33E-09 7.21E-10 6.46E-10 1.80E-11 7.22E-093.61E-15 1.97E-15 1.75E-15 4.85E-17 1.94E-146.74E-10 3.66E-10 3.27E-10 9.10E-12 3.64E-093.67E-10 2.00E-10 1.78E-10 4.96E-12 1.98E-096.30E-10 3.44E-10 3.05E-10 8.47E-12 3.41E-09


0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

VI-44

Documents

Cambridge Environmental