LIFE CYCLE ASSESSMENT FOR LANDFILL LEACHATE … · 2015. 5. 6. · Leachate can be very site specific but some trends have been observed which can be used to provide guidance for

LIFE CYCLE ASSESSMENT FOR LANDFILL LEACHATE PRODUCTION AND TREATMENT

By

JAMES R. WALLY

A THESIS PRESENTED TO THE GRADUATE SCHOOL

OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF ENGINEERING

UNIVERSITY OF FLORIDA

2014

© 2014 James R. Wally

To my wife, Laura

4

ACKNOWLEDGMENTS

I would like to thank my committee chairman, Professor Tim Townsend, for all of

his wisdom and support during this project. I would also like to thank Professor Ben

Koopman and Professor David Kaplan for their support on my committee. I am also

grateful for the LCA resources provided by Professor Mark Brown.

I am also thankful for the research foundations set by Roya Darioosh, and Chris

Moody on landfill leachate, which guided some of my design decisions.

5

TABLE OF CONTENTS page

ACKNOWLEDGMENTS .................................................................................................. 4

LIST OF TABLES ............................................................................................................ 7

LIST OF FIGURES .......................................................................................................... 9

LIST OF ABBREVIATIONS ........................................................................................... 11

ABSTRACT ................................................................................................................... 12

CHAPTER

1 INTRODUCTION .................................................................................................... 13

2 UPDATED LIFECYCLE INVENTORY FOR MSW LANDFILL LEACHATE IN THE UNITED STATES. .......................................................................................... 15

Background ............................................................................................................. 15 Methods .................................................................................................................. 16

Landfill Leachate Chemistry Database ............................................................. 16 Ecoinvent LCA Model and Database ................................................................ 16

Leachate Parameters for Advanced LCI Studies .............................................. 19

Leachate Mass Balance ................................................................................... 22

Results .................................................................................................................... 23 Modified Ecoinvent Leachate LCA ................................................................... 23 Regressions of Leachate Chemistry Parameters Relationships ....................... 23

Leachate Dissolved Solids Mass Balance ........................................................ 25 Conclusions from LCI of Leachate Generation ....................................................... 25

3 LIFE CYCLE ASSESSMENT OF LEACHATE TREATMENT TECHNOLOGIES .... 36

Background ............................................................................................................. 36 Methods .................................................................................................................. 37

LCI Methodology .............................................................................................. 37

Biological Nitrification-Denitrification Treatment System .................................. 39 Membrane Treatment System .......................................................................... 41 Wetland Treatment Systems ............................................................................ 43

Results and Discussion........................................................................................... 44 Treatment Technology LCIs ............................................................................. 44 LCA Results ..................................................................................................... 45

Conclusions from Leachate LCAs ........................................................................... 46

4 CONCLUSION ........................................................................................................ 58

6

LIST OF REFERENCES ............................................................................................... 59

BIOGRAPHICAL SKETCH ............................................................................................ 64

7

LIST OF TABLES

Table page 2-1 Assumed leachate concentrations in the ecoinvent LCA model, and the

leachate database. ............................................................................................. 27

2-2 Results of the regression analysis of conductivity against TDS, COD ,and NH3- N sample results from the leachate database. .......................................... 27

2-3 Results of the regression analysis of conductivity against TDS and NH3-N sample results from the leachate database. ....................................................... 27

2-4 Results of the linear multivariable regression with TDS, COD, and ammonia-nitrogen as the independent variables and Alkalinity as the dependent variable. .............................................................................................................. 28

2-5 Results of the linear multivariable regression of Alkalinity with TDS and NH3-N as independent variables. ............................................................................... 28

2-6 Results of the linear regression of BOD with COD as independent variables. ... 28

2-7 The results of the linear regression of TOC against TDS, COD, and NH3-N for the landfill leachate database. ....................................................................... 28

2-8 The results of the linear regression of TOC against TDS, and COD without an intercept. ........................................................................................................ 28

2-9 Measured leachate parameters as a fraction of TDS in samples from the landfill leachate database. .................................................................................. 29

2-10 The ratio of alkalinity as bicarbonate and total dissolved solids for samples in the leachate database. ....................................................................................... 29

2-11 Summary of regression equations found for various chemical parameters for samples from the leachate database. ................................................................. 29

3-1 Impact categories used in the CML 2000 LCA methodology used in the leachate treatment LCA. ..................................................................................... 48

3-2 Leachate chemistry for LCA comparing the impacts of differences in chemistry on leachate treatment impact estimation. ........................................... 48

3-3 Performance of NF and RO membranes in the treatment of landfill leachate. .... 48

3-4 LCI results for an SBR design treatment process for three different types of landfill leachate. .................................................................................................. 49

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3-5 LCI results for a membrane design treatment process for three different types of landfill leachate. .............................................................................................. 49

3-6 LCI results for a membrane design treatment process for three different types of landfill leachate. .............................................................................................. 50

9

LIST OF FIGURES

Figure page 2-1 Acidification predicted by the ecoinvent 3.1 model for default landfill

chemistry parameters, and chemistry parameters from the leachate database. ............................................................................................................ 30

2-2 Eutrophication potential of leachate treatment in a conventional activated sludge process as predicted by the ecoinvent 3.1 model using the CML 2000 method for the default and database specific chemistry LCIs of landfill leachate. ............................................................................................................. 30

2-3 Conductivity charted against TDS from the landfill leachate database. .............. 31

2-4 Conductivity charted against COD for samples from the landfill leachate database. ............................................................................................................ 31

2-5 Conductivity charted against NH3-N measurements for samples from the landfill leachate database. .................................................................................. 32

2-6 Conductivity charted against pH results for samples from the landfill leachate database. ............................................................................................................ 32

2-7 TDS and Alkalinity correlation of leachate database values. .............................. 33

2-8 Ammonia- N and Alkalinity regression for leachate database parameters. ........ 33

2-9 COD and Alkalinity regression of data from the leachate database.................... 34

2-10 TOC charted against COD for the leachate database sample results ................ 34

2-11 TOC graphed against TDS for the leachate database. ....................................... 35

3-1 Annual exceedance fees charged to a landfill by a wastewater utility for leachate exceeding NH3-N limits. ....................................................................... 51

3-2 Modeled membrane treatment system for the removal of ammonia-nitrogen from leachate typical in the leachate database. .................................................. 51

3-3 Acidification potential results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................................................ 52

3-4 Global warming potential results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................................ 52

3-5 Eutrophication potential results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................................ 53

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3-6 Non-renewable resources consumed for the LCA analysis of three leachate treatment methods across three types of leachates. .......................................... 53

3-7 Non-renewable fossil fuel consumption results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................. 54

3-8 Freshwater aquatic ecotoxicity potential results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................. 54

3-9 Human toxicity potential results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................................ 55

3-10 Marine ecotoxicity potential results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................................ 55

3-11 Ozone depletion potential results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................................ 56

3-12 Photochemical oxidation potential results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................. 56

3-13 Terrestrial ecotoxicity potential results for the LCA analysis of three leachate treatment methods across three types of leachate. ............................................ 57

11

LIST OF ABBREVIATIONS

BOD Biochemical Oxygen Demand

COD Chemical Oxygen Demand

LCA Life Cycle Assessment

LCI Life Cycle Inventory

NH3-N Ammonia as nitrogen

TDS Total Dissolved Solids

12

Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the

Requirements for the Master of Engineering

LIFE CYCLE ASSESSMENT FOR LANDFILL LEACHATE PRODUCTION AND TREATMENT

By

James Wally

December 2014

Chair: Timothy Townsend Major: Environmental Engineering Sciences

Life cycle assessment is a framework for decision making based on

environmental impacts, rather than economic impacts. The ecoinvent database is a

database containing information needed to perform LCA studies. Leachate generation is

incorporated into the life cycle impact of many processes in ecoinvent. In this study,

some default assumptions in the ecoinvent 3.1 model are changed and the results are

compared to the default assumptions. The default assumptions are shown to be

calculated overly conservatively. In the model, as in reality, leachate is generally

considered to be treated at domestic wastewater treatment plants. Using the newly

calculated values for leachate production impacts, three alternative treatment processes

are studied; SBRs, membranes, and wetlands. SBRs are found to have the lowest

impact based on the design assumptions in the project. Two real leachate values are

also studied which change the impact of each treatment method, but do not change

which method has the highest and lowest overall impact.

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CHAPTER 1 INTRODUCTION

Lifecycle assessment is the compilation and evaluation of the inputs, outputs and

the potential environmental impacts of a product system throughout its life cycle (ISO

14040:2006). This is conducted by performing a lifecycle inventory (LCI) which catalogs

the mass and energy flows of a system, then using a LCA methodology to quantify the

environmental impact of those mass and energy flows.

An important aspect of these flows is disposal of used material into a landfill (Doka,

2009). This material is assumed to produce leachate which is assumed to be treated.

Very few LCA studies have been conducted specifically on leachate, which has left the

old and Eurocentric assumptions of many LCA databases unquestioned.

One of the assumptions about leachate in life cycle inventories is that it is treated

at a domestic wastewater treatment plant. While this is generally the case, there is

reason to believe that more landfills will be treating leachate on-site with more advanced

treatment processes (Maurer et al., 2014).

LCA studies have been used in the domestic wastewater treatment field to

recommend best treatment processes (Niero et al., 2014; Coronminas et al., 2013).

Corominas et al., (2013) conducted an extensive review of 45 LCA studies of domestic

wastewater treatment which cataloged a large variation in methodologies. These

studies included conventional activated sludge processes, and non-conventional

processes, such as wetland treatment or biological filters. However, the assumptions

used only domestic wastewater treatment and no non-biological treatment methods

were discussed.

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Leachate is a large part of the end of life assumptions in many LCA models, and

the goal of this research is to investigate these models. The objective of this research is

to analyze the use of LCAs of leachate generation and treatment by comparing the

assumptions and results of a popular LCA modeling database using different leachate

generation and treatment assumptions.

The objective of the research in the second chapter of this thesis will be to

provide a framework for future LCA work on landfill leachate by examining the

assumptions in current LCI models about leachate, and by analyzing properties of

leachate that are important to LCIs. This will be accomplished by analyzing the default

assumptions for leachate generation in ecoinvent, a popular LCI database, and

compare it to measured leachate properties. The impact of these changes in LCI values

will be evaluated in an LCA. A database of current landfill leachate parameters for over

one-hundred landfills in the state of Florida will be used to examine leachate properties

and provide useful relationships for future LCI work.

The objective of the research covered in the third chapter of this thesis is to

conduct an LCA on alternative treatment processes for leachate and compare their

relative impacts to the environment. Three leachate chemistries representing three

landfill types, and three different treatment processes commonly applied to leachate are

compared across multiple impact categories defined by a standard LCA framework.

This will be conducted using the ecoinvent 3.1 database with the assumption

adjustments found in the second chapter.

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CHAPTER 2 UPDATED LIFECYCLE INVENTORY FOR MSW LANDFILL LEACHATE IN THE

UNITED STATES

Background

Some LCA studies have been conducted on leachate characteristics as part of

inventorying the impact of leachate production from landfilling municipal solid waste,

which is an important part of disposal LCIs (Doka, 2009), but few studies have

compared treatment strategies for leachate. Xing et al., (2013) conducted an LCI of two

leachate management strategies, recirculation and evaporation, but did not investigate

treatment strategies. Damgaard, et al., (2011) conducted an LCA study on the benefits

of lined compared to unlined landfills.

Leachate can be very site specific but some trends have been observed which

can be used to provide guidance for more general treatment modeling (Renou et al,.

2008A). The ability to estimate more site-specific information will be useful for future

LCA studies when some specific information cannot be obtained. This will also be

incorporated into the LCA of different leachate treatment methods.

The objective of this study is to use a database developed for collecting

chemistry parameters for lined landfills throughout the state of Florida to analyze default

leachate LCI assumptions in the ecoinvent database, and to provide improved

assumptions for future LCA work. The assumptions of the wastewater treatment model

incorporated into the ecoinvent database are edited to more closely reflect realistic

leachate characteristics.

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Methods

Landfill Leachate Chemistry Database

The University of Florida has maintained a database on leachate quality

parameters for 102 landfills across the state of Florida. This represents 20 years of

monitoring data with 260,103 data points collected from 1992 to 2013. The leachate

database was created as a project to compile the available data on leachate quality

throughout the state of Florida. This data is a compilation of regulatory reports found

through the FDEP OCULUS database, supplemented with personal inquiries to landfill

operators. At the time of this analysis, the database consisted of MSW landfill, with a

few ash landfill data points which were removed prior to analysis.

The large volume of data in the database presented a problem for quality

assurance since much of over 260,000 data points in this database were entered by

hand from scanned lab-reports. There is a high potential for data to be misentered.

Fortunately, the large sample set of the database allows outliers to be easily identified

and removed from the dataset. For the purpose of this paper, outliers will be defined as

any value which is more than 1.5 times further from the upper or lower quartile than the

upper and lower quartile is from the median.

Ecoinvent LCA Model and Database

The ecoinvent model is a popular lifecycle inventory model, but it is designed for

Europe, specifically Switzerland, with corresponding assumptions (Doka, 2009). This

section will review the ecoinvent model’s assumptions about leachate generation for

municipal solid waste and adjustments based on conditions in the United States,

including data from the leachate database, to provide a more applicable LCA model to

the United States.

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The eecoinvent database includes calculations for the environmental burden of

disposing of MSW in a landfill. One of those burdens is leachate production, which is

assumed to be captured by a liner system and treated at a wastewater treatment plant.

The leachate generation per kg of waste is calculated assuming a 10 m tall landfill

receiving 500 l/m2yr of infiltration to be 0.0196 l/yr/kg-waste over 100 years (Doka,

2009). The addition of a landfill cap to stop the infiltration of waste is not included in this

model, which is required in the United States under 40 CFR 258 subpart F. Estimating a

more appropriate leachate production rate to the United States is beyond the scope of

this study, but it is important to note the limitations of the assumptions in the ecoinvent

model.

For the eecoinvent model, the assumed chemistry of the leachate is based on

the elemental composition of the waste in the landfill, and the fraction of that waste

which will degrade and release its elements to the leachate. The fraction of the

elemental composition, which will be released over the first 100 years of the life of the

landfill, is called the release factor, . The release factor is the total mass of an element

released divided by the potential mass of the element that could be released to leachate

due to waste degradation. The release factor is calculated based on the volume of

leachate generated annually, V, the emission potential of the element, , the fraction of

emission to the gas phase, , and typical literature values for element in the

leachate, . Equation 2-1 shows the calculation of the release factor (Doka, 2009).

(2-1)

The potential emission of a given element, , is given by Equation 2-2.

18

(2-2)

Di is the decomposition rate of the waste fraction, i, over 100 years. me,I is the

concentration of the element in the waste fraction. %i is the mass fraction of the element

in the MSW being landfilled.

To find the %gase release, Doka (2009) cites a study (Belvi and Baccini, 1989),

which used distilled water to leach grinded core samples from various levels of a landfill

to conclude the fraction of elements which remained, and the fraction which remained

that could be leached. The contacts time varied from 4 hours to 288 hours in these

leaching experiments. The liquid to solid of these leaching tests were chosen to

simulate two-thousand years of contact time in a landfill.

The decomposition rates for each fraction of waste is calculated from carbon

conversion rates given by Micales and Skog (1997), and other assumptions about the

degradation of non-organic waste fractions, and ultimately arrived at an overall waste

decomposition rate of 18.73%.

The few examples of the literature values used in ecoinvent for co are

contrasted with the average values in the leachate database in Table 2-1. The

elemental compositions are similar, but the TOC, BOD, COD, and organically bound

nitrogen are much higher for the ecoinvent values. The leachate database values are

more consistent with a stable landfill, while the ecoinvent values are more consistent

with young landfills (Kjeldsen et al., 2002). The ecoinvent model predicts that the landfill

will behave as a young, high BOD landfill for 100 years, but it will likely stabilize within

20 years and produce far less BOD. For this alternative leachate LCA model, the

19

leachate database values for Co will be applied to compare the impact on the LCA

results.

The ecoinvent model assumes all leachate is treated at a domestic wastewater

treatment plant which then discharges to surface water over the first 100 years of the

life of the landfill (Doka, 2009). While this is a common case, 39% of all leachate in the

state of Florida is treated at least partially on site (Townsend et al., 2007).

The ecoinvent database assumes all sludge from the WWTP is incinerated per

Swiss statue (Doka, 2009), but 60% of sludge in the US and 30% of sludge in Europe is

land disposed, while a total of only 47% is incinerated globally, 43% is land disposed,

and 4% is disposed in a landfill (CH2MHill Canada, 2000). It was found to be common

practice for landfills studied in the database to dispose of sludge in the often adjacent

landfill. This alternative leachate LCA model will model a domestic wastewater

treatment plant where the sludge is landfilled.

Leachate Parameters for Advanced LCI Studies

More complex LCIs of leachate parameters will be necessary to accommodate

LCIs for more advanced leachate treatment processes. Site specific LCA studies may

not have access to detailed chemistry reports, and thus regression equations which

predict important parameters based on easily measured parameters may be useful to

conducting these LCAs.

The following four parameters have been selected as independent variables in

the regressions due to their wide availability and simple lab or field tests for detection,

and have been used to fit the data of less commonly available data: pH, TDS, COD, and

ammonia – nitrogen.

20

pH is commonly tested as a field parameter and lab parameter in the database. It

is an important parameter for the prediction of the behavior of ammonia, and for the

prediction of scaling for membrane processes (Tijing et al., 2014).

There are 1,961 samples of pH in the leachate database representing leachate

from 88 landfills. The average pH is 7.19 with a standard deviation of 0.74. The median

pH is 7.12.

The parameter, TDS, is typically higher than the freshwater criteria in the state of

Florida, which means it must be treated before leachate can be discharged (CTLs,

2005). Since it is a measure of the total amount of dissolved compounds in the

leachate, it is used as an analogue for the overall strength of leachate.

There are 2,724 samples of TDS in the leachate database representing 98

landfills. The average TDS of the leachate database is 5,440 mg/L with a standard

deviation of 9,360 mg/L and a median of 3,100 mg/L.

COD is a measure of the chemical oxygen demand in the leachate with the

standard method ISO 6060. The method uses potassium dichromate to fully oxidize all

organic matter in the water. This measure is used as an analogue for BOD, which is

regulated to control oxygen depletion in receiving waters (Sawyer et al., 2003). Due to

the low ratio of BOD/COD in leachate, this analogue is not as useful for leachate, but it

is a potential measure of the strength of the leachate (Lee and Nikraz, 2014). Leachate

COD is still largely composed of organic matter such as humic and fulvic acids

(Kurniawan et al., 2006), making it a good measure of the organic content of the

leachate. The average COD value in the database is 611 mg/L with a standard

deviation of 540 mg/L across 509 samples from 48 landfills.

21

Discharge of ammonia-nitrogen to the groundwater in the state of Florida is

limited to 2.8 mg/L, and discharge to the surface water is limited to 0.02 mg/L.

Ammonia-nitrogen is a discharge criteria, and is regulated due to aquatic toxicity (CTLs,

2005). The average NH3-N value of in the database is 166 mg/L with a standard

deviation of 165 mg/L out of 1,986 samples from 94 landfills.

For dependent variables of the regressions, the parameters selected are

conductivity, alkalinity, BOD, and TOC. These parameters are less convenient to

measure than the independent variables, with the exception of specific conductance.

Specific conductivity is often used as a field measurement of total dissolved

solids, which is a calculation based on assumptions about the ratio of conductivity and

total dissolved solids along with temperature (Hem, 1985; Wood, 1976). Thus, the

correlation between conductivity and the input parameters will be used as a reference

for the usefulness of the fits for other parameters. The average conductivity in the

leachate database is 5,473 S/cm with a standard deviation of 3,984 S/cm across

2,362 samples from 100 landfills.

Alkalinity is a measure of the bases which can be titrated with strong acid

(Stumm and Morgan, 1981). Alkalinity is important to treatment of leachate for scaling

(Hwang, and Shin, 2013), and modeling biological nitrification-denitrification (IPPC,

2007), among other reasons. The average alkalinity of the samples in the leachate

database is 2,224 mg/l as bicarbonate, with a standard deviation of 1,799 across 1,417

samples from 87 landfills.

BOD or biochemical oxygen demand, is a measure of the amount of oxygen that

is consumed by the decomposition of organic matter in the sample, and is important to

22

designing biological treatment processes (Sawyer, et al., 2003). The average value of

BOD in the landfill leachate database is 70 mg/L with a standard deviation of 59 across

509 samples from 53 landfills.

Total organic carbon is a measure of the organic content in samples. It is

important from a treatment perspective as a scavenger of oxidative compounds, and

fouling in membranes (Cho et al., 1998; Hong and Elimelech, 1997) in much the same

way as COD since they are different measures of the same thing, organic matter.

The multivariable linear regression function in Microsoft excel is used to produce

linear regressions for every combination of independent and dependent parameters.

Only sampling events which included all parameters were used for regressions,

and since there were only six sampling events which included results for all of the input

parameters, regressions were not performed for all parameters, but only the three with

the highest R2 values.

Linear regression is performed on the most relevant parameters. If the p-value

for any of these parameters is over 0.05, this dataset is discarded and the regression is

performed on the remaining datasets.

Leachate Mass Balance

Aside from distinguishing between organic matter and inorganic matter,

ecoinvent modeling of leachate provides limited distinction of dissolved speciation.

Instead, ecoinvent models leachate treatment based on elemental composition (Doka,

2009). For the purposes of TDS removal through advanced treatment processes, a

mass balance is conducted to determine the major dissolved species in the samples

from the landfill leachate database.

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This mass balance is conducted by matching results in the database for TDS

with results for other sampling parameters. Each resulting ratio counted as one sample

in the average mass balance calculations.

Results

Modified Ecoinvent Leachate LCA

The ecoinvent wastewater treatment model was run for the parameters for the

default ecoinvent leachate parameters, and for the parameters modified by the

database using the CML LCA methodology. Of the eleven impact categories, only two

differed significantly: acidification potential and Eutrophication. Acidification potential

decreased by 24.6% using database leachate values compared to the literature as

shown in Figure 2-1. Eutrophication values are 57% higher for the default leachate

chemistry LCI compared to the chemistry taken from the leachate database as shown in

Figure 2-2.

Regressions of Leachate Chemistry Parameters Relationships

As expected, TDS had the highest correlation as shown in Figure 2-3 with an R2

of 0.66. COD and NH3-N showed a correlation with Conductivity with an R2 of 0.29 and

0.28 respectively as shown in Figure 2-4 and Figure 2-5. This is hypothesized to be due

to covariance with TDS. pH has an R2 value of 0.04 as shown in Figure 2-6 and was

thus not included in the regression.

Table 2-2 shows the results of the first regression of conductivity compared

against TDS, COD, and NH3-N. The R2 value for this regression is 0.64. Since the p-

value was below 0.05 for all parameters except COD, the regression was performed

again for TDS and NH3-N as shown in Table 2-3. The total R2 value for this regression

is the same as for the previous regression of 0.64.

24

The regression equation for the specific conductance is therefore Equation 2-3.

(2-3)

Linear regression was performed on sampling events which included Alkalinity

and at least one of the “input parameters.” The correlation was the strongest to TDS

with an R2 of 0.42. Ammonia-nitrogen and COD correlated with similar R2 values of 0.28

and 0.23 respectively. The least correlated parameter is pH with an R2 value of 0.06

these correlation graphs are shown in Figure 2-7, Figure 2-8, and Figure 2-9.

A linear multivariable regression was performed on the database with TDS, COD,

and ammonia-nitrogen as the independent variables, and Alkalinity as the dependent

variable. The results are shown in Table 2-4, which reveals the p-value for COD is 0.16.

The regression was performed again with only TDS and ammonia-nitrogen as

independent variables. Table 2-5 shows the results of the second linear regression with

all values for p <0.05. The R2 for the two-variable regression is 0.51. Table 2-6 shows

the regression equation found to estimate Alkalinity.

The BOD dataset consisted of two distinct types of landfills: mature landfills with

high lower BOD, and young landfills with high BOD. There were considerably fewer

samples of high BOD leachate, so the algorithm which removed outliers removed all of

the high BOD samples, and all of the high range of COD samples. This left little

correlation between BOD and COD. Restoring the outliers resulted in the only

correlation found with BOD as shown in Table 2-6.

COD has the highest correlation to TOC out of all the input parameters with an

R2 of 0.60 as shown in Figure 2-10. TDS has the second highest correlation among the

25

input parameters at an R2 of 0.40 as is charted in Figure 2-11. NH3-N and pH have

lower correlations of 0.069 and <0.001 respectively.

Table 2-7 shows the results of the linear regression for TOC against TDS, COD,

and NH3-N. Since the p-Value for NH3-N, and the intercept is high, those parameters

were eliminated for the next regression. Table 2-8 shows the regression for TOC

against TDS and COD with no intercept with an overall R2 value of 0.88. The regression

equation, which can be used to estimate leachate parameters, is shown in Table 2-9

Leachate Dissolved Solids Mass Balance

The relative mass basis concentration of TDS in the leachate samples from the

database is shown in Table 2-9. These were found by dividing each sample for the

given parameter by the TDS result from the same sample.

As mentioned in the discussion of TOC, leachate TOC is dominated by humic

and fulvic acids, and other high weight organic molecules. Thus, the molecular weight of

these compounds should be assumed to be in the range of 5,000 g/mole for

calculations of molar concentration using Table 2-9 (Shinozuka, et al., 2003).

The balance of 26.2% is assumed to be largely composed of bicarbonate

alkalinity. The measure of alkalinity is on a mass basis, but some of this is represented

by ammonia-nitrogen with a molecular weight of 14 g/mol. This is equivalent to 4.36 g

per g . Thus, some significant percentage of the alkalinity is actually

ammonia, which is why the alkalinity fraction of TDS shown in Table 2-10 exceeds the

balance shown in Table 2-9.

Conclusions from LCI of Leachate Generation

The assumptions of the ecoinvent model are examined and compared to

leachate characteristics in a database of landfills in the United States. It is shown that

26

the leachate chemistry results of the ecoinvent model do not reflect the leachate

chemistry found in a large sample of landfills in the United States. This inventory has

been shown to be overly conservative when estimating the generation of leachate, due

to the assumption of constant leachate generation and constant leachate chemistry.

When compared to leachate chemistry data, it is apparent that the ecoinvent model

over-predicts leachate production and elemental release of pollution.

For the benefit of future LCIs of landfill leachate treatment, regressions for more

commonly measured parameters are provided, which are summarized in Table 2-11.

Conductance is a commonly used field parameter to estimate TDS, and the R2 value for

this regression is context for the validity of the other regressions. Correlations are

shown between less commonly available parameters BOD, TOC, and alkalinity; and a

set of commonly available field measured parameters with similar or higher R2 values.

This work has provided a framework for future LCA studies of leachate

generation and treatment. More work is needed in future studies to provide more

accurate assumptions for leachate generation and leachate treatment models. In order

to improve the leachate generation and treatment assumptions in end of life portions of

LCA models, a dataset of leachate chemistry results based on waste type must be

constructed, and non-linear release factors must be produced.

27

Table 2-1. Assumed leachate concentrations in the ecoinvent LCA model, and the leachate database.

ecoinvent Co (mg/L) Leachate Database Co (mg/L)

TOC 1625 186

BOD 754 70

COD 2391 611

TOC/CODa 0.385 0.304

NH3-N 115 165

Norg 243 38

sodium 538 679

calcium 160 493

chloride 650 615 a TOC/COD is a mass ratio, which does not have the units mg/L like the rest of the table.

Table 2-2. Results of the regression analysis of conductivity against TDS, COD ,and NH3- N sample results from the leachate database.

Coefficients

Standard

Error t Stat P-value

Lower

95%

Upper

95%

Intercept 663.313 225.976 2.935 3.65E-03 218.210 1108.417

TDS (mg/L) 1.254 0.129 9.696 5.05E-19 1.000 1.509

COD (mg/L) 0.195 0.320 0.610 0.54 -0.435 0.826

NH3-N (mg/L) 4.500 0.802 5.608 5.52E-08 2.919 6.081

Table 2-3. Results of the regression analysis of conductivity against TDS and NH3-N sample results from the leachate database.

Coefficients

Standard


Lower

95%

Upper

95%

Intercept 652.74 225.02 2.90 0.00406 209.521 1095.954

TDS (mg/L) 1.30 0.11 12.26 2.77E-27 1.091 1.508

NH3-N (mg/L) 4.61 0.78 5.89 1.27E-08 3.065 6.147

28

Table 2-4. Results of the linear multivariable regression with TDS, COD, and ammonia-nitrogen as the independent variables and Alkalinity as the dependent variable.

Coefficients

Standard


Lower

95%

Upper

95%

Intercept 376.94 129.57 2.91 0.004 121.5 632.36

TDS (mg/L) 0.57 0.08 7.48 1.95E-12 0.42 0.72

COD (mg/L) -0.26 0.18 -1.41 0.161 -0.61 0.10

NH3-N (mg/L) 2.52 0.45 5.62 6.04E-08 1.63 3.40

Table 2-5. Results of the linear multivariable regression of Alkalinity with TDS and NH3-

N as independent variables.

Coefficients

Standard


Lower

95%

Upper

95%

Intercept 467.37 94.65 4.94 1.13E-06 281.33 653.40

TDS (mg/L) 0.42 0.03 14.01 5.33E-37 0.36 0.48

NH3-N (mg/L) 3.23 0.36 9.04 5.52E-18 2.53 3.94

Table 2-6. Results of the linear regression of BOD with COD as independent variables.

Coefficients

Standard


Lower

95%

Upper

95%

COD 0.111 0.006 17.412 1.88E-49 0.0986 0.1237

Table 2-7. The results of the linear regression of TOC against TDS, COD, and NH3-N for the landfill leachate database.

Coefficients

Standard


Lower

95%

Upper

95%

Intercept 44.191 46.693 0.946 0.350 -50.335 138.717

TDS (mg/L) 0.047 0.027 1.763 0.086 -0.007 0.101

COD (mg/L) 0.187 0.067 2.811 0.008 0.052 0.322

NH3-N (mg/L) -0.094 0.177 -0.531 0.599 -0.452 0.264

Table 2-8. The results of the linear regression of TOC against TDS, and COD without

an intercept.

Coefficients

Standard


Lower

95%

Upper

95%

TDS (mg/L) 0.066 0.014 4.727 <0.0001 0.038 0.094

TOC (mg/L) 0.093 0.048 1.959 0.057 -0.003 0.190

29

Table 2-9. Measured leachate parameters as a fraction of TDS in samples from the landfill leachate database.

Ratio

Standard

Deviation Samples Landfills

Chloride/TDS 0.259 0.136 2535 97

NH3/TDS 0.098 1.092 1665 93

Ca/TDS 0.092 0.108 159 25

Sodium/TDS 0.191 0.094 2400 98

TOC/TDS 0.098 0.096 408 44

Balance 0.262

Table 2-10. The ratio of alkalinity as bicarbonate and total dissolved solids for samples in the leachate database.

Ratio

Standard

Deviation Samples Landfills

Alkalinity as bicarbonate/TDS 0.576 0.308 1103 86

Table 2-11. Summary of regression equations found for various chemical parameters for samples from the leachate database.

Equation R2 value

0.65

0.51

0.46

0.88

30

Figure 2-1. Acidification predicted by the ecoinvent 3.1 model for default landfill chemistry parameters, and chemistry parameters from the leachate database.

Figure 2-2. Eutrophication potential of leachate treatment in a conventional activated sludge process as predicted by the ecoinvent 3.1 model using the CML 2000 method for the default and database specific chemistry LCIs of landfill leachate.

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008 kg

SO

2 e

q./

m3

tre

ated

Leachate Database Default Ecoinvent Values

0

0.05

0.1

0.15

0.2

0.25

kg P

O4

eq

./m

3 t

reat

ed

Leachate Database Default Ecoinvent Values

31

Figure 2-3. Conductivity charted against TDS from the landfill leachate database.

Figure 2-4. Conductivity charted against COD for samples from the landfill leachate database.

y = 1.5037x + 989.15 R² = 0.6568

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

Co

nd

uct

ivit

y (μ

S/cm

)

TDS (mg/L)

y = 2.5981x + 2422.8 R² = 0.2909

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

0 500 1,000 1,500 2,000 2,500

Co

nd

uct

ivit

y (μ

S/cm

)

COD (mg/L)

32

Figure 2-5. Conductivity charted against NH3-N measurements for samples from the landfill leachate database.

Figure 2-6. Conductivity charted against pH results for samples from the landfill leachate database.

y = 10.73x + 2986.7 R² = 0.2841

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

0 100 200 300 400 500 600

Co

nd

uct

ivit

y (μ

S/cm

)

Ammonia - N (mg/L)

y = 1923.6x - 8482.2 R² = 0.0421

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

6 6.2 6.4 6.6 6.8 7 7.2 7.4 7.6 7.8 8

Co

nd

uct

ivit

y (μ

S/cm

)

pH

33

Figure 2-7. TDS and Alkalinity correlation of leachate database values.

Figure 2-8. Ammonia-nitrogen and alkalinity regression for leachate database parameters.

y = 0.5251x + 762.37 R² = 0.4195

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

Alk

alin

ity

(mg/

L)

TDS (mg/L)

y = 5.2374x + 1235.4 R² = 0.2895

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

0 100 200 300 400 500 600

Alk

alin

ity

(mg/

L)

Ammonia - N (mg/L)

34

Figure 2-9. COD and Alkalinity regression of data from the leachate database.

Figure 2-10. TOC charted against COD for the leachate database sample results.

y = 1.1885x + 1251 R² = 0.2339

0

1,000

2,000

3,000

4,000

5,000

6,000

0 500 1,000 1,500 2,000 2,500

Alk

alin

ity

as B

icar

bo

nat

e (

mg/

L)

COD (mg/L)

y = 0.2748x + 90.842 R² = 0.5951

0

100

200

300

400

500

600

700

800

0 500 1,000 1,500 2,000 2,500

TOC

(m

g/L)

COD (mg/L)

35

Figure 2-11. TOC graphed against TDS for the leachate database.

y = 0.0949x R² = 0.4021

0

100

200

300

400

500

600

700

800

0 500 1,000 1,500 2,000 2,500 3,000 3,500

TOC

(m

g/L)

TDS (mg/L)

36

CHAPTER 3 LIFE CYCLE ASSESSMENT OF LEACHATE TREATMENT TECHNOLOGIES

Background

Landfill leachate in the United States is generally disposed of in domestic

wastewater treatment plants (Townsend, et al., 2007), but the characteristics of landfill

leachate differ dramatically from domestic wastewater (Burks, et al., 1994; Kjeldsen et

al., 2002) and emerging wastewater treatment technologies are better able to handle

the high strength of leachate (Mauer et al., 2014; Renou et al., 2008A; Peters, 1998).

The high strength of ammonia in leachate is of particular concern for many

domestic wastewater treatment plants receiving leachate, as evidence by Figure 3-1

which shows the exponential increase one landfill has paid for exceeding typical

ammonia-nitrogen concentrations sent to a domestic wastewater treatment plant over

the past twenty years. Because of restrictions on wastewater parameters such as these,

many landfills are opting to either pre-treat leachate before sending it to a domestic

wastewater treatment plant, or to treat leachate to discharge on site (Townsend, et al.,

2007).

Life cycle assessment, the compilation and evaluation of the inputs, outputs and

potential environmental impacts of a product system throughout its lifecycle, (ISO

14040, 2006), can be used to evaluate what impact different treatment strategies will

have on the environment (Corominas, et al., 2013). This can provide an important

perspective in addition to cost in selecting the most appropriate process for a given

objective. In the case of leachate treatment, LCAs provide treatment process designers

with the ability to compare treatment processes to determine which process will have

the lowest impact on the environment.

37

Using life cycle analysis, this study will analyze three treatment methods which

have been applied to leachate treatment to reduce ammonia concentrations to

determine their relative environmental impacts. These methods will also be compared

across multiple leachate chemistries to ascertain how changing chemistry affects the

relative impacts of the method.

Methods

LCI Methodology

System boundaries are important to define for any LCA study (ISO 14040, 2006).

For the purpose of this study, the boundaries of the system will be defined as the

energy and materials required to treat the leachate. The delivery of the leachate to the

system and the delivery of the leachate to its discharge after the system are not

considered since it is assumed to be the same for all possible processes. Delivery of

waste materials after treatment is considered since it is possible this is different

depending on the treatment process. Capital construction is considered, but not at the

level of detail as operation since in previous wastewater treatment LCAs, it has been

concluded that operation and maintenance contributes 87% of the LCI of a wastewater

treatment plant (Renou et al., 2008B)

There are multiple standard LCA methodologies available and the results

provided for wastewater LCAs are very similar across methodologies (Renou et al.,

2008B). The CML 2000 method is applied in this study due to the broad range of impact

categories relevant to wastewater treatment and the ease of integration with the

ecoinvent LCI database used. The CML method was developed at Centre of

Environmental Studies (CML), University of Leiden, in the Netherlands in 2000. The

38

impacts analyzed, and the quantitative unit used in the CML 2000 method is

summarized in Table 3-1.

Part of the life cycle assessment stage is quantifying the impacts of all

inventoried processes, known as the LCIA stage (ISO 14040, 2006). Many inventoried

processes have already been evaluated and incorporated into a database to simplify

this stage of the study. The ecoinvent 3.1 database is used in this study, which contains

a broad set of processes and products which are important to leachate treatment. The

software used to access the database is an open source program called openLCA.

In order to construct the LCIs for this study, a basic design is constructed to

inventory the inputs and outputs of the process. For each treatment method in this

study, three separate designs are made based on differing leachate properties. The

three example leachates are referred to as leachate A, B, and C. Leachate A and B are

modeled after two Florida landfills that are facing leachate treatment challenges due to

high ammonia-nitrogen. Leachate A is modeled after a closed landfill with high TDS

and ammonia-nitrogen, low degradability and low leachate flow. Leachate B is modeled

after an active landfill with high flow and relatively lower TDS and ammonia-nitrogen.

Leachate C is modeled based on the assumptions of the mean concentrations for

typical leachates from a large database of leachate chemistry parameters in the state of

Florida, which has been compiled by the University of Florida. The chemistry

parameters of each leachate type are shown in Table 3-2.

In order to construct the designs on which to base the LCIs, several design

calculations and assumptions are made based on the example leachate chemistries in

Table 3-2. The processes are designed to achieve ammonia-nitrogen treatment to

39

below the 2005 Florida groundwater cleanup target level of 2.8 mg/L. All LCI values will

be averaged to the treated mass of ammonia-nitrogen, either per unit input for operation

parameters or over the lifetime of the item for construction processes. The design

assumptions for each specific process are listed in the corresponding sections below.

Biological Nitrification-Denitrification Treatment System

The following reactions occur during biological nitrification of ammonia (IPPC,

2007),

(3-1)

(3-2)

Based on these reactions, we can assume that during biological nitrification of 1

kg of ammonia-nitrogen, approximately 4.3 kg of oxygen is consumed, 7.1 kg of

alkalinity as CaCO3 is consumed, and 0.2 kg-dry of sludge is produced. Conversely,

during the denitrification process the reaction presented in Equation 3-3 occurs.

(3-3)

This results in a production of 0.45 kg-dry sludge, 3.6 kg of alkalinity formed, and

the consumption of 2.5 kg of methanol per kg of ammonia-nitrogen removed (IPPC,

2007; Carrera et al., 2003). Since the average alkalinity as CaCO3 of the leachate is

16.4 times higher than the ammonia-nitrogen (change all N to nitrogen) concentration,

no alkalinity adjustments are included. However, due to the relatively low concentration

of BOD available in landfill leachate, methanol addition is included in the model.

The BOD will get fully oxidized to CO2 in the SBR reaction. This implies that

every kilogram of BOD produces 1.38 kg of CO2. Based on the nitrification chemical

40

equations listed above, every 55 moles of ammonia-nitrogen consumes 10 moles CO2.

This leads to a CO2 consumption of 0.57 kg CO2/kg NH3-N. Finally, the process can

lead to releases of nitrous oxide at various rates depending on conditions, which can

range from 2.2% up to 16% of the total ammonia-nitrogen removed (Pijuana et al.,

2014; Mao et al., 2006). Pijuana et al. (2014) reported that for SBR conditions operated

with full denitrification, varying aeration, and found that conservative aeration produced

higher nitrous oxide, around 6% of removed ammonia-nitrogen. Mao et al. (2006)

reported the highest value of nitrous oxide emissions at 16% of removed nitrogen, but

not under full nitrification conditions, for which they reported 8.6% nitrous oxide

emissions. The average of the high value from Pijuan et al. and the low value of Mao et

al. will be used for the design, reflecting similar conditions to the expected operation of

the leachate SBR, conservative aeration and full denitrification. This leads to 0.073 kg

N2O.

The typical residence time for an SBR treating high-strength landfill leachate is

24 hours; therefore, the construction LCIs include the construction of two circular

concrete tanks, each of which can hold the volume of treatment for 24 hours. Depths for

these types of reactors vary, but are more efficient at greater depths (Wagner and

Pöpel, 1998), therefore the assumed depth of the SBR reactors is 10 m. SAE

represents the mass of oxygen transferred per energy applied through blowers as mass

O2/kWh, which can reach as high as 9 kg O2/kWh (Tucker, 2005). The conservative

value of 6 kg O2/kWh will be applied to the model.

To supply the required air, blowers are assumed to be included with the

necessary power. The diffusers are assumed to be composed of plastic membranes,

41

sufficiently dense to have a surface area equal to the area of the bottom of the tank.

Finally, mixing vessels for the methanol will be assumed to require 40 kg of

polyethylene for all designs.

Membrane Treatment System

Membrane treatment processes can be designed in a wide variety of ways. The

important design parameters include the membrane type, the driving pressure for each

membrane vessel, the arrangement of the membrane vessels, and the flow delivered to

each vessel.

Performance of RO and NF membranes in landfill leachate as reported by Peters

(1998) is shown in Table 3-3. As membranes are operated, fouling can occur which

accumulates and damages the membranes (Cho et al., 1998). Some of the fouling is

reversible, but some is permanent, thus the membranes must be periodically replaced.

As explained by Chianese et al., (1999), the permeate flux rate can be estimated

using the solution diffusion model shown in Equation 3-4 (Lonsdale et al., 1965):

(3-4)

J is the permeate flux rate (m3/m2hr), Pw/l is the specific hydraulic permeability of

cellulose acetate membranes, which is estimated to be 0.011 m3 h-1m-2 atm-1 for

nanofiltration, (Filmtec Membranes) and 0.015 for reverse osmosis membranes (DOW

Filmtec). is the driving pressure in atms, and is the difference in the osmotic

pressure in atms as defined in Equation 3-5 below (Chianese et al., 1999).

(3-5)

R is the gas constant, T is the absolute temperature, V is the molar volume of the

solvent ( /mol), and is the molar fraction of solute relative to the solvent. For water,

42

. R = 0.082

The solutes which dominate leachate are discussed

in the previous section, in Table 2-9. The mole fraction of TDS relative to water is

.

Since some of the TDS will permeate through the membrane, the osmotic

pressure gradient which the pumps must overcome is the difference between the

average pressure in the membrane tubes and the osmotic pressure of the permeate

(Chianese et al., 1999). Fouling of these membranes may reduce this modeled flux by

as much as 60% (Alzahrani et al., 2013) over three years of operation before needing to

be replaced (Peters, 1998), which must be accounted for in modeling.

The design example arrangement of membranes, shown in Figure 3-2, is

designed to remove ammonia-nitrogen to 2.8 mg/L. The recirculation rate of the

concentrate from the reverse osmosis vessel is 142% of the inflow. The high

recirculation rate increases the total flow treated, but decreases the pressure required to

treat it, since the reverse osmosis concentrate has a lower concentration of TDS than

the raw leachate. The pressure and flow rate of pump 1 and 2 are calculated based on

the molar concentrations of each leachate, assumed from Table 2-9, and the flow rates

are based on the recirculation rate of the reverse osmosis concentrate, and the driving

pressures applied. The pressure for pump 3 is based on the assumption of a 30 m tall

landfill requiring leachate injection pressure plus head loss of 15 m water.

Periodic cleaning of the membranes is necessary to remove foulants such as

TOC and CaCO3 which are known to be present in the leachate. A cleaning frequency

of biannually is assumed using an EDTA solution at a pH of 11, which is most effective

for the TOC and CaCO3 foulants (Ang et al., 2011). The permeate with low alkalinity will

43

be used to provide cleaning water of 750 L per membrane vessel, which will require

about 40 mg/L of NaOH to adjust to a pH of 11 and an effective dosage of EDTA of 0.5

mM (Ang et al., 2011). Daily passage of leachate at low pressure through the system

can also prolong membrane lifespan by causing forward osmosis which lifts fouling

(Ramon et al., 2013).

Wetland Treatment Systems

The most important aspect of wetland treatment design isproviding a sufficiently

large residence time for treatment. Performance for FWS wetlands is modeled in Kadlec

and Wallace (2009) using the P-k-C* model shown in Equation 3-6.

(3-6)

q is the hydraulic loading rate of the wetland (m/yr), Ci is the influent

concentration(mg/L), C* is a “background” concentration fitting parameter (mg/L), k is a

first order decay coefficient (m/yr), P is a unitless fitting coefficient related to the “tanks

in series” model, and C is the effluent concentration (mg/L). For this model, the values P

= 3, k = 8.7 m/yr, and C* = 1.5 mg/L values are selected from Kadlec and Wallace

(2009) from the 40th percentile of treatment performance. The temperature is assumed

to average 20 degrees celcius.

Wetlands have little LCI inputs or outputs during operation, but do emit

greenhouse gas which must be catalogued. Mander et al., (2014) found that 16.9% of

TOC influent to a treatment wetland was emitted as CH4-C, and that 0.13% of total

nitrogen influent in a treatment wetland became N2O-N. They also found a net

sequestration of 86 g C m-2 yr-1 although Neubauer (2014) found net emission of CO2

44

from wetlands over the first 100 years of operation. Due to this uncertainty, and the fact

that harvested soil will eventually oxidize, no CO2 sequestration or emission is

considered in this inventory, although CH4 and N2O emissions are considered.

The other input to the wetland during operation is excavation of accumulated soil

mass. Soil is assumed to accumulate at a rate of 41 Mg/ha, at a density of 1.66 kg/m3

as has been observed at another high strength wastewater treatment wetland (Maucieri

et al., 2014). This results in 189 m3 of soil accumulation every year which will need to be

removed at some point during the operational life of the landfill.

Construction is a more significant portion of the LCI for treatment wetlands. Since

it is assumed that the wetlands which contain leachate must abide by 40 CFR part 258

subpart D liner requirements. This means it will require 1.5 mm HDPE liner and 61 cm

of compacted clay below the entirety of the wetland. Excavation will also be required,

which is assumed to be 1 m3/m2 wetland area. Land use is also a significant category in

CML 2000, and will be taken into account in the model. Finally, the treatment wetland

will be planted with roots at a density of 3 plants m-2.

Results and Discussion

Treatment Technology LCIs

The results for the LCI of the SBR process for each different type of leachate are

shown in Table 3-4. Many of the significant categories do not vary with leachate

chemistry since the design assumptions are already normalized to ammonia-nitrogen

concentration, such as methanol consumption. Electricity varies only slightly since the

majority of the electricity consumption is normalized to ammonia-nitrogen, and only

differences in BOD drive the differences in electricity consumption. The largest variance

due to the difference in BOD concentration can be seen in the CO2 emissions which are

45

highest for leachate B with the highest BOD to NH3-N ratio and lowest for leachate A

with the lowest BOD to NH3-N ratio.

The LCI for the membrane process is shown in Table 3-5. The variance for most

parameters is due more to the higher TDS of leachate than the variation in ammonia-

nitrogen concentration. For all LCI inputs, leachate A requires the highest value,

followed by leachate C, then leachate B.

The LCI for wetland treatment processes is shown in Table 3-6. The LCI

inputs for this process increase as the concentration of ammonia-nitrogen in the

leachate decreases, requiring relatively higher inventory values to remove more dilute

ammonia-nitrogen. Unlike the previous LCIs, the largest contributor to the inventory is

construction.

LCA Results

The results of the lifecycle assessment show consistent across leachate types,

for each treatment method, but no one method consistently has the lowest impacts.

Figure 3-3 shows the acidification potential for each treatment method and each

leachate. Across all leachate types, wetlands have the lowest impact due to

acidification, followed by SBRs and then membranes, although the impact of treating

leachate B with membranes is similar to that of SBRs. Figure 3-4 shows the global

warming potential impact from each process. In this category, SBRs have the lowest

impact for all leachate types, followed by membranes, and then wetlands. For the

eutrophication potential impact category shown in Figure 3-5, wetlands have the lowest

impact for leachate A, but the highest for leachate C. SBRs have the lowest

eutrophication potential impact for leachate B and C, although leachate B is similar

46

across all treatment methods. The results of the LCA for the other impact methods are

available in the supplementary material.

As can be seen in Figures 3-6 to 3-13, across all impact categories, a pattern is

present in the impact of treating different types of leachate. For wetlands, and for a

lesser extent for SBRs, leachate A always has the lowest impact to treat, followed by B,

then C. This implies the more diluted leachate has a higher impact to treat than the

more concentrated leachate. This pattern does not hold for membranes, where the

lowest impact is found in leachate B, followed by leachate C, then leachate A. This is in

order of TDS which determines the osmotic pressure required to treat the leachate.

SBRs had the smallest variation with the type of leachate being treated. This is

because most of the design assumptions for SBRs scale linearly with ammonia-nitrogen

concentration. For membrane treatment, the largest impact in most categories is

electricity which scales logarithmically with TDS. For wetlands, the biggest impact

categories, liner, land, and excavation, are all related to wetland area required, which

scale geometrically with ammonia-nitrogen loading.

Conclusions from Leachate LCAs

No one process has the lowest impacts across all categories. SBRs have the

lowest impact results across four categories. Wetlands have the lowest impact across

three categories. For some impact categories, the least impactful process varies

depending on leachate chemistry. For three categories, SBRs or wetlands had the

lowest impact. For one category, wetlands or membranes had the lowest impact, and

for one category SBRs or membranes had the lowest impact.

47

Finally, SBRs had the highest impact in one of the assessments due to the

consumption of methanol, but a wide variety of alternative carbon sources are available

which may lessen this impact (Yen et al., 2012). With the exception of wetlands, the

results of the LCA models agree with Renou et al., (2008B) which showed that the

impacts of construction of a wastewater treatment plant are generally smaller than

operations by at least 1 to 10.

These LCA results provide a method to compare the relative environmental

impact of leachate treatment using advanced treatment technologies. This study is very

general, and different design assumptions could very well lead to different results. This

re-enforces the value of site-specific information when conducting an LCA study. While

ammonia-nitrogen is an important treatment indicator, it is not the only parameter which

must be removed and incorporation of more parameters in future studies will improve

the understanding of the impact of leachate treatment.

48

Table 3-1. Impact categories used in the CML 2000 LCA methodology used in the leachate treatment LCA.

Impact Category Functional Unit

Acidification potential - average Europe kg SO2 eq.

Climate change - GWP100 kg CO2 eq.

Depletion of abiotic resources - elements, ultimate

reserves

kg antimony eq.

Depletion of abiotic resources - fossil fuels MJ

Eutrophication – generic kg PO4--- eq.

Freshwater aquatic ecotoxicity - FAETP inf kg 1,4-dichlorobenzene eq.

Human toxicity - HTP inf kg 1,4-dichlorobenzene eq.

Marine aquatic ecotoxicity - MAETP inf kg 1,4-dichlorobenzene eq.

Ozone layer depletion - ODP steady state kg CFC-11 eq.

Photochemical oxidation - high Nox kg ethylene eq.

Terrestrial ecotoxicity - TETP inf kg 1,4-dichlorobenzene eq.

Table 3-2. Leachate chemistry for LCA comparing the impacts of differences in chemistry on leachate treatment impact estimation.

Parameters Database Averages

Landfill A Landfill B

Flow (gpd) 40,000 7,000 65,000

BOD (mg/L) 70 120 220

TDS (mg/L) 3,600 6,000 3,500

NH3-N (mg/L) 166 800 340

Table 3-3. Performance of NF and RO membranes in the treatment of landfill leachate.

Parameter NF rejection RO Rejection

COD 96% 99%

Ammonia 58% 99%

Calcium 93% 99%

Sodium 54% 99%

Chloride 39% 99%

Bicarbonatea 50% 99% aBicarbonate is assumed and calculated from the average of monovalent ions

49

Table 3-4. LCI results for an SBR design treatment process for three different types of

landfill leachate.

Parameters Leachate Type units per kg NH3-N

treated A B C

Operation

Inputs methanol 2.5 2.5 2.5 kg

excavation (sludge) 6.50E-04 6.50E-04 6.50E-04 m3

electricity 0.731 0.813 0.776 kWh

outputs sludge 0.65 0.65 0.65 kg dry

CO2 0.206 0.890 0.580 kg

Nitrous oxide - N 0.072 0.072 0.072 kg

Construction

concrete 8.78E-04 1.08E-03 2.49E-03 m3

excavation 1.28E-03 3.01E-03 6.17E-03 m3

blowers 1.67E-05 1.86E-05 1.77E-05 kWs of blowers

diffusers 2.56E-05 6.03E-05 1.23E-04 m2

tanks 5.17E-04 1.31E-04 4.36E-04 kg plastic

Table 3-5. LCI results for a membrane design treatment process for three different types of landfill leachate.

Parameters

Leachate Type units per kg NH3-N treated A B C

Operation Inputs

membranes 0.024 0.008 0.020 m2 electricity 15.16 5.38 6.06 kWh micron filter 1.55E-03 4.86E-04 1.31E-03 units NaOH 2.35E-05 7.37E-06 1.98E-05 kg EDTA 8.57E-05 2.69E-05 7.23E-05 kg

Outputs Concentrate 1.52 4.28 3.87 m3

Construction pump 1.73E-04 6.14E-05 6.91E-05 kW of pumps vessels 1.29E-03 4.05E-04 1.09E-03 kg pvc building 7.88E-04 2.47E-04 6.64E-04 sq ft building plastic for tanks 5.17E-04 1.62E-04 4.36E-04 kg PE plastic

50

Table 3-6. LCI results for a membrane design treatment process for three different types of landfill leachate.

Parameters Leachate Type units per kg

NH3-N treated A B C

Operation

Input Excavation 0.008 0.012 0.021 m3

Output Methane 0.164 0.293 0.398 kg CH4

Nitrous oxide 0.004 0.004 0.004 kg N2O-N

Construction

HDPE mass 0.320 0.460 0.823 kg

excavation 0.108 0.156 0.278 m3

Land 0.108 0.156 0.278 m2

Clay 0.066 0.095 0.170 m3

plants 0.324 0.467 0.835 units

51

Figure 3-1. Annual exceedance fees charged to a landfill by a wastewater utility for

leachate exceeding NH3-N limits.

Figure 3-2. Modeled membrane treatment system for the removal of ammonia-nitrogen

from leachate typical in the leachate database.

$0

$20,000

$40,000

$60,000

$80,000

$100,000

$120,000

$140,000

$160,000

1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Annual E

xceedance C

harg

es (

$-2

012 )

52

Figure 3-3. Acidification potential results for the LCA analysis of three leachate treatment methods across three types of leachate.

Figure 3-4. Global warming potential results for the LCA analysis of three leachate treatment methods across three types of leachate.

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

SBR Membranes Wetlands

kg S

O2

eq

.

Leachate A Leachate B Leachate C

0

5

10

15

20

25

30

35


kg C

O2

eq

.


53

Figure 3-5. Eutrophication potential results for the LCA analysis of three leachate treatment methods across three types of leachate.

Figure 3-6. Non-renewable resources consumed for the LCA analysis of three leachate treatment methods across three types of leachates.

0

0.001

0.002

0.003

0.004

0.005

0.006


kg P

O4

eq.


0

0.000002

0.000004

0.000006

0.000008

0.00001

0.000012

0.000014

0.000016

0.000018


kg a

nti

mo

ny

eq.


54

Figure 3-7. Non-renewable fossil fuel consumption results for the LCA analysis of three leachate treatment methods across three types of leachate.

Figure 3-8. Freshwater aquatic ecotoxicity potential results for the LCA analysis of three leachate treatment methods across three types of leachate.

0

10

20

30

40

50

60

70

80

90


MJ


0

0.005

0.01

0.015

0.02

0.025

0.03


kg 1

,4-d

ich

loro

ben

zen

e eq

.


55

Figure 3-9. Human toxicity potential results for the LCA analysis of three leachate treatment methods across three types of leachate.

Figure 3-10. Marine ecotoxicity potential results for the LCA analysis of three leachate treatment methods across three types of leachate.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2


kg 1

,4-d

ich

loro

ben

zen

e eq

.


0

2000

4000

6000

8000

10000

12000


kg 1

,4-d

ich

loro

ben

zen

e eq

.


56

Figure 3-11. Ozone depletion potential results for the LCA analysis of three leachate treatment methods across three types of leachate.

Figure 3-12. Photochemical oxidation potential results for the LCA analysis of three leachate treatment methods across three types of leachate.

0

0.00005

0.0001

0.00015

0.0002

0.00025

0.0003

0.00035


kg C

FC-1

1 e

q.


0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009


kg e

thyl

ene

eq.


57

Figure 3-13. Terrestrial ecotoxicity potential results for the LCA analysis of three leachate treatment methods across three types of leachate.

0

0.0005

0.001

0.0015

0.002

0.0025

0.003

0.0035


kg 1

,4-d

ich

loro

ben

zen

e eq

.


58

CHAPTER 4 CONCLUSION

LCAs can provide a valuable comparison between processes and technologies

to minimize the impact of a process on the environment. The ecoinvent 3.1 method of

quantifying leachate generation and treatment are in need of improvement. No previous

LCA studies have been conducted on advanced wastewater treatment processes for

landfill leachate.

Chapter two of this thesis has provided a perspective on the assumptions found

in LCI databases about leachate generation and treatment which will help guide future,

much needed work on leachate’s role in LCA studies. It has found that the ecoinvent 3.1

database provides default assumptions which are overly conservative, predicting more

harmful impacts from leachate than current leachate chemistry data bears out. Chapter

one also established several useful relationships among parameters in leachate,

including regressions of common wastewater treatment parameters, and a mass

balance of typical leachate TDS, which are expected to be useful in future work with

LCIs of leachate treatment.

Chapter three provides a unique LCA study which compares the impact of

several emerging leachate treatment processes removing ammonia-nitrogen from

leachate. This LCA shows that if possible, intensive biological treatment is generally

less impactful than wetland treatment or membrane processes. This LCA is limited by

the design assumptions incorporated into it, and there is a need for more work on more

parameters besides ammonia-nitrogen, and on more arrangements of treatment

processes to answer the question of which process has the lowest impact on the

environment.

59

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64

BIOGRAPHICAL SKETCH

James Wally received his undergraduate degree in environmental engineering at

the University of Florida in 2012. He began his graduate career as research assistant

under Dr. Timothy Townsend in August of 2013, and graduated with his ME in

December of 2014.

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