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INNOVATIVE DISPERSION MODELING PRACTICES TO ACHIEVE A REASONABLE LEVEL OF CONSERVATISM IN AERMODMODELING DEMONSTRATIONSCASE STUDY TO EVALUATE EMVAP, AMR2, AND BACKGROUND CONCENTRATIONS
Presentation to the Board of the Upper Midwest Section of the Air & Waste Management Association
September 16, 2014
Sergio A. Guerra - Wenck Associates, Inc.
AERMOD Model AccuracyAppendix W: 9.1.2 Studies of Model Accuracy a. A number of studies have been conducted to examine model accuracy,
particularly with respect to the reliability of short-term concentrations required for ambient standard and increment evaluations. The results of these studies are not surprising. Basically, they confirm what expert atmospheric scientists have said for some time: (1) Models are more reliable for estimating longer time-averaged concentrations than for estimating short-term concentrations at specific locations; and (2) the models are reasonably reliable in estimating the magnitude of highest concentrations occurring sometime, somewhere within an area. For example, errors in highest estimated concentrations of ± 10 to 40 percent are found to be typical, i.e., certainly well within the often quoted factor-of-two accuracy that has long been recognized for these models. However, estimates of concentrations that occur at a specific time and site, are poorly correlated with actually observed concentrations and are much less reliable.
• Bowne, N.E. and R.J. Londergan, 1983. Overview, Results, and Conclusions for the EPRI Plume Model Validation and Development Project: Plains Site. EPRI EA–3074. Electric Power Research Institute, Palo Alto, CA.
• Moore, G.E., T.E. Stoeckenius and D.A. Stewart, 1982. A Survey of Statistical Measures of Model Performance and Accuracy for Several Air Quality Models. Publication No. EPA–450/4–83–001. Office of Air Quality Planning & Standards, Research Triangle Park, NC.
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Monitored vs Modeled Data:Paired in time and space
AERMOD performance evaluation of three coal-fired electrical generating units in Southwest IndianaKali D. Frost Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
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SO2 Concentrations Paired in Time & Space
Probability analyses of combining background concentrations with model-predicted concentrationsDouglas R. Murray, Michael B. Newman Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
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SO2 Concentrations Paired in Time Only
Probability analyses of combining background concentrations with model-predicted concentrationsDouglas R. Murray, Michael B. Newman Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
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Roadmap• Case study based on 4 reciprocating internal combustion
engines (RICE) used for emergency purposes• Engines are also part of a peaking shaving agreement
and may be required to operate 250 hour per year• 3 Modeling techniques are presented
• EMVAP• ARM2• The use of the 50th percentile monitored concentration as Bkg
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EMVAP• Problem: Currently assume continuous emissions from
proposed project or modification• In this case study an applicant is requesting to load shave
250 hour per year.• Current modeling practices prescribe that the engines be
modeled as if in continuous operation(i.e., 8760 hour/year).
• EMVAP assigns emission rates at random over numerous iterations.
• The resulting distribution from EMVAP yields a more representative approximation of actual impacts
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ARM2• Emission sources emit mostly NOx that is gradually
converted to NO2
• Chemical reactions are based on plume entrapment and contact time
• Chu and Meyers* identified that higher NOxconcentrations and lower NO2/NOx ambient ratios were present in the near proximity of the source, and lower NOxand higher NO2/NOx ratios occurred as distance increased.
* Chu and Meyers, “Use of Ambient Ratios to Estimate Impact of NOx Sources on Annual NO2 Concentration”, presented at the 1991 Air and Waste Management Association annual meeting.
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Four cases evaluatedInput parameter Case 1 Case 2 Case 3 Case 4
Description of Dispersion Modeling
Current Modeling Practices
EMVAP(500 iterations)
ARM2 MethodEMVAP and
ARM2 Method
Maximum peak shaving hours per
year250 250 250 250
Hours of operation assigned in the
model8760 250 8760 250
NOx to NO2
Conversion
Assumed 100%
conversion
Assumed 100% conversion
Calculated based on the ARM2
equation
Calculated based on the ARM2
equation
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Engine Input Parameters
Input parameters per engine
Stack height (m) 10
NOx Emission rate (g/s) 5.0
Exit temperature(degrees K)
700
Diameter (m) 0.305
Exit velocity (m/s) 50
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Results of 1-hour NO2 Concentrations
Case 1 (µg/m3)
Case 2 (µg/m3)
Case 3 (µg/m3)
Case 4 (µg/m3)
Case DescriptionCurrent
Modeling Practices
EMVAP(500 itr.)
ARM2Method
EMVAPand
ARM2Method
H8H 2,455.6 577.8 491.1 157.7Percent of NAAQS
1,306% 307% 261% 84%
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Sitting of Ambient MonitorsAccording to the Ambient Monitoring Guidelines for Prevention of Significant Deterioration (PSD):
The existing monitoring data should be representative of three types of area:1) The location(s) of maximum concentration increase from the proposed source or modification;2) The location(s) of the maximum air pollutant concentration from existing sources; and3) The location(s) of the maximum impact area, i.e., where the maximum pollutant concentration would hypothetically occur based on the combined effect of existing sources and the proposed source or modification. (EPA, 1987)
U.S. EPA. (1987). “Ambient Monitoring Guidelines for Prevention of Significant Deterioration (PSD).”EPA‐450/4‐87‐007, Research Triangle Park, NC.
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24-hr PM2.5 Santa Fe, NM Airport
Background Concentration and Methods to Establish Background Concentrations in Modeling. Presented at the Guideline on Air Quality Models: The Path Forward. Raleigh, NC, 2013.Bruce Nicholson
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Combining 98th percentile Pre and Bkg (1-hr NO2 and 24-hr PM2.5)
P(Pre ∩ Bkg) = P(Pre) * P(Bkg)= (1-0.98) * (1-0.98)
= (0.02) * (0.02)
= 0.0004 = 1 / 2,500Equivalent to one exceedance every 6.8 years!
= 99.96th percentile of the combined distribution
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Combining 99th percentile Pre and Bkg (1-hr SO2)
P(Pre ∩ Bkg) = P(Pre) * P(Bkg)= (1-0.99) * (1-0.99)
= (0.01) * (0.01)
= 0.0001 = 1 / 10,000Equivalent to one exceedance every 27 years!
= 99.99th percentile of the combined distribution
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Proposed Approach to Combine Modeled and Monitored Concentrations• Combining the 98th (or 99th for 1-hr SO2) % monitored
concentration with the 98th % predicted concentration is too conservative.
• A more reasonable approach is to use a monitored value closer to the main distribution (i.e., the median).
Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formationSergio A. Guerra, Shannon R. Olsen, Jared J. Anderson Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
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Combining 98th Pre and 50th Bkg P(Pre ∩ Bkg) = P(Pre) * P(Bkg)
= (1-0.98) * (1-0.50)
= (0.02) * (0.50)
= 0.01 = 1 / 100
= 99th percentile of the combined distribution
Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formationSergio A. Guerra, Shannon R. Olsen, Jared J. Anderson Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
25
Combining 99th Pre and 50th Bkg P(Pre ∩ Bkg) = P(Pre) * P(Bkg)
= (1-0.99) * (1-0.50)
= (0.01) * (0.50)
= 0.005 = 1 / 200
= 99.5th percentile of the combined distribution
Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formationSergio A. Guerra, Shannon R. Olsen, Jared J. Anderson Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
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24-hr PM2.5 observations at Shakopee 2008-2010
Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formationSergio A. Guerra, Shannon R. Olsen, Jared J. Anderson Journal of the Air & Waste Management Association Vol. 64, Iss. 3, 2014
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Background concentrations1) Bkg 1: Maximum 1-hour NO2 observations from the
Blaine monitor averaged over three years.2) Bkg 2: Average of the annual 98th percentile daily
maximum 1-hour NO2 concentrations for years 2010-2012.
3) Bkg 3: 50th percentile concentration from the 2010-2012 hourly observations.
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Case 4 with three different backgrounds
Case 4 with Bkg 1(µg/m3)
Case 4 with Bkg 2(µg/m3)
Case 4 with Bkg 3(µg/m3)
Max. 98th % 50th %H8H 157.7 157.7 157.7
Background 106.6 86.6 9.4Total 264.3 244.2 167.1
Percent of NAAQS
140.6% 130.0% 88.9%
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Histogram of 1-hour NO2 observations
Percentile g/m3
50th 9.4
60th 13.2
70th 16.9
80th 26.4
90th 39.5
95th 52.7
98th 67.7
99.9th 97.8
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Conclusion• Use of EMVAP and ARM2 can help achieve more realistic concentrations
• Use of 50th % monitored concentration is statistically conservative when pairing it with the 98th (or 99th) % predicted concentration
• 3 Methods are protective of the NAAQS while still providing a reasonable level of conservatism
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QUESTIONS…
Sergio A. Guerra, PhDEnvironmental EngineerPhone: (952) [email protected]
www.SergioAGuerra.com
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