### Draft Appendix A Estimated Risks



## A-1 

# Appendix A Estimated Risks for Mass Loading Rate of 1 kg / year
This appendix presents chemical-specific resu lts for a series of pe rcentiles (50th, 75th, 90th, 95th, and 99th) and scenarios that represent the theoretical risk distributions based on the unitized mass loading rate of 1 kg / year. 1 

## Separate tables present the data for each solvent ( Tables A-1 through A-20) . Each table number is followed by an a or b (e.g., Table A-1a and A-1b); those labeled a present results for the ambient air pathway and those labeled b present the results for the groundwater pathway. Results fr om these two pathways were considered separately because of differences in time fr ame and location of exposure. Specifically, air emissions occur almost immediately after waste disposal, whereas it may take hundreds of years for most contaminants to leach from a landfill, travel in the groundwater, and reach a residential dwelling. Table A-4 (for benzen e) has additional letters ( c , d , e , and f ) to accommodate the use of a high-end ( c and d ) and low-end ( e and f ) cancer benchmark. For the groundwater pathway, results are pr esented individually for each exposure route (i.e., drinking water ingestion, shower inhalation, and shower/bathing dermal). In addition, for all carcinogens and for noncarcinogens with the same target organ and eff ect for inhalation and ingestion exposures, combined re sults for all three e xposure pathways toge ther for the adult receptor are presented (i.e., risk estimated based on the sum of the route-specific risks). Under each iteration of the risk model, the model calculates and outputs bot h the route-specific risk and the combined risk values. The distributions of risk, which are indexed on simulation run identification (ID) number, solvent, receptor, and e xposure route, are sorted separately to pull the risk percentiles of interest (e.g., 50 th percentile, 90th percentile). Th is process results in four sets of data for each solvent for groundwater: one se t for drinking water ingestion, one for shower inhalation, one for shower/bathing dermal, and one for combined groundwater risk. Each of the four result type s (drinking water ingestion, shower inhalation, shower/bathing dermal, and combined results for a particular per centile) is associated with a specific simulation run ID. In most cases, these are four different simulation run IDs, and thus reflect slightly different modeling conditions. For this reason, summing the route-specific risk va lues presented here will typically result in a slightly different value than the presented combined value. For example, consider the 50th percentile cancer result for methylene chloride shown at right. The combined adjusted risk based on a singl e run ID (run ID 4569) is slightly different from the value obtained when the risks for the individual routes are summed. Because this summation is based on values from different simulation runs (run IDs 2715 and 3079), it would reflect inco nsistent modeling conditions.

1 

### It should be noted that this appendix does not presen t percentile values where the pathway was not complete and, therefore, no risk was calculated (a risk of zero would result in an infinite mass loading rate). In these cases, some percentiles (e.g., 50th) will not appear as part of the percentile series. Route RunID Risk Drinking Water 6182 7.04E-10 Shower inhalation 8569 1.83E-09 Shower dermal 3486 1.26E-13 Sum NA 2.54E-09 Combined 4299 2.89E-09

# Table A-1a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of 1,1,2-Trichloroethane

CAS 79-00-5

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Inhalation 3.0E-11 50 Inhalation 9.8E-11 75 Inhalation 2.7E-10 90 Inhalation 4.7E-10 95 Inhalation 1.2E-09 99 Child Cancer Inhalation 1.2E-11 50 Inhalation 4.5E-11 75 Inhalation 1.2E-10 90 Inhalation 2.2E-10 95 Inhalation 5.9E-10 99 

## Composite Liner
Adult Cancer Inhalation 2.7E-11 50 Inhalation 9.0E-11 75 Inhalation 2.4E-10 90 Inhalation 4.2E-10 95 Inhalation 1.1E-09 99 Child Cancer Inhalation 1.1E-11 50 Inhalation 4.1E-11 75 Inhalation 1.1E-10 90 Inhalation 1.9E-10 95 Inhalation 5.5E-10 99

A-2

# Table A-1b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of 1,1,2-Trichloroethane

CAS 79-00-5

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Shower 1.2E-08 50 Drinking water 3.3E-09

Dermal bathing 3.7E-10 Combined DW/SH/DM 1.7E-08 Shower 1.2E-07 75 Drinking water 3.5E-08

Dermal bathing 3.6E-09 Combined DW/SH/DM 1.7E-07 Shower 6.8E-07 90 Drinking water 1.8E-07

Dermal bathing 1.9E-08 Combined DW/SH/DM 9.1E-07 Shower 1.6E-06 95 Drinking water 4.2E-07

Dermal bathing 4.0E-08 Combined DW/SH/DM 2.0E-06 Shower 7.1E-06 99 Drinking water 1.9E-06

Dermal bathing 1.8E-07 Combined DW/SH/DM 9.0E-06 Child Cancer Drinking water 3.0E-09 50 Dermal bathing 3.9E-10

Combined DW/DM 3.5E-09 Drinking water 3.0E-08 75 Dermal bathing 3.7E-09

Combined DW/DM 3.4E-08 Drinking water 1.4E-07 90 Dermal bathing 1.8E-08

Combined DW/DM 1.6E-07 Drinking water 3.4E-07 95 Dermal bathing 4.0E-08

Combined DW/DM 3.8E-07 Drinking water 1.4E-06 99 Dermal bathing 1.7E-07

Combined DW/DM 1.6E-06 Adult Noncancer Drinking water 9.9E-05 50 Dermal bathing 1.1E-05

Drinking water 8.8E-04 75 Dermal bathing 9.3E-05

Drinking water 4.1E-03 90 Dermal bathing 4.2E-04

A-3

# Table A-1b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of 1,1,2-Trichloroethane

CAS 79-00-5

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft

Drinking water 9.1E-03 95 Dermal bathing 9.3E-04

Drinking water 3.6E-02 99 Dermal bathing 3.5E-03 Child Noncancer Drinking water 2.1E-04 50 Dermal bathing 2.8E-05

Drinking water 1.9E-03 75 Dermal bathing 2.4E-04

Drinking water 8.5E-03 90 Dermal bathing 1.1E-03

Drinking water 1.9E-02 95 Dermal bathing 2.3E-03

Drinking water 7.3E-02 99 Dermal bathing 8.8E-03

A-4

# Table A-1b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of 1,1,2-Trichloroethane

CAS 79-00-5

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Cancer Shower 2.4E-12 75 Drinking water 7.5E-13

Dermal bathing 7.9E-14 Combined DW/SH/DM 3.7E-12 Shower 6.5E-10 90 Drinking water 1.8E-10

Dermal bathing 2.0E-11 Combined DW/SH/DM 9.1E-10 Shower 4.6E-09 95 Drinking water 1.2E-09

Dermal bathing 1.4E-10 Combined DW/SH/DM 6.2E-09 Shower 8.8E-08 99 Drinking water 2.0E-08

Dermal bathing 2.2E-09 Combined DW/SH/DM 1.2E-07 Child Cancer Drinking water 6.9E-13 75 Dermal bathing 9.4E-14

Combined DW/DM 8.1E-13 Drinking water 1.6E-10 90 Dermal bathing 2.1E-11

Combined DW/DM 1.9E-10 Drinking water 1.0E-09 95 Dermal bathing 1.4E-10

Combined DW/DM 1.2E-09 Drinking water 1.4E-08 99 Dermal bathing 1.9E-09

Combined DW/DM 1.7E-08 Adult Noncancer Drinking water 2.1E-08 75 Dermal bathing 2.3E-09

Drinking water 4.9E-06 90 Dermal bathing 5.3E-07

Drinking water 3.3E-05 95 Dermal bathing 3.2E-06

Drinking water 3.7E-04 99 Dermal bathing 4.3E-05 Child Noncancer Drinking water 4.9E-08 75 Dermal bathing 6.2E-09

Drinking water 9.8E-06 90 Dermal bathing 1.3E-06
A-5

# Table A-1b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of 1,1,2-Trichloroethane

CAS 79-00-5

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft

Drinking water 6.3E-05 95 Dermal bathing 8.7E-06

Drinking water 6.5E-04 99 Dermal bathing 9.0E-05

A-6

# Table A-2a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of 2-Ethoxyethanol

CAS 110-80-5

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 1.6E-10 50 Inhalation 5.3E-10 75 Inhalation 1.4E-09 90 Inhalation 2.7E-09 95 Inhalation 7.4E-09 99 Child Noncancer Inhalation 1.6E-10 50 Inhalation 5.3E-10 75 Inhalation 1.4E-09 90 Inhalation 2.7E-09 95 Inhalation 7.7E-09 99 

## Composite Liner
Adult Noncancer Inhalation 1.5E-10 50 Inhalation 4.9E-10 75 Inhalation 1.3E-09 90 Inhalation 2.5E-09 95 Inhalation 6.8E-09 99 Child Noncancer Inhalation 1.5E-10 50 Inhalation 4.9E-10 75 Inhalation 1.3E-09 90 Inhalation 2.5E-09 95 Inhalation 7.2E-09 99

A-7

# Table A-2b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of 2-Ethoxyethanol

CAS 110-80-5

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 2.0E-09 50 Drinking water 2.4E-07

Dermal bathing 1.3E-09 Shower 2.7E-08 75 Drinking water 3.2E-06

Dermal bathing 1.7E-08 Shower 1.7E-07 90 Drinking water 2.0E-05

Dermal bathing 1.0E-07 Shower 4.1E-07 95 Drinking water 5.1E-05

Dermal bathing 2.5E-07 Shower 2.0E-06 99 Drinking water 2.2E-04

Dermal bathing 1.1E-06 Child Noncancer Drinking water 4.9E-07 50 Dermal bathing 3.3E-09

Drinking water 7.2E-06 75 Dermal bathing 4.4E-08

Drinking water 4.3E-05 90 Dermal bathing 2.6E-07

Drinking water 1.1E-04 95 Dermal bathing 6.4E-07

Drinking water 5.2E-04 99 Dermal bathing 3.0E-06

A-8

# Table A-2b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of 2-Ethoxyethanol

CAS 110-80-5

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 3.9E-19 50 Drinking water 4.9E-17

Dermal bathing 2.7E-19 Shower 7.8E-13 75 Drinking water 9.4E-11

Dermal bathing 4.8E-13 Shower 5.2E-11 90 Drinking water 6.1E-09

Dermal bathing 3.1E-11 Shower 3.1E-10 95 Drinking water 3.5E-08

Dermal bathing 1.9E-10 Shower 6.5E-09 99 Drinking water 6.5E-07

Dermal bathing 3.3E-09 Child Noncancer Drinking water 1.2E-16 50 Dermal bathing 7.2E-19

Drinking water 2.0E-10 75 Dermal bathing 1.3E-12

Drinking water 1.2E-08 90 Dermal bathing 8.5E-11

Drinking water 7.2E-08 95 Dermal bathing 4.7E-10

Drinking water 1.2E-06 99 Dermal bathing 8.5E-09

A-9

# Table A-3a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Acetone

CAS 67-64-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 4.0E-11 50 Inhalation 1.2E-10 75 Inhalation 3.0E-10 90 Inhalation 5.0E-10 95 Inhalation 1.2E-09 99 Child Noncancer Inhalation 4.2E-11 50 Inhalation 1.3E-10 75 Inhalation 3.1E-10 90 Inhalation 5.3E-10 95 Inhalation 1.3E-09 99 

## Composite Liner
Adult Noncancer Inhalation 3.0E-10 50 Inhalation 9.3E-10 75 Inhalation 2.2E-09 90 Inhalation 3.7E-09 95 Inhalation 9.3E-09 99 Child Noncancer Inhalation 3.1E-10 50 Inhalation 9.5E-10 75 Inhalation 2.3E-09 90 Inhalation 3.8E-09 95 Inhalation 9.4E-09 99

A-10

# Table A-3b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Acetone

CAS 67-64-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 2.1E-08 50 Drinking water 5.6E-07

Dermal bathing 3.0E-09 Shower 1.6E-07 75 Drinking water 4.2E-06

Dermal bathing 2.2E-08 Shower 6.2E-07 90 Drinking water 1.6E-05

Dermal bathing 8.3E-08 Shower 1.3E-06 95 Drinking water 3.3E-05

Dermal bathing 1.7E-07 Shower 4.2E-06 99 Drinking water 1.2E-04

Dermal bathing 5.4E-07 Child Noncancer Drinking water 1.2E-06 50 Dermal bathing 8.0E-09

Drinking water 9.0E-06 75 Dermal bathing 5.8E-08

Drinking water 3.5E-05 90 Dermal bathing 2.2E-07

Drinking water 7.7E-05 95 Dermal bathing 4.6E-07

Drinking water 2.4E-04 99 Dermal bathing 1.5E-06

A-11

# Table A-3b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Acetone

CAS 67-64-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 1.4E-19 50 Drinking water 3.9E-18

Dermal bathing 2.0E-20 Shower 4.6E-13 75 Drinking water 1.2E-11

Dermal bathing 6.7E-14 Shower 4.9E-11 90 Drinking water 1.4E-09

Dermal bathing 6.7E-12 Shower 4.2E-10 95 Drinking water 1.2E-08

Dermal bathing 5.9E-11 Shower 1.1E-08 99 Drinking water 2.3E-07

Dermal bathing 1.4E-09 Child Noncancer Drinking water 9.2E-18 50 Dermal bathing 5.8E-20

Drinking water 2.7E-11 75 Dermal bathing 1.7E-13

Drinking water 2.7E-09 90 Dermal bathing 1.9E-11

Drinking water 2.4E-08 95 Dermal bathing 1.5E-10

Drinking water 5.3E-07 99 Dermal bathing 3.1E-09

A-12

# Table A-4a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Benzene

CAS 71-43-2

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 1.7E-06 50 Inhalation 5.2E-06 75 Inhalation 1.2E-05 90 Inhalation 1.8E-05 95 Inhalation 4.2E-05 99 Child Noncancer Inhalation 1.9E-06 50 Inhalation 5.7E-06 75 Inhalation 1.3E-05 90 Inhalation 2.0E-05 95 Inhalation 4.4E-05 99 

## Composite Liner
Adult Noncancer Inhalation 1.9E-06 50 Inhalation 5.5E-06 75 Inhalation 1.2E-05 90 Inhalation 1.9E-05 95 Inhalation 4.3E-05 99 Child Noncancer Inhalation 2.1E-06 50 Inhalation 6.0E-06 75 Inhalation 1.3E-05 90 Inhalation 2.1E-05 95 Inhalation 4.6E-05 99

A-13

# Table A-4b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Benzene

CAS 71-43-2

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 5.6E-04 50 Drinking water 2.5E-04

Dermal bathing 4.5E-05 Combined DW/SH/DM 9.8E-04 Shower 5.9E-03 75 Drinking water 2.3E-03

Dermal bathing 4.0E-04 Combined DW/SH/DM 9.7E-03 Shower 3.0E-02 90 Drinking water 1.1E-02

Dermal bathing 1.8E-03 Combined DW/SH/DM 4.5E-02 Shower 6.7E-02 95 Drinking water 2.3E-02

Dermal bathing 4.0E-03 Combined DW/SH/DM 9.6E-02 Shower 2.9E-01 99 Drinking water 9.5E-02

Dermal bathing 1.6E-02 Combined DW/SH/DM 4.1E-01 Child Noncancer Drinking water 5.5E-04 50 Dermal bathing 1.2E-04

Combined DW/DM 6.8E-04 Drinking water 5.0E-03 75 Dermal bathing 1.0E-03

Combined DW/DM 6.3E-03 Drinking water 2.3E-02 90 Dermal bathing 4.8E-03

Combined DW/DM 2.9E-02 Drinking water 5.1E-02 95 Dermal bathing 9.9E-03

Combined DW/DM 6.1E-02 Drinking water 2.2E-01 99 Dermal bathing 3.8E-02

Combined DW/DM 2.6E-01

A-14

# Table A-4b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Benzene

CAS 71-43-2

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 2.4E-13 50 Drinking water 1.2E-13

Dermal bathing 2.0E-14 Combined DW/SH/DM 4.5E-13 Shower 9.7E-07 75 Drinking water 4.1E-07

Dermal bathing 7.5E-08 Combined DW/SH/DM 1.7E-06 Shower 4.6E-05 90 Drinking water 1.7E-05

Dermal bathing 3.1E-06 Combined DW/SH/DM 7.2E-05 Shower 2.3E-04 95 Drinking water 8.9E-05

Dermal bathing 1.4E-05 Combined DW/SH/DM 3.6E-04 Shower 3.0E-03 99 Drinking water 9.5E-04

Dermal bathing 1.6E-04 Combined DW/SH/DM 4.2E-03 Child Noncancer Drinking water 2.9E-13 50 Dermal bathing 6.8E-14

Combined DW/DM 3.6E-13 Drinking water 9.0E-07 75 Dermal bathing 1.8E-07

Combined DW/DM 1.1E-06 Drinking water 3.7E-05 90 Dermal bathing 7.8E-06

Combined DW/DM 4.6E-05 Drinking water 1.8E-04 95 Dermal bathing 3.8E-05

Combined DW/DM 2.3E-04 Drinking water 1.9E-03 99 Dermal bathing 4.0E-04

Combined DW/DM 2.3E-03

A-15

# Table A-4a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Benzene(high)*

CAS 71-43-2 (H)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Inhalation 6.9E-11 50 Inhalation 2.2E-10 75 Inhalation 5.9E-10 90 Inhalation 9.6E-10 95 Inhalation 2.6E-09 99 Child Cancer Inhalation 2.9E-11 50 Inhalation 1.0E-10 75 Inhalation 2.8E-10 90 Inhalation 4.6E-10 95 Inhalation 1.2E-09 99 

## Composite Liner
Adult Cancer Inhalation 7.3E-11 50 Inhalation 2.4E-10 75 Inhalation 6.1E-10 90 Inhalation 1.0E-09 95 Inhalation 2.6E-09 99 Child Cancer Inhalation 3.1E-11 50 Inhalation 1.1E-10 75 Inhalation 2.8E-10 90 Inhalation 4.8E-10 95 Inhalation 1.3E-09 99

A-16

# Table A-4b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Benzene(high)*

CAS 71-43-2 (H)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Shower 2.1E-08 50 Drinking water 8.0E-09

Dermal bathing 1.4E-09 Combined DW/SH/DM 3.5E-08 Shower 2.4E-07 75 Drinking water 8.6E-08

Dermal bathing 1.5E-08 Combined DW/SH/DM 3.8E-07 Shower 1.4E-06 90 Drinking water 4.5E-07

Dermal bathing 7.4E-08 Combined DW/SH/DM 2.0E-06 Shower 3.3E-06 95 Drinking water 1.0E-06

Dermal bathing 1.7E-07 Combined DW/SH/DM 4.7E-06 Shower 1.6E-05 99 Drinking water 4.3E-06

Dermal bathing 7.0E-07 Combined DW/SH/DM 2.0E-05 Child Cancer Drinking water 7.5E-09 50 Dermal bathing 1.6E-09

Combined DW/DM 9.5E-09 Drinking water 7.5E-08 75 Dermal bathing 1.6E-08

Combined DW/DM 9.4E-08 Drinking water 3.8E-07 90 Dermal bathing 7.6E-08

Combined DW/DM 4.6E-07 Drinking water 9.3E-07 95 Dermal bathing 1.9E-07

Combined DW/DM 1.1E-06 Drinking water 4.2E-06 99 Dermal bathing 7.6E-07

Combined DW/DM 4.9E-06

A-17

# Table A-4b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Benzene(high)*

CAS 71-43-2 (H)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Cancer Shower 8.9E-18 50 Drinking water 4.4E-18

Dermal bathing 6.6E-19 Combined DW/SH/DM 1.6E-17 Shower 3.7E-11 75 Drinking water 1.5E-11

Dermal bathing 2.5E-12 Combined DW/SH/DM 5.9E-11 Shower 1.8E-09 90 Drinking water 6.5E-10

Dermal bathing 1.1E-10 Combined DW/SH/DM 2.8E-09 Shower 1.1E-08 95 Drinking water 3.8E-09

Dermal bathing 6.1E-10 Combined DW/SH/DM 1.5E-08 Shower 1.5E-07 99 Drinking water 5.1E-08

Dermal bathing 7.6E-09 Combined DW/SH/DM 2.0E-07 Child Cancer Drinking water 3.9E-18 50 Dermal bathing 7.2E-19

Combined DW/DM 4.5E-18 Drinking water 1.3E-11 75 Dermal bathing 2.8E-12

Combined DW/DM 1.6E-11 Drinking water 5.8E-10 90 Dermal bathing 1.2E-10

Combined DW/DM 7.2E-10 Drinking water 2.9E-09 95 Dermal bathing 6.0E-10

Combined DW/DM 3.5E-09 Drinking water 3.0E-08 99 Dermal bathing 7.2E-09

Combined DW/DM 3.9E-08

A-18

# Table A-4a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Benzene(low)*

CAS 71-43-2 (L)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Inhalation 1.9E-11 50 Inhalation 6.3E-11 75 Inhalation 1.7E-10 90 Inhalation 2.7E-10 95 Inhalation 7.2E-10 99 Child Cancer Inhalation 8.3E-12 50 Inhalation 3.0E-11 75 Inhalation 7.8E-11 90 Inhalation 1.3E-10 95 Inhalation 3.3E-10 99 

## Composite Liner
Adult Cancer Inhalation 2.1E-11 50 Inhalation 6.6E-11 75 Inhalation 1.7E-10 90 Inhalation 2.9E-10 95 Inhalation 7.2E-10 99 Child Cancer Inhalation 8.9E-12 50 Inhalation 3.1E-11 75 Inhalation 8.0E-11 90 Inhalation 1.3E-10 95 Inhalation 3.6E-10 99

A-19

# Table A-4b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Benzene(low)*

CAS 71-43-2 (L)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Shower 6.0E-09 50 Drinking water 2.2E-09

Dermal bathing 3.9E-10 Combined DW/SH/DM 9.7E-09 Shower 6.7E-08 75 Drinking water 2.3E-08

Dermal bathing 4.2E-09 Combined DW/SH/DM 1.1E-07 Shower 3.9E-07 90 Drinking water 1.2E-07

Dermal bathing 2.0E-08 Combined DW/SH/DM 5.5E-07 Shower 9.4E-07 95 Drinking water 2.8E-07

Dermal bathing 4.8E-08 Combined DW/SH/DM 1.3E-06 Shower 4.4E-06 99 Drinking water 1.2E-06

Dermal bathing 1.9E-07 Combined DW/SH/DM 5.7E-06 Child Cancer Drinking water 2.0E-09 50 Dermal bathing 4.3E-10

Combined DW/DM 2.6E-09 Drinking water 2.1E-08 75 Dermal bathing 4.3E-09

Combined DW/DM 2.6E-08 Drinking water 1.1E-07 90 Dermal bathing 2.1E-08

Combined DW/DM 1.3E-07 Drinking water 2.5E-07 95 Dermal bathing 5.1E-08

Combined DW/DM 3.0E-07 Drinking water 1.1E-06 99 Dermal bathing 2.1E-07

Combined DW/DM 1.3E-06

A-20

# Table A-4b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Benzene(low)*

CAS 71-43-2 (L)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Cancer Shower 2.5E-18 50 Drinking water 1.2E-18

Dermal bathing 1.8E-19 Combined DW/SH/DM 4.5E-18 Shower 1.0E-11 75 Drinking water 4.2E-12

Dermal bathing 6.7E-13 Combined DW/SH/DM 1.7E-11 Shower 5.2E-10 90 Drinking water 1.8E-10

Dermal bathing 2.9E-11 Combined DW/SH/DM 7.7E-10 Shower 3.0E-09 95 Drinking water 1.0E-09

Dermal bathing 1.7E-10 Combined DW/SH/DM 4.3E-09 Shower 4.3E-08 99 Drinking water 1.4E-08

Dermal bathing 2.1E-09 Combined DW/SH/DM 5.7E-08 Child Cancer Drinking water 1.1E-18 50 Dermal bathing 2.0E-19

Combined DW/DM 1.2E-18 Drinking water 3.4E-12 75 Dermal bathing 7.5E-13

Combined DW/DM 4.3E-12 Drinking water 1.6E-10 90 Dermal bathing 3.3E-11

Combined DW/DM 2.0E-10 Drinking water 8.0E-10 95 Dermal bathing 1.6E-10

Combined DW/DM 9.4E-10 Drinking water 8.1E-09 99 Dermal bathing 2.0E-09

Combined DW/DM 1.1E-08

A-21

# Table A-5a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Butanol

CAS 71-36-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No inhalation benchmark for this chemical

A-22

# Table A-5b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Butanol

CAS 71-36-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Drinking water 8.2E-07 50 Dermal bathing 2.1E-08

Drinking water 7.6E-06 75 Dermal bathing 1.9E-07

Drinking water 3.8E-05 90 Dermal bathing 9.7E-07

Drinking water 9.3E-05 95 Dermal bathing 2.2E-06

Drinking water 4.3E-04 99 Dermal bathing 9.7E-06 Child Noncancer Drinking water 1.7E-06 50 Dermal bathing 5.4E-08

Drinking water 1.7E-05 75 Dermal bathing 4.9E-07

Drinking water 8.4E-05 90 Dermal bathing 2.4E-06

Drinking water 2.1E-04 95 Dermal bathing 5.8E-06

Drinking water 8.9E-04 99 Dermal bathing 2.8E-05

A-23

# Table A-5b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Butanol

CAS 71-36-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Drinking water 2.0E-13 50 Dermal bathing 5.1E-15

Drinking water 1.1E-09 75 Dermal bathing 2.7E-11

Drinking water 3.9E-08 90 Dermal bathing 1.0E-09

Drinking water 1.8E-07 95 Dermal bathing 4.7E-09

Drinking water 2.6E-06 99 Dermal bathing 5.0E-08 Child Noncancer Drinking water 4.1E-13 50 Dermal bathing 1.2E-14

Drinking water 2.3E-09 75 Dermal bathing 6.8E-11

Drinking water 8.4E-08 90 Dermal bathing 2.6E-09

Drinking water 3.7E-07 95 Dermal bathing 1.1E-08

Drinking water 4.2E-06 99 Dermal bathing 1.4E-07

A-24

# Table A-6a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Chlorobenzene

CAS 108-90-7

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 6.5E-07 50 Inhalation 2.0E-06 75 Inhalation 4.5E-06 90 Inhalation 7.0E-06 95 Inhalation 1.7E-05 99 Child Noncancer Inhalation 6.9E-07 50 Inhalation 2.1E-06 75 Inhalation 4.8E-06 90 Inhalation 7.6E-06 95 Inhalation 1.8E-05 99 

## Composite Liner
Adult Noncancer Inhalation 6.5E-07 50 Inhalation 2.0E-06 75 Inhalation 4.4E-06 90 Inhalation 6.9E-06 95 Inhalation 1.6E-05 99 Child Noncancer Inhalation 7.0E-07 50 Inhalation 2.1E-06 75 Inhalation 4.8E-06 90 Inhalation 7.5E-06 95 Inhalation 1.7E-05 99

A-25

# Table A-6b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Chlorobenzene

CAS 108-90-7

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 3.2E-04 50 Drinking water 3.5E-05

Dermal bathing 1.5E-05 Shower 3.4E-03 75 Drinking water 3.3E-04

Dermal bathing 1.4E-04 Shower 1.7E-02 90 Drinking water 1.6E-03

Dermal bathing 6.6E-04 Shower 4.1E-02 95 Drinking water 3.7E-03

Dermal bathing 1.4E-03 Shower 1.7E-01 99 Drinking water 1.5E-02

Dermal bathing 6.2E-03 Child Noncancer Drinking water 7.2E-05 50 Dermal bathing 3.9E-05

Drinking water 7.0E-04 75 Dermal bathing 3.5E-04

Drinking water 3.3E-03 90 Dermal bathing 1.6E-03

Drinking water 7.8E-03 95 Dermal bathing 3.7E-03

Drinking water 3.5E-02 99 Dermal bathing 1.5E-02

A-26

# Table A-6b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Chlorobenzene

CAS 108-90-7

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 8.9E-15 50 Drinking water 8.0E-16

Dermal bathing 3.7E-16 Shower 5.6E-07 75 Drinking water 6.1E-08

Dermal bathing 2.4E-08 Shower 3.8E-05 90 Drinking water 3.4E-06

Dermal bathing 1.6E-06 Shower 2.0E-04 95 Drinking water 2.0E-05

Dermal bathing 7.8E-06 Shower 2.5E-03 99 Drinking water 2.2E-04

Dermal bathing 8.9E-05 Child Noncancer Drinking water 1.8E-15 50 Dermal bathing 9.4E-16

Drinking water 1.2E-07 75 Dermal bathing 6.6E-08

Drinking water 7.3E-06 90 Dermal bathing 3.9E-06

Drinking water 3.9E-05 95 Dermal bathing 2.1E-05

Drinking water 4.5E-04 99 Dermal bathing 2.2E-04

A-27

# Table A-7a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Cresols (total)

CAS 1319-77-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 2.0E-10 50 Inhalation 6.2E-10 75 Inhalation 1.6E-09 90 Inhalation 2.8E-09 95 Inhalation 7.5E-09 99 Child Noncancer Inhalation 2.1E-10 50 Inhalation 6.5E-10 75 Inhalation 1.6E-09 90 Inhalation 2.9E-09 95 Inhalation 8.3E-09 99 

## Composite Liner
Adult Noncancer Inhalation 1.8E-10 50 Inhalation 5.7E-10 75 Inhalation 1.4E-09 90 Inhalation 2.5E-09 95 Inhalation 6.6E-09 99 Child Noncancer Inhalation 1.9E-10 50 Inhalation 5.9E-10 75 Inhalation 1.5E-09 90 Inhalation 2.6E-09 95 Inhalation 7.5E-09 99

A-28

# Table A-7b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Cresols (total)

CAS 1319-77-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 1.2E-08 50 Drinking water 4.3E-06

Dermal bathing 4.8E-07 Combined DW/SH/DM 4.9E-06 Shower 1.4E-07 75 Drinking water 5.3E-05

Dermal bathing 5.8E-06 Combined DW/SH/DM 6.0E-05 Shower 8.2E-07 90 Drinking water 2.9E-04

Dermal bathing 3.2E-05 Combined DW/SH/DM 3.2E-04 Shower 2.1E-06 95 Drinking water 7.9E-04

Dermal bathing 8.3E-05 Combined DW/SH/DM 8.7E-04 Shower 9.5E-06 99 Drinking water 3.7E-03

Dermal bathing 3.8E-04 Combined DW/SH/DM 4.1E-03 Child Noncancer Drinking water 8.6E-06 50 Dermal bathing 1.2E-06

Combined DW/DM 1.0E-05 Drinking water 1.1E-04 75 Dermal bathing 1.4E-05

Combined DW/DM 1.2E-04 Drinking water 6.1E-04 90 Dermal bathing 8.2E-05

Combined DW/DM 7.1E-04 Drinking water 1.7E-03 95 Dermal bathing 2.1E-04

Combined DW/DM 1.9E-03 Drinking water 8.9E-03 99 Dermal bathing 9.1E-04

Combined DW/DM 9.6E-03

A-29

# Table A-7b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Cresols (total)

CAS 1319-77-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 4.9E-18 50 Drinking water 1.8E-15

Dermal bathing 1.8E-16 Combined DW/SH/DM 2.0E-15 Shower 1.6E-11 75 Drinking water 5.8E-09

Dermal bathing 6.4E-10 Combined DW/SH/DM 6.6E-09 Shower 8.3E-10 90 Drinking water 2.9E-07

Dermal bathing 3.2E-08 Combined DW/SH/DM 3.3E-07 Shower 4.0E-09 95 Drinking water 1.5E-06

Dermal bathing 1.6E-07 Combined DW/SH/DM 1.7E-06 Shower 5.8E-08 99 Drinking water 2.0E-05

Dermal bathing 2.0E-06 Combined DW/SH/DM 2.2E-05 Child Noncancer Drinking water 3.3E-15 50 Dermal bathing 5.0E-16

Combined DW/DM 3.8E-15 Drinking water 1.2E-08 75 Dermal bathing 1.6E-09

Combined DW/DM 1.4E-08 Drinking water 6.0E-07 90 Dermal bathing 8.1E-08

Combined DW/DM 7.2E-07 Drinking water 3.0E-06 95 Dermal bathing 4.2E-07

Combined DW/DM 3.4E-06 Drinking water 3.9E-05 99 Dermal bathing 4.9E-06

Combined DW/DM 4.2E-05

A-30

# Table A-8a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Cyclohexanone

CAS 108-94-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No inhalation benchmark for this chemical

A-31

# Table A-8b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Cyclohexanone

CAS 108-94-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Drinking water 1.3E-07 50 Dermal bathing 2.7E-09

Drinking water 1.1E-06 75 Dermal bathing 2.2E-08

Drinking water 5.1E-06 90 Dermal bathing 9.7E-08

Drinking water 1.1E-05 95 Dermal bathing 2.1E-07

Drinking water 4.7E-05 99 Dermal bathing 8.5E-07 Child Noncancer Drinking water 2.7E-07 50 Dermal bathing 7.0E-09

Drinking water 2.4E-06 75 Dermal bathing 5.4E-08

Drinking water 1.0E-05 90 Dermal bathing 2.4E-07

Drinking water 2.4E-05 95 Dermal bathing 5.3E-07

Drinking water 1.1E-04 99 Dermal bathing 2.3E-06

A-32

# Table A-8b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Cyclohexanone

CAS 108-94-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Drinking water 7.8E-15 50 Dermal bathing 1.7E-16

Drinking water 2.0E-10 75 Dermal bathing 4.0E-12

Drinking water 6.9E-09 90 Dermal bathing 1.4E-10

Drinking water 3.4E-08 95 Dermal bathing 6.8E-10

Drinking water 4.3E-07 99 Dermal bathing 7.8E-09 Child Noncancer Drinking water 1.8E-14 50 Dermal bathing 4.2E-16

Drinking water 4.2E-10 75 Dermal bathing 9.7E-12

Drinking water 1.5E-08 90 Dermal bathing 3.4E-10

Drinking water 6.5E-08 95 Dermal bathing 1.7E-09

Drinking water 8.1E-07 99 Dermal bathing 1.8E-08

A-33

# Table A-9a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Dichlorobenzene, 1,2-

CAS 95-50-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 7.2E-08 50 Inhalation 2.2E-07 75 Inhalation 5.1E-07 90 Inhalation 8.3E-07 95 Inhalation 2.1E-06 99 Child Noncancer Inhalation 7.7E-08 50 Inhalation 2.3E-07 75 Inhalation 5.5E-07 90 Inhalation 8.7E-07 95 Inhalation 2.2E-06 99 

## Composite Liner
Adult Noncancer Inhalation 6.7E-08 50 Inhalation 2.1E-07 75 Inhalation 4.8E-07 90 Inhalation 7.7E-07 95 Inhalation 1.8E-06 99 Child Noncancer Inhalation 7.2E-08 50 Inhalation 2.2E-07 75 Inhalation 5.1E-07 90 Inhalation 8.2E-07 95 Inhalation 1.9E-06 99

A-34

# Table A-9b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Dichlorobenzene, 1,2-

CAS 95-50-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 2.4E-05 50 Drinking water 3.7E-06

Dermal bathing 3.1E-06 Shower 2.6E-04 75 Drinking water 3.8E-05

Dermal bathing 3.1E-05 Shower 1.4E-03 90 Drinking water 2.0E-04

Dermal bathing 1.5E-04 Shower 3.5E-03 95 Drinking water 4.5E-04

Dermal bathing 3.5E-04 Shower 1.4E-02 99 Drinking water 1.8E-03

Dermal bathing 1.4E-03 Child Noncancer Drinking water 7.7E-06 50 Dermal bathing 7.8E-06

Drinking water 7.7E-05 75 Dermal bathing 7.9E-05

Drinking water 4.0E-04 90 Dermal bathing 3.7E-04

Drinking water 9.7E-04 95 Dermal bathing 8.7E-04

Drinking water 4.2E-03 99 Dermal bathing 3.7E-03

A-35

# Table A-9b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Dichlorobenzene, 1,2-

CAS 95-50-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 3.1E-18 50 Drinking water 5.2E-19

Dermal bathing 3.8E-19 Shower 7.0E-09 75 Drinking water 1.1E-09

Dermal bathing 9.1E-10 Shower 6.9E-07 90 Drinking water 9.6E-08

Dermal bathing 8.4E-08 Shower 4.8E-06 95 Drinking water 6.8E-07

Dermal bathing 5.4E-07 Shower 8.1E-05 99 Drinking water 1.0E-05

Dermal bathing 7.4E-06 Child Noncancer Drinking water 9.6E-19 50 Dermal bathing 1.0E-18

Drinking water 2.4E-09 75 Dermal bathing 2.3E-09

Drinking water 2.0E-07 90 Dermal bathing 2.1E-07

Drinking water 1.3E-06 95 Dermal bathing 1.4E-06

Drinking water 2.1E-05 99 Dermal bathing 1.9E-05

A-36

# Table A-10a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Ethyl acetate

CAS 141-78-6

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No inhalation benchmark for this chemical

A-37

# Table A-10b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Ethyl acetate

CAS 141-78-6

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Drinking water 2.9E-10 50 Dermal bathing 5.3E-12

Drinking water 8.8E-08 75 Dermal bathing 1.5E-09

Drinking water 8.2E-07 90 Dermal bathing 1.4E-08

Drinking water 2.4E-06 95 Dermal bathing 4.0E-08

Drinking water 1.3E-05 99 Dermal bathing 2.1E-07 Child Noncancer Drinking water 6.7E-10 50 Dermal bathing 1.4E-11

Drinking water 1.9E-07 75 Dermal bathing 4.1E-09

Drinking water 1.9E-06 90 Dermal bathing 3.8E-08

Drinking water 5.2E-06 95 Dermal bathing 1.1E-07

Drinking water 2.9E-05 99 Dermal bathing 5.5E-07 

## Composite Liner
Adult Noncancer Drinking water 1.2E-16 90 Dermal bathing 2.2E-18

Drinking water 6.3E-13 95 Dermal bathing 1.2E-14

Drinking water 1.7E-09 99 Dermal bathing 3.6E-11 Child Noncancer Drinking water 2.0E-16 90 Dermal bathing 3.6E-18

Drinking water 9.9E-13 95 Dermal bathing 2.0E-14

Drinking water 3.2E-09 99 Dermal bathing 5.4E-11

A-38

# Table A-11a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Ethyl benzene

CAS 100-41-4

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 2.5E-08 50 Inhalation 7.6E-08 75 Inhalation 1.8E-07 90 Inhalation 2.8E-07 95 Inhalation 6.6E-07 99 Child Noncancer Inhalation 2.7E-08 50 Inhalation 8.1E-08 75 Inhalation 1.9E-07 90 Inhalation 3.0E-07 95 Inhalation 7.1E-07 99 

## Composite Liner
Adult Noncancer Inhalation 2.4E-08 50 Inhalation 7.4E-08 75 Inhalation 1.7E-07 90 Inhalation 2.7E-07 95 Inhalation 6.3E-07 99 Child Noncancer Inhalation 2.6E-08 50 Inhalation 7.9E-08 75 Inhalation 1.8E-07 90 Inhalation 2.9E-07 95 Inhalation 6.9E-07 99

A-39

# Table A-11b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Ethyl benzene

CAS 100-41-4

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 6.8E-06 50 Drinking water 4.3E-06

Dermal bathing 3.0E-06 Shower 7.8E-05 75 Drinking water 4.3E-05

Dermal bathing 3.0E-05 Shower 4.3E-04 90 Drinking water 2.2E-04

Dermal bathing 1.5E-04 Shower 1.0E-03 95 Drinking water 5.1E-04

Dermal bathing 3.3E-04 Shower 4.2E-03 99 Drinking water 2.0E-03

Dermal bathing 1.3E-03 Child Noncancer Drinking water 8.7E-06 50 Dermal bathing 7.6E-06

Drinking water 9.0E-05 75 Dermal bathing 7.4E-05

Drinking water 4.7E-04 90 Dermal bathing 3.7E-04

Drinking water 1.0E-03 95 Dermal bathing 8.1E-04

Drinking water 4.7E-03 99 Dermal bathing 3.2E-03

A-40

# Table A-11b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Ethyl benzene

CAS 100-41-4

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 1.2E-17 50 Drinking water 9.0E-18

Dermal bathing 5.1E-18 Shower 4.3E-09 75 Drinking water 2.4E-09

Dermal bathing 1.7E-09 Shower 3.6E-07 90 Drinking water 1.9E-07

Dermal bathing 1.4E-07 Shower 2.3E-06 95 Drinking water 1.3E-06

Dermal bathing 8.9E-07 Shower 3.5E-05 99 Drinking water 1.7E-05

Dermal bathing 1.2E-05 Child Noncancer Drinking water 1.8E-17 50 Dermal bathing 1.5E-17

Drinking water 5.1E-09 75 Dermal bathing 4.2E-09

Drinking water 3.8E-07 90 Dermal bathing 3.6E-07

Drinking water 2.6E-06 95 Dermal bathing 2.3E-06

Drinking water 3.3E-05 99 Dermal bathing 2.8E-05

A-41

# Table A-12a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Isobutanol

CAS 78-83-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No inhalation benchmark for this chemical

A-42

# Table A-12b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Isobutanol

CAS 78-83-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Drinking water 2.0E-07 50 Dermal bathing 4.2E-09

Drinking water 1.9E-06 75 Dermal bathing 3.9E-08

Drinking water 8.7E-06 90 Dermal bathing 1.9E-07

Drinking water 2.1E-05 95 Dermal bathing 4.3E-07

Drinking water 9.1E-05 99 Dermal bathing 1.7E-06 Child Noncancer Drinking water 4.2E-07 50 Dermal bathing 1.1E-08

Drinking water 4.1E-06 75 Dermal bathing 1.1E-07

Drinking water 2.0E-05 90 Dermal bathing 5.2E-07

Drinking water 4.5E-05 95 Dermal bathing 1.2E-06

Drinking water 2.0E-04 99 Dermal bathing 5.0E-06

A-43

# Table A-12b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Isobutanol

CAS 78-83-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Drinking water 8.1E-15 50 Dermal bathing 1.9E-16

Drinking water 5.1E-11 75 Dermal bathing 1.2E-12

Drinking water 2.4E-09 90 Dermal bathing 4.9E-11

Drinking water 1.4E-08 95 Dermal bathing 2.6E-10

Drinking water 1.9E-07 99 Dermal bathing 4.1E-09 Child Noncancer Drinking water 1.7E-14 50 Dermal bathing 4.4E-16

Drinking water 1.2E-10 75 Dermal bathing 3.0E-12

Drinking water 4.5E-09 90 Dermal bathing 1.2E-10

Drinking water 2.4E-08 95 Dermal bathing 6.6E-10

Drinking water 3.7E-07 99 Dermal bathing 9.3E-09

A-44

# Table A-13a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Methanol

CAS 67-56-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 3.1E-10 50 Inhalation 9.4E-10 75 Inhalation 2.3E-09 90 Inhalation 3.9E-09 95 Inhalation 9.6E-09 99 Child Noncancer Inhalation 3.2E-10 50 Inhalation 1.0E-09 75 Inhalation 2.4E-09 90 Inhalation 4.1E-09 95 Inhalation 1.0E-08 99 

## Composite Liner
Adult Noncancer Inhalation 2.7E-10 50 Inhalation 8.4E-10 75 Inhalation 2.0E-09 90 Inhalation 3.4E-09 95 Inhalation 8.4E-09 99 Child Noncancer Inhalation 2.9E-10 50 Inhalation 9.0E-10 75 Inhalation 2.1E-09 90 Inhalation 3.5E-09 95 Inhalation 9.1E-09 99

A-45

# Table A-13b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methanol

CAS 67-56-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 3.6E-08 50 Drinking water 1.9E-06

Dermal bathing 5.7E-09 Shower 3.7E-07 75 Drinking water 1.9E-05

Dermal bathing 5.7E-08 Shower 1.9E-06 90 Drinking water 9.4E-05

Dermal bathing 2.9E-07 Shower 4.6E-06 95 Drinking water 2.2E-04

Dermal bathing 6.7E-07 Shower 2.1E-05 99 Drinking water 1.1E-03

Dermal bathing 3.0E-06 Child Noncancer Drinking water 3.7E-06 50 Dermal bathing 1.4E-08

Drinking water 3.9E-05 75 Dermal bathing 1.5E-07

Drinking water 2.1E-04 90 Dermal bathing 7.5E-07

Drinking water 4.9E-04 95 Dermal bathing 1.8E-06

Drinking water 2.4E-03 99 Dermal bathing 8.8E-06

A-46

# Table A-13b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methanol

CAS 67-56-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 7.8E-19 50 Drinking water 4.3E-17

Dermal bathing 1.2E-19 Shower 8.6E-12 75 Drinking water 4.1E-10

Dermal bathing 1.3E-12 Shower 8.3E-10 90 Drinking water 4.1E-08

Dermal bathing 1.2E-10 Shower 5.9E-09 95 Drinking water 3.0E-07

Dermal bathing 9.5E-10 Shower 9.9E-08 99 Drinking water 4.4E-06

Dermal bathing 1.3E-08 Child Noncancer Drinking water 8.8E-17 50 Dermal bathing 3.5E-19

Drinking water 8.6E-10 75 Dermal bathing 3.6E-12

Drinking water 8.7E-08 90 Dermal bathing 3.4E-10

Drinking water 6.4E-07 95 Dermal bathing 2.5E-09

Drinking water 8.4E-06 99 Dermal bathing 3.2E-08

A-47

# Table A-14a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Methyl ethyl ketone

CAS 78-93-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 1.0E-08 50 Inhalation 3.1E-08 75 Inhalation 7.1E-08 90 Inhalation 1.1E-07 95 Inhalation 2.5E-07 99 Child Noncancer Inhalation 1.1E-08 50 Inhalation 3.4E-08 75 Inhalation 7.6E-08 90 Inhalation 1.2E-07 95 Inhalation 2.7E-07 99 

## Composite Liner
Adult Noncancer Inhalation 2.2E-09 50 Inhalation 6.8E-09 75 Inhalation 1.6E-08 90 Inhalation 2.7E-08 95 Inhalation 6.9E-08 99 Child Noncancer Inhalation 2.3E-09 50 Inhalation 7.0E-09 75 Inhalation 1.7E-08 90 Inhalation 2.8E-08 95 Inhalation 6.8E-08 99

A-48

# Table A-14b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methyl ethyl ketone

CAS 78-93-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 1.3E-07 50 Drinking water 5.7E-07

Dermal bathing 6.3E-09 Combined DW/SH/DM 7.5E-07 Shower 1.1E-06 75 Drinking water 5.3E-06

Dermal bathing 5.4E-08 Combined DW/SH/DM 6.6E-06 Shower 5.5E-06 90 Drinking water 2.4E-05

Dermal bathing 2.6E-07 Combined DW/SH/DM 3.0E-05 Shower 1.2E-05 95 Drinking water 5.4E-05

Dermal bathing 5.4E-07 Combined DW/SH/DM 6.8E-05 Shower 4.5E-05 99 Drinking water 2.0E-04

Dermal bathing 2.1E-06 Combined DW/SH/DM 2.5E-04 Child Noncancer Drinking water 1.2E-06 50 Dermal bathing 1.7E-08

Combined DW/DM 1.3E-06 Drinking water 1.1E-05 75 Dermal bathing 1.4E-07

Combined DW/DM 1.1E-05 Drinking water 5.3E-05 90 Dermal bathing 6.5E-07

Combined DW/DM 5.4E-05 Drinking water 1.2E-04 95 Dermal bathing 1.5E-06

Combined DW/DM 1.2E-04 Drinking water 4.5E-04 99 Dermal bathing 5.5E-06

Combined DW/DM 4.6E-04

A-49

# Table A-14b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methyl ethyl ketone

CAS 78-93-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 1.6E-17 50 Drinking water 6.0E-17

Dermal bathing 7.7E-19 Combined DW/SH/DM 8.1E-17 Shower 6.0E-12 75 Drinking water 3.0E-11

Dermal bathing 3.0E-13 Combined DW/SH/DM 3.8E-11 Shower 5.1E-10 90 Drinking water 2.5E-09

Dermal bathing 2.5E-11 Combined DW/SH/DM 3.2E-09 Shower 3.6E-09 95 Drinking water 1.6E-08

Dermal bathing 1.7E-10 Combined DW/SH/DM 2.0E-08 Shower 7.1E-08 99 Drinking water 2.7E-07

Dermal bathing 3.3E-09 Combined DW/SH/DM 3.4E-07 Child Noncancer Drinking water 1.5E-16 50 Dermal bathing 1.8E-18

Combined DW/DM 1.5E-16 Drinking water 5.9E-11 75 Dermal bathing 8.3E-13

Combined DW/DM 6.1E-11 Drinking water 5.1E-09 90 Dermal bathing 6.7E-11

Combined DW/DM 5.1E-09 Drinking water 3.4E-08 95 Dermal bathing 4.2E-10

Combined DW/DM 3.4E-08 Drinking water 6.1E-07 99 Dermal bathing 7.9E-09

Combined DW/DM 6.1E-07

A-50

# Table A-15a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Methyl isobutyl ketone

CAS 108-10-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 2.4E-09 50 Inhalation 7.5E-09 75 Inhalation 1.8E-08 90 Inhalation 3.0E-08 95 Inhalation 7.6E-08 99 Child Noncancer Inhalation 2.5E-09 50 Inhalation 7.7E-09 75 Inhalation 1.9E-08 90 Inhalation 3.1E-08 95 Inhalation 7.7E-08 99 

## Composite Liner
Adult Noncancer Inhalation 2.2E-09 50 Inhalation 6.9E-09 75 Inhalation 1.7E-08 90 Inhalation 2.8E-08 95 Inhalation 7.2E-08 99 Child Noncancer Inhalation 2.3E-09 50 Inhalation 7.2E-09 75 Inhalation 1.7E-08 90 Inhalation 2.9E-08 95 Inhalation 7.3E-08 99

A-51

# Table A-15b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methyl isobutyl ketone

CAS 108-10-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 1.7E-07 50 Drinking water 1.6E-06

Dermal bathing 5.8E-08 Shower 1.6E-06 75 Drinking water 1.5E-05

Dermal bathing 5.3E-07 Shower 8.1E-06 90 Drinking water 7.1E-05

Dermal bathing 2.6E-06 Shower 1.8E-05 95 Drinking water 1.7E-04

Dermal bathing 5.8E-06 Shower 7.7E-05 99 Drinking water 7.8E-04

Dermal bathing 2.4E-05 Child Noncancer Drinking water 3.3E-06 50 Dermal bathing 1.5E-07

Drinking water 3.3E-05 75 Dermal bathing 1.4E-06

Drinking water 1.6E-04 90 Dermal bathing 6.9E-06

Drinking water 3.8E-04 95 Dermal bathing 1.6E-05

Drinking water 1.6E-03 99 Dermal bathing 6.7E-05

A-52

# Table A-15b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methyl isobutyl ketone

CAS 108-10-1

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 4.3E-17 50 Drinking water 4.3E-16

Dermal bathing 1.5E-17 Shower 1.4E-11 75 Drinking water 1.3E-10

Dermal bathing 4.8E-12 Shower 8.8E-10 90 Drinking water 8.5E-09

Dermal bathing 3.0E-10 Shower 6.4E-09 95 Drinking water 6.1E-08

Dermal bathing 2.2E-09 Shower 1.1E-07 99 Drinking water 8.6E-07

Dermal bathing 3.2E-08 Child Noncancer Drinking water 9.5E-16 50 Dermal bathing 4.0E-17

Drinking water 2.9E-10 75 Dermal bathing 1.3E-11

Drinking water 1.8E-08 90 Dermal bathing 8.0E-10

Drinking water 1.2E-07 95 Dermal bathing 5.5E-09

Drinking water 1.6E-06 99 Dermal bathing 7.5E-08

A-53

# Table A-16a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Methylene chloride

CAS 75-09-2

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Inhalation 4.5E-12 50 Inhalation 1.5E-11 75 Inhalation 4.1E-11 90 Inhalation 6.9E-11 95 Inhalation 1.8E-10 99 Child Cancer Inhalation 1.8E-12 50 Inhalation 6.7E-12 75 Inhalation 1.8E-11 90 Inhalation 3.1E-11 95 Inhalation 8.5E-11 99 Adult Noncancer Inhalation 1.5E-07 50 Inhalation 4.3E-07 75 Inhalation 9.9E-07 90 Inhalation 1.6E-06 95 Inhalation 3.7E-06 99 Child Noncancer Inhalation 1.5E-07 50 Inhalation 4.5E-07 75 Inhalation 1.0E-06 90 Inhalation 1.6E-06 95 Inhalation 3.7E-06 99

A-54

# Table A-16a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Methylene chloride

CAS 75-09-2

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Cancer Inhalation 4.6E-12 50 Inhalation 1.5E-11 75 Inhalation 4.1E-11 90 Inhalation 7.0E-11 95 Inhalation 1.8E-10 99 Child Cancer Inhalation 1.9E-12 50 Inhalation 6.8E-12 75 Inhalation 1.8E-11 90 Inhalation 3.1E-11 95 Inhalation 8.5E-11 99 Adult Noncancer Inhalation 1.5E-07 50 Inhalation 4.4E-07 75 Inhalation 9.9E-07 90 Inhalation 1.6E-06 95 Inhalation 3.6E-06 99 Child Noncancer Inhalation 1.6E-07 50 Inhalation 4.6E-07 75 Inhalation 1.0E-06 90 Inhalation 1.7E-06 95 Inhalation 3.7E-06 99

A-55

# Table A-16b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methylene chloride

CAS 75-09-2

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Shower 8.4E-10 50 Drinking water 7.6E-10

Dermal bathing 3.4E-11 Combined DW/SH/DM 1.9E-09 Shower 8.3E-09 75 Drinking water 7.5E-09

Dermal bathing 3.1E-10 Combined DW/SH/DM 1.8E-08 Shower 4.4E-08 90 Drinking water 3.7E-08

Dermal bathing 1.5E-09 Combined DW/SH/DM 8.8E-08 Shower 1.0E-07 95 Drinking water 8.1E-08

Dermal bathing 3.2E-09 Combined DW/SH/DM 1.9E-07 Shower 4.3E-07 99 Drinking water 3.4E-07

Dermal bathing 1.4E-08 Combined DW/SH/DM 7.5E-07 Child Cancer Drinking water 7.3E-10 50 Dermal bathing 3.8E-11

Combined DW/DM 7.8E-10 Drinking water 6.5E-09 75 Dermal bathing 3.3E-10

Combined DW/DM 6.9E-09 Drinking water 3.0E-08 90 Dermal bathing 1.5E-09

Combined DW/DM 3.2E-08 Drinking water 6.7E-08 95 Dermal bathing 3.4E-09

Combined DW/DM 7.0E-08 Drinking water 2.7E-07 99 Dermal bathing 1.4E-08

Combined DW/DM 2.9E-07 Adult Noncancer Shower 2.9E-05 50 Drinking water 1.2E-05

Dermal bathing 5.3E-07 Shower 2.6E-04 75 Drinking water 9.4E-05

Dermal bathing 4.2E-06
A-56

# Table A-16b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methylene chloride

CAS 75-09-2

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft

Shower 1.2E-03 90 Drinking water 4.3E-04

Dermal bathing 1.8E-05 Shower 2.7E-03 95 Drinking water 9.0E-04

Dermal bathing 3.6E-05 Shower 1.0E-02 99 Drinking water 3.3E-03

Dermal bathing 1.3E-04 Child Noncancer Drinking water 2.5E-05 50 Dermal bathing 1.4E-06

Drinking water 2.2E-04 75 Dermal bathing 1.1E-05

Drinking water 9.2E-04 90 Dermal bathing 4.5E-05

Drinking water 1.9E-03 95 Dermal bathing 9.3E-05

Drinking water 7.1E-03 99 Dermal bathing 3.5E-04

A-57

# Table A-16b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methylene chloride

CAS 75-09-2

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Cancer Shower 2.9E-24 50 Drinking water 1.9E-24

Dermal bathing 9.0E-26 Combined DW/SH/DM 5.8E-24 Shower 2.4E-14 75 Drinking water 2.2E-14

Dermal bathing 9.5E-16 Combined DW/SH/DM 5.5E-14 Shower 3.4E-12 90 Drinking water 2.8E-12

Dermal bathing 1.2E-13 Combined DW/SH/DM 7.2E-12 Shower 2.4E-11 95 Drinking water 2.2E-11

Dermal bathing 8.6E-13 Combined DW/SH/DM 4.9E-11 Shower 5.3E-10 99 Drinking water 3.9E-10

Dermal bathing 1.7E-11 Combined DW/SH/DM 9.7E-10 Child Cancer Drinking water 2.4E-24 50 Dermal bathing 1.6E-25

Combined DW/DM 2.5E-24 Drinking water 2.2E-14 75 Dermal bathing 1.1E-15

Combined DW/DM 2.3E-14 Drinking water 2.5E-12 90 Dermal bathing 1.3E-13

Combined DW/DM 2.7E-12 Drinking water 1.8E-11 95 Dermal bathing 9.6E-13

Combined DW/DM 1.9E-11 Drinking water 2.9E-10 99 Dermal bathing 1.6E-11

Combined DW/DM 3.0E-10 Adult Noncancer Shower 7.9E-20 50 Drinking water 3.1E-20

Dermal bathing 1.6E-21 Shower 8.6E-10 75 Drinking water 3.5E-10

Dermal bathing 1.4E-11
A-58

# Table A-16b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Methylene chloride

CAS 75-09-2

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft

Shower 1.0E-07 90 Drinking water 3.9E-08

Dermal bathing 1.6E-09 Shower 7.5E-07 95 Drinking water 2.6E-07

Dermal bathing 1.1E-08 Shower 1.4E-05 99 Drinking water 4.0E-06

Dermal bathing 1.8E-07 Child Noncancer Drinking water 7.2E-20 50 Dermal bathing 4.2E-21

Drinking water 7.0E-10 75 Dermal bathing 3.5E-11

Drinking water 8.3E-08 90 Dermal bathing 4.3E-09

Drinking water 5.4E-07 95 Dermal bathing 2.8E-08

Drinking water 9.3E-06 99 Dermal bathing 4.2E-07

A-59

# Table A-17a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Tetrachloroethylene

CAS 127-18-4

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 1.8E-07 50 Inhalation 5.4E-07 75 Inhalation 1.2E-06 90 Inhalation 1.9E-06 95 Inhalation 4.4E-06 99 Child Noncancer Inhalation 2.0E-07 50 Inhalation 5.9E-07 75 Inhalation 1.3E-06 90 Inhalation 2.1E-06 95 Inhalation 4.6E-06 99 

## Composite Liner
Adult Noncancer Inhalation 1.9E-07 50 Inhalation 5.6E-07 75 Inhalation 1.3E-06 90 Inhalation 1.9E-06 95 Inhalation 4.3E-06 99 Child Noncancer Inhalation 2.1E-07 50 Inhalation 6.2E-07 75 Inhalation 1.4E-06 90 Inhalation 2.2E-06 95 Inhalation 4.6E-06 99

A-60

# Table A-17b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Tetrachloroethylene

CAS 127-18-4

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 4.7E-05 50 Drinking water 8.2E-05

Dermal bathing 1.9E-05 Shower 4.8E-04 75 Drinking water 7.5E-04

Dermal bathing 1.7E-04 Shower 2.5E-03 90 Drinking water 3.7E-03

Dermal bathing 8.0E-04 Shower 6.0E-03 95 Drinking water 8.0E-03

Dermal bathing 1.8E-03 Shower 2.5E-02 99 Drinking water 3.2E-02

Dermal bathing 7.0E-03 Child Noncancer Drinking water 1.8E-04 50 Dermal bathing 5.1E-05

Drinking water 1.6E-03 75 Dermal bathing 4.3E-04

Drinking water 7.7E-03 90 Dermal bathing 2.1E-03

Drinking water 1.8E-02 95 Dermal bathing 4.7E-03

Drinking water 7.9E-02 99 Dermal bathing 1.8E-02

A-61

# Table A-17b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Tetrachloroethylene

CAS 127-18-4

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 9.5E-15 50 Drinking water 2.0E-14

Dermal bathing 3.8E-15 Shower 1.1E-07 75 Drinking water 1.9E-07

Dermal bathing 4.2E-08 Shower 5.8E-06 90 Drinking water 8.8E-06

Dermal bathing 2.1E-06 Shower 3.1E-05 95 Drinking water 4.5E-05

Dermal bathing 1.0E-05 Shower 4.4E-04 99 Drinking water 5.3E-04

Dermal bathing 1.2E-04 Child Noncancer Drinking water 3.7E-14 50 Dermal bathing 1.1E-14

Drinking water 3.8E-07 75 Dermal bathing 1.1E-07

Drinking water 1.8E-05 90 Dermal bathing 5.2E-06

Drinking water 9.1E-05 95 Dermal bathing 2.4E-05

Drinking water 1.1E-03 99 Dermal bathing 2.7E-04

A-62

# Table A-17a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Tetrachloroethylene(high)*

CAS 127-18-4(H)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Inhalation 5.4E-11 50 Inhalation 1.7E-10 75 Inhalation 4.6E-10 90 Inhalation 7.5E-10 95 Inhalation 2.0E-09 99 Child Cancer Inhalation 2.3E-11 50 Inhalation 8.2E-11 75 Inhalation 2.2E-10 90 Inhalation 3.6E-10 95 Inhalation 9.2E-10 99 

## Composite Liner
Adult Cancer Inhalation 5.7E-11 50 Inhalation 1.8E-10 75 Inhalation 4.8E-10 90 Inhalation 7.9E-10 95 Inhalation 2.0E-09 99 Child Cancer Inhalation 2.5E-11 50 Inhalation 8.6E-11 75 Inhalation 2.2E-10 90 Inhalation 3.7E-10 95 Inhalation 9.8E-10 99

A-63

# Table A-17b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Tetrachloroethylene(high)*

CAS 127-18-4(H)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Shower 1.3E-08 50 Drinking water 6.5E-08

Dermal bathing 1.6E-08 Combined DW/SH/DM 1.1E-07 Shower 1.5E-07 75 Drinking water 7.1E-07

Dermal bathing 1.5E-07 Combined DW/SH/DM 1.1E-06 Shower 8.8E-07 90 Drinking water 3.8E-06

Dermal bathing 8.4E-07 Combined DW/SH/DM 5.9E-06 Shower 2.2E-06 95 Drinking water 9.0E-06

Dermal bathing 1.9E-06 Combined DW/SH/DM 1.3E-05 Shower 1.0E-05 99 Drinking water 3.5E-05

Dermal bathing 8.0E-06 Combined DW/SH/DM 5.5E-05 Child Cancer Drinking water 5.8E-08 50 Dermal bathing 1.6E-08

Combined DW/DM 7.9E-08 Drinking water 6.0E-07 75 Dermal bathing 1.6E-07

Combined DW/DM 7.8E-07 Drinking water 3.2E-06 90 Dermal bathing 8.6E-07

Combined DW/DM 4.0E-06 Drinking water 7.5E-06 95 Dermal bathing 2.0E-06

Combined DW/DM 9.5E-06 Drinking water 3.3E-05 99 Dermal bathing 8.9E-06

Combined DW/DM 4.1E-05

A-64

# Table A-17b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Tetrachloroethylene(high)*

CAS 127-18-4(H)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Cancer Shower 2.8E-18 50 Drinking water 1.6E-17

Dermal bathing 3.2E-18 Combined DW/SH/DM 2.3E-17 Shower 3.2E-11 75 Drinking water 1.6E-10

Dermal bathing 3.5E-11 Combined DW/SH/DM 2.5E-10 Shower 1.6E-09 90 Drinking water 8.0E-09

Dermal bathing 1.8E-09 Combined DW/SH/DM 1.2E-08 Shower 1.1E-08 95 Drinking water 5.0E-08

Dermal bathing 1.0E-08 Combined DW/SH/DM 7.6E-08 Shower 1.5E-07 99 Drinking water 6.2E-07

Dermal bathing 1.4E-07 Combined DW/SH/DM 9.5E-07 Child Cancer Drinking water 1.4E-17 50 Dermal bathing 4.2E-18

Combined DW/DM 1.9E-17 Drinking water 1.4E-10 75 Dermal bathing 4.0E-11

Combined DW/DM 1.9E-10 Drinking water 7.0E-09 90 Dermal bathing 1.9E-09

Combined DW/DM 9.2E-09 Drinking water 3.7E-08 95 Dermal bathing 9.8E-09

Combined DW/DM 4.8E-08 Drinking water 4.3E-07 99 Dermal bathing 1.3E-07

Combined DW/DM 5.8E-07

A-65

# Table A-17a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Tetrachloroethylene(low)*

CAS 127-18-4(L)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Inhalation 6.5E-12 50 Inhalation 2.1E-11 75 Inhalation 5.5E-11 90 Inhalation 9.1E-11 95 Inhalation 2.4E-10 99 Child Cancer Inhalation 2.8E-12 50 Inhalation 9.9E-12 75 Inhalation 2.6E-11 90 Inhalation 4.3E-11 95 Inhalation 1.1E-10 99 

## Composite Liner
Adult Cancer Inhalation 6.9E-12 50 Inhalation 2.2E-11 75 Inhalation 5.7E-11 90 Inhalation 9.5E-11 95 Inhalation 2.4E-10 99 Child Cancer Inhalation 3.0E-12 50 Inhalation 1.0E-11 75 Inhalation 2.7E-11 90 Inhalation 4.4E-11 95 Inhalation 1.2E-10 99

A-66

# Table A-17b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Tetrachloroethylene(low)*

CAS 127-18-4(L)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Shower 1.6E-09 50 Drinking water 6.5E-08

Dermal bathing 1.6E-08 Combined DW/SH/DM 8.7E-08 Shower 1.8E-08 75 Drinking water 7.1E-07

Dermal bathing 1.5E-07 Combined DW/SH/DM 9.2E-07 Shower 1.1E-07 90 Drinking water 3.8E-06

Dermal bathing 8.4E-07 Combined DW/SH/DM 5.0E-06 Shower 2.6E-07 95 Drinking water 9.0E-06

Dermal bathing 1.9E-06 Combined DW/SH/DM 1.1E-05 Shower 1.2E-06 99 Drinking water 3.5E-05

Dermal bathing 8.0E-06 Combined DW/SH/DM 4.7E-05 Child Cancer Drinking water 5.8E-08 50 Dermal bathing 1.6E-08

Combined DW/DM 7.9E-08 Drinking water 6.0E-07 75 Dermal bathing 1.6E-07

Combined DW/DM 7.8E-07 Drinking water 3.2E-06 90 Dermal bathing 8.6E-07

Combined DW/DM 4.0E-06 Drinking water 7.5E-06 95 Dermal bathing 2.0E-06

Combined DW/DM 9.5E-06 Drinking water 3.3E-05 99 Dermal bathing 8.9E-06

Combined DW/DM 4.1E-05

A-67

# Table A-17b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Tetrachloroethylene(low)*

CAS 127-18-4(L)

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Cancer Shower 3.4E-19 50 Drinking water 1.6E-17

Dermal bathing 3.2E-18 Combined DW/SH/DM 2.0E-17 Shower 3.8E-12 75 Drinking water 1.6E-10

Dermal bathing 3.5E-11 Combined DW/SH/DM 2.1E-10 Shower 2.0E-10 90 Drinking water 8.0E-09

Dermal bathing 1.8E-09 Combined DW/SH/DM 1.0E-08 Shower 1.3E-09 95 Drinking water 5.0E-08

Dermal bathing 1.0E-08 Combined DW/SH/DM 6.3E-08 Shower 1.8E-08 99 Drinking water 6.2E-07

Dermal bathing 1.4E-07 Combined DW/SH/DM 8.2E-07 Child Cancer Drinking water 1.4E-17 50 Dermal bathing 4.2E-18

Combined DW/DM 1.9E-17 Drinking water 1.4E-10 75 Dermal bathing 4.0E-11

Combined DW/DM 1.9E-10 Drinking water 7.0E-09 90 Dermal bathing 1.9E-09

Combined DW/DM 9.2E-09 Drinking water 3.7E-08 95 Dermal bathing 9.8E-09

Combined DW/DM 4.8E-08 Drinking water 4.3E-07 99 Dermal bathing 1.3E-07

Combined DW/DM 5.8E-07

A-68

# Table A-18a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Toluene

CAS 108-88-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 6.7E-09 50 Inhalation 2.0E-08 75 Inhalation 4.6E-08 90 Inhalation 7.2E-08 95 Inhalation 1.6E-07 99 Child Noncancer Inhalation 7.1E-09 50 Inhalation 2.1E-08 75 Inhalation 4.9E-08 90 Inhalation 7.8E-08 95 Inhalation 1.8E-07 99 

## Composite Liner
Adult Noncancer Inhalation 6.6E-09 50 Inhalation 2.0E-08 75 Inhalation 4.5E-08 90 Inhalation 7.0E-08 95 Inhalation 1.6E-07 99 Child Noncancer Inhalation 7.0E-09 50 Inhalation 2.1E-08 75 Inhalation 4.8E-08 90 Inhalation 7.6E-08 95 Inhalation 1.8E-07 99

A-69

# Table A-18b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Toluene

CAS 108-88-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 2.5E-06 50 Drinking water 9.8E-06

Dermal bathing 4.0E-06 Shower 2.7E-05 75 Drinking water 8.8E-05

Dermal bathing 3.6E-05 Shower 1.3E-04 90 Drinking water 4.3E-04

Dermal bathing 1.6E-04 Shower 3.1E-04 95 Drinking water 9.3E-04

Dermal bathing 3.5E-04 Shower 1.4E-03 99 Drinking water 3.9E-03

Dermal bathing 1.4E-03 Child Noncancer Drinking water 2.0E-05 50 Dermal bathing 1.0E-05

Drinking water 1.9E-04 75 Dermal bathing 9.2E-05

Drinking water 8.9E-04 90 Dermal bathing 4.2E-04

Drinking water 2.0E-03 95 Dermal bathing 9.1E-04

Drinking water 9.1E-03 99 Dermal bathing 3.5E-03

A-70

# Table A-18b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Toluene

CAS 108-88-3

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 1.8E-16 50 Drinking water 5.9E-16

Dermal bathing 2.5E-16 Shower 3.6E-09 75 Drinking water 1.3E-08

Dermal bathing 5.1E-09 Shower 2.2E-07 90 Drinking water 7.4E-07

Dermal bathing 3.2E-07 Shower 1.3E-06 95 Drinking water 4.1E-06

Dermal bathing 1.7E-06 Shower 1.6E-05 99 Drinking water 5.1E-05

Dermal bathing 1.8E-05 Child Noncancer Drinking water 1.4E-15 50 Dermal bathing 6.9E-16

Drinking water 2.6E-08 75 Dermal bathing 1.3E-08

Drinking water 1.6E-06 90 Dermal bathing 7.8E-07

Drinking water 8.4E-06 95 Dermal bathing 4.0E-06

Drinking water 9.2E-05 99 Dermal bathing 4.2E-05

A-71

# Table A-19a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Trichloroethylene

CAS 79-01-6

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Inhalation 1.9E-11 50 Inhalation 6.1E-11 75 Inhalation 1.6E-10 90 Inhalation 2.6E-10 95 Inhalation 6.7E-10 99 Child Cancer Inhalation 7.9E-12 50 Inhalation 2.8E-11 75 Inhalation 7.4E-11 90 Inhalation 1.2E-10 95 Inhalation 3.2E-10 99 Adult Noncancer Inhalation 9.1E-08 50 Inhalation 2.7E-07 75 Inhalation 6.2E-07 90 Inhalation 9.7E-07 95 Inhalation 2.2E-06 99 Child Noncancer Inhalation 1.0E-07 50 Inhalation 3.0E-07 75 Inhalation 6.7E-07 90 Inhalation 1.1E-06 95 Inhalation 2.3E-06 99

A-72

# Table A-19a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Trichloroethylene

CAS 79-01-6

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Cancer Inhalation 2.0E-11 50 Inhalation 6.3E-11 75 Inhalation 1.6E-10 90 Inhalation 2.7E-10 95 Inhalation 6.8E-10 99 Child Cancer Inhalation 8.5E-12 50 Inhalation 3.0E-11 75 Inhalation 7.6E-11 90 Inhalation 1.3E-10 95 Inhalation 3.3E-10 99 Adult Noncancer Inhalation 9.8E-08 50 Inhalation 2.9E-07 75 Inhalation 6.5E-07 90 Inhalation 9.9E-07 95 Inhalation 2.2E-06 99 Child Noncancer Inhalation 1.1E-07 50 Inhalation 3.1E-07 75 Inhalation 7.0E-07 90 Inhalation 1.1E-06 95 Inhalation 2.4E-06 99

A-73

# Table A-19b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Trichloroethylene

CAS 79-01-6

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Cancer Shower 4.9E-09 50 Drinking water 1.6E-09

Dermal bathing 5.2E-10 Combined DW/SH/DM 7.9E-09 Shower 5.6E-08 75 Drinking water 1.8E-08

Dermal bathing 5.5E-09 Combined DW/SH/DM 8.8E-08 Shower 3.2E-07 90 Drinking water 9.4E-08

Dermal bathing 2.7E-08 Combined DW/SH/DM 4.6E-07 Shower 8.0E-07 95 Drinking water 2.4E-07

Dermal bathing 6.6E-08 Combined DW/SH/DM 1.1E-06 Shower 3.6E-06 99 Drinking water 8.8E-07

Dermal bathing 2.6E-07 Combined DW/SH/DM 4.8E-06 Child Cancer Drinking water 1.5E-09 50 Dermal bathing 5.6E-10

Combined DW/DM 2.2E-09 Drinking water 1.6E-08 75 Dermal bathing 5.5E-09

Combined DW/DM 2.3E-08 Drinking water 8.2E-08 90 Dermal bathing 2.9E-08

Combined DW/DM 1.1E-07 Drinking water 1.9E-07 95 Dermal bathing 6.9E-08

Combined DW/DM 2.6E-07 Drinking water 7.6E-07 99 Dermal bathing 2.5E-07

Combined DW/DM 1.1E-06 Adult Noncancer Shower 2.5E-05 50 Shower 2.8E-04 75 Shower 1.4E-03 90 Shower 3.2E-03 95 Shower 1.3E-02 99

A-74

# Table A-19b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Trichloroethylene

CAS 79-01-6

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Cancer Shower 1.1E-18 50 Drinking water 4.2E-19

Dermal bathing 1.2E-19 Combined DW/SH/DM 1.9E-18 Shower 8.1E-12 75 Drinking water 2.9E-12

Dermal bathing 8.4E-13 Combined DW/SH/DM 1.4E-11 Shower 4.7E-10 90 Drinking water 1.6E-10

Dermal bathing 4.6E-11 Combined DW/SH/DM 7.5E-10 Shower 2.9E-09 95 Drinking water 9.8E-10

Dermal bathing 2.6E-10 Combined DW/SH/DM 4.2E-09 Shower 4.2E-08 99 Drinking water 1.3E-08

Dermal bathing 3.3E-09 Combined DW/SH/DM 5.4E-08 Child Cancer Drinking water 3.0E-19 50 Dermal bathing 1.2E-19

Combined DW/DM 4.3E-19 Drinking water 2.5E-12 75 Dermal bathing 9.4E-13

Combined DW/DM 3.7E-12 Drinking water 1.4E-10 90 Dermal bathing 4.6E-11

Combined DW/DM 1.9E-10 Drinking water 7.2E-10 95 Dermal bathing 2.6E-10

Combined DW/DM 9.9E-10 Drinking water 7.8E-09 99 Dermal bathing 3.2E-09

Combined DW/DM 1.1E-08 Adult Noncancer Shower 5.3E-15 50 Shower 4.2E-08 75 Shower 2.3E-06 90 Shower 1.3E-05 95 Shower 1.7E-04 99

A-75

# Table A-20a. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Inhalation of Ambient Air of Xylene (mixed isomers)

CAS 1330-20-7

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Inhalation 1.2E-07 50 Inhalation 3.6E-07 75 Inhalation 8.5E-07 90 Inhalation 1.4E-06 95 Inhalation 3.4E-06 99 Child Noncancer Inhalation 1.3E-07 50 Inhalation 3.8E-07 75 Inhalation 9.0E-07 90 Inhalation 1.4E-06 95 Inhalation 3.6E-06 99 

## Composite Liner
Adult Noncancer Inhalation 1.1E-07 50 Inhalation 3.4E-07 75 Inhalation 7.9E-07 90 Inhalation 1.3E-06 95 Inhalation 3.0E-06 99 Child Noncancer Inhalation 1.2E-07 50 Inhalation 3.6E-07 75 Inhalation 8.3E-07 90 Inhalation 1.3E-06 95 Inhalation 3.2E-06 99

A-76

# Table A-20b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Xylene (mixed isomers)

CAS 1330-20-7

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## No Liner
Adult Noncancer Shower 4.4E-05 50 Drinking water 1.4E-06

Dermal bathing 1.0E-06 Shower 4.1E-04 75 Drinking water 1.1E-05

Dermal bathing 8.2E-06 Shower 2.1E-03 90 Drinking water 5.6E-05

Dermal bathing 3.8E-05 Shower 5.0E-03 95 Drinking water 1.2E-04

Dermal bathing 8.1E-05 Shower 1.9E-02 99 Drinking water 4.8E-04

Dermal bathing 3.2E-04 Child Noncancer Drinking water 2.8E-06 50 Dermal bathing 2.5E-06

Drinking water 2.4E-05 75 Dermal bathing 2.0E-05

Drinking water 1.1E-04 90 Dermal bathing 9.4E-05

Drinking water 2.6E-04 95 Dermal bathing 2.0E-04

Drinking water 1.0E-03 99 Dermal bathing 7.7E-04

A-77

# Table A-20b. Risk Results for Select Percentiles at the Unitized Mass Loading Rate (1 kg / year) Groundwater Pathways of Xylene (mixed isomers)

CAS 1330-20-7

Effect Receptor Percentile Pathway Risk or HQ Appendix A Theoretical Risk Distributions Draft



## Composite Liner
Adult Noncancer Shower 1.1E-17 50 Drinking water 4.0E-19

Dermal bathing 2.7E-19 Shower 1.7E-08 75 Drinking water 5.0E-10

Dermal bathing 3.5E-10 Shower 1.9E-06 90 Drinking water 5.3E-08

Dermal bathing 3.6E-08 Shower 1.3E-05 95 Drinking water 3.4E-07

Dermal bathing 2.3E-07 Shower 2.2E-04 99 Drinking water 5.3E-06

Dermal bathing 3.8E-06 Child Noncancer Drinking water 8.2E-19 50 Dermal bathing 6.7E-19

Drinking water 1.1E-09 75 Dermal bathing 9.3E-10

Drinking water 1.0E-07 90 Dermal bathing 9.5E-08

Drinking water 7.0E-07 95 Dermal bathing 6.0E-07

Drinking water 1.2E-05 99 Dermal bathing 9.6E-06

A-78

### Draft Appendix B Chemical-Specific Parameters



## B-1 

# Appendix B Chemical-Specific Parameters for Landfill Source and Shower Models
This appendix presents values and references for the chemical-specific parameters used in the landfill source and shower models, including

 

## Chemical/physical properties

 

## Degradation rates in the landfill waste

 

## Geomembrane permeation coefficients

 

## Parameters for adjusting diffusion coefficien ts and Henry’s constants for temperature effects. Methods for calculating model parameter values from other available data, where applicable (e.g., temperature adjustment to Henry’ s law constants, air and water diffusivities) are also presented.
Tables B-1 through B-20 present the data for each solvent (in alphabetical order; note solvents whose names begin with a number are listed first). The tables include the parameter values and references and also indicate whether a value is taken directly from the source cited or calculated based on equations in that source. The preferred source for chemical/physical properties was the Superfund Chemical Data Matrix (SCDM) (U.S. EPA, 2002), because it is peer reviewed and contains all of the solvents evaluated. Other sources provided chemical/physical property values that were not available in SCDM. The additional sources of chemical/physical property data included the following Internet databases in order of priority: H azardous Substances Data Bank (HSDB) (NLM, 2006) and CHEMFATE (SRC, 2002). If certain data were not found in these sources, the Merck Index was used (Budavari, 1989). In a few cases, data were not available from any of the sources listed above and were estimated using EPA’s Estimation Programs Interface for Windows (EPIWIN) software (available at: http://www.epa.gov/opptintr/exposure/pubs/episuitedl.htm). The rest of this appendix provides additional data collection and derivation details for air and water diffusivities ( Section B.1 ), degradation rates in landfill waste ( Section B.2 ), geomembrane permeation coefficient ( Section B.3 ), Henry’s law constant adjustment for temperature effects ( Section B.4 ), and parameters used in the estimation of dermal exposures to chemicals in water ( Section B.5 ).

### Parameter Description Value

Draft 

## Table B-1. Chemical Parameters for 1,1,2-Trichloroethane (79-00-5)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 2.86E-02 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 8.18E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.27E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 8.24E-04 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 6.4E-03 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.10E+01 Reid et. al., 1977 Pc (atm)

Solubility 4.42E+03 SCDM Sol (mg/L)

Lag time per event 6.00E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.14E+02 SCDM tb (degC)

Critical temperature 3.29E+02 Reid et. al., 1977 tc (degC)

Molar volume 9.74E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-2

### Parameter Description Value

Draft 

## Table B-2. Chemical Parameters for 2-Ethoxyethanol (110-80-5)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 1.50E-03 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 8.55E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.36E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 1.23E-07 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 4.2E-04 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.68E+01 Gonzalez et al., 2001 Pc (atm)

Solubility miscible SCDM Sol (mg/L)

Lag time per event 3.40E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.35E+02 SCDM tb (degC)

Critical temperature 3.13E+02 Gonzalez et al., 2001 tc (degC)

Molar volume 9.68E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-3

### Parameter Description Value

Draft 

## Table B-3. Chemical Parameters for Acetone (67-64-1)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 1.50E-03 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 1.06E-01 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 1.20E-05 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 3.88E-05 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 5.1E-04 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.64E+01 Reid et al., 1977 Pc (atm)

Solubility miscible SCDM Sol (mg/L)

Lag time per event 2.30E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 5.60E+01 SCDM tb (degC)

Critical temperature 2.35E+02 Reid et al., 1977 tc (degC)

Molar volume 6.69E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-4

### Parameter Description Value

Draft 

## Table B-4. Chemical Parameters for Benzene (71-43-2)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 5.06E-02 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 8.95E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 1.03E-05 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 5.55E-03 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 1.5E-02 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.83E+01 Reid et. al., 1977 Pc (atm)

Solubility 1.75E+03 SCDM Sol (mg/L)

Lag time per event 2.90E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 8.00E+01 SCDM tb (degC)

Critical temperature 2.89E+02 Reid et. al., 1977 tc (degC)

Molar volume 9.07E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-5

### Parameter Description Value

Draft 

## Table B-5. Chemical Parameters for Butanol (71-36-3)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 7.30E-03 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 8.99E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.84E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 8.81E-06 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 2.2E-03 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.36E+01 HSDB Pc (atm)

Solubility 7.40E+04 SCDM Sol (mg/L)

Lag time per event 2.80E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.18E+02 SCDM tb (degC)

Critical temperature 2.90E+02 HSDB tc (degC)

Molar volume 9.13E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-6

### Parameter Description Value

Draft 

## Table B-6. Chemical Parameters for Chlorobenzene (108-90-7)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 1.19E-01 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 7.96E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.17E-05 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 3.70E-03 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 2.9E-02 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.46E+01 Reid et. al., 1977 Pc (atm)

Solubility 4.72E+02 SCDM Sol (mg/L)

Lag time per event 4.60E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.32E+02 SCDM tb (degC)

Critical temperature 3.59E+02 Reid et. al., 1977 tc (degC)

Molar volume 1.08E+02 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-7

### Parameter Description Value

Draft 

## Table B-7. Chemical Parameters for Cresols (total) (1319-77-3)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 3.16E-02 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 7.97E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.46E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 9.52E-07 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 7.9E-03 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.84E+01 KDB Pc (atm)

Solubility 2.34E+04 SCDM Sol (mg/L)

Lag time per event 4.30E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.98E+02 SCDM tb (degC)

Critical temperature 4.30E+02 KDB tc (degC)

Molar volume 1.09E+02 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-8

### Parameter Description Value

Draft 

## Table B-8. Chemical Parameters for Cyclohexanone (108-94-1)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 5.80E-03 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 8.21E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.11E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 9.00E-06 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 1.5E-03 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 3.80E+01 Reid et al., 1977 Pc (atm)

Solubility 5.00E+03 SCDM Sol (mg/L)

Lag time per event 3.80E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.55E+02 SCDM tb (degC)

Critical temperature 3.56E+02 Reid et al., 1977 tc (degC)

Molar volume 1.04E+02 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-9

### Parameter Description Value

Draft 

## Table B-9. Chemical Parameters for Dichlorobenzene, 1,2- (95-50-1)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 2.08E-01 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 7.28E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 8.32E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 1.90E-03 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 4.5E-02 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.05E+01 Reid et al., 1977 Pc (atm)

Solubility 1.56E+02 SCDM Sol (mg/L)

Lag time per event 7.10E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.80E+02 SCDM tb (degC)

Critical temperature 4.24E+02 Reid et al., 1977 tc (degC)

Molar volume 1.26E+02 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-10

### Parameter Description Value

Draft 

## Table B-10. Chemical Parameters for Ethyl acetate (141-78-6)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 5.20E-03 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 8.73E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.57E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 1.38E-04 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 1.4E-03 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 3.78E+01 Reid et al., 1977 Pc (atm)

Solubility 8.03E+04 SCDM Sol (mg/L)

Lag time per event 3.30E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 7.71E+01 SCDM tb (degC)

Critical temperature 2.50E+02 Reid et al., 1977 tc (degC)

Molar volume 9.28E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-11

### Parameter Description Value

Draft 

## Table B-11. Chemical Parameters for Ethyl benzene (100-41-4)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 1.92E-01 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 7.36E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 8.23E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 7.88E-03 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 4.9E-02 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 3.56E+01 Reid et al., 1977 Pc (atm)

Solubility 1.69E+02 SCDM Sol (mg/L)

Lag time per event 4.20E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.36E+02 SCDM tb (degC)

Critical temperature 3.44E+02 Reid et al., 1977 tc (degC)

Molar volume 1.32E+02 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-12

### Parameter Description Value

Draft 

## Table B-12. Chemical Parameters for Isobutanol (78-83-1)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 6.30E-03 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 8.99E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.84E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 1.18E-05 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 1.9E-03 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.24E+01 Reid et al., 1977 Pc (atm)

Solubility 8.50E+04 SCDM Sol (mg/L)

Lag time per event 2.80E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.08E+02 SCDM tb (degC)

Critical temperature 2.75E+02 Reid et al., 1977 tc (degC)

Molar volume 9.13E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-13

### Parameter Description Value

Draft 

## Table B-13. Chemical Parameters for Methanol (67-56-1)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 8.00E-04 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 1.62E-01 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 1.80E-05 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 4.55E-06 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 3.5E-04 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 7.99E+01 Reid et. al., 1977 Pc (atm)

Solubility miscible SCDM Sol (mg/L)

Lag time per event 1.60E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 6.46E+01 SCDM tb (degC)

Critical temperature 2.39E+02 Reid et. al., 1977 tc (degC)

Molar volume 2.99E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-14

### Parameter Description Value

Draft 

## Table B-14. Chemical Parameters for Methyl ethyl ketone (78-93-3)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 3.10E-03 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 9.19E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 1.03E-05 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 5.59E-05 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 9.5E-04 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.10E+01 Reid et al., 1977 Pc (atm)

Solubility 2.23E+05 SCDM Sol (mg/L)

Lag time per event 2.70E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 7.95E+01 SCDM tb (degC)

Critical temperature 2.62E+02 Reid et al., 1977 tc (degC)

Molar volume 8.73E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-15

### Parameter Description Value

Draft 

## Table B-15. Chemical Parameters for Methyl isobutyl ketone (108-10-1)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 1.02E-02 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 7.49E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 8.22E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 1.38E-04 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 2.7E-03 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 3.23E+01 Reid et al., 1977 Pc (atm)

Solubility 1.90E+04 SCDM Sol (mg/L)

Lag time per event 3.90E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.17E+02 SCDM tb (degC)

Critical temperature 2.98E+02 Reid et al., 1977 tc (degC)

Molar volume 1.28E+02 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-16

### Parameter Description Value

Draft 

## Table B-16. Chemical Parameters for Methylene chloride (75-09-2)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 1.26E-02 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 1.05E-01 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 1.23E-05 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 2.19E-03 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 3.5E-03 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 6.02E+01 HSDB Pc (atm)

Solubility 1.30E+04 SCDM Sol (mg/L)

Lag time per event 3.20E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 4.00E+01 SCDM tb (degC)

Critical temperature 2.37E+02 HSDB tc (degC)

Molar volume 5.95E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-17

### Parameter Description Value

Draft 

## Table B-17. Chemical Parameters for Tetrachloroethylene (127-18-4)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 5.42E-02 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 7.61E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 8.69E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 1.84E-02 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 1.1E-02 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.40E+01 Reid et al., 1977 Pc (atm)

Solubility 2.00E+02 SCDM Sol (mg/L)

Lag time per event 9.10E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.21E+02 SCDM tb (degC)

Critical temperature 3.47E+02 Reid et al., 1977 tc (degC)

Molar volume 1.11E+02 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-18

### Parameter Description Value

Draft 

## Table B-18. Chemical Parameters for Toluene (108-88-3)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 1.18E-01 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 8.04E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.11E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 6.64E-03 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 3.2E-02 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.06E+01 Reid et al., 1977 Pc (atm)

Solubility 5.26E+02 SCDM Sol (mg/L)

Lag time per event 3.50E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.11E+02 SCDM tb (degC)

Critical temperature 3.19E+02 Reid et al., 1977 tc (degC)

Molar volume 1.11E+02 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-19

### Parameter Description Value

Draft 

## Table B-19. Chemical Parameters for Trichloroethylene (79-01-6)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 8.00E-02 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 8.34E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 9.65E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 1.03E-02 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 1.8E-02 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 4.85E+01 Reid et al., 1977 Pc (atm)

Solubility 1.10E+03 SCDM Sol (mg/L)

Lag time per event 5.80E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 8.72E+01 SCDM tb (degC)

Critical temperature 2.98E+02 Reid et al., 1977 tc (degC)

Molar volume 9.35E+01 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-20

### Parameter Description Value

Draft 

## Table B-20. Chemical Parameters for Xylene (mixed isomers) (1330-20-7)

Reference/Notes Appendix B. Chemical Specific Parameters

Units

Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis 2.01E-01 Calculated based on U.S. EPA, 2004 B (unitless)

Diffusivity of chemical in air 7.36E-02 Calculated based on Lyman, 1990 for 25 deg C. Da (cm2/day)

Diffusion coefficient in water 8.23E-06 Calculated based on Lyman, 1990 for 25 deg C. Dw (cm2/day)

Henry's law constant 6.73E-03 SCDM HLC (atm-m3/mol)

Dermal permeability coefficient of compound in water 5.1E-02 Calculated based on U.S. EPA, 2004 Kp (cm/hr)

Critical pressure 3.55E+01 KDB Pc (atm)

Solubility 1.75E+02 SCDM Sol (mg/L)

Lag time per event 4.20E-01 Calculated based on U.S. EPA, 2004 tau (hr/event)

Boiling point 1.41E+02 SCDM tb (degC)

Critical temperature 3.48E+02 KDB tc (degC)

Molar volume 1.32E+02 Based on Lyman, 1990. Used to calculate constituent diffusivity in air and water Vmol (cm3/mol)



### B-21

### Draft Appendix B Chemical-Specific Parameters



## B-22 

# B.1 Air and Water Diffusivity
B.1.1 Diffusivity in Air ( D a



## ) The Fuller, Schettler, and Giddings (FSG) Method, as documented in Lyman et al. (1990), was used to calculate the diffusivity in air (see Equation B-1 ). The method uses the constituent’s molar volume and molecular weight and incorporates temperature effects. For landfill source model simulations, the temperature was the average waste temperature. For the shower model, the temperature was 25°C.



## D T M PV V a r

A B 

## = ×
+ − 

## 10 3 1 75

13 13 2 .
/ / 

## ( ) (Equation B-1)
where D a 

## = diffusivity in air (cm 2 

## /s) T = temperature (oC) P = density (g/cm 3 

## ) M r 

## = reciprocal of the reduced mass, as calculated below in Equation B-2 V A 

## = molar volume of air (cm 3 

## /mol) V B 

## = constituent molar volume (mol/m 3 

## ).

The reciprocal of the reduced mass, M r 

## , is calculated from the molecular weight of air and the molecular weight of the constituent:

) ( ) (

b a b a r 

## M M M M M × +

= 

## (Equation B-2)
where M a 

## = molecular weight of air (g/mol) M b 

## = constituent molecular weight (g/mol).

For constituents comprising only C, H, O, N, Cl, and S, Fuller, Schettler, and Giddings (1966) provide an estimation method for the constituent molar volume, V B 

## , based on the chemical structure of the molecule. The increments used in that method are shown in Table B-21

. Table B-21. Atomic and Structural Diffusion Volume Increments
Atom ▵ V B 

### (cm 3 

### /mol) C 16.5 H 1.98 O 5.48 N 5.69 Cl 19.5 S 17 Aromatic and heterocyclic rings -20.2

### Draft Appendix B Chemical-Specific Parameters



## B-23 For compounds containing elements other than C, H, O, N, Cl, and S, the molar volume can be estimated to be 85 to 90 percent of the LeBas volume (Lyman et al., 1990). Reid et al. (1977) provide increments for calculating the LeBas volume, shown in Table B-22

. Table B-22. Additive Volume Increments for Calculating LeBas Molar Volume

Atom Increment (cm 3 

### /mol) C 14.8 H 3.7 O (except as noted below) 7.4 In methyl esters and ethers 9.1 In ethyl esters and ethers 9.9 In higher esters and ethers 11.0 In acids 12.0 Joined to S, P, N 8.3 N: Double bonded 15.6 In primary amines 10.5 In secondary amines 12.0 Br 27.0 Cl 24.6 F 8.7 I 37.0 S 25.6 Ring: 3-Membered -6.0 4-Membered -8.5 5-Membered -11.5 6-Membered -15.0 Naphthalene -30.0 Anthracene -47.5 

## B.1.2 Diffusivity in Water ( D w



## ) The Hayduk and Laudie Method as documented in Lyman et al. (1990) was used to calculate the diffusivity in water (see Equation B-3 ). The method uses the molar volume of the constituent and the temperature-dependent viscosity of water. The function used to generate the diffusivity estimates includes viscosity values valid for temperatures between0° and 100°C; if the temperature is outside of that range, the nearest endpoint of the range (0°C for values below the range and 100°C for values above the range) is used. For landfill source model simulations,

### Draft Appendix B Chemical-Specific Parameters



## B-24 the temperature was the average waste temperature. For risk simulations, the temperature was 25°C.

589

. 0 14

. 1 5 

## 10 26

. 13

B w 

## V' vwt D × ×
= − 

## (Equation B-3)
where D w 

## = diffusivity in water (cm 2 

## /s) vwt = viscosity of the water (g/m-s) V' B 

## = LeBas molar volume (cm 3 

## /mol). 

# B.2 Degradation Rates in Landfill Waste
B.2.1 Anaerobic Biotic Decay in Water 

## Anaerobic degradation rates used in the source model were based on data values reported in various sources. The primary source was Howard et al. (1991). Alternative sources, specifically Aronson and Howard (1997) or U.S. EPA (1999), were used only if they provided significantly different values. No values were available for cyclohexanone, so an EPIWIN estimate was used. Although some biodegradation may occur in the air phase, parameter values and studies suggesting the occurrence of air phase biodegradation in landfills were unavailable. Data that were reported as rate constants were converted to half-lives (days):

k t ) 2 ln(
2 / 1 

## = (Equation B-4) where
t 1⁄2 

## = half-life (s) ln(2) = natural log of 2 k = rate constant (s -1 

## ). Table B-23. Biodegradation Half Lives (days)

CAS No. Solvent Half-life (days) Reference

79005 1,1,2-Trichloroethane 1,458 Howard et al. (1991)
110805 2-Ethoxyethanol 112 Howard et al. (1991)
67641 Acetone 187 Aronson and Howard (1997)
71432 Benzene 721 Howard et al. (1991)
71363 Butanol 54 Howard et al. (1991)
108907 Chlorobenzene 600 Howard et al. (1991)
1319773 Cresols (total) 2,390 U.S. EPA (1999)
108941 Cyclohexanone 1,350 EPIWIN

### Draft Appendix B Chemical-Specific Parameters



## B-25 CAS No. Solvent Half-life (days) Reference

95501 Dichlorobenzene, 1,2- 721 Howard et al. (1991)
141786 Ethyl acetate 28 Howard et al. (1991)
100414 Ethyl benzene 1,155 U.S. EPA (1999)
78831 Isobutanol 29 Howard et al. (1991)
67561 Methanol 3,151 U.S. EPA (1999)
78933 Methyl ethyl ketone 128 Aronson and Howard (1997)
108101 Methyl isobutyl ketone 28 Howard et al. (1991)
75092 Methylene chloride 112 Howard et al. (1991)
127184 Tetrachloroethylene 3,648 U.S. EPA (1999)
108883 Toluene 770 U.S. EPA (1999)
79016 Trichloroethylene 845 Aronson and Howard (1997)
1330207 Xylene (mixed isomers) 845 U.S. EPA (1999) 

## B.2.2 Abiotic Degradation 

## Hydrolysis may occur through a first-order degradation term in the source model. Estimates for the hydrolysis rate constants were taken from U.S. EPA (1993) for all chemicals except ethyl acetate, which was taken from HSDB (NLM, 2006). Because of the significant uncertainty, a uniform distribution that varied over two orders of magnitude was used for the hydrolysis half-life. However, the influence of abiotic degradation was negligible relative to biodegradation, because the abiotic degradation rates were orders of magnitude lower.


# B.3 Geomembrane Permeation Coefficient The migration of chemicals through a geomembrane liner or final cover is a three-step process (Sangam and Rowe, 2001):

 

## Partitioning (sorption) between the inner fluid containing the chemical and the geomembrane inner surface

 

## Diffusion through the geomembrane matrix

 

## Partitioning (desorption) between the geomembrane outer surface and the outer fluid (at the lower relative concentration). In dilute solutions, a linear relationship between the concentration in the fluid and the concentration on the geomembrane interface is generally sufficient to describe the sorptive partitioning: 1

1 

### Generic units are provided in this discussion, where M denotes mass units; L, length units; and T, time units.

### Draft Appendix B Chemical-Specific Parameters



## B-26 dg f g 

## K C C × = (Equation B-5) where 

## C g



## = geomembrane concentrations (M/L 3 

## ) 

## C f 

## = fluid concentration (M/L 3 

## ) 

## K dg



## = linear partition coefficient between the fluid and the geomembrane (unitless).
Fick’s law can be used to describe diffusion through the geomembrane:



## dz dC D f g g 

## ×

− = 

## (Equation B-6) where 

## f = mass flux (mass per area per time) (M/L 2 

## -T) 

## D g



## = the geomembrane diffusion coefficient (L 2 

## /T) 

## C g



## = geomembrane concentration (M/L 3 

## )


## z = diffusion direction (L). Combining the above two relationships yields the following:



## dz dC P dz dC K D f f g f dg g 

## − = − = 

## (Equation B-7)

where 

## f

= mass flux (mass per area per time) (M/L 2 

## -T) 

## D g



## = the geomembrane diffusion coefficient (L 2 

## /T) 

## C f 

## = fluid concentration (M/L 3 

## )


## z = diffusion direction (L) 

## P g



## = geomembrane permeation coefficient (L 2 

## /T) = 

## D g 

### x 

## K dg 

## . The landfill source model applies the above formulation to describe transport through geomembranes. The permeation coefficient varies with the chemical concentration and is generally at its lowest value in dilute concentrations (Müller et al., 1988). For many of the solvents, we used the following Sangam and Rowe (2001) empirical correlation relating the estimated permeation coefficient in dilute solutions to the octanol-water partition coefficient ( 

## K

ow 

## ):

2 

## ) (log 3910

. 0 log 2437

. 2 4476

. 13 log ow ow g 

## K K P

− +

− = 

## (Equation B-8)
This correlation showed an r 2 

## correlation of 0.84 in predicting the permeation coefficient for a range of chemicals (Sangam and Ro we, 2001). Sangam And Rowe (2001) provided measured values for the permeation coefficient for ethyl benzene, toluene, trichloroethylene, and xylene. Joo et al. (2004) provided measured values of the diffusion and partition coefficients for benzene, methylene chloride, and tetrachloroethylene; these values were used to calculate the permeation coefficients for these chemicals.

### Draft Appendix B Chemical-Specific Parameters



## B-27 

# B.4 Henry’s Law Constant Adjustment for Temperature Effects
B.4.1 Clausius-Clapeyron Relationship 

## Henry’s law constants generally increase with temperature. The landfill source model adjusted the Henry’s law constants to be valid at the specified average waste temperature using the Clausius-Clapeyron relationship (Perry and Green, 1997; U.S. EPA, 1996):

1 1 exp v adj ref ref 

## h H H R TT ⎡ ⎤ ⎛ ⎞ Δ ⎛ ⎞ =× − − ⎢ ⎥ ⎜ ⎟ ⎜ ⎟ ⎝ ⎠ ⎢ ⎥ ⎝ ⎠ ⎣ ⎦ 

## (Equation B-9)

where 

## H adj 

## = adjusted Henry’s law constant (atm-m 3 

## /mol) 

## H ref



## = reference Henry’s law constant (atm-m 3 

## /mol) at the reference temperature 

## T ref 

## = reference temperature (K) Δ 

## h v 

## = enthalpy of vaporization (cal/mol) 

## T = temperature (K) 

## R = universal gas constant (1.9872 cal/mol K). B.4.2 Enthalpy of Vaporization 

## Lyman et al. (1990) provide a method for estimating the enthalpy of vaporization used in the Clausius-Clapeyron relationship. First, Chen ’s method estimates the enthalpy of vaporization at the boiling point ( Δ 

## h vb 

## ):

c b c b
c
b vb 

## T T T T P T h

− ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ +

−
× = Δ 07

. 1 9

. 7 82

. 7 ) ( log 11

. 7 10 

## (Equation B-10)

where Δ 

## h vb 

## = enthalpy of vaporization at the boiling point (cal/mol) 

## T b 

## = boiling point (K) 

## P c 

## = critical pressure (atm) 

## T c 

## = critical Temperature (K). Then, the enthalpy of vaporization is estimated using the method in Lyman et al. (1990):

n

c b c vb v 

## T T T T
h h ⎟ ⎟ ⎟ ⎟

⎠ ⎞

⎜ ⎜ ⎜ ⎜

⎝ ⎛

− − Δ = Δ 

## 1 1 (Equation B-11)

where the exponent, 

## n , is equal to 0.41 if T/T c 

## > 0.71. If T/T c 

## ≤ 0.71, 

## n is calculated as follows:

### Draft Appendix B Chemical-Specific Parameters



## B-28 116

. 0 74

. 0

− ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

=

c b 

## T T n 

## (Equation B-12)
Most of the critical temperature values we re taken from Reid et al. (1977). Critical temperature values that were not available from Reid et al. (1977) were obtained from the HSDB (NLM, 2006), Korea Thermophysical Properties Data Bank (KDB, n.d.), and Gonzales et al. (2001). The critical pressure values were from Reid et al. (1977).
B.4.3 Conversion to Dimensionless Henry’s Constant 

## The units for the Henry’s law constant were atm-m 3 

## /mol. The landfill source model uses the dimensionless form of the Henry’s law consta nt, converting from the dimensional form using the following equation:



## RT H H = 

## ' (Equation B-13) where 

## H’ = dimensionless Henry’s law constant (unitless) 

## H = Henry’s law constant (atm-m 3 

## /mol) 

## R = universal gas constant = 8.2e-5 atm-m 3 

## /mol-K 

## T = temperature (K). 

# B.5 Dermal Exposure
B.5.1 Permeability Coefficient Ratio (B) 

## This parameter describes the dimensionless ratio of the permeability coefficient of a compound through the stratum corneum to its permeability coefficient across the viable epidermis. It is calculated from Kp and the molecular weight using the following equation (U.S. EPA, 2004):

6

. 2 ) ( 5

. 0 

## MW Kp B ×
= 

## (Equation B-14)

where



## B = Permeability coefficient ratio (dimensionless) 

## Kp = Dermal permeability coefficient of compound in water (cm/hr) 

## MW = Molecular weight (g/mol).
B.5.2 Dermal Permeability Coefficient of Compound in Water 

## (Kp) 

## The dermal permeability coefficient for organics was derived from an empirical predictive correlation as a function of K ow 

## and MW (U.S. EPA, 2004):

### Draft Appendix B Chemical-Specific Parameters



## B-29 MW) 0.0056118

- logK 0.6645865 + (-2.805063 ow 

## 10 × × 

## = Kp 

## (Equation B-15)

where Kp = Dermal permeability coefficient of compound in water (cm/hr) K ow 

## = Octanol/water partition coefficient of the non-ionized species (dimensionless) MW = Molecular weight (g/mol) B.5.3 Lag Time per Event (hr/event)
The lag time is derived as follows (U.S. EPA, 2004):

sc 

## D × = 6 l 2
sc 

## τ (Equation B-16)
where

τ

= Chemical-specific lag time per event (cm/hr) l sc 

## = Apparent thickness of the stratum corneum (cm) – set to a default value of 0.001 D s 

## = Chemical-specific effective diffusion coeffi cient for chemical transfer through the stratum corneum (cm 2 

## /hr). 

# B.6 References
Aronson, D., and P. H. Howard. 1997. Anaerobic Biodegradation of Organic Chemicals in Groundwater: A Summary of Field and Laboratory Studies . Prepared for the American Petroleum Institute, the Chemical Manufactur er’s Association, the National Council of the Paper Industry for Air and Stream Improvement, the Edison Electric Institute, and the American Forest and Paper Association. North Syracuse, NY: Syracuse Research Corporation.
Budavari, S., editor. 1989. The Merck Index, An Encyclopedia of Chemicals, Drugs, and Biologicals . 11th edition. Rahway, NJ: Merck and Co. Inc. Fuller, E. N., P. D. Schettler, and J. C. Giddings. 1966. A New Method for Prediction of Binary Gas-Phase Diffusion Coefficients. Industrial Engineering and Chemistry 58 :19–27.
Gonzalez, J. A., J. C. Cobos, F. J. Carmona, I. G. De La Fuente, V. R. Bhethanabotla, and S. W. Campbell. 2001. Thermodynamics of mixtur es containing alkoxyethanols. Part XV. DISQUAC characterization of systems of al koxyethanols with n-alkanes or cyclohexane. Physical Chemistry Chemical Physics 3:2,856–2,865. Howard, P. H., R. S. Boethling, W. F., Jarvis, W. M. Meylan, and E. M. Michalenko. 1991. Handbook of Environmental Degradation Rates. Boca Raton, FL: Lewis Publishers.

### Draft Appendix B Chemical-Specific Parameters



## B-30 Joo, J. C., J. Y. Kim, A. M. ASCE, and K. Nam. 2004. Mass Transfer of Organic Compounds in Dilute Aqueous Solutions into High Density Polyethylene Geomembranes. Journal of Environmental Engineering 130 (2):175–183. KDB (Korea Thermophysical Properties Data Bank). n.d. Available at http://infosys.korea.ac.kr/ kdb/index.html. Accessed December 2006. Kollig, H.P., ed. 1993. Environmental Fate Constants for Organic Chemicals Under Consideration for EPA’s Hazardous Waste Identification Projects . EPA/600/R-93/132. Prepared for U.S. Environmental Protection Agency, Office of Research and Development, Environmental Research Laboratory, Athens, GA. Lyman, W. J., W. J. Reehl, and D. H. Rosenblatt. 1990. Handbook of Chemical Property Estimation Methods: Environmental Behavior of Organic Compounds . Washington, DC: American Chemical Society. Müller, W., I. Jakob, R. Tatzky-Gerth, and H. August. 1998. Solubilities, Diffusion and Partition Coefficients of Organic Pollutants in HDPE Geomembranes: Experimental Results and Calculations . Federal Institute for Materials Research and Testing, BAM, 1998 Sixth International Conference on Geosynthetics, Berlin, Germany. NLM (National Library of Medicine). 2006. TOXNET: Toxicology Data Network . Available at http://toxnet.nlm.nih.gov. Accessed December 2006. Perry, R. H., and D. W. Green. 1997. Perry’s Chemical Engineers’ Handbook . 7th Edition. New York: McGraw-Hill.
Reid, R. C., J. M. Prausnitz, and T. K. Sherwood. 1977. The Properties of Gases and Liquids

. Third edition. New York: McGraw-Hill Book Company. Sangam, H. P., and R. K. Rowe. 2001. Migrati on of dilute aqueous organic pollutants through HDPE geomembranes

. 

## Geotextiles and Geomembranes 19 (6):329–357. SRC (Syracuse Research Corporation). 1997. Anaerobic Biodegradation of Organic Chemicals in Groundwater: A Summary of Field and Laboratory Studies . SRC, Environmental Research Center, Syracuse, NY. SRC (Syracuse Research Corporation). 2002. CHEMFATE Chemical Search . SRC, Environmental Research Center, Syracuse, NY. Available at: http://www.syrres.com/esc/ default.htm. Accessed December 2006. U.S. EPA (Environmental Protection Agency). 1993. Environmental Fate Constants for Organic Chemicals Under Consideration for EPA’s Hazardous Waste Identification Projects. EPA/600/R-93/132. U.S. EPA, Athens, GA.

### Draft Appendix B Chemical-Specific Parameters



## B-31 U.S. EPA (Environmental Protection Agency). 1996. Soil Screening Guidance: Technical Background Document. EPA/540/R-96/128. NTIS PB96-963502. U.S. EPA, Office of Emergency and Remedial Response, Washington, DC. U.S. EPA (Environmental Protection Agency). 1999. Anaerobic Biodegradation Rates of Organic Chemicals in Groundwater: A Su mmary of Field and Laboratory Studies . U.S. EPA, Office of Solid Waste, Washington, DC. U.S. EPA (Environmental Protection Agency). 2002. Superfund Chemical Data Matrix (SCDM ). Superfund Internet Site, Washington, DC. Available at http://www.epa.gov/oerrpage/ superfund/resources/scdm/index.htm. U.S. EPA (Environmental Protection Agency). 2004. Risk Assessment Guidance for Superfund Volume I: Human Health Evaluation Manual (Part E, Supplemental Guidance for Dermal Risk Assessment). Final. U.S. EPA, Office of Office of Superfund Remediation and Technology Innovation, Washington, DC. Available at http://www.epa.gov/oswer/ riskassessment/ragse/pdf/introduction.pdf.

## [This page intentionally left blank.]

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-1 

# Appendix C Landfill Source Model Mathematical Formulation
This appendix provides the mathematical formulation for the LFCR model. Section C.1 presents the landfill waste addition algorithm. Section C.2 presents the approach to modeling transport in columns of daily waste cells . Section C.3 presents the mathematical formulation of the model and the numerical solution algorithm. 

# C.1 Landfill Waste Addition Algorithm Waste is typically added to municipal landfills in systematic patterns designed to increase efficiency and capacity, as well as to satisfy regulatory design requirements. The typical managed landfill consists of a series of lifts , which cover the lateral extent of an actively managed area (see Figure C-1 ). Waste is added to the working face along the lateral edge of the lift. Once an active area is covere d by a lift, additional lifts are added vertically. In the industry, active areas are typically referred to as landfill cells (in contrast to daily cells , described below). An entire landfill is made up of a series of landfil l cells. Operators typically cover the waste with native soil or other material at the end of each day (the daily cover ). A discrete volume of daily waste and the daily cover mate rial added to a lift is a daily cell . Figure C-1 shows the geometry of a daily cell within a lift. New daily cells are added laterally until a landfill cell is covered by a lift, after which waste is added in a new lift overlying any previ ous ones. Lifts extending above the local grade (above the excavated landfill ba sin) are typically added with a slope of approximately 1 to 3. Our understanding of typica l landfill design practice derived largely from Panagiotakopoulos and Dokas (2001) and Aivaliotis et al. (2004), as well as conversations with Dr. Morton Barlaz at North Carolina State University (Barlaz, 2006).

Liner Lift 1 Lift 2 Lift 3 Ground surface Final cover

Daily cover Daily cell Working face

Note: Figure adapted from Aivaliotis et al., 2004 

### Figure C-1. Geometry of a landfill cell.

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-2 Figure C-2 shows the waste addition pattern de veloped for the LFCR model, which is generally consistent with the typical landfill ope rating practices described above. Each box in the figure represents a daily cell, a nd each lift is shown in a different color. Although some of the details do not match typical pr actice (e.g., sloping side walls above and below grade), this approach captures critical characteristics of land fill waste addition (daily cells added in lifts). Additional details of the landfill-fil ling algorithm are provided below.

a) First daily cell added to the bottom lift.

Each box represents one daily cell. Lifts are shown in different colors. The figures show waste addition over time until the landfill cell is full. The surface of each daily cell and landfill cell is a square. The daily cell depth can vary from the length (however, cubic daily cells are shown here). b) Daily cells added laterally in rows.

c) First lift completed. Second lift started. d) Filled to the fourth lift, fourth row, third cell.

e) Filled to the fifth lift, sixth row, second cell. f) Landfill cell filled through the seventh lift.



### Figure C-2. Model representation of operational landfill waste addition.

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-3 Landfill dimensions (volume and area) are input parameters, as is the landfill operating life (period during which waste is added). A user-specified number of landfill cells, each having the same volume and area, make up the total landfill area. Each landfill cell is filled sequentially during the operating landfill life. For model si mplicity, the surface area s of daily and landfill cells were modeled as squares. The daily cell/l ift height can vary from the daily cell width. The following input parameters characteri ze the waste addition algorithm for a given landfill: total landfill capacity ( V tot 

## ), total landfill area ( A tot 

## ), landfill operating life in years ( T lf



## ), number of landfill cells within the landfill ( N lfcell 

## ), the target lift height ( H targ 

## ), and the fraction of a day when waste is actively added to the la ndfill (and the active daily cell has no cover, f open 

## ). The mass associated with each new da ily cell is added in full at th e beginning of each daily cellfilling period. The following sequential formulas calculate additional landfill-filling algorithm parameters based on the inputs presented above. See Section C.4 for definitions of all symbols used in the following equations. The operating period for each landfill cell within the landfill (in days ) is calculated as follows: 

## 365 lf lfcell lfcell 

## T T N ×

= (Equation C-1)
The lateral length of each landfill cell is calculat ed as follows (note that the top surface is square):

tot lfcell lfcell 

## A L N = 

## (Equation C-2)
The number of daily cells within each landfill cell is calculated as: 

# { } cells lfcell 

## N T = (Equation C-3) where {


## ⋅ } denotes a rounding operator to the nearest integer (the num ber of cells must be an integer). A portion of the total landfill capacity ( 

## V tot 

## ) is taken up by the volume of soil used for the liner, the final cover, and the daily cove rs (as determined by the landfill area and userspecified thicknesses for these layers). The adjusted total capacity ( 

## V adj 

## ) represents the landfill volume after subtracting the final cover and line r volumes. Then, the total volume of each daily cell (inclusive of the daily cove r volume) is calculated as:

adj celltot lfcell cells 

## V V N N = × (Equation C-4)
The number of daily cells per landfil l cell length is then calculated: 1

1 

### This relationship is derived from the following: L cell 

### = L lfcell 

### /N L 

### ; L lfcell 

### = ( A tot 

### /N lfcell 

### ) 1/2 

### ; V cell



### = L cell 2 

### × H targ 

### .

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-4 arg tot lfcell L celltot

t 

## A N N V H ⎧ ⎫ ⎪ ⎪ ⎪ ⎪

=

⎨ ⎬ ⎪ ⎪ ⎪ ⎪ ⎩ ⎭ (Equation C-5)

The number of cells per landfill cell height is calculated as:

*

2 cells H L 

## N N N ⎧ ⎫

= ⎨ ⎬ ⎩ ⎭ 

## (Equation C-6)
where {
⋅ 

## } * 

## denotes an operator to round up 

## to the next integer. The length of each daily cell is calculated as:

lfcell cell L 

## L L N = 

## (Equation C-7)
Finally, the actual height of each lift/daily cell, inclusive of the daily cover height, can be calculated as:

2 celltot celltot cell 

## V H L = (Equation C-8)
The actual daily cell height may be slightly di fferent from the input target height because the number of cells must be an integer. Any roundoff adjustment is compensated by slightly adjusting 

## H celltot 

## . For a similar reason, the uppermost lift in the model may only be partially filled with daily cells when the landfill cell is closed . The height and volume of the refuse within the daily cell ( 

## H cell 

## and 

## V cell 

## ) can then be calculated by subtractin g the height and volume of the daily cover. In addition, th e daily cell surface area ( 

## A cell 

## ) is simply the daily cell volume divided by the height. 

# C.2 Modeling Transport Within Columns of Daily Cells Application of the approach described above for landfill waste addition generates a series of adjacent landfill columns of stack ed daily cells with overlying daily cells added at later times. The model simulates vertical transport within eac h of these columns of daily cells and with the atmosphere and the underlying groundwater zone. The mass loss from an entire landfill to the atmosphere and to the groundwater zone is then the cumulative contribution from all columns. 

# C.3 Mathematical Formulation of the Coupled Reactor Model The LFCR model adopts a mathematical desc ription based on fully mixed reactors coupled in series and applies it within a framew ork consistent with typical landfill operations (daily cells added in lifts as depicted in Figur e C-2). A separate, fully mixed reactor represents each daily cell of waste. Independent models of fully mixed reactors in series represent each column of daily cells. The model is based on a fundamental mass ba lance written around a daily cell, whereby the mass accumulated within a cell is equal to the difference between mass entering the cell and

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-5 mass exiting the cell and transfor med within the cell. Such a mass balance around a daily cell control volume can be written as the overall chan ge in mass within the cell equal to the sum of source/sink terms representing each of the ma ss transport and transformation properties: 

# ( )

,,, , i i ai wi i Di 

## d VC SSSS dt λ 

## =+++ (Equation C-9) where the left hand side of the equation repr esents the change in mass within daily cell 

## i (volume times concentration). The right hand side of the mass balance e quation is the sum of source/sink terms representing mass within flowing air ( 

## S a,i 

## ), mass within flowing water ( 

## S w,i 

## ), mass decay within the cell ( 

## S λ ,i 

## ), and diffusive mass transfer between daily cell 

## i and the vertically adjacent cells (or the atmosphere or groundwater). Source/sink terms may have two components representing mass entering and exi ting the daily cell (for example, water flows in from the top of the cell and out of the bottom). Based on the sign convention in the above equation, mass entering the system would have a positive sign, while mass exiting the system would have a negative sign. In the derivation below, first the mass partitioning relationships between the aqueous, vapor, and solid phases are established. Next, ea ch of the mass source/sink terms are developed to represent the mass transport and decay mechanisms. Finally, the overall mass balance equation is written and rearra nged for numerical solution. The equations presented below describe a column of daily cells as represented by a series of coupled, fully mixed reactors. Daily cells a dded at a later time above existing cells become additional reactors in series. In th e equations below, the subscript 

## i denotes the current daily cell within a column/series. The subscript 

## i varies from 1 to 

## n , with 

## n referring to the uppermost cell in the current column. C.3.1 Total Concentration and Mass Partitioning 

## The model is written in terms of the to tal volumetric concentration within cell 

## i , which includes mass in the aqueous, vapor, and solid phas es. An expression for the total concentration can be developed by considering th e total mass in the cell equal to the mass within each of the phases:

,, , i w wi a ai s si 

## m VC VC MC = + + (Equation C-10)
Where 

## m i 

## is the total chemical mass within the daily cell, 

## V w 

## is the water volume, 

## C w,i 

## is the volumetric concentration of chemical in the water (e.g., kg/m 3 

## ), 

## V a 

## is the air volume, 

## C a,i 

## is the volumetric concentration of chemical in air, 

## M s 

## is the mass of refuse in the daily cell, and 

## C s,i 

## is the mass-based concentration of chemical on th e solid (e.g., kg/kg). Dividing by the total waste volume within the daily cell ( 

## V cell 

## ) gives an expression for the to tal concentration in daily cell 

## i in terms of the phase specific concentrations:

,,, i w wi a ai b si 

## CC C C ε ε ρ = + + (Equation C-11)
where ε w 

## and ε a 

## are the volumetric fractions of water and air, respectively, and ρ b 

## is the dry bulk density. Air-water partitioning is ch aracterized by linear equilibrium and described through Henry’s law:

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-6 i w H i a 

## C K C

, , 

## = (Equation C-12)
where 

## K H



## is the dimensionless Henry’s law constant. Solid-water partitioning is characterized by linear equilibrium, as described by a distribution coefficient ( 

## K d 

## ):

, , s i d wi 

## C KC = (Equation C-13) For organic compounds, the distribution coeffi cient can be estimated from the organiccarbon fraction ( 

## f

oc 

## ) and the organic-carbon di stribution coefficient ( 

## K oc 

## ):

d oc oc 

## K fK = (Equation C-14)

C.3.2 Partition/Retardation Coefficients 

## Although the model is formulated in terms of the total concentrati on, mass transfer and transformation processes are generally active wi thin individual phases (e.g., air advection, aqueous biodegradation). Therefore, an approach to relate the total concentration to the mass/concentration in selected phases is required. Given linear equilibrium phase partitioning, the ratios of solid, aqueous, and gaseous concentr ations are constant (Kje ldsen and Christensen, 2001). Therefore, partition coefficients can be de veloped to relate phase-specific concentrations to each other and to the total concentration, as shown below. The final model formulation is expressed in terms of the total concentration through use of these partition coefficients. Note that in some contexts, the partition coefficients are referred to as retardation coefficients. The concentration in air can be related to the total concentration using the air-total concentration partition/retardation coefficient ( 

## R a 

## ):

, i a ai 

## C RC = (Equation C-15)

w bd
a a H 

## K R K ε ρ ε +
= + (Equation C-16)

The concentration in water can be related to the total concentration using the water-total concentration partition/retardation coefficient ( 

## R w 

## ):

, i w wi 

## C RC = (Equation C-17)

w w aH bd 

## R K K ε ε ρ = + + (Equation C-18) The concentration in the solid can be relate d to the total concentration using the solidtotal concentration partition/retardation coefficient ( 

## R s 

## ):

, i s si 

## C RC = (Equation C-19)

w aH
s b d 

## K R K ε ε ρ +
= + (Equation C-20)

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-7 C.3.3 Advective Gaseous Tr ansport (Landfill Gas) 

## A first-order decay model developed fo r EPA’s LandGEM model (U.S. EPA, 2005) estimates the landfill gas flow rate ( 

## Q a,i 

## ). This model uses a landfill gas generation rate, 

## k (/T), and a potential methane generation capacity, 

## L o 

## (methane volume per waste mass). The gas generation model can be expressed as follows (Bartelt-Hunt et al., 2006):

, 

## 2 exp( ) a i cell b o i 

## Q V L k kt ρ = − 

## (Equation C-21)
where V cell 

## is the waste volume within the daily cell, ρ b 

## is the waste bulk density, and t i 

## is the time from original waste disposal for daily cell i 

## . Note that this formulation assumes that the bulk landfill gas is made up of 50 percent methane (thus, the factor of 2). The advective gaseous transport source/sink term for daily cell i 

## is then based on the difference between the mass entering and leaving the cell via advective gaseous transport. The gas flow in a given cell equals the sum of gas flows generated in all underlying cells in the column, plus the flow generated in the curren t cell (assuming vertically upward gas flow):

1 , , ,1 , , 1 1 i i ai a j ai a j ai j j 

## S QC QC −

−

= = 

## ⎛⎞⎛⎞

= −

⎜⎟⎜⎟ ⎝⎠⎝⎠



# ∑ ∑ (Equation C-22)
Note that the flow entering the cell from below ha s a positive sign, while th e flow exiting the top of the cell has a negative sign. After substituting in the gas generation rate and expressing the equation in terms of the total concentration, the following advective gaseous transport source/sink term results:

1

, , 1 1 , 1 i i a j cell a j cell j j ai i i

a a 

## qV qV SCC R R −

= =

− 

## = − 

# ∑ ∑ (Equation C-23)

where q a,j 

## is equal to [2 ρ b 

## L o 

## k 

## exp( -kt i 

## )] based on Equation C-21. C.3.4 Advective Aqueous Transport (Leachate) 

## The leachate flow rate ( Q w 

## ) is equal to the net infiltration ( N 

## ) multiplied by the surface area ( A 

## ):

w cell 

## Q NA = 

## (Equation C-24) The advective water flow source/sink term for cell i 

## equals the difference between the mass entering and leaving the cell. Assuming ve rtical downward water flow, mass enters the current daily cell ( i 

## ) from the overlying daily cell:

, ,1 , wi w wi w wi 

## S QC QC + 

## = − 

## (Equation C-25) After substituting in the net infiltration and expressing the equation in terms of the total concentration, the following advective aque ous transport source/sink term results:

, 1 cell cell wi i i

w w 

## NA NA S CC R R + 

## ⎛ ⎞⎛ ⎞

= −

⎜ ⎟⎜ ⎟ ⎝ ⎠⎝ ⎠ 

## (Equation C-26)

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-8 C.3.5 Degradation/Transformation 

## A first-order degradation sink term describe s degradation and transformation processes such as biodegradation and hydrolysis: 

# ( ) ( ) ( ) , ,1 2 , 1 2 ,1 2 i cell a a i a a w w i w w b s i s s 

## SVC C C

λ 

## ε λλ ε λ λ ρ λλ ⎡ ⎤ =− + + + + + ⎣ ⎦ 

## (Equation C-27)
where λ a1 

## , λ w1 

## , and λ s1 

## are the biotic first-order degradati on rates in the air, water, and solid phases, respectively, and λ a2 

## , λ w2 

## , and λ s2 

## are the respective abiotic fi rst-order degradation rates. After expressing in terms of the total concentra tion, the following degradation sink term results: 

# ( ) ( ) ( ) 12 1 2 12

, aa a ww w bs s i cell i

aws 

## S VC RRR

λ 

## ελ λ ε λ λ ρλ λ ⎡ ⎤ +++ =− + + ⎢ ⎥ ⎣ ⎦ 

## (Equation C-28)

C.3.6 Diffusive Transport 

## The LFCR model adopts a Fickian diffusion appr oach to describe diffusion between daily cells in air and water. Mass transfer is depe ndent on the chemical concentration gradient ( dC/dx 

## ), the surface area ( A 

## ), and a diffusion coefficient ( D 

## ) in the following general form (Cussler, 1984):

D 

## dC S AD dx = 

## (Equation C-29) Diffusive transport can occur between each daily cell and the overlying and underlying daily cell and within both the air and water phases. These diffusive transport pathways result in four source/sink terms for each cell (vapor and aqueous diffusion with overlying cell and vapor and aqueous diffusion with underlying cell). By convention, the subscript i 

## on the thickness ( L 

## ) refers to the overlying layer. Thus, the following source/sink term describes diffusive transport in air through the overlying cover/liner: 

# ( ) , ,1 , a D ai ai ai i 

## AD S CC L + 

## = − 

## (Equation C-30)
Consistent with the model’s sign convention, th e diffusive source/sink term is positive if the concentration in the overlying cell exceeds the co ncentration in the current cell (which would result in a positive diffusive mass flow into cell i 

## ). Expressing the equation in terms of the tota l concentration yields the following:

, 1 a a D ai i i ia ia 

## AD AD S CC LR LR + 

## ⎛⎞ ⎛⎞

= −

⎜⎟ ⎜⎟ ⎝⎠ ⎝⎠ 

## (Equation C-31)
Diffusion coefficients are dependent on the ch emical, as well as the porous medium in cell i 

## . The diffusion coefficient can be estimated ba sed on the chemical-specific diffusion rate in air or water and the porous medium tortuosity fo r air or water (Millington, 1959). Accordingly, the diffusion coefficient for ai r has the following expression:

a oa 

## D D 

## τ = 

## (Equation C-32)

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-9 where τ 

## is the tortuosity. The tortuo sity for a porous medium (a representation of the tortuous paths for diffusion in a porous medium) can be estimated using the phase volume fraction and the porosity (Millington, 1959):

10 3
2 aC

C 

## ε τ ε



## = 

## (Equation C-33)

The total air diffusion source/sink term for cell i 

## then equals the diffusive transport through the overlying cover/liner minus the diffusive transport through the underlying cover/liner:

, , , ,1 D a tot i Da i Da i 

## S SS

− 

## = − 

## (Equation C-34) A similar approach yields the diffusive transport in the water phase. The following source/sink term describes the diffusive tran sport in water through the overlying cover:

, 1 w w D wi i i iw iw 

## AD AD S CC LR LR + 

## = − 

## (Equation C-35)
The Millington (1959) approach for estimating the diffusion coeffici ent and the tortuosity associated with the water phase yields the following:

w ow 

## D D τ 

## = 

## (Equation C-36)

10 3
2 wC

C 

## ε τ ε



## = 

## (Equation C-37)

The total water diffusion source/sink term for cell i 

## is the difference between the diffusive transport through the overlying and th e underlying cover/liner layers:

1 , , , , − 

## − = i Dw i Dw i tot Dw 

## S S S 

## (Equation C-38) A total diffusive source/sink term then incorporates diffusive transport in both the water and air phases and through the overlying and underlying layers:

, , ,1 , ,1 D i Da i Da i Dw i Dw i 

## SS S S S

− − 

## = − +− 

## (Equation C-39)
C.3.7 Mass Balance Equation 

## The model equation formulation is ba sed on a mass balance for daily cell i 

## , whereby the change in mass over time is equal to the cumulative source/sink terms: 

# ( )

,,, , cell i ai wi i Di 

## dV C SSSS dt λ 

## =+++ 

## (Equation C-40) Dividing by the constant daily cell volume yields the following:

,,, , ai wi i Di i

cell 

## SSSS dC dt V λ 

## + + +

= 

## (Equation C-41)
Below, each of the source/sink terms is divi ded by the volume and expressed in terms of coefficients of the total con centrations within the current and overlying and underlying daily

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-10 cells (C i-1 

## , C i 

## , 

## and C i+1 

## ). These manipulations will lead to the model expression used in the numerical solution. The advective gas flow term is:

1

, , 1 1 , 1 i i aj aj j j a i i i cell a a 

## q q S C C VR R −

= =

− 

## = − 

# ∑ ∑ (Equation C-42)

The advective water flow term is:

, 1 w i i i cell cell w cell w 

## S N N C C V HR HR + 

## ⎛ ⎞⎛ ⎞

= −

⎜ ⎟⎜ ⎟ ⎝ ⎠⎝ ⎠ 

## (Equation C-443)
The degradation term is: 

# ( ) ( ) ( ) , 12 1 2 12 i aa a ww w bs s i cell a w s 

## S C VR R R

λ 

## ελ λ ε λ λ ρλ λ ⎛ ⎞ +++ =− + + ⎜ ⎟ ⎝ ⎠ 

## (Equation C-44)

The total diffusion term is:

, 1 1 1 1

1 1 1 D i aa aa ii ii cell i cell a i cell a i cell a i cell a

ww ww ii i i cell w i cell w i cell w i cell w 

## S DD DD CC CC V LH R LH R L H R L H R
DD DD CC C LH R LH R L H R L H R +

−

− −

+

− − 

## ⎡ ⎤⎡ ⎤

⎛ ⎞ ⎛ ⎞ ⎛ ⎞⎛ ⎞

= −− −

⎢ ⎥⎢ ⎥

⎜ ⎟ ⎜ ⎟ ⎜ ⎟⎜ ⎟ ⎝ ⎠ ⎝ ⎠ ⎝ ⎠⎝ ⎠ ⎣ ⎦⎣ ⎦ ⎡ ⎤

⎛ ⎞ ⎛ ⎞ ⎛ ⎞⎛ + −− −

⎢ ⎥

⎜ ⎟⎜ ⎟ ⎜ ⎟ ⎝ ⎠⎝ ⎠ ⎝ ⎠ ⎣ ⎦ 1 i 

## C

− 

## ⎡ ⎤ ⎞ ⎢ ⎥ ⎜ ⎟ ⎝ ⎠ ⎣ ⎦ 

## (Equation C-45)

The mass balance equation can then be expresse d in terms of the total concentration in cell i 

## as a function of the concen trations in the current ( C i 

## ), the overlying ( C i+1 

## ), and the underlying ( C i-1 

## ) daily cells:

1 3 2 1 1 +

− 

## + + = i i i i 

## C k C k C k dt dC 

## (Equation C-46)

where

1

, 1 1 1 1 i a j j a w
a i cell a i cell w 

## q D D k R LH R LH R −

=

− − 

## ⎛ ⎞ ⎜ ⎟ ⎛ ⎞⎛ ⎞ ⎜ ⎟ =+ + ⎜ ⎟⎜ ⎟ ⎜ ⎟ ⎝ ⎠⎝ ⎠ ⎜ ⎟ ⎝ ⎠



# ∑ (Equation C-47)



# ( ) ( ) ( ) , 1 12 1 2 12

2

1 1 i a j j aa a ww w bs s

a cell w a w s

aaww
i cell a i cell a i cell w i cell w 

## q N R HR R R R k

DDDD LH R L H R LH R L H R ελ λ ε λ λ ρλ λ

=

− − 

## ⎡ ⎤

⎛ ⎞ ⎢ ⎥

⎜ ⎟ ⎛ ⎞ +++ ⎛ ⎞ ⎜ ⎟ ++ + + ⎜ ⎟ ⎜ ⎟ ⎜ ⎟ ⎝ ⎠ ⎝ ⎠

= − ⎜ ⎟ ⎝ ⎠

⎛ ⎞⎛ ⎞⎛ ⎞⎛ ⎞ ++ + +

⎜ ⎟⎜ ⎟⎜ ⎟⎜ ⎟ ⎝ ⎠⎝ ⎠⎝ ⎠⎝ ⎠ ⎣ ⎦ 

# ∑

(Equation C-48)

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-11 3 a w
cell w i cell a i cell w 

## D D N k H R LH R LH R ⎛ ⎞⎛ ⎞⎛ ⎞ =+ +

⎜ ⎟⎜ ⎟⎜ ⎟ ⎝ ⎠⎝ ⎠⎝ ⎠ 

## (Equation C-49)
Equation C-46 is the final form of the mass balance used within the numerical solution. For a given column of n 

## daily cells, this formulation generates a system of n 

## coupled ordinary differential equations. The equations are coupled by the concentrations in adjacent cells, as described by the advective and diffu sive transport between cells. C.3.8 Modifications for the Top and Bottom Cell Boundaries No Top Cover 

## While waste is being added, there is no cover above the active daily cell, which can lead to enhanced losses of volatile compounds. The estimation of such losses was accomplished using an analytical solution to the diffusion equati on presented by Carslaw and Jaeger (1947). This one-dimensional analytical soluti on describes the mass release from a system with a constant starting concentration, a zer o-flux lower boundary, and an upper boundary at a constant concentration of zero. The underlying differential equation for the Cars law and Jaeger (1947) analytical solution is as follows:

2

2 

## C C D t z ∂ ∂

= ∂ ∂ 

## (Equation C-50) The following initial and boundary conditions apply:

0 

## ( ,0) , 0 , initial condition; 0, 0, zero flux boundary; ( , ) 0, 0, specified zero concentration boundary. init

z 

## Cz C z L C t z CLt t = 

## = ≤< ∂ ⎛ ⎞ = ≥ ⎜ ⎟

∂ ⎝ ⎠ = ≥ 

## The analytical solu tion is shown here: 

# ( ) ( ) ( ) ( ) 2 2

2 0 

## 1 21 21 4 ( , ) exp cos 21 4 2 n init

n 

## Dn t n C Czt z n LL π π
π ∞

= 

## ⎛ ⎞ − ++ ⎡ ⎤

= − ⎜ ⎟ ⎢ ⎥ + ⎣ ⎦ ⎝ ⎠ 

# ∑ (Equation C-51)

where C 

## is the concentration, z 

## is the depth, t 

## is time, C init 

## is the constant initial concentration, D 

## is the diffusion coefficient, and L 

## is the total system depth. The lower boundary is zero flux, and the top boundary is a specif ied concentration of zero. Figure C-3 

## presents a series of representative concentration pr ofiles over time. The concentra tion starts at the constant maximum value and decreases over time with zero flux from the lower boundary.

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-12 ConcentrationDepth



## 0 0

Figure C-3. Concentration profiles over time based on the Carslaw and Jaeger (1947) solution. 

## The solution for the diffusive flux ( J 

## ) leaving the top boundary at time t 

## (Carslaw and Jaeger, 1947) is: 

# ( ) 2 2

2 0 

## 2 1 2 ( ) exp 4 init

n 

## Dn t DC J t L L π ∞

= 

## ⎛ ⎞ +

= − ⎜ ⎟ ⎝ ⎠ 

# ∑ (Equation C-52)

Figure C-4 

## shows the flux over time from this solution. After an initial maximum, the flux decreases over time toward zero as mass is depleted.

TimeDiffusive Mass Flux



### 0 0

Figure C-4. Flux over time based on the Carslaw and Jaeger (1947) solution.

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-13 The average flux from time t 1 

## to t 2 

## can be found by integrating J(t) 

## and dividing by the time interval:


# ( ) 2

1 1 2 2 1 

## ( ) (, ) t

t avg 

## J t dt J tt t t =

− 

# ∫ (Equation C-53)
Then, the average flux between time t 1 

## and t 2 

## is based on the defin ite integral between t 1 

## and t 2 

## : 

# ( ) 2 1 1 2 2 1 

## (, ) (, ) (, , ) j j avg j 

## Ft L Ft L J tt L t t −
=

− 

## (Equation C-54)

where


# ( ) ( ) 2 2 2

2 2 2 0 

## 4 2 1 2 ( , ) exp 4 2 1 j init j
n j j 

## L Dn t DC FtL L L D n 

## π

π ∞

= 

## ⎛ ⎞

− +

= − ⎜ ⎟ + ⎝ ⎠ 

# ∑ (Equation C-55)

and L j 

## is the thickness of the wast e layer under consideration. In an active landfill, waste is added to the daily cell working face in layers throughout the workday rather than as a single volume at the st art of the day. In orde r to represent enhanced mass loss associated with this process, the LF CR model applies the solution presented above to sequential layers added to the work ing face over time at a user-specified time interval (the daily cell waste sublayer period) and at a user-specified angle (the working face angle to horizontal). Figures C-5 

## and C-6 

## illustrate the geometry of the solution. As these figures show, the solution is applied using th e no-cover length ( L nc 

## ) and height ( H nc 

## ): 

# ( ) ( ) sin sin cell
nc

nc cell 

## H L

H L θ θ =

= 

## (Equation C-56)

Older Waste Fresh Waste Added in Layers to Active Daily Cell

Bottom of Landfill

Or Older Waste Working

Face Angle



### Figure C-5. Waste applied to the active daily cell in sequential sublayers.

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-14 Solution geometry (flux through the top surface) Actual geometry

H n c H nc



### Working Face Angle L n c L nc

H

cell L cell



### Figure C-6. Representation of mass loss from the open face of the active daily cell. 

## The solution calculates the number of sublayers ( N sl 

## ) as the fraction of day with no cover divided by the waste sublayer period (and converted to the nearest integer). The height of each sublayer ( h inc 

## ) is then equal to H nc 

## divided by N sl 

## . The incremental time over which each sublayer is applied ( t inc 

## ) is equal to the fraction of a day with no cover divided by N sl 

## . The Carslaw and Jaeger solution is then applied to a seri es of layers of increasing thickness ( H inc 

## , 2 H inc 

## , 3 H inc 

## , etc.) to calculate the average flux over the period with no cover ( J nc 

## ): 

# ( )

1 

## 0, , sl N avg inc inc i
nc sl 

## J t ih J N = 

## = 

# ∑ (Equation C-57)
This no-cover flux is applied to th e surface area of th e working face ( L nc 

### x 

## H nc 

## ), as well as to one-half of the daily cell top surface (on aver age, half of the top surface is open to the atmosphere during the time period in which daily waste is added). In reality, diffusive mass loss through an angled working face and the daily ce ll top surface would be a more complex, multidimensional process. Uncertainty is increased through variable disposal practices (e.g., industrial wipes sealed in plasti c bags versus open to the atmosphere, variable waste mixing and compaction). The approach described above pr ovides a relatively simple and reasonable estimation given the complexity, uncerta inty, and variability in conditions. The infinite summation in Equation C-55 was estimated numerically with a finite sum and within a user-specified truncation error to lerance. Diffusive mass loss to the atmosphere occurs through vapor-phase diffusion only (aqueous diffusion does not capture the phase change necessary for migration of aqueous-phase mass to the atmosphere). The solution is expressed in terms of the total concentration. The diffusion coefficient ( D ) in Equation C-55 is an effective diffusion coefficient, accounting for equilibrium pa rtitioning in the air, water, and solid phases. This effective diffusion coefficient is equa l to the vapor-phase diffusion coefficient ( D a,i 

## in Equation C-32) divided by the vapor-phase partit ion/retardation coeffici ent (Equation C-16).
No Bottom Liner 

## The diffusive transport through the bottom of an unlined landfill requires a different formulation than that presented in Section C.3.6 

## , because there is no underlying layer through

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-15 which to describe diffusive transport. The diffu sive flux of interest is from the constantconcentration bottom reactor into the underlying un saturated zone soil. Extending the domain to the water table (and assuming the water table is at a concentra tion of zero), diffusion through the unsaturated soil zone below the landfill can be ap proximated using a steady-state solution to the diffusion equation. The solution domain is the unsaturated zone thickness ( L u 

## ). The upper boundary condition (the bottom of th e landfill) is a constant con centration of the bottom reactor, C 1 

## . The lower boundary condition (at the water table) is a constant concentr ation of zero. Given these boundary conditions, the solu tion for the steady-state diffusi ve flux is the following:

1

, D noliner u

u 

## C J D L = (Equation C-58)
Thus, the sink term for diffusive losses be low the bottom cell of an unlined landfill becomes the following:

1

, D noliner u

u 

## C S AD L = (Equation C-59)
When there is no liner, this diffusive flux, in addition to the advective flux leaving the bottom cell, will constitute the to tal mass transfer to groundwater. Diffusion through the Uppermost Cover and the Liner 

## When the top cell has a cover, the formula tion shown in Equation C-46 is used, except that the atmospheric concentration is assumed to be zero, and diffusion to the atmosphere only occurs in the vapor phase. This eliminates the C n+1 

## term from the mass balance equation. Similarly, the concentration below the liner is assumed to be zero, which eliminates the C o 

## term. Diffusion Through a Geomembrane-Based Liner or Final Cover 

## Diffusive transport through a geomembrane be haves differently from transport through soil, because a geomembrane is not porous (F oose et al., 1999). Rather than diffusing through void spaces filled with air or wate r, chemicals diffuse through the interstitial spaces between the geomembrane polymer molecules. The migration of chemicals through a geomembrane liner or final cover is a three-step pr ocess (Sangam and Rowe, 2001):

 

## Partitioning (sorption) between the inne r fluid containing the chemical and the geomembrane inner surface

 

## Diffusion through the geomembrane matrix

 

## Partitioning (desorption) between the geomem brane outer surface and the outer fluid. In dilute solutions, a linear relationship betw een the concentration in the fluid and the concentration on the geomembrane interface is ge nerally sufficient to describe the sorptive partitioning:

g f dg 

# C CK = (Equation C-60) where C g 

## and C f 

## are the geomembrane and fluid c oncentrations, respectively, and K dg 

## is the linear partition coefficient between the fluid and the geomembrane. Fick’s law describes diffusion through the geomembrane:

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-16 g g 

## dC f D dz = − (Equation C-61) where f is the mass flux, D g 

## is the geomembrane diffusion coefficient, and z is the diffusion direction. Combining these two re lationships yields the following:

f f g dg g 

## dC dC f DK P dz dz =− =− (Equation C-62) where the geomembrane permeation coefficient, P g 

## , is the product of the geomembrane diffusion coefficient and the partition coefficient. Th e landfill source model applies the permeationcoefficient formulation shown above to describe transport through geomembranes. As described in Appendix E 

## , an empirical correlation and literatu re values were used to estimate the permeation coefficient for the wipes analysis. Diffusion Through a Composite Liner 

## A composite liner is typically composed of two layers, a geomembrane overlying a layer of clay. In this situation, an equivalent diffusion coefficient can be calculated to represent diffusion through both layers using a harmonic mean of the individua l diffusion/permeation coefficients (Foose et al., 2002):

g m cl eq gm cl

g m cl 

## L L D L L P D +

= + (Equation C-63)

In the equation above, the composite liner is made up of a geomembrane of length L gm 

## and permeation coefficient P gm 

## and a clay layer of thickness L cl 

## and diffusion coefficient D cl 

## . To account for potential sorption within the soil layer, the diffusion coefficient can be divided by a retardation coefficient. For the industrial wipe s analysis, no sorption wa s allowed within the cover/liner soil layers, because a generalized appro ach to estimate the cove r/liner soil retardation coefficient for national conditions was not id entified, and significant uncertainties and unresolved questions remain in the science of transport within cover/ liner soil layers (see Section 3.1.1.2 

## ). Advection Through the Liner 

## If an engineered liner is in place at the bottom of the landfi ll, much of the advective water flux leaving the bottom cell is captured by a leachat e collection system. In this situation, the majority of the advective water flow is cap tured and does not reach the groundwater zone. However, some fraction of the flow does mi grate through the liner as a result of liner imperfections (e.g., holes, defective seams). In th is situation, mass transfer to groundwater will include the diffusive flux through the liner as calculated by the LFCR model, as well as an advective flux based on a user-spe cified liner leakage rate.
Landfill Closure 

## When a landfill is closed, a final top cover is emplaced. Depending on the type of final cover (e.g., native soil, clay, synthetic liner), th e infiltration rate may significantly decrease after

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-17 closure. Thus, the LFCR model allows the user to specify a separate infiltration rate representative of conditions with a final cover. C.3.9 Numerical Solution Algorithm 

## The numerical solution algorithm is the Runge-Kutte method, as developed algorithmically in Press et al. (2002). Although more efficient solu tions to systems of ordinary differential equations exist (e.g., Bulirsch-Stoer), the Runge-Kutte algorithm is effective because of the relatively small num ber of coupled equations (the numbe r of daily cells within a landfill column is relatively small, typically 5 to 10) . In addition, the Runge-Kutte algorithm is very robust and nearly always successful in generatin g an accurate solution (Press et al., 2002). The numerical solution was implemented in C++.
C.3.10 Model Limitations 

## The model limitations are described in Section 3.1.1.2



## . 

# C.4 Symbols A cell 

## Daily cell surface area [L 2 

## ] A tot 

## Total landfill surface area [L 2 

## ] C

a,i 

## Volumetric air-phase concentration in daily cell i [M/L 3 

## ] C

f 

## Concentration in fluid adjacent to geomembrane [M/ L 3 

## ] C

g 

## Concentration on geomembrane [M/ L 3 

## ] C i 

## Total volumetric concentration in daily cell i [M/L 3 

## ] C

s,i 

## Mass-based, solid-phase c oncentration in daily cell i [M/M] C

w,i 

## Volumetric water-phase concentration in daily cell i [M/L 3 

## ] D a 

## Air-phase diffusion coefficient [L 2 

## /T] D cl 

## Diffusion coefficient for the clay la yer in a composite liner or cover [L 2 

## /T] D eq 

## Equivalent diffusion coefficient for a composite cover or liner [L 2 

## /T] D oa 

## Diffusivity in air [L 2 

## /T] D ow 

## Diffusivity in water [L 2 

## /T] D u 

## Diffusion coefficient in the unsaturated zone [L 2 

## /T] D w 

## Water-phase diffusion coefficient [L 2 

## /T] f

oc 

## Fraction organic carbon [-] f

open 

## Fraction of t cell 

## (typically 1 day) during which the top cell is open with no cover [-] F(t) Function used in the calculation of the diffusive flux with no cover H

cell 

## Daily cell height, wit hout the daily cover [L] H

celltot 

## Lift height, inclusive of daily cover [L] h inc 

## Height of subcell layer in the active, open daily cell [L] H

nc 

## Adjusted daily cell thickness, accounting for the working face angle [L] H

targ 

## User-specified target lift height [L] i Subscript denoting cell i within a column of landfill cells J

avg 

## Average diffusive flux from a waste sublayer with no cover [M/L 2 

## T] J

nc 

## Total diffusive flux from the top cell with no cover (all sublayers) [M/L 2 

## T] k

Landfill gas production rate (/T] k 1 

## Coefficient for C i-1 

## (underlying cell concentration) in the mass balance equation k

2 

## Coefficient for C i 

## (current cell concentration) in the mass balance equation k

3 

## Coefficient for C i+1 

## (overlying cell concentration) in the mass balance equation

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-18 K

d 

## Solid-water phase distribution coefficient [L 3 

## /M] K

dg 

## Geomembrane partition coefficient [-] K

H



## Henry’s law constant [-] K

oc 

## Organic carbon distri bution coefficient [L 3 

## /M] L cell 

## Daily cell length in the lateral dimension [L] L cl 

## Composite liner clay layer thickness [L] L i 

## Thickness of the cover layer overlying cell i [L] L gm 

## Geomembrane thickness [L] L lfcell 

## Length of each lateral dimens ion of a landfill cell [L] L nc 

## Adjusted daily cell width, accounting for the working face angle [L] L o 

## Potential methane generation cap acity [volume methane/waste mass] L u 

## Length of unsaturated zone [L]
m i 

## Chemical mass in daily cell i [T] M s 

## Mass of refuse in daily cell [T]
n Number of cells within column [-] N

Net infiltration rate [L/T] N

cells 

## Number of daily cells within a given landfill cell [-] N

H



## Number of lifts with in a landfill cell in the z dimension [-] N

L 

## Number of daily cells within a landf ill cell in the lateral dimension [-] N

lfcell 

## Number of landfill cells within a given landfill [-] N

sl



## Number of sublayers within a daily cell [-] P g 

## Geomembrane permeation coefficient [L 2 

## /T] q a,i 

## Landfill gas generation rate, per landfill waste volume [/T] Q a,i 

## Air flow rate for daily cell i [L 3 

## /T] Q w 

## Leachate flow rate [L 3 

## /T] R a 

## Air-phase to total concentration partition/retardation coefficient [-] R s 

## Solid-phase to total concentration partition/retardation coefficient [-] R w 

## Water-phase to total concentration partition/retardation coefficient [-] S a,i 

## Advective gaseous transport source/sink term [M/T] S

D ,i 

## Total (air and water) diffusive transport source/sink term [M/T] S

Da,i 

## Gaseous diffusive transport source/si nk term through overlying cover [M/T] S

Da,tot,i 

## Total gaseous diffusive tran sport source/sink term [M/T] S

Dw,i 

## Aqueous diffusive transport source/ sink term through overlying cover [M/T] S

Dw,tot,i 

## Total aqueous diffusive tran sport source/sink term [M/T] S w,i 

## Advective aqueous trans port source/sink term [M/T] S λ ,i 

## Degradation source/sink term [M/T] S

NC 

## Diffusive source/sink term for the act ive daily cell with no cover [M/T] t Time [T] t cell 

## Time increment required to fill one daily cell (typically 1 day) [T] T

lf



## Total operating life of a landfill in years [T] T

lfcell 

## Operating life of an active landfill cell in years [T] t nc 

## Time required to fill a waste subcell with refuse [T] V

a 

## Volume of air within a daily cell [L 3 

## ] V

adj 

## Landfill volume after subtracting the final cover and liner volumes [L 3 

## ] V

cell 

## Daily cell volume, w ithout the daily cover [L 3 

## ] V

celltot 

## Daily cell volume, inclusive of the daily cover volume [L 3 

## ]

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-19 V

lfcell 

## Volume of a landfill cell [L 3 

## ] V

tot



## Total landfill volume [L 3 

## ] V

w 

## Volume of water within a daily cell [L 3 

## ]
ε

a 

## Air-phase volumetric fraction [L 3 

## /L 3 

## ]
ε

aC



## Air-phase volumetric frac tion in overlying cover [L 3 

## /L 3 

## ]
ε

C



## Porosity in overlying cover [L 3 

## /L 3 

## ]
ε

w 

## Water-phase volumetric fraction [L 3 

## /L 3 

## ]
ε

wC 

## Aqueous-phase volumetric fr action in overlying cover [L 3 

## /L 3 

## ] λ

a1 

## First-order biodegradation ra te in the air phase [/T] λ

s1 

## First-order biodegradation rate in the solid phase [/T] λ

w1 

## First-order biodegradation ra te in the water phase [/T] λ

a2 

## First-order abiotic degradati on rate in the air phase [/T] λ

s2 

## First-order abiotic degradation rate in the solid phase [/T] λ

w2 

## First-order abiotic degradation rate in the water phase [/T] ρ

b 

## Dry bulk density of the waste [solid mass/total volume, M/L 3 

## ] θ



## Working face angle [deg]
τ



## Tortuousity [-] 

# C.5 References
Aivaliotis, V., I. Dokas, M. Hatzigiannakou, and D. Pana giotakopoulos. 2004. Functional relationships of landfill and landraise capacity with design and operation parameters. Waste Management and Research 22 (4):283–290. Barlaz, M. 2006. “Topics relevant to devel opment and parameterizatio n of the LFCR landfill source model.” Multiple phone and email co mmunications from Dr. Morton Barlaz, Professor, Water Resources/Env ironmental Engineering, North Carolina State University, to Michael I. Lowry, RTI. July through December. Bartelt-Hunt, S. L., D. R. U. Knappe, P. Kjel dsen, and M. A. Barlaz. 2006. Fate of chemical warfare agents and toxic industrial chemicals in landfills. Environmental Science and Technology 40 (13):4,219–4,225. Carslaw, H. S., and J. C. Jaeger. 1947. Conduction of Heat in Solids . London: Oxford University Press. Cussler, E. L. 1984. Diffusion: Mass Transfer in Fluid Systems. New York: Cambridge University Press. Foose, G. J., C. H. Benson, and T. B. Edil. 1999. Equivalency of Compos ite Geosynthetic Clay Liners as a Barrier to Volat ile Organic Compounds. Pp. 321–334 in Geosynthetics 99 , Industrial Fabrics Association International, St. Paul, MN. Foose, G. J., C. H. Benson, and T. B. Edil. 2002. Comparison of Solu te Transport in Three Composite Liners. Journal of Geotechnical and Ge oenvironmental Engineering 128 (5):391–403.

### Draft Appendix C Landfill Source M odel Mathematical Formulation



## C-20 Kjeldsen, P., and T. H. Christensen. 2001. A simple model for the distribution and fate of organic chemicals in a landfill: MOCLA. Waste Management and Research 19 (3):201– 216. Millington, R. J. 1959. Gas diffusion in porous media. Science 130(3,367):100–102. Panagiotakopoulos, D., and I. Dokas. 2001. Design of landfill daily cells. Waste Management and Research 19 (6):613–622. Press, W. H, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery. 2002. Numerical Recipes in C++: The Art of Scie ntific Computing. Second Edition. New York: Cambridge University Press. Sangam, H. P., and R. K. Rowe. 2001. Migratio n of dilute aqueous organic pollutants through HDPE geomembranes

. 

## Geotextiles and Geomembranes 19 (6): 329–357. U.S. EPA (Environmental Protection Agency). 2005. Landfill Gas Emissions Model (LandGEM) Version 3.02 User’s Guide . EPA-600/R-05/047. U.S. EPA, Office of Research and Development, Morrisville, NC.

### Draft Appendix D Landfill Source Model Testing



## D-1 

# Appendix D Landfill Source Model Testing
This appendix provides landfill source model testing results. The testing ensures the model accuracy and reliabili ty in several areas:

 

## Verification testing ensures the computational accuracy of the landfill coupled reactor (LFCR) model as formulated in Appendix C by comparing model results with known analytical solutions. This ve rification testing includes te st cases focused on specific model operations and transport mechanisms. In addition, this testing verifies the implementation of the landfill filling algorithm. Verification testing is described in Section D.1

.

 

## Model linearity verification ensures that the mass loss resu lts vary linearly with input concentrations. The industrial wipes risk modeling was pe rformed using a single input concentration. If results scale linearly with the input concen tration, linear scaling factors can be used to adjust the results for any input concentration. Given that the model is essentially a first-order decay formulation, the results are expected to vary linearly with the input concentrati on. Linearity verificati on is described in Section D.2

.

 

## Robustness testing evaluates the model’s effectivene ss and reliability in simulating the range of conditions anticipated for the i ndustrial wipes risk assessment. Robustnesstesting scenarios explore the model behavi or using specific chemicals and scenarios representing the extremes of the anticipa ted parameter space (e.g., most/least volatile chemicals, maximum/minimum gas advection). Th e robustness testing c onsists of a series of robustness test cases that maximize and minimize the various model transport processes, such as advection, degradation, and diffusion. Because volatility is a dominant mechanism describing mass loss, the robus tness testing considers two chemicals representing the maximum a nd minimum Henry’s law consta nt. Robustness testing is described in Section D.3

. A series of test cases were developed usi ng average input parameter values to compare modeled landfill gas and leachate concentrations w ith measured values reported in the literature. Due to the uncertainty and absence of measured input concentrations, this analysis cannot fully validate the model. However, it does indicate that the LF CR model can generally reproduce measured landfill behavior. Section D.4 discusses comparison with measured data , Section D.5 discusses independent testing, and Section D.6 summarizes the testing findings. Section D.7 provides definitions of all symbols used in this appendix 

# D.1 Model Verification Testing This section describes specific model opera tions and transport mechanisms along with tests used to verify the accuracy of each m odel implementation. The verification of several of these transport mechanisms relies on comparis ons between analytical solutions and a model simulation where the landfill is re presented as a single landfill ce ll. This approach is adopted because analytical solutions are available for the relatively simple, single-cell scenarios.

### Draft Appendix D Landfill Source Model Testing



## D-2 Table D-1 presents the verification testing requirements. Table D-2 lists the various tests and their correspondence to these requirements. Table D-3 provides the input parameter values held constant for all verification tests. Table D-4 lists parameters and values that were adjusted for the different verification test cases. The si mulations include a sing le cell representing an operating landfill life of 40 years. The total si mulation time is 200 years (although it is extended for some of the tests if the mass loss rate is slow). Many of the testing input values are the median values for the input data used in the indu strial wipes risk analys is. Many of the chemical parameters are representative of tetrachloroethylene, which has th e greatest Henry’s law constant of the chemicals under consideration for the risk assessment. Nevertheless, the verification test scenarios are not intended to be representative of particular chemicals or landfills. In several cases, input values were significan tly adjusted (e.g., degradation ra tes, diffusivities) to verify specific transport mechanisms rather than to repr esent the behavior of pa rticular chemicals or scenarios. Figures D-1 through D-14 (at the end of this appendix) present the graphical comparisons between model results and the an alytical solution results calculated using spreadsheets. Table D-1. LFCR Verification Requirements
LFCR Verification Requirement Description 1 Accurate simulation of equilibrium mass partitioning between the solid, liquid, and air phases 2 Accurate simulation of the landfill gas generation rate 3 Accurate simulation of advective vapor transport 4 Accurate simulation of advective aqueous transport 5 Accurate simulation of first-order degradation/transformation 6 Accurate simulation of vapor diffusive transport 7 Accurate simulation of aqueous diffusive transport 8 Accurate simulation of vapor diffusi ve transport through a composite cover 9 Accurate simulation of vapor diffusive transport with no cover 10 Accurate simulation of vapor diffusive transport through a soil liner 11 Accurate simulation of aqueous di ffusive transport through a soil liner 12 Accurate simulation of vapor diffusive transport through a composite liner 13 Accurate simulation of aqueous diffusive transport through a composite liner 14 Accurate simulation of vapor diffusive transport with no liner 15 Accurate simulation of aqueous diffusive transport with no liner 16 Accurate simulation of the landfill waste addition algorithm 

### Table D-2. Summary of LFCR Verification Tests
Test Requirement 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1. Mass partitioning X X 2. Landfill gas generation X 3. Advective vapor transport X X 4. Advective aqueous transport X X

### Draft Appendix D Landfill Source Model Testing



## D-3 Test Requirement 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 5. First-order degradation X X 6. Vapor diffusive transport X X 7. Aqueous diffusive transport X X 8. Vapor diffusive transport through composite cover X 9. Vapor diffusive transport with no cover X 10. Vapor diffusive transport through soil liner X X 11. Aqueous diffusive transport through soil liner X X 12. Vapor diffusive transport through composite liner X 13. Aqueous diffusive transport through composite liner X 14. Vapor diffusive transport with no liner X 15. Aqueous diffusive transport with no liner X X 16. Landfill waste addition algorithm X 

### Table D-3. Input Parameters Held Constant for the LFCR Verification Tests
Parameter Unit Value Landfill operating life yr 40 Total landfill volume m 3 

### 4,232,637 Total landfill area m 2 

### 360,150 Landfill cell volume m 3 

### 4,232,637 Landfill cell area m 2 

### 360,150 Target cell/lift height m 11.75 Time before permanent cover instal led on landfill cell yr 17.8 Daily cell waste sublayer period hr 8 Working face angle to horizontal deg 19.6 Initial concentration kg/m 3 

### 1 Landfill cell operating life yr 40 Total simulation time yr 200 Initial timestep day 10 RK truncation error tolerance - 1.00E-11 Infinite sum trun cation error tolerance - 1.00E-12 Stopping criterion - 0.001 Output time series concentrations for cell 0,0 - 1 Daily cell period - 14600 Air diffusivity reference temperature C 25 Depth to water table m 9.14

### Draft Appendix D Landfill Source Model Testing



## D-4 Parameter Unit Value Unsaturated zone porosity - 0.43 Unsaturated zone moisture content - 0.284 Daily cover thickness m 0.152 Daily cover porosity - 0.43 Daily cover moisture content - 0.284 Intermediate cover thickness m 0.152 Intermediate cover porosity - 0.43 Intermediate cover moisture content - 0.284 Permanent cover soil thickness, [m] m 0.152 Permanent cover soil porosity - 0.43 Permanent cover soil moisture content - 0.284 Liner thickness m 0.152 Liner porosity - 0.43 Liner moisture content - 0.284 Geomembrane thickness m 0.0015 Organic carbon fraction in waste - 0.5 Porosity in waste - 0.53 Moisture content in waste - 0.17 Waste bulk density kg/L 0.63 Potential methane generation capacity L/kg 100.0 Average waste temperature C 37.4 Liner leakage rate before permanent cover m/yr 0.000219 Liner leakage rate after permanent cover m/yr 0.000219 Molar volume cm 3 

### /mol 111 Le Bas molar volume cm 3 

### /mol 128 Molecular weight g/mol 165.83 Henry's law constant atm-m 3 

### /mol 0.0184 Henry's law constant reference temperature C 25 Critical temperature C 346.85 Critical pressure atm 44 Boiling point C 121.3 Organic carbon distribution coefficient L/kg 218.5 Octanol water distribution coefficient L/kg 0DraftAppendix D Landfill Source Model TestingD-5Table D-4. Input Parameters Varied for the Verification TestingVerification Testing CasesParameterUnitBase123a45678b9c101112131415a16Fraction of day with no cover day 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.26E-05 0.00.0 0.0 0.00.0 0.0 0.0Landfill gas generation rate /yr 0.040.04 0.04 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.000.00 0.00 0.00 0.04 0.04Infiltration rate beforepermanent coverm/yr 0.109 0.109 0.1090 0.109 0 0 0 0 0 0 0 0 0 0 0.109 0.109Infiltration rate withpermanent coverm/yr 0.109 0.109 0.1090 0.109 0 0 0 0 0 0 0 0 0 0 0.109 0.109Liner leakage rate beforepermanent coverm/yr 0.000219 0.000219 0.0002190 0.000219 0 0 0 0 0 0 0 0 0 0 0.000219 0.000219Liner leakage rate afterpermanent coverm/yr 0.000219 0.000219 0.0002190 0.000219 0 0 0 0 0 0 0 0 0 0 0.000219 0.000219Abiotic decay half-life in water day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 20 0Biotic decay half-life in water day 19.3 19.3 19.3 0 0 20 0 0 0 0 0 0 0 0 0 20 19.3Biotic decay half-life in air day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 20 0Abiotic decay half-life in air day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 20 0Biotic decay half-life in solid day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 5000 0Abiotic decay half-life in solid day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 0 5000 0Daily cover moisture content -0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.2840.284 0.43 0.43 0.430.43 0.43 0.284 0.284Intermediate cover moisturecontent- 0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.43 0.43 0.43 0.43 0.43 0.284 0.284Permanent cover soilmoisture content- 0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.284 0.43 0.43 0.43 0.43 0.43 0.284 0.284Liner moisture content - 0.2840.284 0.284 0.284 0.284 0.284 0.43 0.284 0.43 0.43 0.284 0.2840.284 0.284 0.284 0.284 0.284Geomembrane permeationcoefficientcm2/sec 4.5E-07 4.5E-07 4.5E-07 4.5E-07 4.5E-07 4.5E-07 0 4.5E-07 4.5E-07 0 0 4.5E-07 4.5E-07 0 0 4.5E-07 0Liner configuration: 0=noliner; 1=soil liner;2=composite liner- 2 2 2 2 2 2 2 1 2 2 1 2 2 0 0 1 2Permanent coverconfiguration 0=soil only;1=composite- 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 1Diffusivity in airdcm2/sec -9999 -9999 -9999 0 0 0 -9999 0 -9999 -9999 -9999 -9999 0 -9999 0 -9999 -9999Diffusivity in waterdcm2/sec -9999 -9999 -9999 0 0 0 0 -9999 0 0 0 0 -9999 0 1.157E-04 -9999 -9999Water diffusivity referencetemperature (C)C 25 25 25 25 25 25 25 25 25 25 25 25 25 25 37.4 25 25Notes:a Gas generation rate was held constant at the initial value.c The no-cover flux rate was applied through the entire simulation.b Cover type was set to permanent cover for the entire simulation (including before closure).d -9999 is a flag telling the model to calculate the diffusivity using other chemical properties and a method provided inLyman et al. (1990).

### Draft Appendix D Landfill Source Model Testing



## D-6 

## D.1.1 Verification Case 1: Mass Partitioning The model assumes equilibrium phase partitioning based on linear equilibrium sorption described by a distribution coefficient ( K d 

## ) and linear equilibrium air-water partitioning described by a Henr y’s law constant ( K H



## ). According to these relationships, the ratios between phase concentrations (solid, wate r, and air) are constant. Thus, th e concentration within a given phase can be related to the con centration within any other phase and to the total concentration using partition coefficients (formulas presented in Appendix C ). Likewise, the fractions of total mass in the three phases are constant and can be calculated as follows (Kjeldsen and Christensen, 2001):

aa a a
a

ww w w
w

bs b
s
s 

## C f C R C f C R C f C R ε ε

ε ε

ρ ρ = =

= =

= = (Equation D-1)

Appendix C provides expressions for R a 

## , R w 

## , and R s 

## . According to the relationships outlined above, the following phase fractions are valid for the verification case 1 scenario (calculated in a spreadsheet using parame ter values in Tables D-3 and D-4): 0.00689 0.00244 0.99067 a

w

s 

## f f f =

=

= (Equation D-2)

Phase partition coefficients generated fr om a Case 1 simulation were compared successfully to the above values, thus verifying the mass partitioning relationships.


## D.1.2 Verification Case 2: Landfill Gas Generation Rate The model applies an approximation of landfill gas production similar to the LandGEM model (U.S. EPA, 2005) and following the Bartelt- Hunt et al. (2006) version of the Model for Organic Compounds in Landfills (MOCLA). The e xponential decay formulation below describes the decreasing landfill gas production rate over time (Bartelt-Hunt et al., 2006): 

## 2 kt
a o 

## q WL ke − 

## = (Equation D-3) Figure D-1 

## successfully compares the gas genera tion rate over time predicted using a spreadsheet and from a model simulation using th e input parameter values in Tables D-3 and D4. Note that the waste mass ( W ) is the product of the bulk dens ity and the waste volume (the landfill volume for this simulation). Figure D-2 

## shows the maximum value at time 0, because the simulation includes only a single cell, with all waste added at time 0. Note that LFCR simulations typically describe waste addition ove r time in daily cells, and the overall landfill gas generation rate increases and decreases accordingly.

### Draft Appendix D Landfill Source Model Testing



## D-7 

## D.1.3 Verification Case 3: Advective Vapor Transport Advective vapor transport describes the migr ation of mass within the flowing air phase. The following analytical solution de scribes the total concentration over time with a constant gas generation rate:

0 

## ( ) a

a q t VR 

## Ct Ce − 

## = 

## (Equation D-4) Evaluation of advective transport within th e gas phase involved comparison between a single cell model and the analytical solution above. As required by the analytical solution, this verification exercise used a wo rking version of the model with a constant gas production rate. The gas production rate was consta nt and equal to the rate at tim e zero as specified by the input parameters in Tables D-3 and D-4. Transport pa thways other than advection in the gas phase were disabled for this comparison (infiltration, de gradation rates, and diffusivities set to zero). The graph in Figure D-2 shows the successful comparison between the concentration predicted by the model and that generated by a spread sheet using the solution presented above. 

## D.1.4 Verification Case 4: Advective Aqueous Transport Advective aqueous transport de scribes the migration of mass within the flowing water phase. The following analytical solution describes the total concentration over time with a constant infiltration rate:

0 

## ( ) w N t H

R 

## Ct Ce − 

## = 

## (Equation D-5) Evaluation of advective transport within th e aqueous phase involved comparison between a single cell model and the analytical solution pr esented above. Transport pathways other than advection in the aqueous phase were disabled fo r this comparison (gas generation, degradation rates, diffusivities set to zero). Figure D-3 

## shows the successful comparison between the concentration predicted by the model and that generated by a spreadsheet using the solution shown above. Given the relatively small magnitude of the mass loss, the simulation time was extended in order to include a representative exponential decay curve for comparison. 

## D.1.5 Verification Case 5: Degradation/Transformation The model allows abiotic and biotic first-or der degradation within the solid, liquid, and gaseous phases based on six first-order rate constants. The following analytical solution describes the total concentration over time with these first-order degradation mechanisms:

121 212
0 

## () e aa a a ww w w s b s b

aawws s t RRR R RR 

## Ct C λε λ ε λε λ ε λρ λ ρ ⎛ ⎞ − ++ + ++

⎜ ⎟ ⎝ ⎠ 

## = (Equation D-6) The degradation formulation was verified by comparing results from a single-cell model with the analytical solution fo r first-order decay shown above. Other transport pathways were disabled for this verification exercise (infiltra tion, gas production rates, and diffusivities set to zero). Figure D-4 

## shows the successful comparison betw een the concentration predicted by the model and that generated by a spreadsh eet using the solution presented above.

### Draft Appendix D Landfill Source Model Testing



## D-8 

## D.1.6 Verification Case 6: Vapor Diffusive Transport The model describes Fickian diffusion in the air phase. Transport can occur between vertically adjacent daily cells or the atmosphe re. Vapor diffusion can also transfer mass to groundwater (Verifica tion Cases 10, 11, and 13). The followi ng analytical solution describes the total concentration over time with diffusive tr ansport in the air phase through an overlying cover:

0 

## ( ) a

a D t L HR 

## Ct Ce − 

## = 

## (Equation D-7) Note that the diffusion coefficient ( D a 

## ) is calculated from the air volume fraction, porosity, and air diffusivity using the tortuos ity formulation described in Appendix C



## . The formulation of diffusive transport in the air phase was ev aluated by comparing single-cell model results with results from th e analytical solution in Equation D-7. Other transport pathways were disabled for this verifi cation exercise (infiltra tion, degradation, air production rates, and water diffusivi ty set to zero). The parameter values for daily, interim, and permanent covers were identical. Note that te sting of diffusion through a geomembrane-based composite permanent cover occurs under Verifi cation Case 8. Diffusion through the liner was disabled by setting the type to a composite liner and the geomembrane permeation coefficient to
zero. Figure D-5 

## shows the successful comparison between the concentration predicted by the model and that generated by a spreadsheet using Equation D-7. 

## D.1.7 Verification Case 7: Aqueous Diffusive Transport The model describes Fickian diffusion in th e water phase through the liner and the soil cover. Transport can occur between vertically adjacent daily cells and with the underlying groundwater zone. Because the veri fication test case involves a single cell, aqueous diffusive transport through a soil liner wa s evaluated (there is no aque ous diffusion directly to the atmosphere). The following analytical solution describes the total concentration over time with diffusive transport in the water phase:

0 

## ( ) w

w D t LHR 

## Ct Ce − 

## = 

## (Equation D-8) The formulation of diffusive transport in the water phase was evaluated by comparing single-cell model results with results from the analytical solution above. Other transport pathways were disabled for this verification exercise (infiltra tion, degradation, air production rates, and air diffusivity set to zero). Figure D-6 

## shows the successful comparison between the concentration predicted by the model and that generated by a spreadsheet using the above solution. Given the relatively small magnitude of the mass loss, the simulation time was extended so as to include a representativ e exponential decay curve for comparison. 

## D.1.8 Verification Case 8: Vapor Diffu sive Transport through Composite Cover The model can be used to simulate diffusion through a composite permanent cover comprising a geomembrane and a soil layer. An equivalent diffusion coefficient describing transport through the soil and geomembrane is based on a thickness-weighted harmonic mean of the soil diffusion coefficient and the geomembr ane permeation coefficient. The analytical solution for vapor diffusive transport through a geomembrane and soil cover is as follows:

### Draft Appendix D Landfill Source Model Testing



## D-9 0 

## ( ) eq

a D t LHR 

## Ct Ce − 

## = (Equation D-9) The formulation of diffusive vapor trans port through a geomembrane-based cover was verified by comparing single-cell simulation results with results generated from the analytical solution shown in Equation D-9. Other transport pathways were disabled for this verification exercise (infiltration, degradati on, air production rates, and wate r diffusivity set to zero). As required by the analytical solution, a working version of the model was used to set the cover type to permanent cover through an entire simula tion (including before cl osure). Vapor diffusion through the bottom of the cell was disabled by setti ng the moisture content equal to the porosity. Figure D-7 

## shows the successful comparison between th e concentration pred icted by the model and that generated by a spreadsheet using the solution presented above. Given the relatively small magnitude of the mass loss, the simulation time was extended so as to include a representative exponential de cay curve for comparison. 

## D.1.9 Verification Case 9: Vapor Diffusive Transport with No Cover The model describes vapor diffusion with no cover over the waste (during active waste addition before the daily cover is applied) usi ng a Carslaw and Jaeger solution to the diffusion equation as presented in Appendix C 

## . This approach produces an average flux with no cover ( J

avg 

## ). The analytical solution for transport with a constant no-cover flux is as follows:

0 

## ( ) avg calc J t H 

## Ct Ce ⎛ ⎞

− ⎜ ⎟

⎝ ⎠ 

## = (Equation D-10) The implementation of the no-cover diffusive transport was verified by comparing singlecell simulation results with results generated fr om the analytical solution in Equation D-10. Other transport pathways were disabled for this verification exercise (inf iltration, degradation, air production rates, and water diffu sivity set to zero). As requir ed by the analytical solution, a working version of the model was used so that the no-cover flux could be held constant through the entire simulation. The fraction of day with no cover used to calculate the no-cover flux was 8 hours; however, this flux rate was applied as a constant mass loss term throughout the simulation to allow comparison with an analytical solution. Figure D-8a 

## shows the successful comparison between the concentration predic ted by the model and that generated by a spreadsheet using the above solution. The verifying calculation of the average no-cover flux is provided in Figure D8b 

## . Note that the mass loss rate is relatively large, so that most of the mass is lost within approximately 5 years. This rapid mass loss occurs because the flux is applied continuously for a single cell that represents the entire landfill ma ss. For actual risk assessment calculations, the nocover mass loss is applied only during the period with no cover and only to the current active daily cell. Thus, the contribution of the no-cove r mass loss is significantly lower than in this verification scenario. 

## D.1.10 Verification Case 10: Vapor Di ffusive Transport Through a Soil Liner The model can simulate vapor diffusion with a soil-only landfill liner. The analytical solution for transport through a soil liner is as follows:

0 

## ( ) a

a D t L HR 

## Ct Ce − 

## = 

## (Equation D-11)

### Draft Appendix D Landfill Source Model Testing



## D-10 The formulation of diffusive transport in air through a soil li ner was verified by comparing single-cell simulation results with resu lts generated from the analytical solution in Equation D-11. Other transport pathways were disabl ed for this verification exercise (infiltration, degradation, and air production rate s set to zero, and water diffusivity set to a negligible value). Diffusion through the top of the cell was disabled by setting the moisture content equal to the porosity for all cover types. Figure D-9 

## shows the successful comparison between the concentration predicted by the model and that generated by a spreadsheet using the solution shown above. 

## D.1.11 Verification Case 11: Vapor Di ffusive Transport through a Composite Liner The model can simulate vapor diffusion th rough a composite liner made up of a geomembrane and a soil layer. The analytical so lution for transport through a composite landfill liner is as follows:

0 

## ( ) eq

a D t LHR 

## Ct Ce − 

## = (Equation D-12) where the equivalent diffusion coefficient is th e harmonic mean of the geomembrane permeation coefficient and the soil diffusion coefficient. The formulation of diffusive transport in ai r through a composite liner was verified by comparing single-cell simulation results with resu lts generated from the analytical solution in Equation D-12. Other transport pathways were disabl ed for this verification exercise (infiltration, degradation, air production rates, and water diffusivity set to ze ro). Diffusion through the top of the cell was disabled by setting the moisture cont ent equal to the porosity for all cover types. Figure D-10 

## shows the successful comparison between th e concentration predicted by the model and that generated by a spreadsheet using the so lution shown above. Given the relatively small magnitude of the mass loss, the simulation time was extended so as to include a representative exponential decay curve for comparison. 

## D.1.12 Verification Case 12: Aqueous Diffusive Transport through a Composite Liner The model can simulate aqueous diffusion thr ough a composite landfil l liner made up of a geomembrane and soil layer. The analytical solution for transport through a composite landfill liner is as follows:

0 

## ( ) eq

w D t LHR 

## Ct Ce − 

## = (Equation D-13) where the equivalent diffusion coefficient is th e harmonic mean of the geomembrane permeation coefficient and the soil diffusion coefficient. The formulation of diffusive transport in wa ter through a composite liner was verified by comparing single-cell simulation results with resu lts generated using the analytical solution in Equation D-13. Other transport pathways were disabl ed for this verification exercise (infiltration, degradation, air production rates, and air diffusivity set to zero). Figure D-11 

## shows the successful comparison between the concentration predicted by the model and that generated by a spreadsheet using the solution presented above. Gi ven the relatively small magnitude of the mass

### Draft Appendix D Landfill Source Model Testing



## D-11 loss, the simulation time was extended so as to include a representative exponential decay curve for comparison. 

## D.1.13 Verification Case 13: Vapor Diffusive Transport with No Liner The model can simulate vapor diffusion when there is no landfill liner. The sink term for this transport pathway is based on an analytical solution to th e diffusion equation presented in Appendix C 

## . The analytical solution below describes th e change in total concentration over time with no liner due to diffusion in air th rough the underlying unsaturated zone:

0 

## ( ) a

u a D t L HR 

## Ct Ce − 

## = 

## (Equation D-14) The formulation of diffusive transport in ai r with no liner was verified by comparing single-cell simulation results with results genera ted from the analytical solution in Equation D-14. Other transport pathways were disabled for this verification exercise (infiltration, degradation, air production rates, and water diffusivity set to ze ro). Diffusion through the top of the cell was disabled by setting the moisture cont ent equal to the porosity for all cover types. Figure D-12 

## shows the successful comparison between th e concentration predicted by the model and that generated by a spreadsheet using the solution presented above. Given the relatively small magnitude of the mass loss, the simulation time was extended so as to include a representative exponential de cay curve for comparison. 

## D.1.14 Verification Case 14: Aqueou s Diffusive Transport with No Liner The model can simulate aqueous diffusion when there is no landfill liner. The sink term for this transport pathway is based on an analy tical solution to the diffu sion equation presented in Appendix C 

## . The analytical solution below describes th e change in total concentration over time with no liner due to diffusion in water through the underlying unsaturated zone:

0 

## ( ) w

u w D t L HR 

## Ct Ce − 

## = 

## (Equation D-15) The formulation of diffusive transport in wa ter with no liner was verified by comparing single-cell simulation results with results genera ted from the analytical solution in Equation D-15. Other transport pathways were disabled for this verification exercise (infiltration, degradation, air production rates, and air diffusivity set to zero). Note that the water diffusivity was increased versus the base-case calculated value so as to incr ease the mass loss attributable to aqueous diffusion (without the increase, the co ncentration change would be too small for effective comparison with the analytical solution). Figure D-13 

## shows the successful comparison between the concentration predic ted by the model and that generated by a spreadsheet using the solution presented above. Given the relatively sm all magnitude of the mass loss, the simulation time was extended so as to include a represen tative exponential decay curve for comparison.


## D.1.15 Verification Case 15: Base Ca se Simulation/Simultaneous Mechanisms The verification cases above consider differe nt transport mechanisms in independent simulations. Verification Case 15 consider s multiple transport mechanisms acting simultaneously. The analytical solution below desc ribes the change in to tal concentration over time with the following transport mechanisms: advective vapor transport with a constant gas

### Draft Appendix D Landfill Source Model Testing



## D-12 production rate; advective aqueous transport with a constant infiltration ra te; degradation in the solid, gas, and aqueous phases; di ffusion in air through an overly ing soil cover and an underlying soil liner; and diffusion in water through an underlyi ng soil liner.

121 212 2

0 

## ( ) a aa a a ww w w s b s b a w

a wa a w w s s a w q DD N t VR HR R R R R R R LHR LHR 

## Ct Ce λε λ ε λε λ ε λρ λ ρ ⎛ ⎞ − ++ + + + + + + +

⎜ ⎟ ⎝ ⎠ 

## = (Equation D-16) Note that in the solution shown above, it is assumed that the cove r and liner input parameters are the same and are consistent between cover types. Verification Case 15 involved comparing si ngle-cell simulation results with results generated from the analytical solution in Equa tion D-16. A working version of the model was used to hold the gas production ra te constant at the initial value. Note that the solid-phase degradation half-life was increased versus the degradation test case (Verification Case 5), so that this mechanism would not dominate the transport. Figure D-14 

## shows the successful comparison between the concentration predic ted by the model and that generated by a spreadsheet using the solution presented above.


## D.1.16 Verification Case 16: Accuracy of the Landf ill Waste Addition Algorithm The landfill waste addition algorithm describes th e addition of daily landfill waste in the geometric pattern of cells and lifts shown in Figure 3-1 (see Section 3.1 

## ). The algorithm tracks the appropriate locations for each cell and its relationship to other cells. Different cell characteristics apply, depending on the cell loca tion and timing. For ex ample, the algorithm maintains information about whethe r a given cell is within a bottom, middle, or top lift, so that the appropriate liner, cover, or inter-cell transport pathways are parameterized. Detailed results of the model waste addition algorithm were exported from the model and reviewed for accuracy. The following results were verified: cell ID, colu mn ID, whether the cell is a top cell, whether the cell is a bottom cell, and the top configuratio n (open cover, daily cover, interim cover, or permanent cover). 

# D.2 Model Linearity Verification Model linearity verification ensures that the mass loss results vary linearly with input concentrations (and the corres ponding mass loading ra te). The industrial wipes risk modeling was performed using a single input concentration. If results scale linearly with the input concentration, linear scaling factor s can be used to adjust the resu lts for any input concentration. Given that the model is essentially a first-order decay formulation, the results are expected to vary linearly with the input concentration. Model linearity verification i nvolved a series of test cas es with different initial concentrations. The input paramete r values corresponded to the base case values in Table D-4. Five simulations were performed with input conc entrations of 0.01, 0.1, 1, 10, and 100. The results were compared, and all mass loss results s caled linearly with the input concentration. 

# D.3 Model Robustness and Sensitivity Testing The robustness testing evaluates the model eff ectiveness and reliability in simulating the range of conditions anticipated for the industrial wipes risk assessment. Robustness testing scenarios explore the model behavi or using specific chemicals a nd conditions representative of

### Draft Appendix D Landfill Source Model Testing



## D-13 the extremes of anticipated parameter sp ace (e.g., most/least volatile chemicals, maximum/minimum vapor advection). The robustness testing includes a series of robustness test cases that maximize and minimize the various model transport mechanisms, such as advection, degradation, and diffusion. Because volatility is a dominant mechanism describing mass loss, two chemicals are included in the robustness testing, based on the maximum and minimum Henry’s law constant. Table D-5 

## lists the robustness te sting requirements, and Table D-6 

## provides a summary of the robustness tests a nd their correspondence to the requirements. Table D-5. Source Model Robustness Requirements
Robustness Requirement Description 1 Ability to complete long simulation times (hundreds of years) within a short execution time (less than a minute) across most simulation conditions. 2 Ability to generate mass-conservative results acro ss the anticipated range of parameter space. 3 Ability to maintain solution numerical accuracy across the anticipated range of parameter space. 4 Ability to simulate the scenario and constituent with the maximum potential chemical advection rate in air. 5 Ability to simulate the scenario and constituent with the minimum potential chemical advection rate in air. 6 Ability to simulate the scenario and constituent with the maximum potential chemical advection rate in water. 7 Ability to simulate the scenario and constituent with the minimum potential chemical advection rate in water. 8 Ability to simulate the scenario and constituent with the maximum potential chemical diffusion rate in air. 9 Ability to simulate the scenario and constituent with the minimum potential chemical diffusion rate in air. 10 Ability to simulate the scenario and constituent with the maximum potential chemical diffusion rate in water. 11 Ability to simulate the scenario and constituent with the minimum potential chemical diffusion rate in water. 12 Ability to simulate the scenario and constituen t with the maximum potential decay rate. 13 Ability to simulate the scenario and constituent with the minimum potential decay rate. 14 Ability to simulate the scenario and constituent with the maximum diffusion to groundwater with no liner. 15 Ability to simulate the scenario and constituent with the minimum diffusion to groundwater with no liner. 16 Ability to simulate the scenario and constituent with the maximum diffusion with no cover. 17 Ability to simulate the scenario and constituent with the minimum diffusion with no cover. 18 Ability to simulate the maximum landfill volume and area within the anticipated range of parameter space. 19 Ability to simulate the minimum landfill volume and area within the anticipated range of parameter space.

### Draft Appendix D Landfill Source Model Testing



## D-14 Table D-6. Summary of Robustness Tests
Test Requirement 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1. Simulation runtime X X X X X X X X X X X X X X X X X X 2. Mass conservation X X X X X X X X X X X X X X X X X X 3. Numerical accuracy X X X X X X X X X X X X X X X X X X 4. Maximum vapor advection X 5. Minimum vapor advection X 6. Maximum aqueous advection X 7. Minimum aqueous advection X 8. Maximum vapor diffusion X 9. Minimum vapor diffusion X 10. Maximum aqueous diffusion X 11. Minimum aqueous diffusion X 12. Maximum decay X 13. Minimum decay X 14. Maximum diffusion with no liner X X
15. Minimum diffusion with no liner X X
16. Maximum diffusion with no cover X
17. Minimum diffusion with no cover X
18. Maximum landfill area/volume X
19. Minimum landfill area/volume X



## The general strategy for the robus tness testing was to select parameter combinations that would maximize and minimize the transport proc ess under consideration. For example, Test Cases 1 and 2 respectively maximize and mini mize vapor-phase advection by using endpoint values for the landfill gas generation and phase partitioning to the gas phase. Table D-7 

## provides the parameter values held consta nt for the robustness testing. Table D-8 

## lists the range of variable parameter values within the risk asse ssment database and the parameterization scheme for each robustness test. As the table indicate s, the robustness tests will use the maximum, minimum, or median values within the parame ter space. The chemicals with the maximum and minimum volatility are tetrachloroet hylene and cresols, respectively.

### Draft Appendix D Landfill Source Model Testing



## D-15 Table D-7. Robustness Testing Parameters Held at Constant Values
Parameter Unit Value Fraction of day with no cover - 0.33 Daily cell waste sublayer period hr 1 Initial concentration kg/m 3 

### 1 Total simulation time yr 200 Initial timestep day 0.33 RK truncation error tolerance - 1.00E-12 Infinite sum trun cation error tolerance - 1.00E-12 Stopping criterion - 0.001 Output time series concentrations for cell 0,0 - 0 Daily cell period - 1 Diffusivity in air cm 2 

### /sec -9999 Air diffusivity reference temperature C 25 Diffusivity in water cm 2 

### /sec -9999 Water diffusivity reference temperature C 25 Octanol water distribution coefficient L/kg 0 Biotic decay half-life in air day 0 Abiotic decay half-life in air day 0 Biotic decay half-life in solid day 0 Abiotic decay half-life in solid day 0 Daily cover thickness m 0.152 Intermediate cover thickness m 0.305 Permanent cover soil thickness, [m] m 0.61 Liner thickness m 0.61 Liner porosity - 0.427 Liner moisture content - 0.2 Geomembrane thickness m 0.0015DraftAppendix D Landfill Source Model TestingD-16Table D-8. Robustness Testing Variable Input Parameter Values

### Draft Appendix D Landfill Source Model Testing



## D-17 Each robustness test included evaluations fo r simulation runtime, mass conservation, and numerical accuracy (Robustness Requirements 1 through 3). Thes e evaluations ensure that Requirements 1 through 3 are maintained through out the parameter space under consideration for the industrial wipes risk assessment. Each of these first three Robustness Requirements is discussed in more detail below. Because of the large number of simulations re quired, a short simulation runtime is critical to implementing the Monte Carlo–b ased risk assessment. The i ndustrial wipes risk assessment considers 20 chemicals and 2 independent liner scenarios. Each chemical and scenario will have 10,000 realizations with variable parameter values. Thus, the project requires 400,000 simulations. The runtime requirement for a singl e simulation will be 0.2 minutes. With this runtime and the available computer hardware, the complete set of source model simulations should take approximately 1 week to complete. The model implements a comprehensive mass balance evaluation of the results. Through each simulation, the cumulative relative mass bala nce error is calculated at the end of each time step:

, ,

, in tot out tot lf

in tot 

## M M M M − − 

## (Equation D-17)
In addition, the relative mass balance error associated with each time step is calculated
as: ( ) ( ) ( ) ( 1) ( ) ( 1) in out lf lf
lf lf 

## Mi M i Mi Mi Mi Mi − − +−

− − (Equation D-18)
The standard output includes these mass balan ce results, which were reviewed for all robustness tests to ensure that the mass balance error did not exceed a requirement of 1 percent for any test case. The Runge-Kutte implementation estimates th e solution error and compares it with a user-specified tolerance following each time step. If the error exceeds this tolerance, a smaller time step is used until the error is sufficiently low. Thus, the solution accuracy is internally controlled through adaptive time step adjustment. There is a tradeoff between the Runge-Kutte error tolerance, the runtime, and the mass balance error: as the error tolerance decreases, runtimes increase and the mass balance error decr eases. Preliminary simulations suggest that an error tolerance of 1e-11 provi des an appropriate balance between the runtime and the mass balance error. This value will be used for all robustness tests. If the mass balance error exceeds the 1 percent requirement for any robustness test case, the error tolerance will be decreased until an acceptable mass balance error is achieved. The series of robustness tests will provide an evaluation of the appropriateness of the 1e-11 va lue for the range of pa rameter space anticipated for the risk assessment. This section describes the design and results of specific robustness tests. Documentation of the robustness testing include s the total mass loss per pathwa y associated with each test ( Table D-9 

## ) as well as graphs showing the mass loss per pathway over time ( Figures D-15 

## through D-30 

## ). Table D-9 also provides summary result s for simulations using median parameter values for comparison. Standard output includes the total mass lost from the system via the following pathways: diffusion to the atmosphere, diffusion to the groundwater zone, degradation

### Draft Appendix D Landfill Source Model Testing



## D-18 in solid, degradation in water, degradation in ai r, diffusion with no cover, advection in the air phase, and advection in the water phase. This information and comparisons between robustness test results provide qualitative sensitivity analysis to ensure that the model produces the expected results as parameters are varied. The robustness-testing simulations consider one landfill cell (landfil l section) with a 4-year operating life. An entire landfill simulation would include a sequential series of such landfill cell results. Results for a single landfill cell are representative of the entire landfill, because each landfill cell behaves identically.


## D.3.1 Robustness Tests 1 and 2: Maxi mum/Minimum Vapor-Phase Advection The model should reliably simulate the scenar ios and constituents with the maximum and minimum potential chemical advection rates in air. Parameters controlling the vapor-phase advection rate include landfill gas generation parameters (gas generation rate and the methane generation capacity) and phase partitioning wast e properties (Henry’s law constant, organic carbon distribution coefficient, fraction organic carbon, moistu re content, porosity, and bulk density). These parameters were set to values that maximize and minimize the gas production rate and the phase partitioning to air, as described in Table D- 8 under Test Cases 1 and 2. The parameter values selected were the endpoint valu es of the respective distributions (maxima and minima), thus evaluating the range of parameter space associated with the industrial wipes risk assessment. Table D-9 shows that the re lative contribution of vapor- phase advection follows the expected pattern (79 percent versus 0.04 percent for the maximum and minimum cases, respectively). Also, the mass balance and simulation time results meet the requirements. Figures D-15a 

## , D-15b 

## , and D-15c 

## show the mass loss associated with particular pathways over time for Test Case 1. The vapor advection rate increases over the 4-year operating life of the landfill cell, with the changes in slope occurring when new lifts are added (there are four lifts in this simulation). Diffusion through the ov erlying cover increases as the first lift is added to the system, as a result of the increase in surface area . Thereafter, the rate decreases slowly as waste is added above the initial lift; th e rate decreases because an incr easing amount of mass is lost to vapor advection. At 4 years, an interim cover is added to the landfill cell, causing a sharp decrease in the diffusive loss rate. The loss rate with no cover is consta nt during the operating life of the landfill cell and decreases to zero after the 4-year operating life is over. The relative significance of the no-cover flux indicates that it is the dominant mechanism within a single daily cell (compare the fluxes at time zero); howev er, the no-cover flux only applies to the active daily cell, so that the no-cover mass loss contribu tion is smaller relative to the entire landfill waste. Diffusion to groundwater is the primary mechanism fo r loss to groundwater, although the significance in Test Case 1 relative to atmospheric losses is low. Figures D-16a 

## , D-16b 

## , and D-16c 

## show the mass loss associated with Test Case 2. As Figure D-16a shows, aqueous advection and degradation are the dominant loss mechanisms. Neither of these mechanisms results in mass loss to air or groundwater (aqueous advection is recovered in a leachate collection system when there is a composite liner). Figu re D-16b shows that no-cover mass loss is the dominant mechanism for transfer of mass to th e atmosphere. The decrease in diffusion through the cover at 17.8 years occurs when the perman ent cover is placed over the landfill cell. These results collectively show the expected mode l behavior associated with maximizing and minimizing vapor-phase advection. The releva nt robustness requirements are satisfied.DraftAppendix D Landfill Source Model TestingD-19Table D-9a. Robustness Testing Summary Results (Median and Test Cases 1–4)Robustness Testing CasesMedian Value Cases1234No LinerComposite LinerVapor AdvectionAqueous AdvectionTotalMassLoss perPathway(total g)Max HMin HMax HMin HMaxMinMaxMinVaporadvection toatmosphere2.74E+08 72.72% 351313 0.16% 2.62E+08 73.91% 333963 0.16% 2.92E+08 79.20% 77734.90.04% 50806.4 0.01%3.07E+08 84.36%Diffusion toatmosphere9.55E+07 25.33% 433212 0.20% 7.67E+0721.63% 321316 0.15% 7.39E+07 20.07% 1072620.06% 339075 0.09% 5.26E+07 14.43%Loss with nocover (alsoincluded indiffusion toair)1.26E+07 3.35% 268443 0.12% 1.22E+073.44% 258913 0.12% 2.91E+07 7.89% 78788.9 0.04% 292153 0.08% 1.29E+07 3.55%Decay inwater2.51E+06 0.66% 1.67E+08 76.20%2.42E+06 0.68% 1.57E+08 75.02%193662 0.05% 1.59E+08 82.00% 1.21E+08 31.99% 3.51E+05 0.10%Aqueousadvection tobottom1.20E+06 0.32% 5.10E+07 23.36%1.12E+06 0.32% 5.08E+07 24.28%1.30E+01 0.00% 3.42E+07 17.64%2.57E+08 67.88% 1.36E+01 0.00%Loss to linerleakage1.20E+06 0.32% 5.10E+07 23.36%1.12E+06 0.32% 5.08E+07 24.28%0 0.00% 4.20E+06 2.16% 2.57E+08 67.88% 0.00E+00 0.00%Diffusion togroundwater3.65E+06 0.97% 177406 0.08% 1.23E+073.47% 805101 0.38% 2.50E+06 0.68% 5253560.27% 109077 0.03% 4.05E+06 1.11%Total loss toair3.70E+08 98.05% 784528 0.36% 3.39E+0895.54% 655275 0.31% 3.66E+08 99.27% 1849960.10% 389881 0.10% 3.60E+08 98.79%Total loss togroundwater4.84E+06 1.28% 5.12E+07 23.44%1.34E+07 3.78% 5.16E+07 24.66%2.50E+06 0.68% 4.72E+06 2.43%2.57E+08 67.91% 4.05E+06 1.11%Massreleased fromsystem3.77E+08 2.19E+08 3.55E+08 2.09E+083.68E+08 1.94E+08 3.79E+08 3.64E+08Mass addedto system3.89E+08 3.89E+08 3.69E+08 3.69E+083.69E+08 3.69E+08 3.89E+08 3.69E+08Massremainingwithin landfill1.08E+07 1.70E+08 1.31E+07 1.59E+08366713 1.74E+08 8.32E+06 3.64E+06% massbalance error0.37% 0.29% 0.36% 0.30%0.15% 0.21% 0.52% 0.28%Massremainingwithin landfill(%)2.77% 43.57% 3.56% 43.00%0.10% 47.22% 2.14% 0.99%DraftAppendix D Landfill Source Model TestingD-20Robustness Testing CasesMedian Value Cases1234No LinerComposite LinerVapor AdvectionAqueous AdvectionTotalMassLoss perPathway(total g)Max HMin HMax HMin HMaxMinMaxMinSimulationstopped bymass losscriterionNo No No No Yes No No NoFinal time 200.18 201.362 201.855201.362 191.226 202.11200.241 200.256Simulationruntime0.1 0.0833333 0.1 0.10.15 0.083333 0.1 0.1Table D-9b. Robustness Testing Summary Results (Test Cases 5–12)Robustness Testing Cases56789101112Vapor DiffusionAqueous DiffusionDegradationNo-Liner Vapor DiffusionTotalMassLoss perPathway(total g)MaxMinMaxMinMaxMinMaxMinVaporadvection toatmosphere1.06E+08 27.28% 178328 0.10% 659188 0.27%2.82E+08 98.52% 65890.6 0.02% 2.58E+08 75.12% 2.06E+08 53.21% 180225 0.09%Diffusion toatmosphere2.82E+08 72.39% 84108.4 0.05%0 0.00% 0.00E+00 0.00% 3935610.11% 7.00E+07 20.34% 9.74E+07 25.10% 1.59E+05 0.07%Loss with nocover (alsoincluded indiffusion toair)3.01E+07 7.75% 78788.9 0.04%0 0.00% 0.00E+00 0.00% 3697230.10% 1.09E+07 3.16% 3.01E+07 7.77% 81737.3 0.04%Decay inwater231510 0.06% 1.73E+08 98.08% 2.34E+0896.26% 3671160 1.28% 3.64E+08 99.52% 8688610.25% 280682 0.07% 1.72E+08 80.97%Aqueousadvection tobottom197908 0.05% 2.58E+06 1.47% 7.44E+06 3.06% 5.23E+05 0.18% 1.26E+06 0.34% 1.23E+06 0.36%102897 0.03% 4.00E+07 18.87%Loss to linerleakage197908 0.05% 80281 0.05% 109826 0.05% 5.24E+03 0.00% 2538.87 0.00% 1.23E+060.36% 102897 0.03% 4.00E+07 18.87%Diffusion togroundwater860833 0.22% 533853 0.30% 993495 0.41% 3.13E+04 0.01% 20024.6 0.01% 1.35E+07 3.93% 8.38E+0721.59% 3.39E+03 0.00%Total loss toair3.88E+08 99.67% 262437 0.15% 659188 0.27%2.82E+08 98.52% 459453 0.13% 3.28E+0895.46% 3.04E+08 78.31% 339086 0.16%Total loss togroundwater1.06E+06 0.27% 614135 0.35% 1103320 0.45% 3.65E+04 0.01% 22563.4 0.01% 1.47E+07 4.29% 8.39E+07 21.62% 4.00E+07 18.87%DraftAppendix D Landfill Source Model TestingD-21Robustness Testing Cases56789101112Vapor DiffusionAqueous DiffusionDegradationNo-Liner Vapor DiffusionTotalMassLoss perPathway(total g)MaxMinMaxMinMaxMinMaxMinMassreleased fromsystem3.89E+08 1.76E+08 2.43E+08 2.86E+083.66E+08 3.44E+08 3.88E+08 2.12E+08Mass addedto system3.89E+08 3.69E+08 3.69E+08 3.69E+083.69E+08 3.69E+08 3.89E+08 3.89E+08Massremainingwithin landfill389018 1.92E+08 1.24E+08 8.06E+07364705 2.37E+07 388612 1.76E+08% massbalance error0.02% 0.21% 0.48% 0.63%0.80% 0.37% 0.26% 0.28%Massremainingwithin landfill(%)0.10% 52.08% 33.59% 21.83%0.10% 6.43% 0.10% 45.28%Simulationstopped bymass losscriterionYes No No NoYes No Yes NoFinal time 50.0011 201.781 201.362202.222 21.6581 201.65538.3756 201.362Simulationruntime0.16667 0.083333 0.083333 0.0666670.1 0.1 0.1 0.083333Table D-9c. Robustness Testing Summary Results (Test Cases 13–18)Robustness Testing Cases131415161718No-Liner Aqueous DiffusionNo-Cover DiffusionLandfill Depth(total g TotalMass Lossper Pathway)MaxMinMaxMinMaxMinVapor advection toatmosphere663007 0.23% 2.47E+08 72.71% 2.42E+08 65.91% 176191 0.10% 1.82E+09 94.31% 30147.3 0.16%Diffusion toatmosphere795626 0.28% 8.71E+07 25.67% 1.17E+08 31.77% 93268 0.05% 8.30E+07 4.30% 94776.1 0.52%Loss with no cover(also included indiffusion to air)499906 0.17% 9.42E+06 2.77% 4.01E+07 10.93% 61181.7 0.03% 3.88E+07 2.01% 54803.9 0.30%Decay in water 2.24E+08 77.87% 2.98E+06 0.88% 6517650.18% 1.72E+08 96.95% 1.85E+07 0.96% 1.43E+07 77.78%DraftAppendix D Landfill Source Model TestingD-22Robustness Testing Cases131415161718No-Liner Aqueous DiffusionNo-Cover DiffusionLandfill Depth(total g TotalMass Lossper Pathway)MaxMinMaxMinMaxMinAqueous advectionto bottom5.18E+07 18.03% 2.20E+06 0.65%353037 0.10% 4.60E+06 2.60% 2.68E+05 0.01% 3.49E+06 18.96%Loss to linerleakage5.18E+07 18.03% 2.20E+06 0.65% 1002.7 0.00% 80162.5 0.05%1500.24 0.00% 60189.3 0.33%Diffusion togroundwater1.03E+07 3.60% 3.02E+05 0.09% 7.49E+06 2.04% 533066 0.30%8.18E+06 0.42% 474725 2.58%Total loss to air 1.46E+06 0.51% 3.34E+08 98.38% 3.59E+08 97.69%269458 0.15% 1.90E+09 98.60% 124924 0.68%Total loss togroundwater6.22E+07 21.63% 2.51E+06 0.74% 7.50E+06 2.04% 613228 0.35%8.18E+06 0.42% 534915 2.91%Mass releasedfrom system2.87E+08 3.39E+08 3.67E+081.77E+08 1.93E+09 1.84E+07Mass added tosystem3.89E+08 3.89E+08 3.69E+083.69E+08 2.09E+09 3.46E+07Mass remainingwithin landfill9.93E+07 4.85E+07 1.22E+061.91E+08 1.51E+08 1.61E+07% mass balanceerror0.65% 0.38% 0.19%0.21% 0.24% 0.27%Mass remainingwithin landfill (%)25.51% 12.44% 0.33%51.85% 7.25% 46.58%Simulation stoppedby mass losscriterionNo No No No No NoFinal time 201.362 200.426200.148 201.362 202.406 200.118Simulation runtime 0.083333 0.083333 0.1166667 0.083333 0.1 0.083333

### Draft Appendix D Landfill Source Model Testing



## D-23 

## D.3.2 Robustness Tests 3 and 4: Maxi mum/Minimum Aqueous-Phase Advection The model should reliably simulate the scenar ios and constituents with the maximum and minimum potential chemical advection rates in water. Parameters controlling the aqueous-phase advection rate include the net infiltration and liner leakage rates and phase partitioning waste properties (Henry’s law constant, organic carb on distribution coeffici ent, fraction organic carbon, moisture content, porosity, and bulk density ). These parameters were set to values that maximize and minimize the infiltration and liner l eakage rates and the mass partitioning to water, as described in Table D-8 under Test Cases 3 an d 4. The parameter values selected were the endpoint values of the respectiv e distributions (maxima and mini ma), thus evaluating the range of parameter space associated with th e industrial wipes risk assessment. Table D-9 shows that the rela tive contribution of aqueous-p hase advection follows the expected pattern (68 percent versus 0 pe rcent for the maximum and minimum cases, respectively). Also, the mass balance and simulation time results meet the requirements. Figures D-17a 

## , D-17b 

## , and D-17c 

## show the mass loss associated with particular pathways over time for Test Case 3. Aqueous degradation is relatively si gnificant, which appears to be a general pattern as the significance of vapor-phase loss decrease s. Also, no-cover loss is the most dominant vapor-phase loss mechanism, although the relativ e significance of vapor losses is small. As expected by the input parameters, aqueous a dvection is the dominant loss mechanism. Figures D-18a 

## , D-18b 

## , and D-18c 

## show the mass loss for Test Case 4, where vapor-phase losses are dominant and aqueous-phase advect ion is relatively insignificant. These results collectively show the expected model behavior associated with maximizing and minimizing aqueous-phase advection. The relevant robustn ess requirements are satisfied.


## D.3.3 Robustness Tests 5 and 6: Maxi mum/Minimum Vapor-Phase Diffusion The model should reliably simulate scenario s and constituents with the maximum and minimum potential chemical diffusion rates in air. Parameters controlling the vapor-phase diffusion rate include air diffusivity, phase pa rtitioning waste properties (moisture content, porosity, bulk density, organic carbon distribut ion coefficient, and fr action organic carbon), cover/liner properties (type, thickness, moisture c ontent, porosity), and th e fraction of a day with no cover. These parameters were set to values that maximize and minimize the diffusion coefficients and the phase partitioning to air, as described in Table D-8 u nder Test Cases 5 and 6. The parameter values selected were the endpoint values of the respective distributions (maxima and minima), thus evaluating the range of parame ter space associated w ith the industrial wipes risk assessment. Table D-9 shows that the rela tive contribution of diffusion to the atmosphere follows the expected pattern (72 percent versus 0.05 percent for the maximum and minimum cases, respectively). Also, the mass balance and simulation time results meet the requirements. Figures D-19a 

## , D-19b 

## , and D-19c 

## show the mass loss associated with particular pathways over time for Test Case 5. Vapor-phase transport clearly dom inates the mass loss. The influence of vaporphase fluxes can even be seen in groundwater lo sses around year 2, when the flux rate reflects the vapor-phase flux patterns. Figures D-20a 

## , D-20b 

## , and D-20c 

## show the mass loss for Test Case 6. In this case, the transport is dominated by degradation, and there is relatively little mass loss to the atmosphere or groundwater. These re sults collectively show the expected model

### Draft Appendix D Landfill Source Model Testing



## D-24 behavior associated with maximizing and mi nimizing vapor-phase diffusion. The relevant robustness requirements are satisfied.


## D.3.4 Robustness Tests 7 and 8: Maxi mum/Minimum Aqueous-Phase Diffusion The model should reliably simulate the scenar ios and constituents with the maximum and minimum potential chemical diffusion rates in wa ter. Parameters controlling the aqueous-phase diffusion rate include the water diffusivity, phas e partitioning waste properties (moisture content, porosity, bulk density, organic carbon distributio n coefficient, and frac tion organic carbon), and cover/liner properties (type, thickness, moisture c ontent, porosity). These parameters were set to values that maximize and minimize the diffusion co efficients and the phase partitioning to water, as described in Table D-8 under Test Cases 7 an d 8. The parameter values selected were the endpoint values of the respectiv e distributions (maxima and mini ma), thus evaluating the range of parameter space associated with th e industrial wipes risk assessment. Table D-9 shows that the re lative contribution of diffusi on to groundwater follows the expected pattern (0.41 percent versus 0.01 percent for the maximum and minimum cases, respectively). Also, the mass balance and simulation time results meet the requirements. Note that the air diffusivity was set to zero for Test Cases 7 and 8, because vapor diffusion otherwise would dominate the changes reflected in the aqueous diffusion (vapor diffusivities are orders of magnitude greater than aqueous diffusivities). Even with the elimination of vapor-phase diffusion, the relative importance of aqueous diffu sion is less than 1 percent of the mass loss. Figures D-21a 

## , D-21b 

## , and D-21c 

## show the mass loss associated with particular pathways over time for Test Case 7. Test Case 7 is domina ted by degradation, because the vapor-phase partitioning and transport parameters were minimi zed for the less volatile chemical (cresols). Figures D-22a 

## , D-22b 

## , and D-22c 

## show the mass loss associated with particular pathways over time for Test Case 8. Test Case 8 is dominated by vapor advection, because the chemical is the more volatile tetrachloroethylene. These results collectively show the expected model behavior associated with maximizing and minimizing aque ous-phase diffusion. The relevant robustness requirements are satisfied.


## D.3.5 Robustness Tests 9 and 10: Ma ximum/Minimum Degradation Rate The model should reliably simulate the scenar ios and constituents with the maximum and minimum potential mass loss through first-order degradation. Paramete rs controlling mass loss through degradation include the decay rates a nd phase-partitioning wast e properties (moisture content, porosity, bulk density, organic carbon distribution coefficient, and fraction organic carbon). These parameters were set to values th at maximize and minimize the degradation rate, as described in Table D-8 under Test Cases 9 an d 10. The phase-partitioning parameters for Test Cases 9 and 10 were specified to maximize and minimize the partitioning to the aqueous phase (the only phase within which de gradation occurs for the risk a ssessment). The parameter values selected were the endpoint values of the resp ective distributio ns (maxima and minima), thus evaluating the range of parameter space associated with the industrial wi pes risk assessment. Table D-9 shows that the re lative contribution of degrad ation follows the expected pattern (99.5 percent versus 0.25 percent for the maximum and minimum cases, respectively). Also, the mass balance and simulation time results meet the requirements. Figures D-23a 

## , D-23b 

## , and D-23c 

## show the mass loss associated with pa rticular pathways over time for Test Case 9. Test Case 9 is domina ted by degradation, as expected. Figures D-24a 

## , D-24b 

## , and D-24c

### Draft Appendix D Landfill Source Model Testing



## D-25 show the mass loss associated with particular path ways over time for Test Case 10. Test Case 10 is dominated by vapor advection rather than degr adation, as expected. These results collectively show the expected model behavior associated with maximizing and mi nimizing aqueous-phase degradation. The relevant robustn ess requirements are satisfied. 

## D.3.6 Robustness Tests 11 and 12: Maximum/Minimum Vapor-Phase Diffusion with No Liner The model should reliably simulate the scenar ios and constituents with the maximum and minimum potential mass loss through diffusion w ith no liner. Parameters controlling diffusive mass loss with no liner include unsaturated zone pa rameters (depth to water, moisture content, and porosity), diffusivities, and pha se-partitioning waste parameters (moisture content, porosity, bulk density, organic carbon dist ribution coefficient, and fr action organic carbon). These parameters were set to values that maximize a nd minimize the diffusion in air with no liner, as described in Table D-8 under Test Cases 11 and 12. The parameter values selected will be the endpoint values of the respectiv e distributions (maxima and mini ma), thus evaluating the range of parameter space associated with th e industrial wipes risk assessment. Table D-9 shows that the re lative contribution of diffusi on to groundwater follows the expected pattern (21.6 percent versus 0 percent for the maximum and minimum cases, respectively). Also, the mass balance and simulation time results meet the requirements. Figures D-25a 

## , D-25b 

## , and D-25c 

## show the mass loss associated with particular pathways over time for Test Case 11. Figures D-26a 

## , D-26b 

## , and D-26c 

## show the mass loss associated with particular pathways over time for Test Case 12. The diffusi ve loss to groundwater is much more significant in Test Case 11 than Test Case 12, as expect ed. These results collectively show the expected model behavior associated with maximizing a nd minimizing vapor-phase diffusion with no liner. The relevant robustness requirements are satisfied. 

## D.3.7 Robustness Tests 13 and 14: Maximum/Minimum Aqueous-Phase Diffusion with No Liner The model should reliably simulate the scenar ios and constituents with the maximum and minimum potential chemical diffusion rates in wa ter with no liner. Parameters controlling the aqueous-phase diffusion rate with no liner include the water diffusivity, phase partitioning waste properties (moisture content, po rosity, bulk density, organic carbon distribution coefficient, and fraction organic carbon), and unsat urated zone properties (porosity , moisture content, thickness). These parameters were set to values that maximize and minimize the diffusion in water with no liner, as described in Table D-8 under Test Cases 13 and 14. The pa rameter values selected were the endpoint values of the resp ective distributions (maxima and minima), thus evaluating the range of parameter space associated with the industrial wipes risk assessment. Table D-9 shows that the re lative contribution of diffusi on to groundwater follows the expected pattern (3.6 percent versus 0.09 percent for the maximum and minimum cases, respectively). Also, the mass balance and simulation time results meet the requirements. Figures D-27a 

## , D-27b 

## , and D-27c 

## show the mass loss associated with particular pathways over time for Test Case 13. Test Case 13 is dominated by de gradation, because the vapor-phase partitioning and transport parameters were minimized for the less volatile chemical (cresols). Figures D-28a 

## , D-28b 

## , and D-28c 

## show the mass loss associated with pa rticular pathways over time for Test Case 14. Test Case 14 is dominated by vapor ad vection, because the chemical is the more

### Draft Appendix D Landfill Source Model Testing



## D-26 volatile tetrachloroethylene. These results co llectively show the exp ected model behavior associated with maximizing and minimizing aque ous-phase diffusion with no liner. The relevant robustness requirements are satisfied.


## D.3.8 Robustness Tests 15 and 16: Maximum/Minimum Diffusion with No Cover The model should reliably simulate the scenar ios and constituents with the maximum and minimum potential chemical diffusion rates with no cover. Parameters controlling the diffusion rate with no cover include the air diffusivity, phase partitioni ng waste properties (moisture content, porosity, bulk density, organic carbon distribution coefficient, and fraction organic carbon), daily cell geometry information, the wo rking face angle to horizontal, and the waste sublayer period. These parameters were set to values that maximize and minimize the diffusion with no cover, as described in Table D-8 under Test Cases 15 and 16. The parameter values selected were the endpoint values of the resp ective distributio ns (maxima and minima), thus evaluating the range of parameter space associated with the industrial wi pes risk assessment. Table D-9 shows that the rela tive contribution of no-cover losses follows the expected pattern (10.9 percent versus 0.03 percent for the maximum and minimum cases, respectively). Also, the mass balance and simulation time results meet the requirements. Figures D-29a 

## , D29b 

## , and D-29c 

## show the mass loss associated with partic ular pathways over time for Test Case 15. Test Case 15 is dominated by vapor advection, because the chemical is the more volatile tetrachloroethylene. Figures D-30a 

## , D-30b 

## , and D-30c 

## show the mass loss associated with particular pathways over time for Test Case 16. Test Case 16 is dominated by degradation, because the vapor-phase partitioning and transport parameters were minimized for the less volatile chemical (cresols). Interestingly, the proportion of no-cover losses relative to the total loss to air is greater in Test Case 16 than in Te st Case 15. However, the magnitude of the Test Case 16 no-cover losses relative to the total mass loss is small. These results collectively show the expected model behavior associated with maximizing and minimizing diffusion with no cover. The relevant robustne ss requirements are satisfied.


## D.3.9 Robustness Tests 17 and 18 Maximum/Minimum Landfill Geometry The model should reliably simulate scenar ios with the maximum and minimum landfill geometry characteristics. The primary geometric characteristic controlling transport is landfill height. Thus, parameters cont rolling height were set to ma ximum and minimum values, as described in Table D-8 under Te st Cases 17 and 18. The parameter values selected were the endpoint values of the respectiv e distributions (maxima and mini ma), thus evaluating the range of parameter space associated with th e industrial wipes risk assessment. Table D-9 shows the relative contribution of different mass loss pathways. Also, the mass balance and simulation time results meet the requ irements. The differences in transport between Test Cases 17 and 18 are due primarily to the different chemicals—the more volatile tetrachloroethylene for Test Case 17 and the less vol atile cresols for Test Case 18. Nevertheless, these simulations demonstrate that the model successfully simulates th e endpoint geometries anticipated for the industrial wi pes risk assessment. The releva nt robustness requirements are satisfied.

### Draft Appendix D Landfill Source Model Testing



## D-27 

# D.4 Comparison with Measured Data Validation of the model would require a long fi eld experiment with extensive control and monitoring of the landfill, including initial cont aminant concentrations, water infiltration, gas production and operating parameters . Although a suitable data set is not available for such model validation, it is possible to compare predicted landfill gas and leachate concentrations from the LFCR model with measured values reported in the literature. Thus, a series of test cases were develope d to compare modeled and measured landfill gas and leachate concentrations. The simulations use average input-parameter values associated with the Monte Carlo analysis. Simulations were performed for benzene, trichloroethylene, toluene, acetone, and methyl ethyl ketone ( Figures D-31 

## through D-35 

## ). The range of measured concentrations are from Allen etal. (1997) and Kjeldsen et al . (2003). As these figures show, predicted concentrations fall within the ranges of measured values, thus demonstrating that the LFCR model can reproduce la ndfill behavior reported in the literature. Table D-10 

## shows the initial chemical concen trations used in the comparison simulations. Although there is a large degree of uncertainty in the initial contaminant concentrations, order of magnitude estimates ar e possible using assumed fractions of household hazardous waste (HHW) and chemicals within landf ill waste. In California, HHW is estimated to comprise 0.2 percent (2,000 mg/kg) of la ndfilled waste (California Integrated Waste Management Board, 2004). This waste fraction incl udes containers of paint, vehicle fluids, used oil, batteries, and mixed residential HHW. Furt her assuming the HHW to contain from 0.001 to 1 percent of chemical (10–10,000 mg chemical/kg HHW) and a wet waste density of 795 kg/m 3 

## (see Table D-10), the volumetric initial chemical concentration in the waste would range from 16 to 16,000 mg/m 3 

## . (HHW concentration in landfill waste × chemical concentration in HHW × wet density of waste). The assumed LFCR input c oncentrations for the comparison simulations (Table D-10) are all within this range. Table D-10. LFCR Input Concentrations for the Comparison Simulations Total Input Concentrations

Chemical Volumetric (mg chemical/m 3 

### waste) Mass-based (mg chemical/kg wet waste) Benzene 1,000 1.26 Trichloroethylene 1,000 1.26 Toluene 10,000 12.6 Acetone 1,000 1.26 Methyl ethyl ketone 1,000 1.26 Notes: The mass-based concentration equals the volume tric concentration divided by the density of wet waste (795 kg/m 3 ). The wet waste density equals the dry bulk density added to the (density of water X volumetric moisture content). Average values in Monte Carlo analysis: dry bulk density = 0.63 kg/L; density of water = 0.997 kg/L; volumetric moisture content = 0.165. 

## The above calculations of initial solvent concentrations in la ndfill waste and the comparisons between measured and modeled leachate and landfill gas concentrations are clearly approximate. Although the analysis cannot be used to fully validate the LFCR, it does

### Draft Appendix D Landfill Source Model Testing



## D-28 demonstrate that the model can reproduce measur ed landfill behavior us ing reasonable input concentrations and the average Monte Carlo parameter values. 

# D.5 Independent Testing Model testing documentation provides the input parameter values, so that an independent party could reproduce the test resu lts. All robustness tests use the st andard version of the model. Some of the verification test cas es used working versions of th e model with specific processes disabled, as described above. Due to budget and sc hedule constraints, test packages will not be prepared and archived for this project. 

# D.6 Summary The testing results documented in this appe ndix provide a compre hensive demonstration of the computational accuracy of transport mechan isms and pathways in the model. A series of verification test cases successfully verify th e implementation of the transport mechanisms. Additional tests verified the implementation of the landfill-filling algorithm. Model linearity verification demonstrated that mass loss results scale linearly with input concentrations, as expected. Robustness testing ensu red the model’s reliability throughout the anticipated range of parameter space for the industrial wipes risk assessment. The nume rical accuracy, mass balance, and runtime satisfied the requirements for all ro bustness tests. The documentation of the tests would allow independent parties to repr oduce the test results, if necessary. Due to resource and data availability constrai nts, we have not atte mpted to validate the LFCR model by comparing with measured data. We are not currently aware of a data set in which trace organics exiting a la ndfill via multiple pathways have been measured over long time scales (years). Should resources and data be available, model valida tion could be pursued. 

# D.7 Symbols C

a 

## Air-phase concentration [M/L 3 

## ] C

s 

## Solid-phase concentration [M/M] C

Total concentration [M/L 3 

## ] C 0 

## Initial total concentration [M/L 3 

## ] C

w 

## Water-phase concentration [M/L 3 

## ] D a 

## Vapor-phase diffusion coefficient [L 2 

## /T] D eq 

## Equivalent diffusion coefficient for a composite geomembrane and soil layer [L 2 

## /T] D w 

## Aqueous-phase diffusion coefficient [L 2 

## /T] f

a 

## Fraction of total mass in the air phase [-] f

w



## Fraction of total mass in the water phase [-] f

s 

## Fraction of total mass in the solid phase [-] H

Cell/landfill height [L 3 

## ] H

calc 

## The domain height used for the no-cover flux, based on the angle to horizontal and the daily cell geometry [L] J

avg 

## Average no-cover flux [M/L 2 

## T] k

Landfill gas generation rate [/T] K

H



## Henry’s law constant [-] K

d 

## Solid-water phase distribution coefficient [L 3 

## /M] L Length of the diffusive layer [L]

### Draft Appendix D Landfill Source Model Testing



## D-29 L o 

## Methane generation capacity [L 3 

## /M] L u 

## Unsaturated zone thickness [L] M in,tot 

## Cumulative total mass entering the landfill during a simulation [M] M in 

## (i) Mass entering the landfill over time step i [M] M lf



## Mass stored within the landfill [M] M lf



## (i) Mass stored within the landfill over time step i [M] M out,tot 

## Cumulative total mass leaving the landfill during a simulation [M] M out 

## (i) Mass leaving the landfill over time step i [M] N

Net infiltration rate [L/T] q a 

## Landfill gas generation rate, per landfill waste volume [/T] R a 

## Air-phase to total concentration partition coefficient [-] R s 

## Solid-phase to total concentration partition coefficient [-] R w 

## Water-phase to total concentration partition coefficient [-] t Time [T] V

Cell/landfill volume [L 3 

## ] W

Mass of waste [M] ε

a 

## Air-phase volumetric fraction [L 3 

## /L 3 

## ] ε

w 

## Water-phase volumetric fraction [L 3 

## /L 3 

## ] λ

a1 

## Biotic first-order degradation rate in the air phase [/T] λ

w1 

## Biotic first-order degradation rate in the water phase [/T] λ

s1 

## Biotic first-order degradation rate in the solid phase [/T] λ

a2 

## Abiotic first-order degradati on rate in the air phase [/T] λ

w2 

## Abiotic first-order degradation rate in the water phase [/T] λ

s2 

## Abiotic first-order degradation rate in the solid phase [/T] ρ

b 

## Solid-phase bulk density [solid mass/total volume M/L 3 

## ] 

# D.8 References
Allen, M. R.; Braithwaite, A.; Hills, C. C. 1997. Trace organic compounds in landfill gas at seven UK waste disposal sites. Environ. Sci. Technol. 31:1054–1061. Bartelt-Hunt, S. L., D. R. U. Knappe, P. Kjel dsen, and M. A. Barlaz. 2006. Fate of chemical warfare agents and toxic industrial chemicals in landfills. Environmental Science and Technology 40 (13):4,219–4,225. California Integrated Waste Management Boar d, 2004, State Wide Characterization Study, Sacramento, CA. Available at http://www. ciwmb.ca.gov/WasteChar/WasteStudies.htm #2004. Carslaw, H. S., and J. C. Jaeger. 1947. Conduction of Heat in Solids . London: Oxford University Press. Kjeldsen, P., and T. H. Christensen. 2001. A simple model for the distribution and fate of organic chemicals in a landfill: MOCLA. Waste Management and Research 19 (3):201– 216.

### Draft Appendix D Landfill Source Model Testing



## D-30 Kjeldsen, P., Barlaz, M. A., Rooker, A. P., Baun, A., Ledin, A. and T. H. Christensen. 2003, Present and Long Term Composition of MSW Landfill Leachate – A Review, Critical Reviews in Environmenta l Science and Technology 32(4):297–336. Lyman, W. J., W. J. Reehl, and D. H. Rosenblatt 1990. Handbook of Chemical Property Estimation Methods: Environmen tal Behavior of Organic Compounds . Washington, DC: American Chemical Society.
U.S. EPA. 2003. Risk Assessment Technical Background Document for the Dye and Pigment Industry Hazardous Waste Listing Determination . U.S. EPA, Office of Solid Waste, Washington, DC.
U.S. EPA. 2005. Landfill Gas Emissions Model (LandG EM) Version 3.02 User’s Guide

. EPA-600/R-05/047. U.S. EPA, Office of Res earch and Development, Morrisville, NC.Figure D-1 LFCR Verification Case 2 Landfill Gas Generation Rate 0

10,000

20,000

30,000

40,000

50,000

60,000 0 20 40 60 80 100 120 140 160 180 200 YearsGas Generation Rate (m3/day)

Spreadsheet LFCR Figure D-2 LFCR Verification Case 3 Advective Vapor Transport 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 0 10 20 30 40 50 60 70 80 YearsC/Co Analytical LFCRFigure D-3 LFCR Verification Case 4 Advective Aqueous Transport 0

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0.7

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0.9

1 0 2000000 4000000 6000000 8000000 10000000 12000000 14000000 YearsC/Co Analytical LFCR Figure D-4 LFCR Verification Case 5 Degradation/Transformation 0

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0.4

0.5

0.6

0.7

0.8

0.9

1 0 0.05 0.1 0.15 0.2 0.25 0.3 YearsC/Co Analytical LFCRFigure D-5 LFCR Verification Case 6 Vapor Diffusive Transport 0

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0.3

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0.5

0.6

0.7

0.8

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1 0 20 40 60 80 100 120 140 160 180 200 YearsC/Co Analytical LFCR Figure D-6. LFCR Verification Case 7 Aqueous Diffusive Transport 0

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0.4

0.5

0.6

0.7

0.8

0.9

1 0 20000 40000 60000 80000 100000 120000 140000 160000 180000 200000 YearsC/Co Analytical LFCRFigure D-7. LFCR Verification Case 8 Vapor Diffusive Transport through Geomembrane Composite Cover 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 0 1000 2000 3000 4000 5000 6000 7000 8000 YearsC/Co Analytical LFCR Figure D-8a. LFCR Verification Case 9 Vapor Diffusive Transport with No Cover 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 0123456 YearsC/Co Analytical LFCRFigure D-8b. LFCR Verification Case 9 Supplemental Calculation Calculation of the no-cover average flux. Based on a Carslow and Jaeger (1947) solution to the diffusion equation. C init 1 kg m 3

 Initial concentration Do 0.705894 m 2 day

 Diffusivity VF 0.53 0.17 Moisture content in waste Porosity 0.53 Porosity in waste Ra 52.2685 Air partition coefficient L 201.31288 m  Thickness (based on cell geometry and working face angle)

t_inc 8 hr



D Do VF
10 3 Porosity 2 Ra 

 Diffusion coefficient Calculation of the average flux between t1 and t2 requires integration of the flux solution. Integral_J t ( ) 2 D  C init

 L 0

1000000 n

1 D 2 n  1 ( ) 2  S 2  1 4 L 2 


e
D 2 n  1 ( ) 2  S 2  t 4 L 2 

  =

 The average flux between t1 and t2 is the definite integral between t1 and t2 divided by the time interval. Average_J t1 t2  ( ) Integral_J t2( ) Integral_J t1 ( ) t2 t1 Average_J 0 day

 t_inc  ( ) 0.07795 kg m 2 day

 Figure D-9. LFCR Verification Case 10 Vapor Diffusive Transport through a Soil Liner 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 0 20 40 60 80 100 120 140 160 180 200 YearsC/Co Analytical LFCRFigure D-10. LFCR Verification Case 11 Vapor Diffusive Transport through a Composite Liner 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 0 500 1000 1500 2000 2500 3000 3500 YearsC/Co Analytical LFCR Figure D-11. LFCR Verification Case 12 Aqueous Diffusive Transport through a Composite Liner 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 0 50000 100000 150000 200000 250000 300000 350000 400000 YearsC/Co Analytical LFCRFigure D-12. LFCR Verification Case 13 Vapor Diffusive Transport with No Liner Verification 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 0 5000 10000 15000 20000 25000 30000 YearsC/Co Analytical LFCR Figure D-13. LFCR Verification Case 14 Aqueous Diffusive Transport with No Liner Verification 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 0 200000 400000 600000 800000 1000000 1200000 1400000 YearsC/Co Analytical LFCRFigure D-14. LFCR Verification Case 15 Base Case Simulation/Simultaneous Mechanisms 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 0 2 4 6 8 10 12 14 16 YearsC/Co Analytical LFCR Figure D-15a. Mass Loss Proportions Robustness Testing Case 1 0

50,000

100,000

150,000

200,000

250,000 0 2 4 6 8 10 12 14 16 18 20 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to GroundwaterFigure D-15b. Mass Loss to Atmosphere Robustness Testing Case 1 0

50,000

100,000

150,000

200,000

250,000

300,000 0 2 4 6 8 10 12 14 16 18 20 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover Loss Figure D-15c. Mass Loss to Groundwater Robustness Testing Case 1 0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000 0 5 10 15 20 25 30 35 40 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater LeachingFigure D-16a. Mass Loss Proportions Robustness Testing Case 2 0

1,000

2,000

3,000

4,000

5,000

6,000 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to Groundwater Figure D-16b. Mass Loss to Atmosphere Robustness Testing Case 2 0

10

20

30

40

50

60

70 0 10 20 30 40 50 60 70 80 90 100 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover LossFigure D-16c. Mass Loss to Groundwater Robustness Testing Case 2 0

10

20

30

40

50

60

70

80

90

100 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater Leaching Figure D-17a. Mass Loss Proportions Robustness Testing Case 3 0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to GroundwaterFigure D-17b. Mass Loss to Atmosphere Robustness Testing Case 3 0

50

100

150

200

250 0 10 20 30 40 50 60 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover Loss Figure D-17c. Mass Loss to Groundwater Robustness Testing Case 3 0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater LeachingFigure D-18a. Mass Loss Proportions Robustness Testing Case 4 0

50,000

100,000

150,000

200,000

250,000 0 5 10 15 20 25 30 35 40 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to Groundwater Figure D-18b. Mass Loss to Atmosphere Robustness Testing Case 4 0

50,000

100,000

150,000

200,000

250,000 0 5 10 15 20 25 30 35 40 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover LossFigure D-18c. Mass Loss to Groundwater Robustness Testing Case 4 0

200

400

600

800

1,000

1,200

1,400

1,600 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater Leaching Figure D-19a. Mass Loss Proportions Robustness Testing Case 5 0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000 0 5 10 15 20 25 30 35 40 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to GroundwaterFigure D-19b. Mass Loss to Atmosphere Robustness Testing Case 5 0

50,000

100,000

150,000

200,000

250,000 0 5 10 15 20 25 30 35 40 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover Loss Figure D-19c. Mass Loss to Groundwater Robustness Testing Case 5 0

100

200

300

400

500

600 0 5 10 15 20 25 30 35 40 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater LeachingFigure D-20a. Mass Loss Proportions Robustness Testing Case 6 0

500

1,000

1,500

2,000

2,500

3,000

3,500 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to Groundwater Figure D-20b. Mass Loss to Atmosphere Robustness Testing Case 6 0

10

20

30

40

50

60

70

80 0 10 20 30 40 50 60 70 80 90 100 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover LossFigure D-20c. Mass Loss to Groundwater Robustness Testing Case 6 0

2

4

6

8

10

12

14 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater Leaching Figure D-21a. Mass Loss Proportions Robustness Testing Case 7 0

1,000

2,000

3,000

4,000

5,000

6,000 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to GroundwaterFigure D-21b. Mass Loss to Atmosphere Robustness Testing Case 7 0

10

20

30

40

50

60

70

80

90 0 10 20 30 40 50 60 70 80 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover Loss Figure D-21c. Mass Loss to Groundwater Robustness Testing Case 7 0

5

10

15

20

25

30 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater LeachingFigure D-22a. Mass Loss Proportions Robustness Testing Case 8 0

10,000

20,000

30,000

40,000

50,000

60,000 0 10 20 30 40 50 60 70 80 90 100 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to Groundwater Figure D-22b. Mass Loss to Atmosphere Robustness Testing Case 8 0

10,000

20,000

30,000

40,000

50,000

60,000 0 10 20 30 40 50 60 70 80 90 100 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover LossFigure D-22c. Mass Loss to Groundwater Robustness Testing Case 8 0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater Leaching Figure D-23a. Mass Loss Proportions Robustness Testing Case 9 0

50,000

100,000

150,000

200,000

250,000 0 2 4 6 8 10 12 14 16 18 20 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to GroundwaterFigure D-23b. Mass Loss to Atmosphere Robustness Testing Case 9 0

50

100

150

200

250

300

350 0 2 4 6 8 10 12 14 16 18 20 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover Loss Figure D-23c. Mass Loss to Groundwater Robustness Testing Case 9 0

2

4

6

8

10

12

14

16

18

20 0 2 4 6 8 10 12 14 16 18 20 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater LeachingFigure D-24a. Mass Loss Proportions Robustness Testing Case 10 0

10,000

20,000

30,000

40,000

50,000

60,000

70,000 0 10 20 30 40 50 60 70 80 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to Groundwater Figure D-24b. Mass Loss to Atmosphere Robustness Testing Case 10 0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000 0 10 20 30 40 50 60 70 80 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover LossFigure D-24c. Mass Loss to Groundwater Robustness Testing Case 10 0

200

400

600

800

1,000

1,200

1,400 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater Leaching Figure D-25a. Mass Loss Proportions Robustness Testing Case 11 0

20,000

40,000

60,000

80,000

100,000

120,000

140,000 0 5 10 15 20 25 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to GroundwaterFigure D-25b. Mass Loss to Atmosphere Robustness Testing Case 11 0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

200,000 0 5 10 15 20 25 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover Loss Figure D-25c. Mass Loss to Groundwater Robustness Testing Case 11 0

20,000

40,000

60,000

80,000

100,000

120,000 0 5 10 15 20 25 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater LeachingFigure D-26a. Mass Loss Proportions Robustness Testing Case 12 0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to Groundwater Figure D-26b. Mass Loss to Atmosphere Robustness Testing Case 12 0

10

20

30

40

50

60

70

80

90 0 10 20 30 40 50 60 70 80 90 100 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover LossFigure D-26c. Mass Loss to Groundwater Robustness Testing Case 12 0

100

200

300

400

500

600

700

800 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater Leaching Figure D-27a. Mass Loss Proportions Robustness Testing Case 13 0

1,000

2,000

3,000

4,000

5,000

6,000 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to GroundwaterFigure D-27b. Mass Loss to Atmosphere Robustness Testing Case 13 0

50

100

150

200

250

300

350

400

450

500 0 10 20 30 40 50 60 70 80 90 100 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover Loss Figure D-27c. Mass Loss to Groundwater Robustness Testing Case 13 0

200

400

600

800

1,000

1,200

1,400

1,600 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater LeachingFigure D-28a. Mass Loss Proportions Robustness Testing Case 14 0

10,000

20,000

30,000

40,000

50,000

60,000 0 10 20 30 40 50 60 70 80 90 100 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to Groundwater Figure D-28b. Mass Loss to Atmosphere Robustness Testing Case 14 0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000 0 10 20 30 40 50 60 70 80 90 100 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover LossFigure D-28c. Mass Loss to Groundwater Robustness Testing Case 14 0

20

40

60

80

100

120

140 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater Leaching Figure D-29a. Mass Loss Proportions Robustness Testing Case 15 0

20,000

40,000

60,000

80,000

100,000

120,000 0 1 0 2 0 3 0 4 0 5 0 6 0 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to GroundwaterFigure D-29b. Mass Loss to Atmosphere Robustness Testing Case 15 0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000 0 10 20 30 40 50 60 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover Loss Figure D-29c. Mass Loss to Groundwater Robustness Testing Case 15 0

500

1,000

1,500

2,000

2,500 0 1 0 2 0 3 0 4 0 5 0 6 0 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater LeachingFigure D-30a. Mass Loss Proportions Robustness Testing Case 16 0

500

1,000

1,500

2,000

2,500

3,000

3,500 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Aqueous Degradation Vapor Advection Diffusion With Cover No Cover Loss Aqueous Advection Diffusion to Groundwater Figure D-30b. Mass Loss to Atmosphere Robustness Testing Case 16 0

10

20

30

40

50

60

70

80 0 10 20 30 40 50 60 70 80 90 100 YearsMass Loss (g/day)

Total to Atmosphere Vapor Advection Diffusion With Cover No Cover LossFigure D-30c. Mass Loss to Groundwater Robustness Testing Case 16 0

2

4

6

8

10

12

14 0 20 40 60 80 100 120 140 160 180 200 YearsMass Loss (g/day)

Total to Groundwater Diffusion to Groundwater Leaching Figure D-31. Measured and Predicted Benzene Concentrations in Landfill Gas and Leachate 0

5

10

15

20

25

30

35

40

45 0 20 40 60 80 100 120 Yearsmg/m3 Leachate Landfill Gas

Reported range in measured benzene concentrations in leachate (0.2 - 1630 mg/m3) Reported range in measured benzene concentrations in landfill gas (<0.1 - 7 mg/m3)Figure D-32. Measured and Predicted TCE Concentrations in Landfill Gas and Leachate 0

5

10

15

20

25 0 20 40 60 80 100 120 Yearsmg/m3 Leachate Landfill Gas

Reported range in measured TCE concentrations in leachate (0.05 - 750 mg/m3) Reported range in measured TCE concentrations in air (<0.1 - 152 mg/m3) Figure D-33. Measured and Predicted Toluene Concentrations in Landfill Gas and Leachate 0

20

40

60

80

100

120 0 20 40 60 80 100 120 Yearsmg/m3 Leachate Landfill Gas

Reported range in measured toluene concentrations in leachate (1 - 12,300 mg/m3) Reported range in measured toluene concentrations in air (10 - 287 mg/m3)Figure D-34. Measured and Predicted Acetone Concentrations in Landfill Gas and Leachate 0

200

400

600

800

1000

1200

1400 0 5 10 15 20 25 30 35 40 45 50 Yearsmg/m3 Leachate Landfill Gas

Reported range in measured acetone concentrations in leachate (6 - 4400 mg/m3) No reported concentrations in landfill gas Figure D-35. Measured and Predicted MEK Concentrations in Landfill Gas and Leachate 0

200

400

600

800

1000

1200

1400 0 5 10 15 20 25 30 35 40 45 50 Yearsmg/m3 Leachate Landfill Gas

Reported range in measured MEK concentrations in leachate (110 - 6600 mg/m3) No reported concentrations in landfill gas

### Draft Appendix E Landfill Source Modeling Parameters



## E-1 

# Appendix E Landfill Source Modeling Parameters
This appendix presents input parameter va lues and distributions used by the landfill source model, and includes a table with the parameter name, unit, value, and reference information.

### Parameter Reference/Notes Value Units Appendix E Source Modeling Parameters Draft


## Table E-1. Source Model Variables for Landfills

Cover/Liner Characterization (See Section 3.1.2.2) 6", consistent with Subtitle D regulations. Daily cover thickness 0.152 m Ldc

60 mil, consistent with Subtitle D regulations Geomembrane thickness 0.0015 m Lgm

12", consistent with Subtitle D regulations Interim cover thickness 0.305 m Lic

2 ft, consistent with Subtitle D regulations Liner thickness No Liner scenario: NA Composite liner Scenario: 0.61 m Ll

2 ft, consistent with Subtitle D regulations Final cover thickness 0.61 m Lpc

The effective porosity for the specific EPACMTP cover soil type (ISTYPE2). See Appendix F. Daily cover porosity EPACMTP WCS, soil type specific unitless vol voids/vol total Porosity_dc

The effective porosity for the specific EPACMTP cover soil type (ISTYPE2). See Appendix F. Intermediate cover porosity EPACMTP WCS, soil type specific unitless vol voids/vol total Porosity_ic

HELP documentation (Schroeder, et al., 1994). Liner porosity No Liner scenario: NA Composite Liner scenario: 0.427 unitless vol voids/vol total Porosity_l

No Liner scenario: The effective porosity for the specific EPACMTP cover soil type (ISTYPE2). See Appendix F. Composite Liner scenario: HELP documentation (Schroeder, et al., 1994). Final cover porosity No Liner scenario: EPACMTP WCS Composite Liner scenario: 0.427 unitless vol voids/vol total Porosity_pc

Field capacity assumed to be a representative long term average moisture condition (Bartelt-Hunt, 2006). Cover soil type = EPACMTP ISTYPE2. Daily cover moisture content Field capacity of the EPACMTP cover soil unitless vol water/vol total VFwdc

Field capacity assumed to be a representative long term average moisture condition (Bartelt-Hunt, 2006). Cover soil type = EPACMTP ISTYPE2. Intermediate cover moisture content Field capacity of the EPACMTP cover soil unitless vol water/vol total VFwic

E-2

### Parameter Reference/Notes Value Units Appendix E Source Modeling Parameters Draft


## Table E-1. Source Model Variables for Landfills

Composite Liner: Average of measured clay liner moisture contents reported in Bensen et al. (1999) (Bartelt-Hunt, 2006). Liner moisture content No Liner Scenario: NA Composite Liner scenario: 0.2 unitless vol water/vol total VFwl

No Liner Scenario: Field capacity assumed to be a representative long term average moisture condition. Cover soil type = EPACMTP ISTYPE2. Composite Liner Scenario: Bensen et al. (1999), (Bartelt-Hunt (2006) Final cover moisture content No Liner scenario: Field capacity of the EPACMTP cover soil Composite Liner scenario: 0.2 unitless vol water/vol total VFwpc

Hydrogeologic Setting (See Section 3.1.2.3) See Appendix F. Depth to watertable EPACMTP DSOIL m Lu The effective porosity for the specific EPACMTP regional soil type (ISTYPE1). See Appendix F. Unsaturated zone porosity EPACMTP WCS unitless vol voids/vol total Porosity_u

Field capacity assumed to be a representative long term average moisture condition (Bartelt-Hunt, 2006). Regional soil type = EPACMTP ISTYPE1. Unsaturated zone moisture content Field capacity of the EPACMTP regional soil unitless vol water/vol total Vfwu

Infiltration and Liner Leakage (See Section 3.1.2.1) EPACMTP infiltration rates based on HELP simulations. See Appendix F. Infiltration rate after final cover is placed EPACMTP SINFIL (liner scenario specific) m/yr Inf_post

EPACMTP infiltration rates based on HELP simulations. See Appendix F. No liner rates used for pre-closure in both composite and no liner scenarios, because the no liner HELP scenario is more consistent with active-landfill conditions. Infiltration rate before final cover is placed EPACMTP SINFIL (no liner scenario values) m/yr Inf_pre

No liner values based on EPACMTP HELP simulations; composite liner values based on EPACMTP empirical data. See Appendix F. Leach rate after final cover is placed EPACMTP SINFIL (liner scenario specific) m/yr Leach_post

No liner values based on EPACMTP HELP simulations; composite liner values based on EPACMTP empirical data. See Appendix F. Leach rate before final cover is placed EPACMTP SINFIL (liner scenario specific) m/yr Leach_pre

E-3

### Parameter Reference/Notes Value Units Appendix E Source Modeling Parameters Draft


## Table E-1. Source Model Variables for Landfills

Landfill Characterization (See Section 3.1.2.4) Calculated Landfill cell area Total landfill area / number of landfill cells. (Number of landfill cells = total landfill active life / landfill cell active life). m2 Alfc

Based on EPA-WBJ data. Total landfill area EPACMTP AREA m2 Atot Barlaz (2006). Typical industry practice. Fraction of day without a
cover 0.33 unitless Fnc

Aivaliotis et al. (2004) and Barlaz (2006). Daily cell/lift height Uniform distribution, min=1.2, max=6.1 m Htarg

Barlaz (2006). Typical industry practice. Daily cell waste sublayer period 1 hr SubLayT

Based on EPA-WBJ data. Adjusted to be evenly divisible by the landfill cell active life. Landfill active life EPACMTP Active Life yr Tlf

Barlaz (2006). Typical industry practice. Landfill cell active life Uniform distribution, min=3, max=5 yr Tlfc

Barlaz (2006). Typical industry practice. Time before final cover installed on landfill cell/section Triangular distribution, min=10, max=30, mode=15 yr Tpc

Calculated Landfill cell volume total landfill volume / number of landfill cells. (Number of landfill cells = total landfill active life / landfill cell active life). m3 Vlfc

Calculated. Depth and area based on EPA-WBJ data. Total landfill volume EPACMTP DEPTH x EPACMTP AREA m3 Vtot

Aivolatis et al. (2004) Working face angle to horizontal Triangular distribution, min=12, max=30, mode=18 deg Wfangle

Simulation Parameters (See Section 3.1.2.5) Setting equal to Fnc provides runtime efficiency. Initial timestep Set to Fnc: 0.33 day dt_init

After less than 0.1% of mass remaining, mass loss was insignificant for all testing simulations. Stopping the simulation improves runtime. Simulation stopping criterion (based on the fraction of total mass remaining) 0.001 unitless FracStop

E-4

### Parameter Reference/Notes Value Units Appendix E Source Modeling Parameters Draft


## Table E-1. Source Model Variables for Landfills

Detemines how many terms the nocover diffusion infinite sum will be carried out. 1e-12 provides sufficient accuracy. Infinite sum truncation error tolerance 1e-12 unitless InfSum_tol

Liner type (0=no liner, 2=composite liner) Scenario specific LinerType

1 day is inherent to the source model. Varied only for testing. Daily cell period 1 day Tcell

Adjusted to maintain a mass balance error < 1% for all robustness testing simulations (See Appendix D). RK truncation error tolerance 1e-11 unitless TruncErr_tol

In all testing simulations, the mass loss after 200 years was insignificant (see Appendix D). Total simulation time 200 yr Tsim

Waste Characterization (See Section 3.1.2.6) Barlaz (2006) Average waste temperature Triangular distribution, min=30, max=45, mode=37.5 deg C AvgT

Barlaz (2006). Based on wet density from 1200 to 1500 lb/cyd and gravimetric moisture content from 0.15 to 0.25. Inversely correlated with porosity (corr. coeff. = -0.75) Waste bulk density (dry) Uniform distribution, min=0.6, max=0.67 kg/L BD

The input concentration was normalized to 1. (Note that the results were normalized to a constant mass loading rate for risk modeling.) Initial concentration 1 kg/m3 Cin

Bartelt-Hunt (2006) and Barlaz (2006). Organic carbon fraction in waste Uniform distribution, min=0.4, max=0.6 unitless focW

Function relating the gas generation rate and the pre-closure infiltration rate developed based on Bartelt-Hunt et al. (2006), Barlaz (2006), and AP-42 guidance (EPA, 1997). Landfill gas generation rate Varies from 0.01 to 0.1. Calculated from Inf_pre. k

Barlaz (2006) and LandGEM guidance (U.S. EPA, 2005). Potential methane generation capacity Triangular distribution, min=70, max=130, mode=100 L/kg Lo

Barlaz (2006) and Qian et al. (2002). Inversely correlated with bulk density (corr. coeff. = -0.75) Porosity of the waste Uniform distribution, min=0.4, max=0.67 unitless vol voids/vol total Porosity

E-5

### Parameter Reference/Notes Value Units Appendix E Source Modeling Parameters Draft


## Table E-1. Source Model Variables for Landfills

Barlaz (2006). Based on a range of wet waste density from 1200 to 1500 lb/cyd and a gravimetric moisture content from 0.15 to 0.25. Correlated with Inf_pre (corr coeff 0.85). Moisture content of waste Uniform distribution, min=0.11, max=0.22 unitless vol water/vol total VFw

NA: Not applicable EPACMTP: Composite Model for Leachate Migration with Transformation Products (U.S. EPA, 2003). HELP: Hydraulic Evaluation of Landfill Performance model (Schroeder, et al., 1994).

E-6

### Draft Appendix E Landfill Source Modeling Parameters



## E-7 

# References
Aivaliotis, V., I. Dokas, M. Hatzigiannakou, and D. Pana giotakopoulos. 2004. Functional relationships of landfill and landraise capacity with design and operation parameters. Waste Management and Research 22 (4):283–290. Barlaz, M. 2006. “Topics relevant to developm ent and parameterizatio n of the LFCR landfill source model.” Multiple phone and email co mmunications from Dr. Morton Barlaz, Professor, Water Resources/Env ironmental Engineering, Nort h Carolina State University, to Michael I. Lowry, RTI. July through December. Bartelt-Hunt, S. 2006. “Topics relevant to de velopment and parameterization of the LFCR landfill source model.” Multiple phone and email communications from Dr. Shannon L. Bartelt-Hunt, Assistant Profe ssor, Department of Civil Engineering, University of Nebraska-Lincoln, to Michael I. Lowry, RTI. July through December. Bartelt-Hunt, S.L., D.R.U. Knappe, P. Kjelds en, and M.A. Barlaz. 2006. Fate of chemical warfare agents and toxic industrial chemicals in landfills. Environmental Science and Technology 40 (13):4219-4225. Benson, C.H., D.E. Daniel, and G.P. Boutwell. 1999. Field performance of compacted clay liners. Journal of Geotechnical and Ge oenvironmental Engineering 125 (5):390–403. Schroeder, P.R., T.S. Dozier, P.A. Zappi, B.M. McEnroe, J.W. Sjostrom, and R.L. Peyton. 1994. The Hydrologic Evaluation of Landfill Pe rformance (HELP) Model: Engineering Documentation for Version 3 . EPA/600/R-94/168b. U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC. U.S. EPA (Environmental Protection Agency). 1997. Emission Factor Documentation For AP-42 Section 2.4, Municipal Solid Waste Landfills, Revised. U.S. EPA, Office of Air Quality Planning and Standards, Office of Air and Radiation. Research Triangle Park, NC. U.S. EPA (Environmental Protection Agency). 2003. EPA’s Composite Model for Leachate Migration with Transformation Products (EPACMTP) Parameters/Data Background Document. EPA530-R-03-003. U.S. EPA, Office of Solid Waste. U.S. EPA (Environmental Protection Agency). 2005. Landfill Gas Emissions Model (LandGEM) Version 3.02 User’s Guide . EPA-600/R-05/047. U.S. EPA, Office of Research and Development, Morrisville, NC.

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### Draft Appendix F Groundwater Modeling Parameters



## F-1 

# Appendix F Groundwater Modeling Parameters

The groundwater pathway modeling determined residential drinking water well concentrations resulting from a release of waste constituents from a landfill. The transport of leachate from the landfill through the unsaturated and saturated zones was simulated using the EPA Composite Model for Leachate Migration with Transformation Products (EPACMTP; U.S. EPA, 1997, 2003a). This appendix presents the input values and the distributions used in modeling the groundwater pathway using EPACMTP. Table F-1 presents all the EPACMTP input parameters organized by the primary components of the groundwater modeling scenario shown in Figure 3-4:

 

## Aquifer (or saturated zone) parameters

 

## Chemical parameters associated with the leachate

 

## Exposure parameters associated with the receptor well

 

## Vadose (or unsaturated zone) parameters

 

## Waste Management Unit (landfill) parameters. Table F-1 provides the EPACMTP variable ID, the parameter description, units, distribution type, default values (if applicable), and data sources (where appropriate).
Table F-2 presents detailed information on the four empirical correlated groundwater pathway parameters: GRADNT, XKX, ZB, and DSOIL. Each record in the table represents a correlated sampling of each of the four parameters from a single site. Table F-2 represents data collected from 400 hazardous waste sites in the United States (Newell et al., 1990) grouped into 12 subsurface environments, identified by Aquifer Code. The value “-999” denotes that site data were unavailable. This value (-999) triggers the model to estimate the value using methods described in Section 5.5 of the EPACMTP Technical Background Document (U.S. EPA, 2003b). Details regarding data origins, organization, and use in EPACMTP are provided in Section 5.3.4 of the EPACMTP Parameters/Data Background Document (U.S. EPA, 2003c).
Table F-3 presents all remaining parameters represented by empirical distributions. For each parameter, a set of paired values consisting of a parameter value and the associated cumulative distribution function percentile (e.g., 0.25 denotes the 25th percentile) are shown. The derivation of each distribution is treated in detail in various sections of the Parameters/Data Background Document (U.S. EPA, 2003c).
Table F-4 presents the primary landfill database for offsite industrial landfills used to supplement the characterization of the source models and to provide correlations to regional and site-based parameters (e.g., nearest climate center, hydrogeologic environment). The origins and use of these databases are discussed in detail in Section 3.1.2.4 of the main document and in Appendix D of the EPACMTP Parameters/Data Background Document (U.S. EPA, 2003c).

### Draft Appendix F Groundwater Modeling Parameters



## F-2 The percolation of water through unlined landfills (infiltration) and soils surrounding the landfill (recharge) was estimated using modeling results from the Hydrogeologic Evaluation of Landfill Performance (HELP) model (Schroeder et al., 1994). As shown in Table F-5 , the rates are correlated with the cover soil and the climate center nearest the landfill. The compilation and creation of this data are described in detail Appendix A of EPACMTP Parameters/Data Background Document (U.S. EPA, 2003c).
Table F-6 presents the constituent-specific fate and transport parameters used to model the migration of releases from the landfill through the subsurface media.Variable ID Parameter Units Type Value ReferenceTable F-1. Groundwater Model VariablesCommentsAppendix F Groundwater Modeling ParametersDraftAquiferAL Longitudinal dispersivity(aquifer)m Empirical Calculated from a national distributionand radial distance to well (RADIS)See attached Table F-3ANGLE Angle of well off plumecenterlineDegrees Uniform Randomly selected from uniformdistributionU.S. EPA, 2003bANIST Anisotropy ratio Unitless Constant 1U.S. EPA, 2003bNo anisotropyAT Transverse dispersivity m Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from longitudinal dispersivityAV Vertical dispersivity m Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from longitudinal dispersivityBULKD Bulk density g/cm3 Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from porosityDIAM Avg. particle diameter cm Empirical Randomly selected from nationaldistributionSee attached Table F-3FOC Fraction organic carbon (FOC) g/g Johnson SB Randomly selected from nationaldistributionU.S. EPA, 2003bMean = 0.000432; stdev = 0.0456; min = 0; max= 0.0638GRADNT Hydraulic gradient m/m EmpiricalcorrelatedAquifer-specifc See attached Table F-2Randomly selected based on aquifer code(IGWR) using EPACMTPPH Groundwater pH std. Units Empirical Randomly selected from nationaldistributionSee attached Table F-3Assumed equal to average soil pH for 20-miradius around locationPOR Effective porosity Unitless Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from particle diameterRADIS Radial distance to well (R) m Empirical Randomly selected from nationaldistributionSee attached Table F-3EPA OSW survey of landfillsRETARD Retardation coefficient Unitless Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from bulk density, Kd, and porosityTEMP Groundwater temperature DegreesC Constant Site-specific Todd, 1980Groundwater temperature map; average for 20-mi radius around locationVXCS Groundwater seepage velocity m/yr Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from conductivity and gradientXKX Longitudinal hydraulicconductivity (K)m/yr EmpiricalcorrelatedAquifer-specifc See attached Table F-2Randomly selected based on aquifer code(IGWR) using EPACMTPXWELL Longitudinal distance to well m Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from radial distance (R) and angle tothe wellYWELL Distance from plumecenterline to wellm Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from radial distance (R) and angle tothe well and constrained to lay within the arealplume extentZB Aquifer thickness m EmpiricalcorrelatedAquifer-specifc See attached Table F-2Randomly selected based on aquifer code(IGWR) using EPACMTPZWELL Depth of well below water table Fraction Uniform Randomly selected from uniform distr.within ZB or within upper 10 m ofaquifer if ZB>10 mU.S. EPA, 2003bF-3Variable ID Parameter Units Type Value ReferenceTable F-1. Groundwater Model VariablesCommentsAppendix F Groundwater Modeling ParametersDraftChemicalAHYDR2nd order acid hydrolysis rate 1/mol/yr Constant Chemical-specific Kollig, 1993; See attached Table F-6BHYDR2nd order base hydrolysis rate 1/mol/yr Constant Chemical-specific Kollig, 1993; See attached Table F-6BIOS Biodegradation rate in aquifer 1/yr Constant 0 No biodegradationBIOU Biodegradation rate in vadosezone1/yr Constant 0 No biodegradationCSLAM Chemical decay rate in aquifer 1/yr Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from dissolved and sorbed rates fororganics onlyCZERO Leachate concentration mg/L Derived Calculated by LFCR Transient mass fluxes generated by LFCR andread by EPACMTP, converted to transientconcentrationsDSTAR Molecular diffusion coefficient m2/yr Constant Chemical-specific U.S. EPA, 1987, U.S.EPA, 2001; Seeattached Table F-6KOC Organic carbon distributioncoefficient (KOC)mL/g Constant Chemical-specific Kollig, 1993; See attached Table F-6NHYDR Neutral hydrolysis rate 1/yr Constant Chemical-specific Kollig,1993; See attached Table F-6RLAM1 Dissolved hydrolysis rate 1/yr Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from rate constantsRLAM2 Sorbed hydrolysis rate 1/yr Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from rate constantsRTEMP Reference temperature C Constant Chemical-specific Kollig, 1993SFCOF Freundlich isothermcoefficient (Kd) in aquifercm3/g Derived orempiricalisothermChemical-specific U.S. EPA, 2003bFunction of KOC and POMSFEXP Freundlich isotherm exponentin aquiferUnitless Constant 1 Linear sorptionUCLAM Chemical decay rate 1/yr Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from dissolved and sorbed ratesUFCOF Freundlich isothermcoefficient (Kd) in vadose zonecm3/g Derived orempiricalisothermChemical-specific U.S. EPA, 2003bFunction of KOC and POMUFEXP Freundlich isotherm exponentvadose zoneUnitless Constant 1 Linear sorptionExposureCARC Groundwater averaging time yr Empirical Distributions of Child and Adultexposure timesUsed to represent long-term concentration forchronic exposureF-4Variable ID Parameter Units Type Value ReferenceTable F-1. Groundwater Model VariablesCommentsAppendix F Groundwater Modeling ParametersDraftVadoseALPHA Moisture retention parameter(a)1/cm Constant Site-specific U.S. EPA, 2003bRandomly selected value from distribution for agiven soil texture (ISTYPE1)BETA Moisture retention parameter(b)Unitless Constant Site-specific U.S. EPA, 2003bRandomly selected value from distribution for agiven soil texture (ISTYPE1)DISPR Longitudinal dispersivity(vadose)m Derived Calculated by EPACMTP U.S. EPA, 2003bDerived from unsaturated zone thicknessDSOIL Unsaturated zone thickness m EmpiricalcorrelatedAquifer-specifc See attached Table F-2Randomly selected based on aquifer code(IGWR)POM Percent organic matter (POM) % Constant Site-specific U.S. EPA, 2003bRandomly selected value from distribution for agiven soil texture (ISTYPE1)RHOB Soil bulk density g/cm3 Constant Site-specific U.S. EPA, 2003bRandomly selected value from distribution for agiven soil texture (ISTYPE1)SATK Saturated hydraulicconductivitycm/hr Constant Site-specific U.S. EPA, 2003bRandomly selected value from distribution for agiven soil texture (ISTYPE1)WCR Residual water content L/L Constant Site-specific U.S. EPA, 2003bRandomly selected value from distribution for agiven soil texture (ISTYPE1)WCS Saturated water content L/L Constant Site-specific U.S. EPA, 2003bRandomly selected value from distribution for agiven soil texture (ISTYPE1)WMUAREA WMU area m2 Empirical Randomly selected from a nationaldistributionEPA-WBJDBGS Depth of WMU base belowground surfacem Constant 0 Constant value of 0 used for groundwatermodelingDEPTH WMU depth m Derived Randomly selected from a nationaldistributionEPA-WBJICLR Climate Center Integer Constant Site-specific U.S. EPA, 2003 b, See attached Tables F-4and F-5Nearest appropriate climate center to WMUlocationsIGWR Hydrogeologic Environment Integer Constant Site-specific See attached Table F-4; U.S. EPA, 1990Derived using state-specific aquifer mapsISTYPE1 Regional soil type Integer Constant WMU-Specific U.S. EPA, 2003bRandom selection from frequency distributionISTYPE2 Landfill cover soil type Integer Constant Calculated by EPACMTP U.S. EPA, 1990; U.S. EPA, 2003 bRandomly selected from frequency distributionsfor landfillsRECH Recharge rate m/yr Derived Site-specific See attached Table F-5Selected based on climate center (ICLR) andregional soil type (ISTYPE1) for all scenariosSINFIL Infiltration rate (no linerscenario)m/yr Derived Calculated by EPACMTP See attached Table F-5Selected based on climate center (ICLR) andcover soil type (ISTYPE2)SINFIL Infiltration rate (compositeliner scenario)m/yr Empirical Randomly selected from empiricaldistributionSee attached Table F-3Random selection from empirical distributionF-5Variable ID Parameter Units Type Value ReferenceTable F-1. Groundwater Model VariablesCommentsAppendix F Groundwater Modeling ParametersDraftTSOURCE Duration of leaching period yr Derived Calculated by LFCR Calculated based on transient mass fluxes readby EPACMTPXY WMU length m Derived Calculated by EPACMTP U.S. EPA, 2003bSquare root of areaYD WMU width m Derived Calculated by EPACMTP U.S. EPA, 2003bSquare root of areaF-6

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

1 -999 25.9 -999 0.0166 1 3.15 16.8 152 -999 1 -999 15.2 15.2 -999 1 -999 610 -999 0.0001 1 -999 5.79 9.14 0.05 1 946 4.57 -999 0.014 1 1580 3.05 -999 0.014 1 63.1 4.88 12.2 0.07 1 3470 6.1 152 0.03 1 28.4 2.04 9.14 0.01 1 126 6.1 7.32 0.03 1 15.8 3.81 32.9 0.09 1 315 21.3 3.05 -999 1 -999 6.1 6.1 0.000007 1 11000 3.05 18.3 0.02 1 94.6 1.83 4.27 0.04 1 -999 1.22 9.14 0.01 1 7570 1.52 3.05 0.000007 1 6.31 0.914 6.1 0.038 1 6.31 1.83 7.62 0.1 1 31.5 6.1 -999 0.06 1 31.5 0.305 6.1 0.005 1 -999 9.14 152 0.008 1 -8.52129 2.81441 3.76962 -3.97399 Mean 1 6.82319 1.07478 1.80348 -0.39418 Covariance 1 1.07478 0.8005 0.55257 0.4367 Covariance 1 1.80348 0.55257 1.1956 0.17788 Covariance 1 -0.39418 0.4367 0.17788 0.81424 Covariance 1 3.15 0.305 3.05 0.000007 Minimum 1 11000 610 152 0.81424 Maximum 2 63.1 6.1 22.9 0.08 2 28.4 6.1 79.3 -999 2 1890 76.5 -999 0.008 2 5990 30.5 183 0.001 2 315 65.5 45.7 0.0057 2 31.5 15.2 21.3 0.1 2 1580 174 30.5 -999 2 315 5.97 3.6 -999 2 22.1 12.2 10.7 0.028 2 284 16.8 3.05 0.0032 2 9.46 6.1 152 0.031 2 221 9.14 -999 0.008 2 3.15 3.96 4.57 0.01 2 3.15 4.57 91.4 0.001 2 2210 15.2 30.5 0.033 2 11000 18.3 91.4 -999 2 126 13.4 7.62 0.004 2 1330 6.1 21.3 0.005 2 31500 1.83 3.05 -999



### F-7

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

2 -999 4.27 89 -999 2 1890 53.6 6.1 0.043 2 9780 18.3 30.5 0.012 2 6.31 12.2 24.4 0.015 2 3.15 12.2 12.2 0.025 2 12.6 3.7 30 0.01 2 22100000 9.14 1.52 1 2 34700 12.2 4.57 0.008 2 31500 15.2 6.1 0.05 2 3.15 3.66 9.14 0.04 2 315 9.14 21.3 0.005 2 315 8.53 19 0.025 2 -999 4.88 -999 -999 2 -999 3.05 -999 0.024 2 63.1 4.57 19.8 0.04 2 189 6.1 61 0.023 2 22100000 4.57 1.83 1 2 -999 183 12.2 0.0004 2 22.1 2.74 3.05 -999 2 189 15.2 61 0.012 2 11000 15.2 22.9 0.0005 2 -999 3.66 18.3 -999 2 63.1 8.23 518 0.007 2 126 4.57 107 0.03 2 -999 1.52 91.4 -999 2 -7.68877 3.4698 4.2618 -4.42479 Mean 2 12.3279 1.32509 0.47331 -1.46902 Covariance 2 1.32509 0.54208 -0.01357 -0.1757 Covariance 2 0.47331 -0.01357 1.61831 -0.39626 Covariance 2 -1.46902 -0.1757 -0.39626 1.75145 Covariance 2 3.15 1.52 1.52 0.0004 Minimum 2 22100000 183 518 1 Maximum 3 25500 3.66 3.66 0.0009 3 946 9.14 5.33 0.005 3 1260 1.77 6.1 0.000000004 3 28.4 6.1 -999 0.034 3 3780 16.8 1.52 0.04 3 2680 6.71 2.44 0.009 3 31.5 9.45 -999 0.05 3 -999 7.62 -999 0.01 3 63.1 2.3 4.12 0.007 3 6620 30.5 21.3 0.02 3 126 3.06 15.2 0.01 3 31.5 -999 -999 0.01 3 8830 5.33 45.7 0.0005 3 158 0.914 4.57 0.003 3 6.31 1.37 3.66 0.027 3 9.46 2.56 2.74 0.042 3 -7.81342 2.72776 2.93298 -4.6888 Mean


### F-8

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

3 21.2765 2.78074 0.6463 -1.30916 Covariance 3 2.78074 1.07038 0.17468 0.29718 Covariance 3 0.6463 0.17468 0.96341 -0.64536 Covariance 3 -1.30916 0.29718 -0.64536 1.9708 Covariance 3 6.31 0.914 1.52 0.000000004 Minimum 3 25500 30.5 45.7 0.05 Maximum 4 50800 4.57 9.14 0.005 4 13900 -999 33.5 0.028 4 -999 6.1 -999 -999 4 -999 12.2 4.57 0.01 4 1580 2.13 12.2 0.001 4 3.15 19.8 2.44 0.007 4 12.6 4.57 10.7 0.07 4 -999 0.914 6.1 0.043 4 2520 1.52 3.05 0.02 4 3150 2.44 -999 0.000002 4 9.46 1.83 6.04 0.055 4 94.6 0.61 3.96 0.006 4 -999 6.98 53.3 -999 4 116000 15.2 76.2 0.004 4 12600 7.62 6.4 0.049 4 4100 2.13 32 0.003 4 -999 10.7 8.53 0.0006 4 -999 0.61 7.62 0.001 4 3150 0.305 9.14 0.003 4 221 1.52 7.62 0.004 4 -999 4.57 27.4 0.015 4 3.15 3.05 3.05 0.02 4 631 2.44 7.62 0.005 4 -999 50.8 145 0.092 4 -999 15.2 6.1 0.0000001 4 31.5 33.5 -999 0.023 4 315 9.14 3.05 0.002 4 4420 1.52 19.8 0.002 4 631 2.21 0.332 0.001 4 -999 1.22 -999 -999 4 -999 9.14 3.05 0.005 4 7880 22.9 3.05 0.02 4 5360 3.05 6.1 0.001 4 -6.82634 2.65875 3.3063 -4.9212 Mean 4 9.60704 0.51036 1.46619 -1.4956 Covariance 4 0.51036 1.5223 -0.01024 0.0939 Covariance 4 1.46619 -0.01024 1.28413 -0.02391 Covariance 4 -1.4956 0.0939 -0.02391 1.83998 Covariance 4 3.15 0.305 0.332 0.0000001 Minimum 4 116000 50.8 145 0.092 Maximum 5 5680 3.05 21.3 0.002 5 -999 0.914 3.96 -999 5 946 -999 15.2 0.093


### F-9

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

5 -999 3.05 6.1 0.01 5 158000 6.1 3.05 0.0001 5 63100 5.18 1.52 0.005 5 -999 6.1 3.05 0.005 5 15.6 38.1 1.52 0.025 5 126000 4.57 4.57 0.001 5 -999 4.57 22.9 0.03 5 7570 30.5 -999 -999 5 -999 101 15.2 0.05 5 1580 33.5 914 0.001 5 31500 30.5 24.4 0.001 5 -999 9.75 15.2 -999 5 6.31 3.38 7.62 0.003 5 -999 32.9 4.57 -999 5 23700 42.7 6.1 0.003 5 -999 10.7 1.07 -999 5 1580 19.8 24.4 0.005 5 1260 2.44 -999 -999 5 3150 12.2 3.81 -999 5 126 15.2 4.57 0.002 5 946 3.05 3.05 0.002 5 -999 4.57 -999 -999 5 -999 2.44 -999 -999 5 1390 34.1 91.4 0.003 5 -999 12.2 85.3 -999 5 -999 3.66 -999 -999 5 -999 27.4 -999 0.006 5 -999 15.9 16.2 0.0004 5 94.6 7.01 9.14 0.0003 5 2840 42.7 30.5 0.002 5 158 13 130 0.001 5 -999 18.3 3.66 0.01 5 1260 7.32 18.3 0.0001 5 63.1 82.3 -999 -999 5 15800 36.6 -999 0.001 5 3470 7.62 15.2 0.02 5 -999 12.2 15.2 0.001 5 126 1.83 11 0.002 5 2210 15.2 9.14 -999 5 3.15 3.66 2.44 0.005 5 -999 12.2 48.8 0.01 5 -999 36.6 -999 0.068 5 63700 61 -999 -999 5 3.15 61 15.2 0.015 5 -999 7.01 18.3 -999 5 631 14.6 24.4 0.003 5 3190000 9.14 0.305 0.000002 5 3150 10.7 3.05 0.006 5 3.15 4.72 18.3 0.07


### F-10

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

5 946 13.7 6.1 0.008 5 3150 7.62 7.62 -999 5 315 4.88 9.14 0.017 5 11000 2.44 6.1 -999 5 -999 2.44 5.18 0.04 5 -999 3.96 18.3 -999 5 12.6 2.13 0.61 -999 5 2210 9.14 1.52 0.025 5 -999 3.05 6.1 0.013 5 22100 6.1 91.4 0.001 5 -5.61434 3.43835 3.53678 -5.61773 Mean 5 9.98295 0.28014 0.08839 -2.96927 Covariance 5 0.28014 0.8396 0.54136 0.0448 Covariance 5 0.08839 0.54136 2.05569 -0.71488 Covariance 5 2.96927 0.0448 -0.71488 4.17328 Covariance 5 3.15 0.914 0.305 0.000002 Minimum 5 3190000 101 914 0.093 Maximum 6 -999 15.2 18.3 0.005 6 -999 1.83 9.14 0.002 6 315 4.88 15.2 0.001 6 631 8.53 9.14 0.01 6 107000 3.51 7.32 0.005 6 1890 24.4 36.6 0.001 6 3.15 2.74 3.66 0.003 6 -999 21.3 7.62 0.001 6 4100 27.4 3.05 0.001 6 16700 2.44 6.4 0.004 6 11000 5.49 13.1 0.002 6 315 1.52 3.05 0.002 6 -999 1.22 1.83 0.008 6 11000 5.79 -999 0.0005 6 -999 3.96 4.27 0.017 6 -999 12.2 16.8 0.002 6 1580 4.57 7.62 0.04 6 33100 30.5 22.9 0.01 6 -999 4.57 7.62 0.1 6 252 11.5 -999 0.005 6 14200 4.57 18.3 0.0007 6 3150 1.52 1.52 0.0000004 6 5680 3.05 6.1 0.001 6 1890 3.66 6.1 0.002 6 315 3.66 0.61 0.000001 6 31.5 1.52 -999 0.00000002 6 3150 1.19 3.66 -999 6 15500 5.18 7.93 0.006 6 5520 3.66 5.49 0.01 6 3150 3.05 16.8 0.013 6 158 1.52 3.05 0.012 6 22.1 1.22 13.7 0.004


### F-11

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

6 -999 1.83 9.14 0.011 6 9.46 0.914 6.1 0.008 6 -999 10.7 15.2 0.00008 6 -999 12.2 12.2 0.000001 6 -6.7624 2.65846 3.15814 -5.6184 Mean 6 13.8058 1.67704 2.14642 -0.09303 Covariance 6 1.67704 0.8987 0.34951 -0.23716 Covariance 6 2.14642 0.34951 0.86919 0.00252 Covariance 6 -0.09303 -0.23716 0.00252 1.23921 Covariance 6 3.15 0.914 0.61 0.00000002 Minimum 6 107000 30.5 36.6 0.1 Maximum 7 946 2.44 8.23 0.002 7 1260 2.13 305 0.003 7 -999 35.4 -999 -999 7 6940 -999 22.9 0.003 7 23300 15.2 36.6 0.004 7 4420 1.83 38.1 0.0007 7 56100 3.05 10.1 0.002 7 55200 3.05 61 -999 7 9460 57.9 9.14 0.000001 7 -999 9.14 9.14 0.0002 7 -999 12.2 9.14 0.002 7 946 3.05 3.05 0.008 7 9780 3.05 3.05 0.013 7 -999 5.18 12.2 0.002 7 4420 3.66 15.2 0.005 7 4420 24.4 21.3 0.01 7 1580 1.52 24.4 0.01 7 82000 14.9 8.53 0.003 7 946 12.2 18.3 0.000002 7 11000 3.05 4.57 -999 7 -999 4.57 13.7 0.01 7 6940 2.13 7.99 0.004 7 6310 7.01 5.18 0.049 7 23700 4.88 18.3 0.033 7 17700 5.79 42.7 0.002 7 1890 4.57 10.7 0.000004 7 14500 1.52 18.3 0.012 7 120000 22 -999 0.01 7 2520 1.52 6.1 0.011 7 12.6 5.79 4.27 0.021 7 315 0.61 4.57 0.006 7 31.5 0.457 -999 0.001 7 -999 45.7 3.05 -999 7 -5.22204 2.81441 3.78819 -5.30668 Mean 7 13.0649 -1.10808 0.50353 -0.73884 Covariance 7 -1.10808 1.13841 0.0496 0.26902 Covariance 7 0.50353 0.0496 1.11517 -0.46202 Covariance 7 -0.73884 0.26902 -0.46202 1.11713 Covariance


### F-12

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

7 12.6 0.457 3.05 0.000001 Minimum 7 120000 57.9 305 0.049 Maximum 8 6310 7.62 61 0.001 8 24000 4.88 22.9 0.002 8 30000 2.99 18.9 0.004 8 -999 12.2 6.71 0.001 8 2520 3.05 21.3 0.0000008 8 110000 9.14 21.3 0.004 8 13300 5.49 12.2 0.006 8 37800 4.57 9.14 0.003 8 1260 10.7 -999 0.008 8 2210 3.05 22.9 0.0009 8 9780 3.35 15.2 0.0007 8 1890 48.8 32 0.03 8 34400 7.62 26.2 0.006 8 44200 4.88 18.6 0.002 8 15800 29 24.4 0.001 8 7250 9.14 39.6 0.0006 8 13900 12.2 122 0.002 8 29000 2.74 10.1 -999 8 99700 2.13 7.01 0.0007 8 -999 4.57 6.1 0.003 8 14800 1.83 61 0.001 8 7880 2.44 3.05 0.03 8 -999 15.2 76.2 0.0009 8 5680 2.44 6.1 0.001 8 18900 4.57 7.62 0.005 8 3880 3.66 7.62 0.004 8 -999 22 18.3 0.0006 8 473 6.1 4.57 0.017 8 10400 7.62 30.5 0.001 8 22100 9.14 7.62 0.005 8 27800 7.62 24.4 0.002 8 27800 7.62 24.4 0.002 8 -999 6.1 4.57 0.00004 8 11000 12.2 3.05 0.075 8 19200 5.33 12.2 0.008 8 631 0.914 10.7 0.01 8 19200 18.3 10.7 0.013 8 5050 0.61 12.2 0.003 8 -999 7.62 30.5 0.002 8 33100 15.2 30.5 0.0004 8 -999 4.57 22.9 0.01 8 2210 2.13 3.66 0.02 8 60900 20 30.5 0.003 8 -3.59646 2.97372 3.92385 -5.86511 Mean 8 5.02 0.48626 0.15471 -0.8019 Covariance 8 0.4862 0.85551 0.26963 0.07004 Covariance 8 0.1547 0.26963 0.75329 -0.62236 Covariance


### F-13

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

8 -0.8019 0.07004 -0.62236 1.62199 Covariance 8 473 0.61 3.05 0.0000008 Minimum 8 110000 48.8 122 0.075 Maximum 9 946 2.1 13.7 0.05 9 315 13.7 12.2 0.001 9 18.9 3.66 5.49 0.008 9 21800 6.1 15.2 0.004 9 3470 39.6 54.9 0.017 9 3150 21.3 4.57 0.01 9 126 1 30 -999 9 31.5 7.62 3.05 0.009 9 -999 3.05 30.5 0.0000005 9 31.5 5.18 10.7 0.03 9 315 3.96 22.9 0.007 9 63.1 4.57 2.96 0.022 9 915 2.44 12.2 0.0007 9 -999 7.32 12.2 -999 9 1890 1.83 0.914 0.005 9 3150 7.62 7.62 -999 9 631 3.66 2.13 -999 9 6310 2.44 9.14 0.00000004 9 -999 2.13 7.62 0.009 9 4100 1.52 6.1 0.01 9 126 3.05 4.57 0.05 9 126 3.05 7.62 0.02 9 -999 0.61 1.83 -999 9 12.6 1.83 -999 0.04 9 8830 1.52 18.3 0.004 9 315 1.52 6.1 -999 9 284 1.74 9.14 0.01 9 9.46 18.3 2.44 0.003 9 1580 3.35 6.1 0.000004 9 -7.67984 2.48552 3.22796 -4.68545 Mean 9 11.259 0.17085 0.72472 -0.72109 Covariance 9 0.17085 0.87319 0.13478 -0.12094 Covariance 9 0.72472 0.13478 0.81983 -0.0043 Covariance 9 -0.72109 -0.12094 -0.0043 1.28625 Covariance 9 9.46 0.61 0.914 0.00000004 Minimum 9 21800 39.6 54.9 0.05 Maximum 10 -999 3.35 14.6 0.03 10 4420 11.6 54.9 0.005 10 284 4.57 7.62 0.01 10 19600 39.6 21.4 0.0003 10 158 4.57 3.05 0.0006 10 315 1.52 6.1 0.004 10 -999 6.1 3.66 0.000001 10 126 7.62 2.29 0.005 10 315 15.2 10.7 0.01 10 31.5 2.74 6.86 0.017


### F-14

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

10 126 3.05 4.12 0.003 10 -999 3.81 6.1 0.00001 10 -999 3.66 15.2 0.1 10 631 4.57 0.914 0.005 10 3470 3.05 3.05 0.002 10 2210 25.9 7.62 0.00001 10 -999 1.52 15.2 0.002 10 2840 2.74 4.57 -999 10 -999 1.83 2.44 0.008 10 2210 13.7 7.62 0.01 10 126 12.2 12.2 0.025 10 -999 3.81 16.8 0.002 10 -999 3.32 1.83 0.06 10 3.15 3.66 11.6 0.01 10 25.2 1.83 4.57 0.0095 10 4420 10.7 9.14 0.014 10 -999 6.1 42.7 0.00175 10 -6.97635 2.80942 3.15655 -5.57335 Mean 10 4.99889 1.27993 0.51266 -1.74813 Covariance 10 1.27993 0.86035 0.40799 -0.71454 Covariance 10 0.51266 0.40799 0.8467 0.03369 Covariance 10 -1.74813 -0.71454 0.03369 3.61694 Covariance 10 3.15 1.52 0.914 0.000001 Minimum 10 19600 39.6 54.9 0.1 Maximum 11 946 2.13 305 0.01 11 63.1 2.74 30.5 0.03 11 7250 9.14 36.6 0.0006 11 24300 4.57 10.7 0.0068 11 -999 1.52 305 0.001 11 7570 3.05 45.7 0.006 11 12600 0.914 4.57 0.005 11 631 0.914 6.1 0.01 11 3150 1.52 6.1 -999 11 1260 1.22 10.7 0.002 11 31.5 0.914 15.2 0.005 11 13900 1.52 61 0.002 11 -999 1.68 15.2 0.002 11 2520 2 2 0.002 11 1260 1.22 3.05 0.017 11 -999 0.914 7.62 -999 11 315 1.52 1.52 0.05 11 1580 2.74 4.57 0.023 11 -999 3.35 4.27 0.019 11 315 3.05 24.4 0.001 11 284 1.07 30.5 0.003 11 946 2.13 1.68 0.0002 11 -999 2.74 21.3 0.00003 11 8170 7.01 6.1 0.0033 11 -999 -999 6.71 -999


### F-15

### Aquifer Code Longitudinal Hydraulic Conductivity Aquifer

(m/yr) Unsaturated Zone Thickness (m) Aquifer Thickness (m) Hydraulic Gradient

(m/yr) Notes 

## Table F-2. Correlated Empirical Distributions Appendix F Groundwater Modeling Parameters Draft

11 -999 3.05 42.7 0.0005 11 -5.38023 1.8991 3.7492 -5.61773 Mean 11 3.48349 0.52513 -0.00422 -0.63963 Covariance 11 0.52513 0.46903 0.18069 -0.2284 Covariance 11 -0.00429 0.18069 2.02612 -0.08327 Covariance 11 -0.63963 -0.2284 -0.08327 1.97797 Covariance 11 31.5 0.914 1.52 0.00003 Minimum 11 24300 9.14 305 0.05 Maximum 12 158000 30 30 0.006 12 -999 50 10 0.005 12 1580 50.8 144 0.023 12 -999 15.2 91.4 -999 12 -999 3.05 -999 0.012 12 1580 45.7 -999 -999 12 126 3.05 15.2 0.00005 12 315 12.2 61 0.033 12 -999 30.5 -999 0.02 12 -999 320 -999 0.009 12 -999 5.33 15.2 0.001 12 15800 29.3 19.5 -999 12 -999 18.3 -999 -999 12 221 -999 39.6 0.002 12 315 3.96 3.05 0.018 12 24900 1.52 -999 0.002 12 12300 3.96 18.3 0.009 12 -999 3.05 305 0.001 12 94.6 7.62 19.8 0.01 12 1260 400 18 0.000002 12 2180 1.68 7.32 0.00042 12 6310 1.22 3.05 -999 12 -5.6496 3.47765 4.32063 -5.49537 Mean 12 12.0503 1.43257 0.53279 0.79733 Covariance 12 1.43257 1.25667 0.99541 1.35511 Covariance 12 0.53279 0.99541 1.2437 0.81321 Covariance 12 0.79733 1.35511 0.81132 4.45451 Covariance 12 94.6 1.22 3.05 0.000002 Minimum 12 158000 400 305 0.033 Maximum 13 1890 5.18 10.1 0.0057 13 -5.6496 3.47765 4.32063 -5.49537 Mean 13 12.0503 1.43257 0.53279 0.79733 Covariance 13 1.43257 1.25667 0.99541 1.35511 Covariance 13 0.53279 0.99541 1.2437 0.81321 Covariance 13 0.79733 1.35511 0.81132 4.45451 Covariance 13 3.15 0.305 0.305 0.000000004 Minimum 13 22100000 610 914 1 Maximum References: Newell et al., 1989 U.S. EPA, 1997 U.S. EPA, 2003b


### F-16

### VariableID CDF Parameter [Reference] Value Units 

## Table F-3. Empirical Distributions for Groundwater Modeling Appendix F Groundwater Modeling Parameters Draft



### 0 8.18 Active life of the landfill [ b ] y rs ActiveLife 0.1 22.95 0.25 29.54 0.5 38.73 0.75 51.36 0.9 65.44 1 194.17 0

0.1 Lon g itudinal dis p ersivit y ( a q uifer ) [ a ] m AL 0.1 1 0.7 10 1 100 0 4072 Landfill area [ b ] m^2 AREA 0.1 67650 0.25 150300 0.5 360100 0.75 846200 0.9 1860000 1 16810000 0 2.9 Landfill de p th [ b ] m DEPTH 0.1 3.93 0.25 5.84 0.5 10.94 0.75 22.42 0.9 42.61 1 114.8 0 0.00039 Av g
. p article diameter [ d ] c m DIAM 0.038 0.00078 0.104 0.0016 0.171 0.0031 0.262 0.0063 0.371 0.0125 0.56 0.025 0.792 0.05 0.904 0.1 0.944 0.2 0.976 0.4 1 0.8 0 3.2 Groundwater p H [ d ] std. Units PH 0.01 3.6 0.05 4.5 0.1 5.2 0.25 6.07 0.5 6.8 0.75 7.4 0.9 7.9 0.95 8.2 0.99 8.95 1 9.7 0 0.6 Radial distance to well [ d ] m RADIS 0.03 13.7

F-17

### VariableID CDF Parameter [Reference] Value Units 

## Table F-3. Empirical Distributions for Groundwater Modeling Appendix F Groundwater Modeling Parameters Draft



### 0.04 19.8 Radial distance to well [ d ] m RADIS 0.05 45.7 0.1 103.6 0.15 152.4 0.2 182.9 0.25 243.8 0.3 304.8 0.35 304.8 0.4 365.7 0.45 396.2 0.5 426.7 0.55 457.2 0.6 609.6 0.65 762 0.7 804.6 0.75 868.6 0.8 914.4 0.85 1158.2 0.9 1219.1 0.95 1371.5 0.98 1523.9 1 1609.3 0 0 Landfill com p osite liner infiltration rate [ c ] m/ y r SINFIL 0.26 0 0.28 0.0000365 0.3 0.0000365 0.32 0.000073 0.38 0.000073 0.4 0.0001095 0.42 0.000146 0.44 0.00021353 0.46

0.000219 0.5 0.000219 0.52 0.0003285 0.54 0.0004015 0.56 0.000876 0.58 0.000876 0.6 0.000949 0.62 0.001022 0.64 0.0011315 0.66 0.0012045 0.68 0.001241 0.7 0.001314 0.72 0.001533 0.74 0.002263 0.76 0.002336 0.78 0.002555 0.8 0.0026645 0.82 0.0031755 0.84 0.0038325 0.86 0.0043435

F-18

### VariableID CDF Parameter [Reference] Value Units 

## Table F-3. Empirical Distributions for Groundwater Modeling Appendix F Groundwater Modeling Parameters Draft



### 0.88 0.0049275 Landfill com p osite liner infiltration rate [ c ] m/ y r SINFIL 0.9 0.005475 0.92 0.0055845 0.94 0.005986 0.96 0.0060955 0.98 0.006351 1 0.0116435

References: [a] Gelhar et al., 1992

[d] U.S. EPA, 2003b CDF = Cumulative distribution function

[c] U.S. EPA, 1988 [b] Based on EPA/WBJ data



### F-19

### IGWR TEMP 

## Table F-4. Offsite Industrial Landfill Database Appendix F Groundwater Modeling Parameters

ICLR SiteID Draft



### 5 22.5 92 1 12 12.5 85 2 5 12.5 51 3 2 7.5 32 4 12 12.5 42 5 2 17.5 36 6 1 12.5 71 7 9 12.5 32 8 12 12.5 49 9 12 12.5 71 10 12 22.5 93 11 4 17.5 29 12 2 17.5 89 13 2 12.5 28 14 4 22.5 96 15 1 12.5 63 16 13 7.5 49 17 5 12.5 74 18 12 12.5 87 19 5 12.5 74 20 12 17.5 89 21 12 17.5 85 22 4 22.5 81 23 13 12.5 26 24 5 22.5 21 25 5 12.5 3 26 5 17.5 21 27 4 17.5 79 28 12 12.5 54 29 5 12.5 87 30 5 17.5 12 31 12 12.5 49 32 4 17.5 79 33 13 7.5 50 34 4 17.5 93 35 2 7.5 31 36 8 7.5 41 37 2 7.5 50 38 4 7.5 45 39 2 7.5 50 40 1 7.5 62 41 8 12.5 32 42 1 7.5 44 43 12 22.5 78 44 13 12.5 24 45 8 12.5 32 46 2 22.5 21 47 2 22.5 22 48 6 12.5 89 49

F-20

### IGWR TEMP 

## Table F-4. Offsite Industrial Landfill Database Appendix F Groundwater Modeling Parameters

ICLR SiteID Draft



### 12 22.5 91 50 2 12.5 52 51 12 12.5 71 52 1 17.5 77 53 5 17.5 13 54 12 17.5 85 55 4 12.5 66 56 4 17.5 20 57 4 17.5 29 58 4 22.5 92 59 8 12.5 46 60 4 17.5 20 61 4 17.5 93 62 2 12.5 52 63 8 12.5 32 64 4 12.5 72 65 1 17.5 79 66

References: U.S. EPA, 2003 b TEMP = Aquifer temperature IGWR = Hydrogeologic environment ICLR = Climate Center



### F-21

### ICLR City State Silty Loam Sandy Loam Silt Clay Loam 

## Table F-5. HELP Infiltration Rates fo r Landfill Recharge and No-liner Infiltration Appendix F Groundwater Modeling Parameters Draft

1 Fresno CA 0.0307 0.0368 0.0381 2 Boise ID 0.0008 0.0094 0.0038 3 Denver CO 0.0008 0.0008 0.0036 4 Grand Junction CO 0.0000 0.0000 0.0003 5 Pocatello ID 0.0000 0.0000 0.0000 6 Glasgow KY 0.0099 0.0074 0.0099 7 Bismarck ND 0.0239 0.0300 0.0196 8 Pullman WA 0.0069 0.0132 0.0084 9 Yakima WA 0.0000 0.0023 0.0003 10 Cheyenne WY 0.0005 0.0013 0.0086 11 Lander WY 0.0033 0.0053 0.0094 12 Los Angeles CA 0.0787 0.0950 0.0699 13 Sacramento CA 0.1024 0.0876 0.0945 14 San Diego CA 0.0221 0.0340 0.0241 15 Santa maria CA 0.0947 0.1151 0.0841 16 Ely NV 0.0000 0.0000 0.0003 17 Rapid City SD 0.0005 0.0071 0.0033 18 Cedar City UT 0.0000 0.0008 0.0000 19 Albuquerque NM 0.0000 0.0000 0.0003 20 Las Vegas NV 0.0000 0.0000 0.0018 21 Phoenix AZ 0.0000 0.0003 0.0003 22 Tucson AZ 0.0000 0.0003 0.0005 23 El Paso TX 0.0076 0.0130 0.0081 24 Medford OR 0.2073 0.2309 0.2096 25 Great Falls MT 0.0036 0.0069 0.0074 26 Salt Lake City UT 0.0130 0.0269 0.0185 27 Grand Island NE 0.0442 0.0627 0.0323 28 Flagstaff AZ 0.0239 0.0630 0.0226 29 Dodge City KS 0.0135 0.0345 0.0226 30 Midland TX 0.0180 0.0254 0.0135 31 St. Cloud MN 0.0602 0.0831 0.0554 32 E. Lansing MI 0.1090 0.1452 0.1102 33 North Omaha NE 0.0671 0.0795 0.0536 34 Tulsa OK 0.0686 0.1006 0.0465 35 Brownsville TX 0.0549 0.1049 0.0384 36 Dallas TX 0.0599 0.1067 0.0531 37 Oklahoma City OK 0.0612 0.0942 0.0389 38 Concord NH 0.1585 0.2057 0.1372 39 Pittsburg PA 0.0894 0.1313 0.0792 40 Portland OR 0.4171 0.4387 0.3927 41 Caribou ME 0.1082 0.1491 0.0886



### F-22

### ICLR City State Silty Loam Sandy Loam Silt Clay Loam 

## Table F-5. HELP Infiltration Rates fo r Landfill Recharge and No-liner Infiltration Appendix F Groundwater Modeling Parameters Draft

42 Chicago IL 0.0798 0.1138 0.0620 43 Burlington VT 0.1359 0.1781 0.1166 44 Bangor ME 0.1471 0.2045 0.1227 45 Rutland VT 0.1212 0.1598 0.1008 46 Seattle WA 0.4384 0.4582 0.4077 47 Montpelier VT 0.1062 0.1483 0.0879 48 Sault St. Marie MI 0.1651 0.2101 0.1435 49 Put-in-Bay OH 0.0508 0.1003 0.0495 50 Madison WI 0.0912 0.1400 0.0686 51 Columbus OH 0.0765 0.1158 0.0663 52 Cleveland OH 0.0780 0.1212 0.0823 53 Des Moines IA 0.1143 0.1641 0.1156 54 E. St. Louis IL 0.1435 0.1676 0.0704 55 Columbia MO 0.1529 0.1989 0.1224 56 Topeka KS 0.1049 0.1483 0.0762 57 Tampa FL 0.0658 0.1031 0.0475 58 San Antonio TX 0.1095 0.1646 0.0820 59 Hartford CT 0.1709 0.2228 0.1405 60 Syracuse NY 0.2545 0.3251 0.2118 61 Worchester MA 0.2022 0.2591 0.1697 62 Augusta ME 0.2116 0.2700 0.1674 63 Providence RI 0.2131 0.2863 0.1753 64 Portland ME 0.2294 0.2840 0.1872 65 Nashua NH 0.2268 0.2812 0.1943 66 Ithaca NY 0.1684 0.2136 0.1392 67 Boston MA 0.2332 0.2383 0.1542 68 Schenectady NY 0.1473 0.1928 0.1224 69 Lynchburg VA 0.3081 0.3612 0.2570 70 New York City NY 0.2436 0.2944 0.1969 71 Philadelphia PA 0.2007 0.2609 0.1641 72 Seabrook NJ 0.1814 0.2428 0.1427 73 Indianapolis IN 0.1300 0.1862 0.1064 74 Cincinnati OH 0.1554 0.2210 0.1539 75 Bridgeport CT 0.1953 0.2464 0.1615 76 Orlando FL 0.1016 0.1697 0.0805 77 Greensboro NC 0.3256 0.3896 0.2705 78 Jacksonville FL 0.1511 0.2106 0.1102 79 Watkinsville GA 0.2891 0.3556 0.2332 80 Norfolk VA 0.3122 0.0000 0.2685 81 Shreveport LA 0.2296 0.2939 0.1842 82 Astoria OR 1.0762 1.1494 0.9647



### F-23

### ICLR City State Silty Loam Sandy Loam Silt Clay Loam 

## Table F-5. HELP Infiltration Rates fo r Landfill Recharge and No-liner Infiltration Appendix F Groundwater Modeling Parameters Draft

83 New Haven CT 0.3520 0.4628 0.2855 84 Plainfield MA 0.1900 0.2540 0.1521 85 Knoxville TN 0. 4107 0.4460 0.3543 86 Central Park NY 0.3363 0.4171 0.2738 87 Lexington KY 0.3294 0.3970 0.2700 88 Edison NJ 0.3122 0.3914 0.2492 89 Nashville TN 0.4674 0.5395 0.3769 90 Little Rock AK 0.3531 0.4336 0.2824 91 Tallahassee FL 0.5913 0.7308 0.4564 92 New Orleans LA 0.5893 0.7445 0.4503 93 Charleston SC 0.2609 0.3287 0.2123 94 W. Palm Beach FL 0.2611 0.3490 0.1783 95 Atlanta GA 0.3416 0.3993 0.2822 96 Lake Charles LA 0.3647 0.4641 0.2817 97 Miami FL 0.1450 0.2201 0.1019



### F-24

### Chemical Name BHYDR KOC NHYDR AHYDR 

## Table F-6. Chemical Parameters for Groundwater Modeling Appendix F Groundwater Modeling Parameters

DSTAR CAS Draft



### 0 0 0.08 0 Methanol 0.052 67561 0 0 0.26 0 Acetone 0.0363 67641 0 0 3.18 0 Butanol n- 0 71363 0 0 63.10 0 Benzene 0.0325 71432 0.6 0.001 8.51 0 Meth y lene Chloride 0.0394 75092 0 0 2.75 0 Isobut y l alcohol 0 78831 0 0 0.93 0 Meth y l eth y l ketone 0.0322 78933 49500 2.73E-05 53.70 0 Trichloroethane 1,1,2- 0.0315 79005 0 0 125.89 0 Trichloroeth y lene 0.0322 79016 0 0 1202.26 0 Dichlorobenzene 1,2- 0.0281 95501 0 0 1000.00 0 Eth y lbenzene 0.0267 100414 0 0 7.41 0 Meth y l isobut y l ketone 0.0264 108101 0 0 269.15 0 Toluene 0.0291 108883 0 0 378.44 0 Chlorobenzene 0.0299 108907 0 0 66.07 0 C y clohexanone 0 108941 0 0 0.29 0 Ethox y ethanol 2- 0.0308 110805 0 0 162.18 0 Tetrachloroeth y lene 0.0298 127184 3400000 0.0048 2.24 3500 Eth y l acetate 0 141786 0 0 131.83 0 Cresols 0.0299 1319773 0 0 1198.55 0 X y lenes ( total ) 0.0268 1330207

References: Kollig, 1993 KOC = Organic Carbon Distribution Coefficient [ml/g] AHYDR = 2nd Order Acid Hydrolysis Rate [1/mol/yr] NHYDR = Neutral Hydrolysis Rate [1/yr] BHYDR = 2nd Order Base Hydrolysis Rate [1/mol/yr] DSTAR = Molecular Diffusivity in water [m^2/yr]

U.S. EPA, 2001



### F-25

### Draft Appendix F Groundwater Modeling Parameters



## F-26 

# References Gelhar, L.W., C. Welty, and K.R. Rehfedldt. 1992. A critical review of data on field-scale dispersion in aquifers. Water Resources Research 28 (7):1955–1974. Kollig, H., editor. 1993. Environmental Fate Constants for Organic Chemicals under Consideration for EPA’s Hazardous Waste Identification Projects . U.S. Environmental Protection Agency, Environmental Resear ch Laboratory, Office of Research and Development, Athens, GA. Newell, C.J., L.P. Hopkins, and P.B Bedien t. 1990. A hydrogeologic database for groundwater modeling. Ground Water . September. Schroeder, P.R., T.S. Dozier, P.A. Zappi, B.M. McEnroe, J.W. Sjostrom, and R.L. Peyton. 1994. The Hydrogeologic Evaluation of Landfill Performance (HELP) Model: Engineering Documentation for Version 3 . EPA/600/R-94/168b. U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC. Todd, D.K. 1980. Groundwater Hydrology (2nd Edition) . New York: John Wiley and Sons. U.S. EPA. (Environmental Protection Agency). 1987. Process Coefficients and Models for Simulating Toxic Organics and Heavy Metals in Surface Waters . U.S. EPA, Office of Research and Development. Washington, DC: U.S. Government Printing Office. U.S. EPA (Environmental Protection Agency). 1988. National Survey of Solid Waste (Municipal) Landfill Facilities (Draft). EPA/530-SW88-034. U.S. EPA, Office of Solid Waste and Emergency Response, Washington, DC. U.S. EPA (Environmental Protection Agency). 1990. Toxicity Characteristic Final Rule. 55 FR 11796. March 29. U.S. EPA (Environmental Protection Agency). 1997. EPACMTP: User’s Guide . U.S. EPA, Office of Solid Waste, Washington, DC. U.S. EPA (Environmental Protection Agency). 2001. WATER9 . U.S. EPA, Office of Air Quality Planning and Standards, Research Triangle Park, NC. Web site: http://www.epa.gov/ttn/chief/ software/water/index.html U.S. EPA (Environmental Protection Agency). 2003a. IWEM Technical Background Document. USEPA 530-R-02-012. U.S. EPA, Office of Solid Waste, Washington, DC. U.S. EPA (Environmental Protection Agency). 2003b. EPACMTP: Technical Background Document. USEPA 530-R-03-002. U.S. EPA, Office of Solid Waste, Washington, DC. U.S. EPA (Environmental Protection Agency). 2003c. EPACMTP: Parameters/Data Background Document. USEPA 530-R-03-003. U.S. EPA, Office of Solid Waste, Washington, DC.

### Draft Appendix G Unitized Air Concentrations



## G-1 

# Appendix G Unitized Air Concentrations
This appendix describes the interpolati on methods used to develop unitized air concentrations (UACs) used in the solvent industrial wipes analysis. The a pproach applied under this analysis is consistent with the technical approach used in the dyes and pigments assessment (U.S. EPA, 2003) and implemented in the Indus trial Waste Air (IWAIR) model (U.S. EPA, 2002). This approach, which includes the interpol ation of UACs, is intended to minimize time and cost by using representative air dispersion modeling outputs. The representative UAC data set used in the current analysis was developed by conducting air dispersion modeling with the Indu strial Source Complex – Short Term model, version 3 (ISCST3). Modeling was conducted for many different locations, landfill surface areas, distances, and directions designe d to cover a broad range of landfill characteristics.

 

## Location. Meteorological data for 31 different meteorological stations were used. EPACMTP Climate Center locations were used to place landfill locations, as described in Section 2.2.4 . Each location was then cross-referenced to one of the 57 meteorological regions developed for the IWAIR model to represent the different climatic and geographical regions of the contiguous 48 states. As a result, 31 different mete orological regions were identified.

 

## Surface Area. Nineteen surface areas for landfills ranging from 4,000 m 2 

## to approximately 17,000,000
m 2 

## were modeled (see box).

 

## Distance. Eight receptor distan ces from the edge of landfill were modeled (see box).

 

## Direction. Thirty-six directions were modeled: on each distance ring, receptors were placed every 10° around the full 360° of the landfill. The resulting representative UAC data set was used to determine a UAC for each of the 10,000 scenarios. Each scenario was indexed on location, surface area, distance, and direction. The interpolation algorithm select s two UACs for the same locati on, distance, and direction that reflect the modeled surface areas that bracket the actual landfill su rface area, and interpolates to the actual surface area for the specific landf ill using standard lin ear interpolation: 

# ( ) i i j i j i 

## UAC UAC UAC A A A A UAC +

− × ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

− − = (Equation G-1) Landfill Areas Modeled 4,000 m 2 

### 420,000 m 2 

### 6,045 m 2 

### 607,000 m 2 

### 8,090 m 2 

### 906,528 m 2 

### 14,145 m 2 

### 1,157,442 m 2 

### 20,200 m 2 

### 1,408,356 m 2 

### 40,450 m 2 

### 3,146,678 m 2 

### 60,700 m 2 

### 4,885,000 m 2 

### 127,350 m 2 

### 9,350,000 m 2 

### 194,000 m 2 

### 17,000,000 m 2 

### 307,000 m 2


### Ring Distances Modeled 25 m 300 m 50 m 500 m 75 m 1,000 m 150 m 2,000 m

### Draft Appendix G Unitized Air Concentrations



## G-2 where UAC = UAC for specific landfill ([ F g/m 3 

## ]/[ F g/m 2 

## -s]) A = area of specific landfill (m 2 

## ) A i 

## = modeled surface area immediately below area of specific landfill (m 2 

## ) A

j 

## = modeled surface area immediately above area of specific landfill (m 2 

## ) UAC i 

## = UAC for area i ([ F g/m 3 

## ]/[ F g/m 2 

## -s]) UAC j 

## = UAC for area j ([ F g/m 3 

## ]/[ F g/m 2 

## -s]). To ensure that the 19 modeled surface areas were appropriate for linear interpolation, an analysis was performed to evaluate the adequacy of the selected ar eas in achieving a goal of less than 5 percent interpolation erro r. Modeling was performed for thre e meteorological stations that represent a range of wind roses and climate regimes: Fresno, CA; Minneapolis, MN; and Salt Lake City, UT. A similar analysis using the same three meteorological stations was done during the development of IWAIR. Consistent with the IWAIR Technical Background Document (EPA, 2002), the following process was applied to com pute the percentage interpolation error:
1. 

## For each of the three meteorological stations, ISCST3 was run to generate outputs at a set of surface areas that represent midpoints between the initial set of areas, because the error should be the largest at the midpoints. These ISCST3 outputs represent the true values for purposes of calculating interpolation errors.
2. 

## For each of the area midpoints, the interpol ation algorithm was applied to estimate the ISCST3 output value using the initial set of areas. These are the interpolated values. 3. The percentage interpolation e rror was computed as follows: 

# ( ) ( ) 100 × − value true value ed interpolat value true (Equation G-2)
Results from the analysis indicated that the go al of less than 5 per cent interpolation error was achieved. As a consequence, the 19 surface areas described above were selected for the current analysis. 

# References
U.S. EPA. 2002. Industrial Waste Air Model Technical Background Document. U.S. EPA, Office of Solid Waste, Washington, DC.
U.S. EPA. 2003. Risk Assessment Technical Background Document for the Dye and Pigment Industry Hazardous Waste Listing Determination . U.S. EPA, Office of Solid Waste, Washington, DC.

### Draft Appendix H Equations



## H-1 

# Appendix H

Equations
This appendix presents the equations that were used to estimate ambient air and shower/bathroom air concentrations, ambien t air and groundwater pathway exposures, and human health risks for cancer and noncancer end points. These equations ar e grouped as follows:

 

## Calculation of ambient air concentrations ( Table H1-1 )

 

## Calculation of shower i ndoor air concentrations ( Tables H2-1 to H2-10 )

 

## Calculation of ingestion dose ( Tables H3-1 to H3-2 )

 

## Calculation of dermal dose ( Tables H4-1 to H4-2 )

 

## Calculation of risk. ( Tables H5-1 to H5-6 ). Calculation of groundwater con centrations is not presented here because it is estimated using the EPACMTP model, which is discussed in Section 3.3 and Appendix F

.

## Table H1-1. Ambient Air Concentration (mg/m^3)

Name Descri p tion Value 

# C

air 

### Appendix H Equations Draft Calculation of Ambient Air Concentrations



# [ ] 001

. 0 86400 / 000 , 000 , 1 × × × = Q

UAC C air



### UAC Calculated from dispersion modeling Unitized Air Concentration (ug/m^3) per (ug/s-m^2)
1000000 Conversion factor (ug/g) Q Calculated from source modeling Emission rate from source (g/d-m^2)
86400 Conversion factor (sec/day)
0.001 Conversion factor (mg/ug) 

### This equation is used to calculate ambient air concentra tion from a unitized air concentration and an emission rate from the source model.

H-2

## Table H2-1. Average Daily Concentration in Indoor Air (mg/m^3)

Name Descri p tion Value 

# C

airindoor 

### Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations



# ( )( ) 1440 bathroom m airBathroo Shower airShower airIndoor 

## T C T C C × + ×
=



# ( ) 

# [ ]

s t s ts t s airShower 

## n y y C 1000 2

, , 

## × +

= 

# ∑ +



# ( ) 

# [ ]

b t b ts t b

m airBathroo 

## n y y C 1000 2

, , 

## × +

= 

# ∑ +



### Calculated above Average concentration in bathroom (mg/m^3) C airBathroom 

### Calculated above Average concentration in shower (mg/m^3) 

### C airShower 

### Calculated; see Table H2-10 Total time spent in shower stall (min) T shower 

### Calculated; see Table H2-2 Vapor-phase constituent concentra tion in the shower at the end of time step (mg/L) y s , t+ts


### Calculated; see Table H2-3 Vapor-phase constituent concentration in the bathroom at the end of time step (mg/L) y b, t+ts


### Calculated from last time step Vapor-phase constituent concentration in the bathroom at the beginning of time step (mg/L) y b, t


### Calculated from last time step Vapor-phase constituent concentr ation in the shower at the beginning of time step (mg/L) y s , t


### Exposure data; see Appendix I Time spent in bathroom, not in shower (min) T b athroom 

### Calculated as Tshower divided by ts Number of time steps corresponding to time spent in the shower (unitless) n s 

### Calculated as Tbathroom divided by ts Number of time steps corresponding to time spent in the bathroom (unitless) n b



### 1440 Minutes per day (min)
1000 Conversion factor (L/m^3) 

### The above equations are used to calculate the time-weighted average daily indoor air concentration to which a receptor is exposed. The equation a ssumes that receptors are only exposed to contamin ants in the shower and bathroom.

H-3

## Table H2-2. Vapor-Phase Constituent Concentration in the Shower at End of Time Step (mg/L)

Name Descri p tion Value 

# y s , t+ts 

### Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations



# ( ) 

# ( ) 

# [ ]
y y E Q y y ts V s, t ts s, t s sb s, t b, t

s + 

## = + −×− ×

× 1000

Calculated; see Table H2-4 Mass emitted in the shower for a given time step (mg) E s 

### Calculated from last time step Vapor-phase constituent concentration in the bathroom at the beginning of time step (mg/L) y b, t


### Calculated from last time step Vapor-phase constituent concentr ation in the shower at the beginning of time step (mg/L) y s , t


### 100; estimated from the volume and flow rate in McKone (1987) such that the exchange rate equals the volume divided by the residence time (e.g., 2000L/20 min). Volumetric exchange rate between the shower and the bathroom (L/min) Q sb



### 2 Volume of shower stall (m^3) V s


### ts Time step = 0.2 (min)
1000 Conversion factor (L/m^3) 

### This equation is used to calculate the vapor-phase constituent concentration in the shower at end of time step. The equation is derived from Equation 9 in Little (1992).

H-4

## Table H2-3. Vapor-Phase Constituent Concentration in the Bathroom at End of Time Step (mg/L)

Name Descri p tion Value 

# y b , t+ts 

### Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations



# ( )( ) 

# ( ) 

# [ ]
y y Q y y Q y y ts V b t ts b t sb s t ts b t bh b t h t

b , , , , ,,

+ + 

## = + × − −× − ×

× 1000

Calculated; see Table H2-2 Vapor-phase constituent concentra tion in the shower at the end of time step (mg/L) y s , t+ts


### Calculated from last time step Vapor-phase constituent concentration in the bathroom at the beginning of time step (mg/L) y b, t


### 300; estimated from the volume and flow rate in McKone (1987) such that the exchange rate equals the volume divided by the residence time (e.g., 10,000L/30 min). Volumetric exchange rate between the bathroom and the house (L/min) Q b h



### 100; estimated from the volume and flow rate in McKone (1987) such that the exchange rate equals the volume divided by the residence time (e.g., 2000L/20 min). Volumetric exchange rate between the shower and the bathroom (L/min) Q sb



### 10 Volume of bathroom (m^3) V b 

### 1000 Conversion factor (L/m^3)

ts Time step = 0.2 (min) Vapor-phase constituent concentration in the house at the beginning of time step; Assumed deminimus: yh, t=0 (mg/L) y h , t


### The above equations are used to calculate the time-weighted average daily indoor air concentration to which a receptor is exposed. The equation a ssumes that receptors are only exposed to contamin ants in the shower and bathroom.

H-5

## Table H2-4. Contaminant Mass Emitted in the Shower for a Given Time Step (mg)

Name Descri p tion Value 

# E s 

### Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations



## For Et > Emax,

max s 

## E E =



## For E t 

## ≤ 

## E max 

## ,

t s 

## E E =



## Where,

em in t 

## f ts ShowerRate C E × × × =



## 1000

, 

## × ×

− = s t s eq max 

## V ) y (y E

Calculated above Potential mass of constituent emitted from shower during time step (mg) E t



### Calculated above Maximum possible mass of constituent emitted from shower during time step (mg) E max


### Calculated; see Table H2-5 Fraction of constituent emitted from a droplet (unitless) f e m 

### Calculated; see Table H2-9 Dimensionless Henry's law constant (unitless) H’ Calculated from last time step Vapor-phase constituent concentr ation in the shower at the beginning of time step (mg/L) y s , t



### H' x Cin Vapor-phase contaminant concentration in equilibrium between water and air (mg/L) 

### y eq 

### Exposure data; see Appendix I Constituent concentration in incoming water (mg/L) C in 

### ShowerRate 5.5; calculated based on droplet diameter and nozzle velocity. Rate of flow from showerhead (L/min)

2 Volume of shower stall (m^3) V s 

### 1000 Conversion factor (L/m^3)

ts Time step = 0.2 (min) 

### This equation is used to calculate the vapor-phase constituent concentration in the shower at end of time step. The equation is derived from Equation 9 in Little (1992).

H-6

## Table H2-5. Fraction of Constituen t Emitted from a Droplet (unitless)

Name Descri p tion Value 

# f

em 

### Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations



## ) e ( ) f ( f N sat em −



## − ×

− = 1 1

Calculated; see Table H2-6 Fraction of gas-phase saturation (unitless) f sat 

### N Calculated; see Table H2-7 Dimensionless overall mass transfer coefficient (unitless) 

### The above equations are used to determine the mass of contaminant emitted for a given time step. The equilibrium concentration in air (y_eq) is calculated from Equation 1 in Little (1992).

H-7

## Table H2-6. Fraction of Vapor-Phase Saturation in Shower (unitless)

Name Descri p tion Value 

# f

sat 

### Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations

eq ts t s sat 

## y y f + 

## = ,



### Calculated; see Table H2-2 Vapor-phase constituent concentra tion in the shower at the end of time step (mg/L) y s , t+ts


### Calculated from last time step Vapor-phase constituent concentr ation in the shower at the beginning of time step (mg/L) y s , t



### H' x Cin Vapor-phase contaminant concentration in equilibrium between water and air (mg/L) 

### y eq


### This equation is used to calculate the fraction of a give n chemical emitted from a droplet of water in the shower. The equation is based on Equation 5 in Little (1992).

H-8

## Table H2-7. Dimensionless Overall Mass Transfer Coefficient (unitless)

Name Descri p tion Value 

## N Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations



## Time Res Drop AVRatio K N ol 

## × × =



## DropDiam AVRatio 6

=

DropVel NozHeight Time Res Drop 100 ×
=

AVRatio Calculated above Area-to-volume ratio for a sphere (cm^2/cm^3) DropResTime Calculated above Residence time for falling drops (s) Calculated; see Table H2-8 Overall mass transfer coefficient (cm/s) K o l 

### DropDiam Exposure data; see Appendix I Drop diameter (cm) DropVel Exposure data; see Appendix I Drop terminal velocity (cm/s) NozHeight Exposure data; see Appendix I Nozzle height (m)
100 Conversion factor (cm/m) 

### This equation is used to calculate the fraction of a give n chemical emitted from a droplet of water in the shower. The equation is based on Equation 5 in Little (1992).

H-9

## Table H2-8. Overall Mass Transfer Coefficient (cm/s)

Name Descri p tion Value 

# K

ol 

### Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations

1

3 / 2 3 / 2 

## 1 5

. 2 − 

## ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

′ × + × = H D D K

a w ol 

## β

Calculated; see Table H2-9 Dimensionless Henry's law constant (unitless) H’ Chemical data; see Appendix B Diffusivity of chemical in air (cm^2/s) D a 

### Chemical data; see Appendix B Diffusivity in water (cm^2/s) D w 

### 216 Proportionality constant (cm-s)^-1/3 

### β 

### This equation calculates the dimensionless overall mass tran sfer coefficient. The above equation is based on Little (1992).

H-10

## Table H2-9. Dimensionless Henry's Law Constant (unitless)

Name Descri p tion Value 

# H’ Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations



## HLC HLC H coef 

## × = ′

Temp R HLC coef 

## × = 1

Calculated above Coefficient to Henry's law constant (unitless) HLC coef 

### HLC Chemical data; see Appendix B Henry's law constant (atm-m^3/mole) Ideal Gas Constant; R=0. 00008205 (atm-m^3/K-mole) R Temp Temperature (K) 

### This equation calculates the dimensionless Henry's law constant.

H-11

## Table H2-10. Total Time Spent in Shower Stall (min)

Name Descri p tion Value 

# T

shower 

### Appendix H Equations Draft Calculation of Shower Indoor Air Concentrations

showering l showerstal shower 

## T T T + =

Exposure data; see Appendix I Duration of shower (min) 

### T showering 

### Exposure data; see Appendix I Time in shower stall after showering (min) T showerstall 

### This equation calculates the total time that a receptor is exposed to vapors.

H-12

## Table H3-1. Average Daily Dose of Contaminant from Consumption of Drinking Water (mg/kg BW/d)

Name Descri p tion Value 

# ADD dw 

### Appendix H Equations Draft Calculation of Ingestion Dose



## 1000 × × ×
= BW F CR C ADD dw dw water dw



### Calculated from groundwater model Total concentration in the water (mg/L) C water 

### Exposure data; see Appendix I Consumption rate of water (mL/day) CR dw 

### BW Exposure data; see Appendix I Body weight (kg)
Set to 1 Fraction of drinking water ingested that is contaminated (unitless) F dw



### 1000 Conversion factor (mL/L) 

### Source: U.S. EPA, 2005.

H-13

## Table H3-2. Lifetime Average Daily Dose (mg/kg/d)

Name Descri p tion Value 

## LADD Appendix H Equations Draft Calculation of Ingestion Dose



## 365 

## × × ×
= AT EF ED ADD LADD dw



### ADD Calculated; see Table H3-1 Average daily dose (mg/kg/day)
AT Exposure data; see Appendix I (NOTE: lf the start age (SA) plus the exposure duration (ED) is greater than 70, then the averaging time (AT) is set to ED) Averaging time (yr)

EF Exposure data; see Appendix I Exposure frequency (d/yr)
ED Exposure data; see Appendix I Exposure duration (yr)
SA Set to 1yr for child and 20yrs for adult Start age (yr)
365 Conversion factor (days/yr) 

### Source: U.S. EPA, 2005.

H-14

## Table H4-1. Dermal Absorbed Dose per Event for Organic Compounds - Water Contact (mg/cm2-event)

Name Descri p tion Value 

# DA event 

### Appendix H Equations Draft Calculation of Dermal Dose



## If t t then DA FA K C tau t event event p w event 

## ≤ = ×× × * 2 6

π



# ( ) If t t then DA FA K C t B tau B B B event event p w event 

## > =×× + + + +
+ ⎛ ⎝ ⎜ ⎜ ⎞ ⎠

⎟ ⎟ ⎡ ⎣ ⎢ ⎢ ⎤ ⎦ ⎥ ⎥ * 1 2 13 3 1 2

2



### Set to 1 Fraction absorbed water (unitless) FA 

### Calculated (U.S. EPA, 2004) Dermal permeability coefficient of compound in water (cm/hr) K p 

### Calculated (U.S. EPA, 2004) Dimensionless ratio of the permeability coefficient of a compound through the stratum corneum relative to its permeability coefficient across the viable epidermis (unitless) B



### Exposure data; see Appendix I Event duration (hr/event) t event 

### Calculated (U.S. EPA, 2004) Lag time per event (hr/event) tau 

### 2.4 * tau (U.S. EPA, 2004) Time to reach steady-state (hr) t* 

### Calculated from groundwater model Chemical concentration in water (mg/cm3) C w



### H-15

## Table H4-2. Dermal Absorbed Dose - Water Content (mg/kg-day)

Name Descri p tion Value 

# DAD Appendix H Equations Draft Calculation of Dermal Dose



## DAD DA EV ED EF SA BW AT event 

## = ××××
×

Calculated; see Table H4-1 Absorbed dose per event (mg/cm2-event) DA event 

### EF Exposure data; see Appendix I Exposure frequency (d/yr) Exposure data; see Appendix I Event frequency (events/day) EV 

### Exposure data; see Appendix I Averaging time (day) AT


### BW Exposure data; see Appendix I Body weight (kg)
ED Exposure data; see Appendix I Exposure duration (yr) Exposure data; see Appendix I Skin surface area available for contact (cm2) SA



### H-16

## Table H5-1. Cancer Risk Due to Inhalation (unitless)

Name Descri p tion Value 

# R isk air 

### Appendix H Equations Draft Calculation of Risk



## AT ED URF C Risk Inhal air air 

## × × ×
= 1000

1000 Conversion factor (ug/mg) Toxicity data; see Table 6-1 Inhalation unit risk factor (ug/m^3)^-1 URF inhal 

### LADD Calculated; see Table H3-2 Lifetime average daily dose (mg/kg/day) Calculated; see Table H1-1 Concentration in air (mg/m^3) C air 

### ED Exposure data; see Appendix I Exposure duration (yr)
AT Exposure data; see Appendix I (NOTE: lf the start age (SA) plus the exposure duration (ED) is greater than 70, then the averaging time (AT) is set to ED) Averaging time (yr)



### Source: U.S. EPA, 2005.

H-17

## Table H5-2. Cancer Risk Due to Ingestion (unitless)

Name Descri p tion Value 

# R isk oral 

### Appendix H Equations Draft Calculation of Risk

oral oral 

## CSF LADD Risk × =

Toxicity data; see Table 6-1 Oral cancer slope factor (mg/kg/day)-1 CSF oral 

### LADD Calculated; see Table H3-2 Lifetime average daily dose (mg/kg/day) 

### Source: U.S. EPA, 2005.

H-18

## Table H5-3. Dermal Cancer Risk (unitless)

Name Descri p tion Value 

# Risk dermal 

### Appendix H Equations Draft Calculation of Risk



## Risk DAD SF dermal ABS 

## = ×

Applied oral cancer slope factor Absorbed cancer slope factor (mg/kg-day)^-1 SF ABS 

### Calculated; see Table H4-2 Dermal absorbed dose (mg/kg-day) DAD



### H-19

## Table H5-4. Noncancer Hazard Quotient Due to Inhalation (unitless)

Name Descri p tion Value 

# HQ air 

### Appendix H Equations Draft Calculation of Risk



## RfC C HQ air air 

## =

Toxicity data; see Table 6-1 Noncancer reference concentration (mg/m^3) RfC Calculated; see Table H1-1 Total concentration in air (mg/m^3) C air 

### Source: U.S. EPA, 2005.

H-20

## Table H5-5. Noncancer Hazard Quot ient Due to Ingestion (unitless)

Name Descri p tion Value 

# HQ oral 

### Appendix H Equations Draft Calculation of Risk



## RfD ADD HQ oral 

## =

Toxicity data; see Table 6-1 Noncancer reference dose (mg/kg/day) RfD
ADD Calculated; see Table H3-1 Average daily dose (mg/kg/day) 

### Source: U.S. EPA, 2005.

H-21

## Table H5-6. Dermal Noncancer Hazard Quotient (unitless)

Name Descri p tion Value 

# HQ dermal 

### Appendix H Equations Draft Calculation of Risk



## HQ DAD RfD dermal ABS 

## =

Applied noncancer reference dose Absorbed reference dose (mg/kg-day) RFD ABS 

### Calculated; see Table H4-2 Dermal absorbed dose (mg/kg-day) DAD



### H-22

### Draft Appendix H Equations



## H-23 

# References McKone, T.E. 1987. Human exposure to volatile organic compounds in household tap water: The indoor inhalation pathway. Environmental Science and Technology 21 (12):1194– 1201. Little, J.C. 1992. Applying the tw o resistance theory to contamin ant volatilization in showers. Environmental Science and Technology 26 (7):1341–1349. U.S. EPA (Environmental Protection Agency). 2005. Human Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities . EPA530-R-05-006. Office of Solid Waste and Emergency Response, Washington, DC. Se ptember. Available at www.epa.gov/osw.

## [This page intentionally left blank.]

### Draft Appendix I Human Exposure Factors



## I-1 

# Appendix I Human Exposure Factors Exposure factors are data that quantify human behavior patterns (e.g., ingestion rates of drinking water) and characteristics (e.g., body weight) that affect human exposure to environmental contaminants. These data can be used to construct realistic assumptions concerning an individual’s exposure to and subsequent intake of a contaminant in the environment. The exposure factors data were developed in such a way as to allow the exposure of individuals of different ages (e.g., children ve rsus adults) to be differentiated. The derivation and values used for the human exposure factors in this analysis are described below, and the exposure factors selected for the probabilistic analyses are also presented. The derivation methodologies and values used in this analysis are consistent with those applied in previous EPA risk assessments. 

# I.1 Exposure Parameters Used in Probabilistic Analysis

I.1.1 Introduction The general methodology for collecting human exposure data for the probabilistic analysis relied on the Exposure Factors Handbook (EFH) , Volumes I, II, and III (U.S. EPA, 1997a,b,c), which was used in one of three ways:

 When EFH percentile data were adequate (as was the case for most input variables), maximum likelihood estimation was used to fit selected parametric models (gamma, lognormal, Weibull, generalized gamma) to the EFH data. The chi-square measure of goodness of fit was then used to choose the best distribution. Parameter uncertainty information (e.g., for averages, standard deviations) was also derived using the asymptotic normality of the maximum likelihood estimate or a regression approach.

 For a few variable conditions for which percentile data were not adequate for statistical model fitting, models were selected on the basis of results for other age cohorts or, if no comparable information was available, were determined by assuming lognormal as a default distribution and reasonable coefficients of variation (CVs).

 Other variables for which data were not adequate for either of the approaches above were fixed at EFH-recommended mean values or according to established EPA policy.
Table I-1 lists all of the parameters used in the probabilistic analysis. Both fixed variables and the values used to define distributed data are provided, along with the minimum and maximum values imposed on the distributions to avoid selecting unrealistically large or small values, because some of the distribution types are infinite, but the underlying characteristics are not (e.g., the range of adult body weights is not infinite).DraftAppendix I Human Exposure FactorsI-2Table I-1. Summary of Exposure Parameters Used in Probabilistic AnalysisParameterUnitsVariableTypeConstantsMean(or shape)aStd Dev(or scale)aMinimumMaximumReferenceAveraging time for carcinogens yr Constant 7.00E+01U.S. EPA (1989)Body weight (adult) kg Lognormal7.12E+01 1.33E+01 1.50E+01 3.00E+02 U.S. EPA (1997a); Tbl 7-2,7-4, 7-5Body weight (child 1) kg Lognormal1.55E+01 2.05E+00 4.00E+00 5.00E+01 U.S. EPA (1997b); Tbl 7-3,7-6, 7-7Body weight (child 2) kg Lognormal3.07E+01 5.96E+00 6.00E+00 2.00E+02 U.S. EPA (1997a); Tbl 7-3,7-6, 7-7Body weight (child 3) kg Lognormal5.82E+01 1.02E+01 1.30E+01 3.00E+02 U.S. EPA (1997a); Tbl 7-3,7-6, 7-7Event frequency (shower/bath)event/d Constant 1.00E+00U.S. EPA (1997c); Tbl 15-176 and U.S.EPA (2006);Tbl 9-16Exposure duration (adult resident) yr Weibull1.34E+00 1.74E+01 1.00E+00 CappedbU.S. EPA (1999) (ACS)Exposure duration (child) yr Weibull1.32E+00 7.06E+00 1.00E+00 CappedbU.S. EPA (1999) (ACS)Exposure frequency (adult resident) d/y Constant 3.50E+02U.S. EPA PolicyFraction contaminated: drinkingwaterFraction Constant 1.00E+00U.S. EPA PolicyIngestion rate: drinking water (adultresident)mL/d Gamma3.88E+00 3.57E+02 1.04E+02 1.10E+04 U.S.EPA (1997a); Tbl 3-6Ingestion rate: drinking water (child1 resident)mL/d Gamma2.95E+00 2.37E+02 2.60E+01 3.84E+03 U.S.EPA (1997a); Tbl 3-6Ingestion rate: drinking water (child2 resident)mL/d Gamma3.35E+00 2.35E+02 3.40E+01 4.20E+03 U.S.EPA (1997a); Tbl 3-6Ingestion rate: drinking water (child3 resident)mL/d Gamma2.82E+00 3.42E+02 3.30E+01 5.40E+03 U.S.EPA (1997a); Tbl 3-6Time spent showering min Gamma2.83E+00 5.89E+00 1.00E+00 6.00E+01 U.S.EPA (1997c); Tbl 15-21Time spent in shower stall aftershoweringmin Weibull9.60E-01 8.36E+00 1.00E+00 6.00E+01 U.S.EPA (1997c); Tbl 15-23Time spent in bathroom immediatelyfollowing showermin Weibull9.80E-01 9.75E+00 1.00E+00 1.20E+02 U.S.EPA (1997c); Tbl 15-32Bathing contact time (child resident) min/eventLognormal2.68E+01 1.41E+01 1.00E+00 6.00E+01 U.S.EPA (2006); Tbl 9-16(child 1–6 years)DraftAppendix I Human Exposure FactorsI-3ParameterUnitsVariableTypeConstantsMean(or shape)aStd Dev(or scale)aMinimumMaximumReferenceRatio of surface area to body weight(child 1)m2/kgcLognormal4.18E-02 1.17E-02 3.00E-02 1.10E-01 U.S. EPA(1997c); Tbl 6-9;U.S. EPA (2006); Tbl 8-4Ratio of surface area to body weight(child 2 and 3)m2/kgcWeibull3.63E-02 7.7E-03 1.00E-02 6.00E-02 U.S. EPA(1997c); Tbl 6-9;U.S. EPA (2006); Tbl 8-4Ratio of surface area to body weight(adult resident)m2/kgcWeibull7.27 E+00 1.730E-022.00E-02 4.00E-02 U.S.EPA (1997c); Tbl 6-9aMean and std dev for lognormal distributions, and shape and scale for gamma and Weibull distributions.bExposure duration was capped so that the maximum value would notexceed the 70-year lifetime assumption implicit in the averaging time used. For example, exposure durationfor adults was capped at 50 years. This is the maximum exposureduration, starting at age 20, that will not exceed the 70-yearlifetime assumption implicit in the averaging time used.cConverted to cm2/kg for dermal exposure modeling.

### Draft Appendix I Human Exposure Factors



## I-4 I.1.2 Exposure Parameter Distribution Methodology This section describes how stochastic or di stributed input data for each exposure factor were collected and processed. Exposure parameter distributions were developed for use in the Monte Carlo analysis. For most variables for which distributions were developed, exposure factor data from the EFH were analyzed to fit selected parametric models (i.e., gamma, lognormal, Weibull). Steps in the development of distributions included preparing data, fitting models, assessing fit, and preparing parameters to characterize distributional uncertainty in the model inputs. For many exposure factors, EFH data include sample sizes and estimates of the following parameters for specific receptor types and age groups: mean, standard deviation, standard error, and percentiles corresponding to a subset of the following probabilities: 0.01, 0.02, 0.05, 0.10, 0.15, 0.25, 0.50, 0.75, 0.85, 0.90, 0.95, 0.98, and 0.99. These percentile data, where available, were used as a basis for fitting distributions. Although in no case were all of these percentiles actually provided for a single factor, seven or mo re were typically present in the EFH data. Therefore, using the percentiles makes fuller use of the available information than fitting distributions simply based on the method of moments (e.g., selecting models that agree with the data mean and standard deviation). For some factors, certain percentiles were not used in the fitting process because sample sizes were too small to justify their use. Percentiles were used only if at least one data point was in the tail of the distribution. If the EFH data repeated a value across several adjacent percentiles, only one value (the most central, or closest to the median) was used in most cases (e.g., if both the 98th and 99th percentiles had the same value, only the 98th percentile value was used). The EFH does not use standardized age cohorts across exposure factors, but rather, different exposure factors have data reported for di fferent age categories. Therefore, to obtain the percentiles for fitting the four standardized age cohorts (ages 1 to 5, 6 to 11, 12 to 19, and over 20), each EFH cohort-specific value for a given e xposure factor was assigned to one of these four cohorts. When multiple EFH cohorts fit into a single standardized cohort, the EFH percentiles were averaged within each cohort (so, for example, data on children aged 1–2 years and 3–5 years were averaged for the ages 1–5 cohort). If sample sizes were available, weighted averages were used, with weights proportional to sample sizes. If sample sizes were not available, equal weights were assumed (i.e., the percentiles were simply averaged). Because the EFH data are always positive and are almost always skewed to the right (i.e., have a long right tail), three two-parameter probability models commonly used to characterize such data (gamma, lognormal, and Weibull) were selected for many of the parameters. In addition, a three-parameter model (generalized gamma) was used to unify them 1 

## and allow for a likelihood ratio test of the fit of the two-para meter models. However, only the two-parameter models were selected for use in the analysis, because the three-parameter generalized gamma model did not significantly improve the goodness of fit over the two-parameter models. This simple setup constitutes a considerable improvement over the common practice of using a lognormal model in which adequate EFH data were available to support maximum likelihood

1 

### The gamma, Weibull, and lognormal distributions are all special cases of the generalized gamma distribution.

### Draft Appendix I Human Exposure Factors



## I-5 estimation. However, in a few cases, data were not adequate to fit a distribution, and the lognormal model was assumed as the default. Lognormal, gamma, Weibull, and generalized gamma distributions were fit to the data set for each factor using maximum likelihood estimation (Burmaster and Thompson, 1998). When sample sizes were available, the goodness of fit was calculated for each of the four models using the chi-square test (Bickel and Doksum, 1977). When percentile data were available but sample sizes were unknown, a regression F-test for the goodness of fit against the generalized gamma model was used. For each of the two-parameter models, parameter uncertainty information (i.e., mean, standard deviation, scale, and shape) was provided as parameter estimates for a bivariate normal distribution that could be used for simulating parameter values (Burmaster and Thompson, 1998). The information necessary for such simulations includes estimates of the two model parameters, their standard errors, and their correlation. To obtain this parameter uncertainty information, the asymptotic normality of the maximum likelihood estimate (Burmaster and Thompson, 1998) was used when sample sizes were available, and a regression approach was used when sample sizes were not available (Jennrich and Moore, 1975; Jennrich and Ralston, 1979). In either case, uncertainty can be expressed as a bivariate normal distribution for the model parameters.
Section I.1.3 discusses fixed parameters. Section I.1.4 describes the variable parameters, including the EFH data used to develop the distributions and the final distributional statistics.

I.1.3 Fixed Parameters Certain parameters were fixed, based on central tendency values from the best available source (usually EFH recommendations), either because no variability was expected or because the available data were not adequate to generate distributions. Fixed (constant) parameters are shown in Table I-2 , along with the value selected for the risk analysis and the data source. These constants include variables for which limited or no percentile data were provided in the EFH: exposure frequency, showering frequency, and fracti on contaminated for drinking water. Most of these values were extracted directly from the EFH. When evaluating carcinogens, total dose is averaged over the lifetime of the individual, assumed to be 70 years.
Table I-2. Summary of Human Exposure Fact or Data Used in Modeling: Constants Description Value Units Source
Fraction contaminated: drinki ng water 1 fraction EPA policy Exposure frequency (adult resident, child resident) 350 d/yr EPA policy Shower/bath frequency (adult and child resident) 1 x/d U.S. EPA (1997c) and U.S. EPA (2006) Averaging time for carcinogens (adult residen t, child resident) 70 yr U.S. EPA (1989) Source: EFH (U.S. EPA, 1997a,b,c) 

## The fraction contaminated for drinking water wa s assumed to be 1 (i.e., all drinking water available for consumption at a site is potentially contaminated), with actual concentrations depending on fate and transport model results. Thus, households for which the drinking water

### Draft Appendix I Human Exposure Factors



## I-6 pathway was analyzed were assumed to get 100 percent of their drinking water from groundwater. Exposure frequency was set to 350 days per year, in accordance with EPA policy, assuming that residents take an average of 2 weeks’ vacation time away from their homes each year. In addition to the general exposure factors above that were fixed, many of the shower model parameters (which are not available from the EFH) were also fixed. Fixed shower model parameters are presented in Table I-3

.
Table I-3. Fixed Shower Parameters Description Value Units Source Diameter of shower water drop 0.098 cm RTI-derived value Terminal velocity of water drop 400 cm/s RTI-derived value Height of shower head 1.8 m Little (1992) Volumetric exchange rate between the bathroom and the house 300 L/min RTI-derived val ue based on McKone (1987) data Volumetric exchange rate between the shower and the bathroom 100 L/min RTI-derived val ue based on McKone (1987) data Rate of water flow from shower head 10 L/ min RTI-derived value based on Little (1992) data Volume of the bathroom 10 m 3 

### McKone (1987) Volume of shower 2 m 3 

### McKone (1987)


## I.1.4 Variable Parameters The variable parameters include drinking water intake, various shower parameters, body weight, and exposure duration Drinking Water Intake. Drinking water intake data and distributions are presented in Table I-4 . These data are consistent with the data applied in previous EPA risk assessments, including 3MRA. Drinking water intake data were obtained from Table 3-6 of the EFH (U.S. EPA, 1997a). Data (in mL/d) were presented by age groups. Weighted averages of percentiles, means, and standard deviations were calculated for the three child age groups and for adults. Percentile data were used to fit parametric models (gamma, lognormal, and Weibull) using maximum likelihood estimation. Measures of goodness of fit were used to select the most appropriate model.
Shower and Bath Parameters. Shower parameters and distributions are presented in Table I-5 . Percentile data for time spent taking a shower, time spent in the shower stall after showering, and time spent in the bathroom immediately following a shower were provided in EFH Tables 15-21, 15-23, and 15-32, respectively (U.S. EPA, 1997c). Percentile data were used to fit parametric models (gamma, lognormal, and Weibull) using maximum likelihood estimation. Measures of goodness-of-fit were used to select the most appropriate model for each variable.DraftAppendix I Human Exposure FactorsI-7Table I-4. Drinking Water Intake Data and DistributionsEFH Data (mL/d)DistributionsAgeCohortNDataMeanDataSDevP01P05P10P25P50P75P90P95P99DistributionPopEstdMeanPopEstdSDev1–5 3,200 697.1 401.5 51.62 187.6 273.5 419.2 616.5 900.8 1,236 1,473 1,917 Gamma 698 4066–11 2,405 787 417 68 241 318 484 731 1,0161,338 1,556 1,998 Gamma 787 43012–19 5,801 963.2 560.6 65.15 241.4 353.8 574.4 868.5 1,247 1,694 2,033 2,693 Gamma 965 57420+ 13,394 1,384 721.6 207.6 457.5 607.3 899.6 1,2751,741 2,260 2,682 3,737 Gamma 1,383 703N = Number of samples; P01-P99 = Percentiles; Pop-Estd = Population-estimated; SDev = Standard deviation.DraftAppendix I Human Exposure FactorsI-8Table I-5. Shower and Bathing Parameter Data and DistributionsEFH DataDistributionsParameterAgeCohortNP02/P05aP10P25P50P75P90P95P98P99DistributionPopEstdMean orShapebPopEstd StdDev orScalebTime spentshowering (adult)(minutes)all ages 3,547 4 5 10 15 20 30 35 50 60 Gamma 2.83 5.89Time spent inshower stall aftershowering (adult)(minutes)all ages 3,533 1 3 5 10 20 30 40 50 Weibull 0.96 8.36Time spent inbathroom aftershower (adult)(minutes)all ages 4,182 1 4 5 15 20 30 40 60 Weibull 0.98 9.75Time spent bathing(child)c(minutes)1-5 20 60 Lognormal 26.84 14.081-5 0.047 0.00507 0.05630.0617 0.0719 0.0784 0.0846Lognormal 0.0418 0.01176-11 0.0291 0.0328 0.03760.0422 0.0454 0.0501 0.0594Weibull 6.186 0.036312-19 0.0291 0.0328 0.0360.0422 0.0454 0.0501 0.0594Weibull 6.186 0.0363Ratio of surfacearea to bodyweight (SA/BWratio) (m2/kg)d20+ 0.0238 0.0244 0.02700.0286 0.0302 0.0316 0.0329Weibull 7.27 0.0173N = number of samples; P02-P99 = percentiles; Pop-Estd = population-estimated.aData are P02 for time spent showering and P05 for ratio of surface area to body weight.bMean and std dev for lognormal distributions, and shape and scale for gamma and Weibull distributions.cBathing data were presented in U.S. EPA (2006) for ages 1–6. These data were applied to the child bathing scenario with an exposure start age of 1 year.dThe data for SA/BW ratio in the EFH was presented for somewhatdifferent age ranges than the cohorts used here. For child 1 (ages 1-5), we used EFH data for ages 0-2; for child 2(ages 6-11) and child 3 (12-19), we used EFH data for ages 2.1-17.9; and for child 4/adult (20+), we used EFH data for ages >18. Data were converted to cm2/kg for dermal exposuremodeling.

### Draft Appendix I Human Exposure Factors



## I-9 Data for bathing time and ratio of body surface area to body weight are presented for selected percentiles in the Child-Specific EFH, Table 9-16 (U.S. EPA, 2006) and the EFH, Table 6-9 (U.S. EPA, 1997c), respectively. A goodness-of-fit test was performed to determine the best fit between these data points and standard probability distributions (e.g., lognormal) using @Risk software (Palisade Co., Newfield, NY). Th e distribution with the highest-ranking fit was selected and subsequently used. For each Monte Carlo simulation, values for these two inputs were sampled from these continuous probability distributions. Body Weight. Body weight data and distributions are presented in Table I-6 . Body weight data were obtained from Tables 7-2 th rough 7-7 of the EFH (U.S. EPA, 1997a). Data (in kg) were presented by age and gender. Weighted averages of percentiles, means, and standard deviations were calculated for 1- to 5-year-olds, 6- to 11-year-olds, 12- to 19-year olds, and adult age groups; male and female data were weighted and combined for each age group. These percentile data were used as the basis for fitting distributions. These data were analyzed to fit parametric models (gamma, lognormal, and Weibull) using maximum likelihood estimation. Measures of goodness of fit were used to select the most appropriate model. Exposure Duration. Exposure duration data and distributions are presented in Table I-7

. Exposure duration was assumed to be equivalent to the average residence time for each receptor. Exposure durations for adult and child residents were determined using data on residential occupancy from the EFH Table 15-168 (U.S. EPA, 1997c). The data represent the total time a person is expected to live at a single location, based on age. The table presents male and female data combined. Adult residents aged 21 to 90 were pooled. For child residents, the age 3 group was used to represent the 1- to 5-year-olds. In an analysis of residential occupancy data, Myers et al. (2000) found that the data, for most ages, were best fit by a Weibull distribution. The Weibull distribution as implemented in Crystal Ball is characterized by three parameters: location, shape, and scale. Location is the minimum value and, in this case, was presumed to be zero. Shape and scale were determined by fitting a Weibull distribution to the pooled data. To pool residential occupancy data for the age cohorts, an arithmetic mean of data means was calculated for each age group. Then, assuming a Weibull distribution, the variance within each age group was calculated in the age cohort. These variances in turn were pooled over the age cohort using equal weights. This is not the usual type of pooled variance, which would exclude the variation in the group means. However, this way, the overall variance reflected the variance of means within the age groups. The standard deviation was estimated as the square root of the variance. The CV was calculated as the ratio of the standard deviation divided by the Weibull mean. For each cohort, the population-estimated parameter uncertainty information (e.g., shape and scale) was calculated based on a Weibull distribution, the calculated data mean for the age cohort, and the CV.DraftAppendix I Human Exposure FactorsI-10Table I-6. Body Weight Data and DistributionsEFH Data (kg)DistributionsAgeCohortNDataMeanDataSDevP05P10P15P25P50P75P85P90P95Distribu-tionPopEstdMeanPopEstdSDev1–5 3,762 15.52 3.719 12.5 13.1 13.45 14.03 15.26 16.67 17.58 18.32 19.45 Lognormal 15.5 2.056–11 1,725 30.84 9.561 22.79 24.05 25.07 26.44 29.58 33.44 36.82 39.66 43.5 Lognormal 30.7 5.9612–19 2,615 58.45 13.64 43.84 46.52 48.31 50.94 56.77 63.57 68.09 71.98 79.52 Lognormal 58.2 10.220+ 12,504 71.41 15.45 52.86 55.98 58.21 61.69 69.26 78.49 84.92 89.75 97.64Lognormal 71.2 13.3N = Number of samples; P05-P95 = Percentiles; Pop-Estd = Population-estimated; SDev = Standard deviation.Table I-7. Exposure Duration Data and DistributionsEFH DataDistributionsAgeCohortData Mean(yr)DistributionPop-Estd Shape(yr)aPop-Estd Scale(yr)1–5 6.5 Weibull 1.32 7.059Adult 16.0 Weibull 1.34 17.38Pop-Estd = Population-estimated; SDev = Standard deviation.aDistributions used in analysis.

### Draft Appendix I Human Exposure Factors



## I-11 

# I.2 References Bickel, P.J., and K.A. Doksum. 1977. Mathematical Statistics: Basic Ideas and Selected Topics

. San Francisco, CA: Holden-Day. Burmaster, D.E, and K.M. Thompson. 1998. Fitting second-order parametric distributions to data using maximum likelihood estimation. Human and Ecological Risk Assessment 4 (2):319– 339. Jennrich, R.I., and R.H. Moore. 1975. Maximum likelihood estimation by means of nonlinear least squares. Pp. 57–65 in Statistical Computing Section Proceedings of American Statistical Association . Alexandria, VA: American Statistical Association. Jennrich, R.I., and M.L. Ralston. 1979. Fitting nonlinear models to data. Annual Review Biophysical Bioengineering 8 :195–238. Little, J.C. 1992. Applying the two resistance theory to contaminant volatilization in showers. Environmental Science and Technology 26 (7):1,341–1,349. McKone, T.E. 1987. Human exposure to volatile organic compounds in household tap water: The indoor inhalation pathway. Environmental Science and Technology 21 (12):1,194– 1,201. Myers, L., M. Riggs, J. Lashley, R. Whitmore, and J. Moya. 2000. Options for Development of Parametric Probability Distributions for Exposure Factors. EPA/600/R-00/058. U.S. Environmental Protection Agency, National Center for Environmental Assessment, Office of Research and Development, Washington, DC. U.S. EPA (Environmental Protection Agency). 1989. Risk Assessment Guidance for Superfund. Volume I: Human Health Evaluation Manual (Part A) (Interim Final). EPA/540/1- 89/002. Prepared by U.S. EPA, Office of Emergency and Remedial Response, Washington, DC. U.S. EPA (Environmental Protection Agency). 1997a. Exposure Factors Handbook, Volume I, General Factors. EPA/600/P-95/002Fa. U.S. EPA, Offi ce of Research and Development, Washington, DC. U.S. EPA (Environmental Protection Agency). 1997b. Exposure Factors Handbook, Volume II, Food Ingestion Factors. EPA/600/P-95/002Fa. U.S. EPA, Office of Research and Development, Washington, DC. U.S. EPA (Environmental Protection Agency). 1997c. Exposure Factors Handbook, Volume III, Activity Factors. EPA/600/P-95/002Fa. U.S. EPA, Offi ce of Research and Development, Washington, DC.

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## I-12 U.S. EPA (Environmental Protection Agency). 1999. Revised Risk Assessment for the Air Characteristic Study. Volume II: Technical Background Document . EPA/530/R-99/019b. U.S. EPA, Office of Solid Waste, Washington, DC. U.S. EPA (Environmental Protection Agency). 2006. Child-Specific Exposure Factors Handbook (External Review Draft) . EPA-600/R-06-096a. U.S. EPA, National Center for Environmental Assessment, Cincinnati, OH. September. Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=56747.