Draft Appendix A Estimated Risks 

A-1 

Appendix A 

Estimated Risks 

for Mass Loading Rate of 1 kg / year 

This appendix presents chemical-specific results for a series of percentiles (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 from these two pathways were considered 

separately because of differences in time frame 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 benzene) 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 presented 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 effect for inhalation and 

ingestion exposures, combined results for all three exposure pathways together 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 both 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 exposure route, are sorted separately to pull the 

risk percentiles of interest (e.g., 50th percentile, 90th percentile). This process results in four sets 

of data for each solvent for groundwater: one set for drinking water ingestion, one for shower 

inhalation, one for shower/bathing dermal, and one for combined groundwater risk. 

Each of the four result types (drinking water ingestion, shower inhalation, shower/bathing 

dermal, and combined results for a particular percentile) 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 values 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 single 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 inconsistent modeling conditions. 

 

1

 It should be noted that this appendix does not present 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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Inhalation 3.0E-11

75 Inhalation 9.8E-11

90 Inhalation 2.7E-10

95 Inhalation 4.7E-10

99 Inhalation 1.2E-09

Cancer Child

50 Inhalation 1.2E-11

75 Inhalation 4.5E-11

90 Inhalation 1.2E-10

95 Inhalation 2.2E-10

99 Inhalation 5.9E-10

Composite Liner

Cancer Adult

50 Inhalation 2.7E-11

75 Inhalation 9.0E-11

90 Inhalation 2.4E-10

95 Inhalation 4.2E-10

99 Inhalation 1.1E-09

Cancer Child

50 Inhalation 1.1E-11

75 Inhalation 4.1E-11

90 Inhalation 1.1E-10

95 Inhalation 1.9E-10

99 Inhalation 5.5E-10

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Shower 1.2E-08

Drinking water 3.3E-09

Dermal bathing 3.7E-10

Combined DW/SH/DM 1.7E-08

75 Shower 1.2E-07

Drinking water 3.5E-08

Dermal bathing 3.6E-09

Combined DW/SH/DM 1.7E-07

90 Shower 6.8E-07

Drinking water 1.8E-07

Dermal bathing 1.9E-08

Combined DW/SH/DM 9.1E-07

95 Shower 1.6E-06

Drinking water 4.2E-07

Dermal bathing 4.0E-08

Combined DW/SH/DM 2.0E-06

99 Shower 7.1E-06

Drinking water 1.9E-06

Dermal bathing 1.8E-07

Combined DW/SH/DM 9.0E-06

Cancer Child

50 Drinking water 3.0E-09

Dermal bathing 3.9E-10

Combined DW/DM 3.5E-09

75 Drinking water 3.0E-08

Dermal bathing 3.7E-09

Combined DW/DM 3.4E-08

90 Drinking water 1.4E-07

Dermal bathing 1.8E-08

Combined DW/DM 1.6E-07

95 Drinking water 3.4E-07

Dermal bathing 4.0E-08

Combined DW/DM 3.8E-07

99 Drinking water 1.4E-06

Dermal bathing 1.7E-07

Combined DW/DM 1.6E-06

Noncancer Adult

50 Drinking water 9.9E-05

Dermal bathing 1.1E-05

75 Drinking water 8.8E-04

Dermal bathing 9.3E-05

90 Drinking water 4.1E-03

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 

Draft Appendix A Theoretical Risk Distributions

95 Drinking water 9.1E-03

Dermal bathing 9.3E-04

99 Drinking water 3.6E-02

Dermal bathing 3.5E-03

Noncancer Child

50 Drinking water 2.1E-04

Dermal bathing 2.8E-05

75 Drinking water 1.9E-03

Dermal bathing 2.4E-04

90 Drinking water 8.5E-03

Dermal bathing 1.1E-03

95 Drinking water 1.9E-02

Dermal bathing 2.3E-03

99 Drinking water 7.3E-02

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Cancer Adult

75 Shower 2.4E-12

Drinking water 7.5E-13

Dermal bathing 7.9E-14

Combined DW/SH/DM 3.7E-12

90 Shower 6.5E-10

Drinking water 1.8E-10

Dermal bathing 2.0E-11

Combined DW/SH/DM 9.1E-10

95 Shower 4.6E-09

Drinking water 1.2E-09

Dermal bathing 1.4E-10

Combined DW/SH/DM 6.2E-09

99 Shower 8.8E-08

Drinking water 2.0E-08

Dermal bathing 2.2E-09

Combined DW/SH/DM 1.2E-07

Cancer Child

75 Drinking water 6.9E-13

Dermal bathing 9.4E-14

Combined DW/DM 8.1E-13

90 Drinking water 1.6E-10

Dermal bathing 2.1E-11

Combined DW/DM 1.9E-10

95 Drinking water 1.0E-09

Dermal bathing 1.4E-10

Combined DW/DM 1.2E-09

99 Drinking water 1.4E-08

Dermal bathing 1.9E-09

Combined DW/DM 1.7E-08

Noncancer Adult

75 Drinking water 2.1E-08

Dermal bathing 2.3E-09

90 Drinking water 4.9E-06

Dermal bathing 5.3E-07

95 Drinking water 3.3E-05

Dermal bathing 3.2E-06

99 Drinking water 3.7E-04

Dermal bathing 4.3E-05

Noncancer Child

75 Drinking water 4.9E-08

Dermal bathing 6.2E-09

90 Drinking water 9.8E-06

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 

Draft Appendix A Theoretical Risk Distributions

95 Drinking water 6.3E-05

Dermal bathing 8.7E-06

99 Drinking water 6.5E-04

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 1.6E-10

75 Inhalation 5.3E-10

90 Inhalation 1.4E-09

95 Inhalation 2.7E-09

99 Inhalation 7.4E-09

Noncancer Child

50 Inhalation 1.6E-10

75 Inhalation 5.3E-10

90 Inhalation 1.4E-09

95 Inhalation 2.7E-09

99 Inhalation 7.7E-09

Composite Liner

Noncancer Adult

50 Inhalation 1.5E-10

75 Inhalation 4.9E-10

90 Inhalation 1.3E-09

95 Inhalation 2.5E-09

99 Inhalation 6.8E-09

Noncancer Child

50 Inhalation 1.5E-10

75 Inhalation 4.9E-10

90 Inhalation 1.3E-09

95 Inhalation 2.5E-09

99 Inhalation 7.2E-09

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 2.0E-09

Drinking water 2.4E-07

Dermal bathing 1.3E-09

75 Shower 2.7E-08

Drinking water 3.2E-06

Dermal bathing 1.7E-08

90 Shower 1.7E-07

Drinking water 2.0E-05

Dermal bathing 1.0E-07

95 Shower 4.1E-07

Drinking water 5.1E-05

Dermal bathing 2.5E-07

99 Shower 2.0E-06

Drinking water 2.2E-04

Dermal bathing 1.1E-06

Noncancer Child

50 Drinking water 4.9E-07

Dermal bathing 3.3E-09

75 Drinking water 7.2E-06

Dermal bathing 4.4E-08

90 Drinking water 4.3E-05

Dermal bathing 2.6E-07

95 Drinking water 1.1E-04

Dermal bathing 6.4E-07

99 Drinking water 5.2E-04

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 3.9E-19

Drinking water 4.9E-17

Dermal bathing 2.7E-19

75 Shower 7.8E-13

Drinking water 9.4E-11

Dermal bathing 4.8E-13

90 Shower 5.2E-11

Drinking water 6.1E-09

Dermal bathing 3.1E-11

95 Shower 3.1E-10

Drinking water 3.5E-08

Dermal bathing 1.9E-10

99 Shower 6.5E-09

Drinking water 6.5E-07

Dermal bathing 3.3E-09

Noncancer Child

50 Drinking water 1.2E-16

Dermal bathing 7.2E-19

75 Drinking water 2.0E-10

Dermal bathing 1.3E-12

90 Drinking water 1.2E-08

Dermal bathing 8.5E-11

95 Drinking water 7.2E-08

Dermal bathing 4.7E-10

99 Drinking water 1.2E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 4.0E-11

75 Inhalation 1.2E-10

90 Inhalation 3.0E-10

95 Inhalation 5.0E-10

99 Inhalation 1.2E-09

Noncancer Child

50 Inhalation 4.2E-11

75 Inhalation 1.3E-10

90 Inhalation 3.1E-10

95 Inhalation 5.3E-10

99 Inhalation 1.3E-09

Composite Liner

Noncancer Adult

50 Inhalation 3.0E-10

75 Inhalation 9.3E-10

90 Inhalation 2.2E-09

95 Inhalation 3.7E-09

99 Inhalation 9.3E-09

Noncancer Child

50 Inhalation 3.1E-10

75 Inhalation 9.5E-10

90 Inhalation 2.3E-09

95 Inhalation 3.8E-09

99 Inhalation 9.4E-09

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 2.1E-08

Drinking water 5.6E-07

Dermal bathing 3.0E-09

75 Shower 1.6E-07

Drinking water 4.2E-06

Dermal bathing 2.2E-08

90 Shower 6.2E-07

Drinking water 1.6E-05

Dermal bathing 8.3E-08

95 Shower 1.3E-06

Drinking water 3.3E-05

Dermal bathing 1.7E-07

99 Shower 4.2E-06

Drinking water 1.2E-04

Dermal bathing 5.4E-07

Noncancer Child

50 Drinking water 1.2E-06

Dermal bathing 8.0E-09

75 Drinking water 9.0E-06

Dermal bathing 5.8E-08

90 Drinking water 3.5E-05

Dermal bathing 2.2E-07

95 Drinking water 7.7E-05

Dermal bathing 4.6E-07

99 Drinking water 2.4E-04

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 1.4E-19

Drinking water 3.9E-18

Dermal bathing 2.0E-20

75 Shower 4.6E-13

Drinking water 1.2E-11

Dermal bathing 6.7E-14

90 Shower 4.9E-11

Drinking water 1.4E-09

Dermal bathing 6.7E-12

95 Shower 4.2E-10

Drinking water 1.2E-08

Dermal bathing 5.9E-11

99 Shower 1.1E-08

Drinking water 2.3E-07

Dermal bathing 1.4E-09

Noncancer Child

50 Drinking water 9.2E-18

Dermal bathing 5.8E-20

75 Drinking water 2.7E-11

Dermal bathing 1.7E-13

90 Drinking water 2.7E-09

Dermal bathing 1.9E-11

95 Drinking water 2.4E-08

Dermal bathing 1.5E-10

99 Drinking water 5.3E-07

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 1.7E-06

75 Inhalation 5.2E-06

90 Inhalation 1.2E-05

95 Inhalation 1.8E-05

99 Inhalation 4.2E-05

Noncancer Child

50 Inhalation 1.9E-06

75 Inhalation 5.7E-06

90 Inhalation 1.3E-05

95 Inhalation 2.0E-05

99 Inhalation 4.4E-05

Composite Liner

Noncancer Adult

50 Inhalation 1.9E-06

75 Inhalation 5.5E-06

90 Inhalation 1.2E-05

95 Inhalation 1.9E-05

99 Inhalation 4.3E-05

Noncancer Child

50 Inhalation 2.1E-06

75 Inhalation 6.0E-06

90 Inhalation 1.3E-05

95 Inhalation 2.1E-05

99 Inhalation 4.6E-05

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 5.6E-04

Drinking water 2.5E-04

Dermal bathing 4.5E-05

Combined DW/SH/DM 9.8E-04

75 Shower 5.9E-03

Drinking water 2.3E-03

Dermal bathing 4.0E-04

Combined DW/SH/DM 9.7E-03

90 Shower 3.0E-02

Drinking water 1.1E-02

Dermal bathing 1.8E-03

Combined DW/SH/DM 4.5E-02

95 Shower 6.7E-02

Drinking water 2.3E-02

Dermal bathing 4.0E-03

Combined DW/SH/DM 9.6E-02

99 Shower 2.9E-01

Drinking water 9.5E-02

Dermal bathing 1.6E-02

Combined DW/SH/DM 4.1E-01

Noncancer Child

50 Drinking water 5.5E-04

Dermal bathing 1.2E-04

Combined DW/DM 6.8E-04

75 Drinking water 5.0E-03

Dermal bathing 1.0E-03

Combined DW/DM 6.3E-03

90 Drinking water 2.3E-02

Dermal bathing 4.8E-03

Combined DW/DM 2.9E-02

95 Drinking water 5.1E-02

Dermal bathing 9.9E-03

Combined DW/DM 6.1E-02

99 Drinking water 2.2E-01

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 2.4E-13

Drinking water 1.2E-13

Dermal bathing 2.0E-14

Combined DW/SH/DM 4.5E-13

75 Shower 9.7E-07

Drinking water 4.1E-07

Dermal bathing 7.5E-08

Combined DW/SH/DM 1.7E-06

90 Shower 4.6E-05

Drinking water 1.7E-05

Dermal bathing 3.1E-06

Combined DW/SH/DM 7.2E-05

95 Shower 2.3E-04

Drinking water 8.9E-05

Dermal bathing 1.4E-05

Combined DW/SH/DM 3.6E-04

99 Shower 3.0E-03

Drinking water 9.5E-04

Dermal bathing 1.6E-04

Combined DW/SH/DM 4.2E-03

Noncancer Child

50 Drinking water 2.9E-13

Dermal bathing 6.8E-14

Combined DW/DM 3.6E-13

75 Drinking water 9.0E-07

Dermal bathing 1.8E-07

Combined DW/DM 1.1E-06

90 Drinking water 3.7E-05

Dermal bathing 7.8E-06

Combined DW/DM 4.6E-05

95 Drinking water 1.8E-04

Dermal bathing 3.8E-05

Combined DW/DM 2.3E-04

99 Drinking water 1.9E-03

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Inhalation 6.9E-11

75 Inhalation 2.2E-10

90 Inhalation 5.9E-10

95 Inhalation 9.6E-10

99 Inhalation 2.6E-09

Cancer Child

50 Inhalation 2.9E-11

75 Inhalation 1.0E-10

90 Inhalation 2.8E-10

95 Inhalation 4.6E-10

99 Inhalation 1.2E-09

Composite Liner

Cancer Adult

50 Inhalation 7.3E-11

75 Inhalation 2.4E-10

90 Inhalation 6.1E-10

95 Inhalation 1.0E-09

99 Inhalation 2.6E-09

Cancer Child

50 Inhalation 3.1E-11

75 Inhalation 1.1E-10

90 Inhalation 2.8E-10

95 Inhalation 4.8E-10

99 Inhalation 1.3E-09

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Shower 2.1E-08

Drinking water 8.0E-09

Dermal bathing 1.4E-09

Combined DW/SH/DM 3.5E-08

75 Shower 2.4E-07

Drinking water 8.6E-08

Dermal bathing 1.5E-08

Combined DW/SH/DM 3.8E-07

90 Shower 1.4E-06

Drinking water 4.5E-07

Dermal bathing 7.4E-08

Combined DW/SH/DM 2.0E-06

95 Shower 3.3E-06

Drinking water 1.0E-06

Dermal bathing 1.7E-07

Combined DW/SH/DM 4.7E-06

99 Shower 1.6E-05

Drinking water 4.3E-06

Dermal bathing 7.0E-07

Combined DW/SH/DM 2.0E-05

Cancer Child

50 Drinking water 7.5E-09

Dermal bathing 1.6E-09

Combined DW/DM 9.5E-09

75 Drinking water 7.5E-08

Dermal bathing 1.6E-08

Combined DW/DM 9.4E-08

90 Drinking water 3.8E-07

Dermal bathing 7.6E-08

Combined DW/DM 4.6E-07

95 Drinking water 9.3E-07

Dermal bathing 1.9E-07

Combined DW/DM 1.1E-06

99 Drinking water 4.2E-06

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Cancer Adult

50 Shower 8.9E-18

Drinking water 4.4E-18

Dermal bathing 6.6E-19

Combined DW/SH/DM 1.6E-17

75 Shower 3.7E-11

Drinking water 1.5E-11

Dermal bathing 2.5E-12

Combined DW/SH/DM 5.9E-11

90 Shower 1.8E-09

Drinking water 6.5E-10

Dermal bathing 1.1E-10

Combined DW/SH/DM 2.8E-09

95 Shower 1.1E-08

Drinking water 3.8E-09

Dermal bathing 6.1E-10

Combined DW/SH/DM 1.5E-08

99 Shower 1.5E-07

Drinking water 5.1E-08

Dermal bathing 7.6E-09

Combined DW/SH/DM 2.0E-07

Cancer Child

50 Drinking water 3.9E-18

Dermal bathing 7.2E-19

Combined DW/DM 4.5E-18

75 Drinking water 1.3E-11

Dermal bathing 2.8E-12

Combined DW/DM 1.6E-11

90 Drinking water 5.8E-10

Dermal bathing 1.2E-10

Combined DW/DM 7.2E-10

95 Drinking water 2.9E-09

Dermal bathing 6.0E-10

Combined DW/DM 3.5E-09

99 Drinking water 3.0E-08

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Inhalation 1.9E-11

75 Inhalation 6.3E-11

90 Inhalation 1.7E-10

95 Inhalation 2.7E-10

99 Inhalation 7.2E-10

Cancer Child

50 Inhalation 8.3E-12

75 Inhalation 3.0E-11

90 Inhalation 7.8E-11

95 Inhalation 1.3E-10

99 Inhalation 3.3E-10

Composite Liner

Cancer Adult

50 Inhalation 2.1E-11

75 Inhalation 6.6E-11

90 Inhalation 1.7E-10

95 Inhalation 2.9E-10

99 Inhalation 7.2E-10

Cancer Child

50 Inhalation 8.9E-12

75 Inhalation 3.1E-11

90 Inhalation 8.0E-11

95 Inhalation 1.3E-10

99 Inhalation 3.6E-10

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Shower 6.0E-09

Drinking water 2.2E-09

Dermal bathing 3.9E-10

Combined DW/SH/DM 9.7E-09

75 Shower 6.7E-08

Drinking water 2.3E-08

Dermal bathing 4.2E-09

Combined DW/SH/DM 1.1E-07

90 Shower 3.9E-07

Drinking water 1.2E-07

Dermal bathing 2.0E-08

Combined DW/SH/DM 5.5E-07

95 Shower 9.4E-07

Drinking water 2.8E-07

Dermal bathing 4.8E-08

Combined DW/SH/DM 1.3E-06

99 Shower 4.4E-06

Drinking water 1.2E-06

Dermal bathing 1.9E-07

Combined DW/SH/DM 5.7E-06

Cancer Child

50 Drinking water 2.0E-09

Dermal bathing 4.3E-10

Combined DW/DM 2.6E-09

75 Drinking water 2.1E-08

Dermal bathing 4.3E-09

Combined DW/DM 2.6E-08

90 Drinking water 1.1E-07

Dermal bathing 2.1E-08

Combined DW/DM 1.3E-07

95 Drinking water 2.5E-07

Dermal bathing 5.1E-08

Combined DW/DM 3.0E-07

99 Drinking water 1.1E-06

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Cancer Adult

50 Shower 2.5E-18

Drinking water 1.2E-18

Dermal bathing 1.8E-19

Combined DW/SH/DM 4.5E-18

75 Shower 1.0E-11

Drinking water 4.2E-12

Dermal bathing 6.7E-13

Combined DW/SH/DM 1.7E-11

90 Shower 5.2E-10

Drinking water 1.8E-10

Dermal bathing 2.9E-11

Combined DW/SH/DM 7.7E-10

95 Shower 3.0E-09

Drinking water 1.0E-09

Dermal bathing 1.7E-10

Combined DW/SH/DM 4.3E-09

99 Shower 4.3E-08

Drinking water 1.4E-08

Dermal bathing 2.1E-09

Combined DW/SH/DM 5.7E-08

Cancer Child

50 Drinking water 1.1E-18

Dermal bathing 2.0E-19

Combined DW/DM 1.2E-18

75 Drinking water 3.4E-12

Dermal bathing 7.5E-13

Combined DW/DM 4.3E-12

90 Drinking water 1.6E-10

Dermal bathing 3.3E-11

Combined DW/DM 2.0E-10

95 Drinking water 8.0E-10

Dermal bathing 1.6E-10

Combined DW/DM 9.4E-10

99 Drinking water 8.1E-09

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 

Draft Appendix A Theoretical Risk Distributions

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Drinking water 8.2E-07

Dermal bathing 2.1E-08

75 Drinking water 7.6E-06

Dermal bathing 1.9E-07

90 Drinking water 3.8E-05

Dermal bathing 9.7E-07

95 Drinking water 9.3E-05

Dermal bathing 2.2E-06

99 Drinking water 4.3E-04

Dermal bathing 9.7E-06

Noncancer Child

50 Drinking water 1.7E-06

Dermal bathing 5.4E-08

75 Drinking water 1.7E-05

Dermal bathing 4.9E-07

90 Drinking water 8.4E-05

Dermal bathing 2.4E-06

95 Drinking water 2.1E-04

Dermal bathing 5.8E-06

99 Drinking water 8.9E-04

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Drinking water 2.0E-13

Dermal bathing 5.1E-15

75 Drinking water 1.1E-09

Dermal bathing 2.7E-11

90 Drinking water 3.9E-08

Dermal bathing 1.0E-09

95 Drinking water 1.8E-07

Dermal bathing 4.7E-09

99 Drinking water 2.6E-06

Dermal bathing 5.0E-08

Noncancer Child

50 Drinking water 4.1E-13

Dermal bathing 1.2E-14

75 Drinking water 2.3E-09

Dermal bathing 6.8E-11

90 Drinking water 8.4E-08

Dermal bathing 2.6E-09

95 Drinking water 3.7E-07

Dermal bathing 1.1E-08

99 Drinking water 4.2E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 6.5E-07

75 Inhalation 2.0E-06

90 Inhalation 4.5E-06

95 Inhalation 7.0E-06

99 Inhalation 1.7E-05

Noncancer Child

50 Inhalation 6.9E-07

75 Inhalation 2.1E-06

90 Inhalation 4.8E-06

95 Inhalation 7.6E-06

99 Inhalation 1.8E-05

Composite Liner

Noncancer Adult

50 Inhalation 6.5E-07

75 Inhalation 2.0E-06

90 Inhalation 4.4E-06

95 Inhalation 6.9E-06

99 Inhalation 1.6E-05

Noncancer Child

50 Inhalation 7.0E-07

75 Inhalation 2.1E-06

90 Inhalation 4.8E-06

95 Inhalation 7.5E-06

99 Inhalation 1.7E-05

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 3.2E-04

Drinking water 3.5E-05

Dermal bathing 1.5E-05

75 Shower 3.4E-03

Drinking water 3.3E-04

Dermal bathing 1.4E-04

90 Shower 1.7E-02

Drinking water 1.6E-03

Dermal bathing 6.6E-04

95 Shower 4.1E-02

Drinking water 3.7E-03

Dermal bathing 1.4E-03

99 Shower 1.7E-01

Drinking water 1.5E-02

Dermal bathing 6.2E-03

Noncancer Child

50 Drinking water 7.2E-05

Dermal bathing 3.9E-05

75 Drinking water 7.0E-04

Dermal bathing 3.5E-04

90 Drinking water 3.3E-03

Dermal bathing 1.6E-03

95 Drinking water 7.8E-03

Dermal bathing 3.7E-03

99 Drinking water 3.5E-02

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 8.9E-15

Drinking water 8.0E-16

Dermal bathing 3.7E-16

75 Shower 5.6E-07

Drinking water 6.1E-08

Dermal bathing 2.4E-08

90 Shower 3.8E-05

Drinking water 3.4E-06

Dermal bathing 1.6E-06

95 Shower 2.0E-04

Drinking water 2.0E-05

Dermal bathing 7.8E-06

99 Shower 2.5E-03

Drinking water 2.2E-04

Dermal bathing 8.9E-05

Noncancer Child

50 Drinking water 1.8E-15

Dermal bathing 9.4E-16

75 Drinking water 1.2E-07

Dermal bathing 6.6E-08

90 Drinking water 7.3E-06

Dermal bathing 3.9E-06

95 Drinking water 3.9E-05

Dermal bathing 2.1E-05

99 Drinking water 4.5E-04

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 2.0E-10

75 Inhalation 6.2E-10

90 Inhalation 1.6E-09

95 Inhalation 2.8E-09

99 Inhalation 7.5E-09

Noncancer Child

50 Inhalation 2.1E-10

75 Inhalation 6.5E-10

90 Inhalation 1.6E-09

95 Inhalation 2.9E-09

99 Inhalation 8.3E-09

Composite Liner

Noncancer Adult

50 Inhalation 1.8E-10

75 Inhalation 5.7E-10

90 Inhalation 1.4E-09

95 Inhalation 2.5E-09

99 Inhalation 6.6E-09

Noncancer Child

50 Inhalation 1.9E-10

75 Inhalation 5.9E-10

90 Inhalation 1.5E-09

95 Inhalation 2.6E-09

99 Inhalation 7.5E-09

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 1.2E-08

Drinking water 4.3E-06

Dermal bathing 4.8E-07

Combined DW/SH/DM 4.9E-06

75 Shower 1.4E-07

Drinking water 5.3E-05

Dermal bathing 5.8E-06

Combined DW/SH/DM 6.0E-05

90 Shower 8.2E-07

Drinking water 2.9E-04

Dermal bathing 3.2E-05

Combined DW/SH/DM 3.2E-04

95 Shower 2.1E-06

Drinking water 7.9E-04

Dermal bathing 8.3E-05

Combined DW/SH/DM 8.7E-04

99 Shower 9.5E-06

Drinking water 3.7E-03

Dermal bathing 3.8E-04

Combined DW/SH/DM 4.1E-03

Noncancer Child

50 Drinking water 8.6E-06

Dermal bathing 1.2E-06

Combined DW/DM 1.0E-05

75 Drinking water 1.1E-04

Dermal bathing 1.4E-05

Combined DW/DM 1.2E-04

90 Drinking water 6.1E-04

Dermal bathing 8.2E-05

Combined DW/DM 7.1E-04

95 Drinking water 1.7E-03

Dermal bathing 2.1E-04

Combined DW/DM 1.9E-03

99 Drinking water 8.9E-03

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 4.9E-18

Drinking water 1.8E-15

Dermal bathing 1.8E-16

Combined DW/SH/DM 2.0E-15

75 Shower 1.6E-11

Drinking water 5.8E-09

Dermal bathing 6.4E-10

Combined DW/SH/DM 6.6E-09

90 Shower 8.3E-10

Drinking water 2.9E-07

Dermal bathing 3.2E-08

Combined DW/SH/DM 3.3E-07

95 Shower 4.0E-09

Drinking water 1.5E-06

Dermal bathing 1.6E-07

Combined DW/SH/DM 1.7E-06

99 Shower 5.8E-08

Drinking water 2.0E-05

Dermal bathing 2.0E-06

Combined DW/SH/DM 2.2E-05

Noncancer Child

50 Drinking water 3.3E-15

Dermal bathing 5.0E-16

Combined DW/DM 3.8E-15

75 Drinking water 1.2E-08

Dermal bathing 1.6E-09

Combined DW/DM 1.4E-08

90 Drinking water 6.0E-07

Dermal bathing 8.1E-08

Combined DW/DM 7.2E-07

95 Drinking water 3.0E-06

Dermal bathing 4.2E-07

Combined DW/DM 3.4E-06

99 Drinking water 3.9E-05

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 

Draft Appendix A Theoretical Risk Distributions

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Drinking water 1.3E-07

Dermal bathing 2.7E-09

75 Drinking water 1.1E-06

Dermal bathing 2.2E-08

90 Drinking water 5.1E-06

Dermal bathing 9.7E-08

95 Drinking water 1.1E-05

Dermal bathing 2.1E-07

99 Drinking water 4.7E-05

Dermal bathing 8.5E-07

Noncancer Child

50 Drinking water 2.7E-07

Dermal bathing 7.0E-09

75 Drinking water 2.4E-06

Dermal bathing 5.4E-08

90 Drinking water 1.0E-05

Dermal bathing 2.4E-07

95 Drinking water 2.4E-05

Dermal bathing 5.3E-07

99 Drinking water 1.1E-04

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Drinking water 7.8E-15

Dermal bathing 1.7E-16

75 Drinking water 2.0E-10

Dermal bathing 4.0E-12

90 Drinking water 6.9E-09

Dermal bathing 1.4E-10

95 Drinking water 3.4E-08

Dermal bathing 6.8E-10

99 Drinking water 4.3E-07

Dermal bathing 7.8E-09

Noncancer Child

50 Drinking water 1.8E-14

Dermal bathing 4.2E-16

75 Drinking water 4.2E-10

Dermal bathing 9.7E-12

90 Drinking water 1.5E-08

Dermal bathing 3.4E-10

95 Drinking water 6.5E-08

Dermal bathing 1.7E-09

99 Drinking water 8.1E-07

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 7.2E-08

75 Inhalation 2.2E-07

90 Inhalation 5.1E-07

95 Inhalation 8.3E-07

99 Inhalation 2.1E-06

Noncancer Child

50 Inhalation 7.7E-08

75 Inhalation 2.3E-07

90 Inhalation 5.5E-07

95 Inhalation 8.7E-07

99 Inhalation 2.2E-06

Composite Liner

Noncancer Adult

50 Inhalation 6.7E-08

75 Inhalation 2.1E-07

90 Inhalation 4.8E-07

95 Inhalation 7.7E-07

99 Inhalation 1.8E-06

Noncancer Child

50 Inhalation 7.2E-08

75 Inhalation 2.2E-07

90 Inhalation 5.1E-07

95 Inhalation 8.2E-07

99 Inhalation 1.9E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 2.4E-05

Drinking water 3.7E-06

Dermal bathing 3.1E-06

75 Shower 2.6E-04

Drinking water 3.8E-05

Dermal bathing 3.1E-05

90 Shower 1.4E-03

Drinking water 2.0E-04

Dermal bathing 1.5E-04

95 Shower 3.5E-03

Drinking water 4.5E-04

Dermal bathing 3.5E-04

99 Shower 1.4E-02

Drinking water 1.8E-03

Dermal bathing 1.4E-03

Noncancer Child

50 Drinking water 7.7E-06

Dermal bathing 7.8E-06

75 Drinking water 7.7E-05

Dermal bathing 7.9E-05

90 Drinking water 4.0E-04

Dermal bathing 3.7E-04

95 Drinking water 9.7E-04

Dermal bathing 8.7E-04

99 Drinking water 4.2E-03

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 3.1E-18

Drinking water 5.2E-19

Dermal bathing 3.8E-19

75 Shower 7.0E-09

Drinking water 1.1E-09

Dermal bathing 9.1E-10

90 Shower 6.9E-07

Drinking water 9.6E-08

Dermal bathing 8.4E-08

95 Shower 4.8E-06

Drinking water 6.8E-07

Dermal bathing 5.4E-07

99 Shower 8.1E-05

Drinking water 1.0E-05

Dermal bathing 7.4E-06

Noncancer Child

50 Drinking water 9.6E-19

Dermal bathing 1.0E-18

75 Drinking water 2.4E-09

Dermal bathing 2.3E-09

90 Drinking water 2.0E-07

Dermal bathing 2.1E-07

95 Drinking water 1.3E-06

Dermal bathing 1.4E-06

99 Drinking water 2.1E-05

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 

Draft Appendix A Theoretical Risk Distributions

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Drinking water 2.9E-10

Dermal bathing 5.3E-12

75 Drinking water 8.8E-08

Dermal bathing 1.5E-09

90 Drinking water 8.2E-07

Dermal bathing 1.4E-08

95 Drinking water 2.4E-06

Dermal bathing 4.0E-08

99 Drinking water 1.3E-05

Dermal bathing 2.1E-07

Noncancer Child

50 Drinking water 6.7E-10

Dermal bathing 1.4E-11

75 Drinking water 1.9E-07

Dermal bathing 4.1E-09

90 Drinking water 1.9E-06

Dermal bathing 3.8E-08

95 Drinking water 5.2E-06

Dermal bathing 1.1E-07

99 Drinking water 2.9E-05

Dermal bathing 5.5E-07

Composite Liner

Noncancer Adult

90 Drinking water 1.2E-16

Dermal bathing 2.2E-18

95 Drinking water 6.3E-13

Dermal bathing 1.2E-14

99 Drinking water 1.7E-09

Dermal bathing 3.6E-11

Noncancer Child

90 Drinking water 2.0E-16

Dermal bathing 3.6E-18

95 Drinking water 9.9E-13

Dermal bathing 2.0E-14

99 Drinking water 3.2E-09

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 2.5E-08

75 Inhalation 7.6E-08

90 Inhalation 1.8E-07

95 Inhalation 2.8E-07

99 Inhalation 6.6E-07

Noncancer Child

50 Inhalation 2.7E-08

75 Inhalation 8.1E-08

90 Inhalation 1.9E-07

95 Inhalation 3.0E-07

99 Inhalation 7.1E-07

Composite Liner

Noncancer Adult

50 Inhalation 2.4E-08

75 Inhalation 7.4E-08

90 Inhalation 1.7E-07

95 Inhalation 2.7E-07

99 Inhalation 6.3E-07

Noncancer Child

50 Inhalation 2.6E-08

75 Inhalation 7.9E-08

90 Inhalation 1.8E-07

95 Inhalation 2.9E-07

99 Inhalation 6.9E-07

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 6.8E-06

Drinking water 4.3E-06

Dermal bathing 3.0E-06

75 Shower 7.8E-05

Drinking water 4.3E-05

Dermal bathing 3.0E-05

90 Shower 4.3E-04

Drinking water 2.2E-04

Dermal bathing 1.5E-04

95 Shower 1.0E-03

Drinking water 5.1E-04

Dermal bathing 3.3E-04

99 Shower 4.2E-03

Drinking water 2.0E-03

Dermal bathing 1.3E-03

Noncancer Child

50 Drinking water 8.7E-06

Dermal bathing 7.6E-06

75 Drinking water 9.0E-05

Dermal bathing 7.4E-05

90 Drinking water 4.7E-04

Dermal bathing 3.7E-04

95 Drinking water 1.0E-03

Dermal bathing 8.1E-04

99 Drinking water 4.7E-03

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 1.2E-17

Drinking water 9.0E-18

Dermal bathing 5.1E-18

75 Shower 4.3E-09

Drinking water 2.4E-09

Dermal bathing 1.7E-09

90 Shower 3.6E-07

Drinking water 1.9E-07

Dermal bathing 1.4E-07

95 Shower 2.3E-06

Drinking water 1.3E-06

Dermal bathing 8.9E-07

99 Shower 3.5E-05

Drinking water 1.7E-05

Dermal bathing 1.2E-05

Noncancer Child

50 Drinking water 1.8E-17

Dermal bathing 1.5E-17

75 Drinking water 5.1E-09

Dermal bathing 4.2E-09

90 Drinking water 3.8E-07

Dermal bathing 3.6E-07

95 Drinking water 2.6E-06

Dermal bathing 2.3E-06

99 Drinking water 3.3E-05

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 

Draft Appendix A Theoretical Risk Distributions

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Drinking water 2.0E-07

Dermal bathing 4.2E-09

75 Drinking water 1.9E-06

Dermal bathing 3.9E-08

90 Drinking water 8.7E-06

Dermal bathing 1.9E-07

95 Drinking water 2.1E-05

Dermal bathing 4.3E-07

99 Drinking water 9.1E-05

Dermal bathing 1.7E-06

Noncancer Child

50 Drinking water 4.2E-07

Dermal bathing 1.1E-08

75 Drinking water 4.1E-06

Dermal bathing 1.1E-07

90 Drinking water 2.0E-05

Dermal bathing 5.2E-07

95 Drinking water 4.5E-05

Dermal bathing 1.2E-06

99 Drinking water 2.0E-04

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Drinking water 8.1E-15

Dermal bathing 1.9E-16

75 Drinking water 5.1E-11

Dermal bathing 1.2E-12

90 Drinking water 2.4E-09

Dermal bathing 4.9E-11

95 Drinking water 1.4E-08

Dermal bathing 2.6E-10

99 Drinking water 1.9E-07

Dermal bathing 4.1E-09

Noncancer Child

50 Drinking water 1.7E-14

Dermal bathing 4.4E-16

75 Drinking water 1.2E-10

Dermal bathing 3.0E-12

90 Drinking water 4.5E-09

Dermal bathing 1.2E-10

95 Drinking water 2.4E-08

Dermal bathing 6.6E-10

99 Drinking water 3.7E-07

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 3.1E-10

75 Inhalation 9.4E-10

90 Inhalation 2.3E-09

95 Inhalation 3.9E-09

99 Inhalation 9.6E-09

Noncancer Child

50 Inhalation 3.2E-10

75 Inhalation 1.0E-09

90 Inhalation 2.4E-09

95 Inhalation 4.1E-09

99 Inhalation 1.0E-08

Composite Liner

Noncancer Adult

50 Inhalation 2.7E-10

75 Inhalation 8.4E-10

90 Inhalation 2.0E-09

95 Inhalation 3.4E-09

99 Inhalation 8.4E-09

Noncancer Child

50 Inhalation 2.9E-10

75 Inhalation 9.0E-10

90 Inhalation 2.1E-09

95 Inhalation 3.5E-09

99 Inhalation 9.1E-09

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 3.6E-08

Drinking water 1.9E-06

Dermal bathing 5.7E-09

75 Shower 3.7E-07

Drinking water 1.9E-05

Dermal bathing 5.7E-08

90 Shower 1.9E-06

Drinking water 9.4E-05

Dermal bathing 2.9E-07

95 Shower 4.6E-06

Drinking water 2.2E-04

Dermal bathing 6.7E-07

99 Shower 2.1E-05

Drinking water 1.1E-03

Dermal bathing 3.0E-06

Noncancer Child

50 Drinking water 3.7E-06

Dermal bathing 1.4E-08

75 Drinking water 3.9E-05

Dermal bathing 1.5E-07

90 Drinking water 2.1E-04

Dermal bathing 7.5E-07

95 Drinking water 4.9E-04

Dermal bathing 1.8E-06

99 Drinking water 2.4E-03

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 7.8E-19

Drinking water 4.3E-17

Dermal bathing 1.2E-19

75 Shower 8.6E-12

Drinking water 4.1E-10

Dermal bathing 1.3E-12

90 Shower 8.3E-10

Drinking water 4.1E-08

Dermal bathing 1.2E-10

95 Shower 5.9E-09

Drinking water 3.0E-07

Dermal bathing 9.5E-10

99 Shower 9.9E-08

Drinking water 4.4E-06

Dermal bathing 1.3E-08

Noncancer Child

50 Drinking water 8.8E-17

Dermal bathing 3.5E-19

75 Drinking water 8.6E-10

Dermal bathing 3.6E-12

90 Drinking water 8.7E-08

Dermal bathing 3.4E-10

95 Drinking water 6.4E-07

Dermal bathing 2.5E-09

99 Drinking water 8.4E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 1.0E-08

75 Inhalation 3.1E-08

90 Inhalation 7.1E-08

95 Inhalation 1.1E-07

99 Inhalation 2.5E-07

Noncancer Child

50 Inhalation 1.1E-08

75 Inhalation 3.4E-08

90 Inhalation 7.6E-08

95 Inhalation 1.2E-07

99 Inhalation 2.7E-07

Composite Liner

Noncancer Adult

50 Inhalation 2.2E-09

75 Inhalation 6.8E-09

90 Inhalation 1.6E-08

95 Inhalation 2.7E-08

99 Inhalation 6.9E-08

Noncancer Child

50 Inhalation 2.3E-09

75 Inhalation 7.0E-09

90 Inhalation 1.7E-08

95 Inhalation 2.8E-08

99 Inhalation 6.8E-08

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 1.3E-07

Drinking water 5.7E-07

Dermal bathing 6.3E-09

Combined DW/SH/DM 7.5E-07

75 Shower 1.1E-06

Drinking water 5.3E-06

Dermal bathing 5.4E-08

Combined DW/SH/DM 6.6E-06

90 Shower 5.5E-06

Drinking water 2.4E-05

Dermal bathing 2.6E-07

Combined DW/SH/DM 3.0E-05

95 Shower 1.2E-05

Drinking water 5.4E-05

Dermal bathing 5.4E-07

Combined DW/SH/DM 6.8E-05

99 Shower 4.5E-05

Drinking water 2.0E-04

Dermal bathing 2.1E-06

Combined DW/SH/DM 2.5E-04

Noncancer Child

50 Drinking water 1.2E-06

Dermal bathing 1.7E-08

Combined DW/DM 1.3E-06

75 Drinking water 1.1E-05

Dermal bathing 1.4E-07

Combined DW/DM 1.1E-05

90 Drinking water 5.3E-05

Dermal bathing 6.5E-07

Combined DW/DM 5.4E-05

95 Drinking water 1.2E-04

Dermal bathing 1.5E-06

Combined DW/DM 1.2E-04

99 Drinking water 4.5E-04

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 1.6E-17

Drinking water 6.0E-17

Dermal bathing 7.7E-19

Combined DW/SH/DM 8.1E-17

75 Shower 6.0E-12

Drinking water 3.0E-11

Dermal bathing 3.0E-13

Combined DW/SH/DM 3.8E-11

90 Shower 5.1E-10

Drinking water 2.5E-09

Dermal bathing 2.5E-11

Combined DW/SH/DM 3.2E-09

95 Shower 3.6E-09

Drinking water 1.6E-08

Dermal bathing 1.7E-10

Combined DW/SH/DM 2.0E-08

99 Shower 7.1E-08

Drinking water 2.7E-07

Dermal bathing 3.3E-09

Combined DW/SH/DM 3.4E-07

Noncancer Child

50 Drinking water 1.5E-16

Dermal bathing 1.8E-18

Combined DW/DM 1.5E-16

75 Drinking water 5.9E-11

Dermal bathing 8.3E-13

Combined DW/DM 6.1E-11

90 Drinking water 5.1E-09

Dermal bathing 6.7E-11

Combined DW/DM 5.1E-09

95 Drinking water 3.4E-08

Dermal bathing 4.2E-10

Combined DW/DM 3.4E-08

99 Drinking water 6.1E-07

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 2.4E-09

75 Inhalation 7.5E-09

90 Inhalation 1.8E-08

95 Inhalation 3.0E-08

99 Inhalation 7.6E-08

Noncancer Child

50 Inhalation 2.5E-09

75 Inhalation 7.7E-09

90 Inhalation 1.9E-08

95 Inhalation 3.1E-08

99 Inhalation 7.7E-08

Composite Liner

Noncancer Adult

50 Inhalation 2.2E-09

75 Inhalation 6.9E-09

90 Inhalation 1.7E-08

95 Inhalation 2.8E-08

99 Inhalation 7.2E-08

Noncancer Child

50 Inhalation 2.3E-09

75 Inhalation 7.2E-09

90 Inhalation 1.7E-08

95 Inhalation 2.9E-08

99 Inhalation 7.3E-08

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 1.7E-07

Drinking water 1.6E-06

Dermal bathing 5.8E-08

75 Shower 1.6E-06

Drinking water 1.5E-05

Dermal bathing 5.3E-07

90 Shower 8.1E-06

Drinking water 7.1E-05

Dermal bathing 2.6E-06

95 Shower 1.8E-05

Drinking water 1.7E-04

Dermal bathing 5.8E-06

99 Shower 7.7E-05

Drinking water 7.8E-04

Dermal bathing 2.4E-05

Noncancer Child

50 Drinking water 3.3E-06

Dermal bathing 1.5E-07

75 Drinking water 3.3E-05

Dermal bathing 1.4E-06

90 Drinking water 1.6E-04

Dermal bathing 6.9E-06

95 Drinking water 3.8E-04

Dermal bathing 1.6E-05

99 Drinking water 1.6E-03

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 4.3E-17

Drinking water 4.3E-16

Dermal bathing 1.5E-17

75 Shower 1.4E-11

Drinking water 1.3E-10

Dermal bathing 4.8E-12

90 Shower 8.8E-10

Drinking water 8.5E-09

Dermal bathing 3.0E-10

95 Shower 6.4E-09

Drinking water 6.1E-08

Dermal bathing 2.2E-09

99 Shower 1.1E-07

Drinking water 8.6E-07

Dermal bathing 3.2E-08

Noncancer Child

50 Drinking water 9.5E-16

Dermal bathing 4.0E-17

75 Drinking water 2.9E-10

Dermal bathing 1.3E-11

90 Drinking water 1.8E-08

Dermal bathing 8.0E-10

95 Drinking water 1.2E-07

Dermal bathing 5.5E-09

99 Drinking water 1.6E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Inhalation 4.5E-12

75 Inhalation 1.5E-11

90 Inhalation 4.1E-11

95 Inhalation 6.9E-11

99 Inhalation 1.8E-10

Cancer Child

50 Inhalation 1.8E-12

75 Inhalation 6.7E-12

90 Inhalation 1.8E-11

95 Inhalation 3.1E-11

99 Inhalation 8.5E-11

Noncancer Adult

50 Inhalation 1.5E-07

75 Inhalation 4.3E-07

90 Inhalation 9.9E-07

95 Inhalation 1.6E-06

99 Inhalation 3.7E-06

Noncancer Child

50 Inhalation 1.5E-07

75 Inhalation 4.5E-07

90 Inhalation 1.0E-06

95 Inhalation 1.6E-06

99 Inhalation 3.7E-06

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Cancer Adult

50 Inhalation 4.6E-12

75 Inhalation 1.5E-11

90 Inhalation 4.1E-11

95 Inhalation 7.0E-11

99 Inhalation 1.8E-10

Cancer Child

50 Inhalation 1.9E-12

75 Inhalation 6.8E-12

90 Inhalation 1.8E-11

95 Inhalation 3.1E-11

99 Inhalation 8.5E-11

Noncancer Adult

50 Inhalation 1.5E-07

75 Inhalation 4.4E-07

90 Inhalation 9.9E-07

95 Inhalation 1.6E-06

99 Inhalation 3.6E-06

Noncancer Child

50 Inhalation 1.6E-07

75 Inhalation 4.6E-07

90 Inhalation 1.0E-06

95 Inhalation 1.7E-06

99 Inhalation 3.7E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Shower 8.4E-10

Drinking water 7.6E-10

Dermal bathing 3.4E-11

Combined DW/SH/DM 1.9E-09

75 Shower 8.3E-09

Drinking water 7.5E-09

Dermal bathing 3.1E-10

Combined DW/SH/DM 1.8E-08

90 Shower 4.4E-08

Drinking water 3.7E-08

Dermal bathing 1.5E-09

Combined DW/SH/DM 8.8E-08

95 Shower 1.0E-07

Drinking water 8.1E-08

Dermal bathing 3.2E-09

Combined DW/SH/DM 1.9E-07

99 Shower 4.3E-07

Drinking water 3.4E-07

Dermal bathing 1.4E-08

Combined DW/SH/DM 7.5E-07

Cancer Child

50 Drinking water 7.3E-10

Dermal bathing 3.8E-11

Combined DW/DM 7.8E-10

75 Drinking water 6.5E-09

Dermal bathing 3.3E-10

Combined DW/DM 6.9E-09

90 Drinking water 3.0E-08

Dermal bathing 1.5E-09

Combined DW/DM 3.2E-08

95 Drinking water 6.7E-08

Dermal bathing 3.4E-09

Combined DW/DM 7.0E-08

99 Drinking water 2.7E-07

Dermal bathing 1.4E-08

Combined DW/DM 2.9E-07

Noncancer Adult

50 Shower 2.9E-05

Drinking water 1.2E-05

Dermal bathing 5.3E-07

75 Shower 2.6E-04

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 

Draft Appendix A Theoretical Risk Distributions

90 Shower 1.2E-03

Drinking water 4.3E-04

Dermal bathing 1.8E-05

95 Shower 2.7E-03

Drinking water 9.0E-04

Dermal bathing 3.6E-05

99 Shower 1.0E-02

Drinking water 3.3E-03

Dermal bathing 1.3E-04

Noncancer Child

50 Drinking water 2.5E-05

Dermal bathing 1.4E-06

75 Drinking water 2.2E-04

Dermal bathing 1.1E-05

90 Drinking water 9.2E-04

Dermal bathing 4.5E-05

95 Drinking water 1.9E-03

Dermal bathing 9.3E-05

99 Drinking water 7.1E-03

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Cancer Adult

50 Shower 2.9E-24

Drinking water 1.9E-24

Dermal bathing 9.0E-26

Combined DW/SH/DM 5.8E-24

75 Shower 2.4E-14

Drinking water 2.2E-14

Dermal bathing 9.5E-16

Combined DW/SH/DM 5.5E-14

90 Shower 3.4E-12

Drinking water 2.8E-12

Dermal bathing 1.2E-13

Combined DW/SH/DM 7.2E-12

95 Shower 2.4E-11

Drinking water 2.2E-11

Dermal bathing 8.6E-13

Combined DW/SH/DM 4.9E-11

99 Shower 5.3E-10

Drinking water 3.9E-10

Dermal bathing 1.7E-11

Combined DW/SH/DM 9.7E-10

Cancer Child

50 Drinking water 2.4E-24

Dermal bathing 1.6E-25

Combined DW/DM 2.5E-24

75 Drinking water 2.2E-14

Dermal bathing 1.1E-15

Combined DW/DM 2.3E-14

90 Drinking water 2.5E-12

Dermal bathing 1.3E-13

Combined DW/DM 2.7E-12

95 Drinking water 1.8E-11

Dermal bathing 9.6E-13

Combined DW/DM 1.9E-11

99 Drinking water 2.9E-10

Dermal bathing 1.6E-11

Combined DW/DM 3.0E-10

Noncancer Adult

50 Shower 7.9E-20

Drinking water 3.1E-20

Dermal bathing 1.6E-21

75 Shower 8.6E-10

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 

Draft Appendix A Theoretical Risk Distributions

90 Shower 1.0E-07

Drinking water 3.9E-08

Dermal bathing 1.6E-09

95 Shower 7.5E-07

Drinking water 2.6E-07

Dermal bathing 1.1E-08

99 Shower 1.4E-05

Drinking water 4.0E-06

Dermal bathing 1.8E-07

Noncancer Child

50 Drinking water 7.2E-20

Dermal bathing 4.2E-21

75 Drinking water 7.0E-10

Dermal bathing 3.5E-11

90 Drinking water 8.3E-08

Dermal bathing 4.3E-09

95 Drinking water 5.4E-07

Dermal bathing 2.8E-08

99 Drinking water 9.3E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 1.8E-07

75 Inhalation 5.4E-07

90 Inhalation 1.2E-06

95 Inhalation 1.9E-06

99 Inhalation 4.4E-06

Noncancer Child

50 Inhalation 2.0E-07

75 Inhalation 5.9E-07

90 Inhalation 1.3E-06

95 Inhalation 2.1E-06

99 Inhalation 4.6E-06

Composite Liner

Noncancer Adult

50 Inhalation 1.9E-07

75 Inhalation 5.6E-07

90 Inhalation 1.3E-06

95 Inhalation 1.9E-06

99 Inhalation 4.3E-06

Noncancer Child

50 Inhalation 2.1E-07

75 Inhalation 6.2E-07

90 Inhalation 1.4E-06

95 Inhalation 2.2E-06

99 Inhalation 4.6E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 4.7E-05

Drinking water 8.2E-05

Dermal bathing 1.9E-05

75 Shower 4.8E-04

Drinking water 7.5E-04

Dermal bathing 1.7E-04

90 Shower 2.5E-03

Drinking water 3.7E-03

Dermal bathing 8.0E-04

95 Shower 6.0E-03

Drinking water 8.0E-03

Dermal bathing 1.8E-03

99 Shower 2.5E-02

Drinking water 3.2E-02

Dermal bathing 7.0E-03

Noncancer Child

50 Drinking water 1.8E-04

Dermal bathing 5.1E-05

75 Drinking water 1.6E-03

Dermal bathing 4.3E-04

90 Drinking water 7.7E-03

Dermal bathing 2.1E-03

95 Drinking water 1.8E-02

Dermal bathing 4.7E-03

99 Drinking water 7.9E-02

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 9.5E-15

Drinking water 2.0E-14

Dermal bathing 3.8E-15

75 Shower 1.1E-07

Drinking water 1.9E-07

Dermal bathing 4.2E-08

90 Shower 5.8E-06

Drinking water 8.8E-06

Dermal bathing 2.1E-06

95 Shower 3.1E-05

Drinking water 4.5E-05

Dermal bathing 1.0E-05

99 Shower 4.4E-04

Drinking water 5.3E-04

Dermal bathing 1.2E-04

Noncancer Child

50 Drinking water 3.7E-14

Dermal bathing 1.1E-14

75 Drinking water 3.8E-07

Dermal bathing 1.1E-07

90 Drinking water 1.8E-05

Dermal bathing 5.2E-06

95 Drinking water 9.1E-05

Dermal bathing 2.4E-05

99 Drinking water 1.1E-03

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Inhalation 5.4E-11

75 Inhalation 1.7E-10

90 Inhalation 4.6E-10

95 Inhalation 7.5E-10

99 Inhalation 2.0E-09

Cancer Child

50 Inhalation 2.3E-11

75 Inhalation 8.2E-11

90 Inhalation 2.2E-10

95 Inhalation 3.6E-10

99 Inhalation 9.2E-10

Composite Liner

Cancer Adult

50 Inhalation 5.7E-11

75 Inhalation 1.8E-10

90 Inhalation 4.8E-10

95 Inhalation 7.9E-10

99 Inhalation 2.0E-09

Cancer Child

50 Inhalation 2.5E-11

75 Inhalation 8.6E-11

90 Inhalation 2.2E-10

95 Inhalation 3.7E-10

99 Inhalation 9.8E-10

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Shower 1.3E-08

Drinking water 6.5E-08

Dermal bathing 1.6E-08

Combined DW/SH/DM 1.1E-07

75 Shower 1.5E-07

Drinking water 7.1E-07

Dermal bathing 1.5E-07

Combined DW/SH/DM 1.1E-06

90 Shower 8.8E-07

Drinking water 3.8E-06

Dermal bathing 8.4E-07

Combined DW/SH/DM 5.9E-06

95 Shower 2.2E-06

Drinking water 9.0E-06

Dermal bathing 1.9E-06

Combined DW/SH/DM 1.3E-05

99 Shower 1.0E-05

Drinking water 3.5E-05

Dermal bathing 8.0E-06

Combined DW/SH/DM 5.5E-05

Cancer Child

50 Drinking water 5.8E-08

Dermal bathing 1.6E-08

Combined DW/DM 7.9E-08

75 Drinking water 6.0E-07

Dermal bathing 1.6E-07

Combined DW/DM 7.8E-07

90 Drinking water 3.2E-06

Dermal bathing 8.6E-07

Combined DW/DM 4.0E-06

95 Drinking water 7.5E-06

Dermal bathing 2.0E-06

Combined DW/DM 9.5E-06

99 Drinking water 3.3E-05

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Cancer Adult

50 Shower 2.8E-18

Drinking water 1.6E-17

Dermal bathing 3.2E-18

Combined DW/SH/DM 2.3E-17

75 Shower 3.2E-11

Drinking water 1.6E-10

Dermal bathing 3.5E-11

Combined DW/SH/DM 2.5E-10

90 Shower 1.6E-09

Drinking water 8.0E-09

Dermal bathing 1.8E-09

Combined DW/SH/DM 1.2E-08

95 Shower 1.1E-08

Drinking water 5.0E-08

Dermal bathing 1.0E-08

Combined DW/SH/DM 7.6E-08

99 Shower 1.5E-07

Drinking water 6.2E-07

Dermal bathing 1.4E-07

Combined DW/SH/DM 9.5E-07

Cancer Child

50 Drinking water 1.4E-17

Dermal bathing 4.2E-18

Combined DW/DM 1.9E-17

75 Drinking water 1.4E-10

Dermal bathing 4.0E-11

Combined DW/DM 1.9E-10

90 Drinking water 7.0E-09

Dermal bathing 1.9E-09

Combined DW/DM 9.2E-09

95 Drinking water 3.7E-08

Dermal bathing 9.8E-09

Combined DW/DM 4.8E-08

99 Drinking water 4.3E-07

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Inhalation 6.5E-12

75 Inhalation 2.1E-11

90 Inhalation 5.5E-11

95 Inhalation 9.1E-11

99 Inhalation 2.4E-10

Cancer Child

50 Inhalation 2.8E-12

75 Inhalation 9.9E-12

90 Inhalation 2.6E-11

95 Inhalation 4.3E-11

99 Inhalation 1.1E-10

Composite Liner

Cancer Adult

50 Inhalation 6.9E-12

75 Inhalation 2.2E-11

90 Inhalation 5.7E-11

95 Inhalation 9.5E-11

99 Inhalation 2.4E-10

Cancer Child

50 Inhalation 3.0E-12

75 Inhalation 1.0E-11

90 Inhalation 2.7E-11

95 Inhalation 4.4E-11

99 Inhalation 1.2E-10

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Shower 1.6E-09

Drinking water 6.5E-08

Dermal bathing 1.6E-08

Combined DW/SH/DM 8.7E-08

75 Shower 1.8E-08

Drinking water 7.1E-07

Dermal bathing 1.5E-07

Combined DW/SH/DM 9.2E-07

90 Shower 1.1E-07

Drinking water 3.8E-06

Dermal bathing 8.4E-07

Combined DW/SH/DM 5.0E-06

95 Shower 2.6E-07

Drinking water 9.0E-06

Dermal bathing 1.9E-06

Combined DW/SH/DM 1.1E-05

99 Shower 1.2E-06

Drinking water 3.5E-05

Dermal bathing 8.0E-06

Combined DW/SH/DM 4.7E-05

Cancer Child

50 Drinking water 5.8E-08

Dermal bathing 1.6E-08

Combined DW/DM 7.9E-08

75 Drinking water 6.0E-07

Dermal bathing 1.6E-07

Combined DW/DM 7.8E-07

90 Drinking water 3.2E-06

Dermal bathing 8.6E-07

Combined DW/DM 4.0E-06

95 Drinking water 7.5E-06

Dermal bathing 2.0E-06

Combined DW/DM 9.5E-06

99 Drinking water 3.3E-05

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Cancer Adult

50 Shower 3.4E-19

Drinking water 1.6E-17

Dermal bathing 3.2E-18

Combined DW/SH/DM 2.0E-17

75 Shower 3.8E-12

Drinking water 1.6E-10

Dermal bathing 3.5E-11

Combined DW/SH/DM 2.1E-10

90 Shower 2.0E-10

Drinking water 8.0E-09

Dermal bathing 1.8E-09

Combined DW/SH/DM 1.0E-08

95 Shower 1.3E-09

Drinking water 5.0E-08

Dermal bathing 1.0E-08

Combined DW/SH/DM 6.3E-08

99 Shower 1.8E-08

Drinking water 6.2E-07

Dermal bathing 1.4E-07

Combined DW/SH/DM 8.2E-07

Cancer Child

50 Drinking water 1.4E-17

Dermal bathing 4.2E-18

Combined DW/DM 1.9E-17

75 Drinking water 1.4E-10

Dermal bathing 4.0E-11

Combined DW/DM 1.9E-10

90 Drinking water 7.0E-09

Dermal bathing 1.9E-09

Combined DW/DM 9.2E-09

95 Drinking water 3.7E-08

Dermal bathing 9.8E-09

Combined DW/DM 4.8E-08

99 Drinking water 4.3E-07

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 6.7E-09

75 Inhalation 2.0E-08

90 Inhalation 4.6E-08

95 Inhalation 7.2E-08

99 Inhalation 1.6E-07

Noncancer Child

50 Inhalation 7.1E-09

75 Inhalation 2.1E-08

90 Inhalation 4.9E-08

95 Inhalation 7.8E-08

99 Inhalation 1.8E-07

Composite Liner

Noncancer Adult

50 Inhalation 6.6E-09

75 Inhalation 2.0E-08

90 Inhalation 4.5E-08

95 Inhalation 7.0E-08

99 Inhalation 1.6E-07

Noncancer Child

50 Inhalation 7.0E-09

75 Inhalation 2.1E-08

90 Inhalation 4.8E-08

95 Inhalation 7.6E-08

99 Inhalation 1.8E-07

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 2.5E-06

Drinking water 9.8E-06

Dermal bathing 4.0E-06

75 Shower 2.7E-05

Drinking water 8.8E-05

Dermal bathing 3.6E-05

90 Shower 1.3E-04

Drinking water 4.3E-04

Dermal bathing 1.6E-04

95 Shower 3.1E-04

Drinking water 9.3E-04

Dermal bathing 3.5E-04

99 Shower 1.4E-03

Drinking water 3.9E-03

Dermal bathing 1.4E-03

Noncancer Child

50 Drinking water 2.0E-05

Dermal bathing 1.0E-05

75 Drinking water 1.9E-04

Dermal bathing 9.2E-05

90 Drinking water 8.9E-04

Dermal bathing 4.2E-04

95 Drinking water 2.0E-03

Dermal bathing 9.1E-04

99 Drinking water 9.1E-03

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 1.8E-16

Drinking water 5.9E-16

Dermal bathing 2.5E-16

75 Shower 3.6E-09

Drinking water 1.3E-08

Dermal bathing 5.1E-09

90 Shower 2.2E-07

Drinking water 7.4E-07

Dermal bathing 3.2E-07

95 Shower 1.3E-06

Drinking water 4.1E-06

Dermal bathing 1.7E-06

99 Shower 1.6E-05

Drinking water 5.1E-05

Dermal bathing 1.8E-05

Noncancer Child

50 Drinking water 1.4E-15

Dermal bathing 6.9E-16

75 Drinking water 2.6E-08

Dermal bathing 1.3E-08

90 Drinking water 1.6E-06

Dermal bathing 7.8E-07

95 Drinking water 8.4E-06

Dermal bathing 4.0E-06

99 Drinking water 9.2E-05

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Inhalation 1.9E-11

75 Inhalation 6.1E-11

90 Inhalation 1.6E-10

95 Inhalation 2.6E-10

99 Inhalation 6.7E-10

Cancer Child

50 Inhalation 7.9E-12

75 Inhalation 2.8E-11

90 Inhalation 7.4E-11

95 Inhalation 1.2E-10

99 Inhalation 3.2E-10

Noncancer Adult

50 Inhalation 9.1E-08

75 Inhalation 2.7E-07

90 Inhalation 6.2E-07

95 Inhalation 9.7E-07

99 Inhalation 2.2E-06

Noncancer Child

50 Inhalation 1.0E-07

75 Inhalation 3.0E-07

90 Inhalation 6.7E-07

95 Inhalation 1.1E-06

99 Inhalation 2.3E-06

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Cancer Adult

50 Inhalation 2.0E-11

75 Inhalation 6.3E-11

90 Inhalation 1.6E-10

95 Inhalation 2.7E-10

99 Inhalation 6.8E-10

Cancer Child

50 Inhalation 8.5E-12

75 Inhalation 3.0E-11

90 Inhalation 7.6E-11

95 Inhalation 1.3E-10

99 Inhalation 3.3E-10

Noncancer Adult

50 Inhalation 9.8E-08

75 Inhalation 2.9E-07

90 Inhalation 6.5E-07

95 Inhalation 9.9E-07

99 Inhalation 2.2E-06

Noncancer Child

50 Inhalation 1.1E-07

75 Inhalation 3.1E-07

90 Inhalation 7.0E-07

95 Inhalation 1.1E-06

99 Inhalation 2.4E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Cancer Adult

50 Shower 4.9E-09

Drinking water 1.6E-09

Dermal bathing 5.2E-10

Combined DW/SH/DM 7.9E-09

75 Shower 5.6E-08

Drinking water 1.8E-08

Dermal bathing 5.5E-09

Combined DW/SH/DM 8.8E-08

90 Shower 3.2E-07

Drinking water 9.4E-08

Dermal bathing 2.7E-08

Combined DW/SH/DM 4.6E-07

95 Shower 8.0E-07

Drinking water 2.4E-07

Dermal bathing 6.6E-08

Combined DW/SH/DM 1.1E-06

99 Shower 3.6E-06

Drinking water 8.8E-07

Dermal bathing 2.6E-07

Combined DW/SH/DM 4.8E-06

Cancer Child

50 Drinking water 1.5E-09

Dermal bathing 5.6E-10

Combined DW/DM 2.2E-09

75 Drinking water 1.6E-08

Dermal bathing 5.5E-09

Combined DW/DM 2.3E-08

90 Drinking water 8.2E-08

Dermal bathing 2.9E-08

Combined DW/DM 1.1E-07

95 Drinking water 1.9E-07

Dermal bathing 6.9E-08

Combined DW/DM 2.6E-07

99 Drinking water 7.6E-07

Dermal bathing 2.5E-07

Combined DW/DM 1.1E-06

Noncancer Adult

50 Shower 2.5E-05

75 Shower 2.8E-04

90 Shower 1.4E-03

95 Shower 3.2E-03

99 Shower 1.3E-02

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Cancer Adult

50 Shower 1.1E-18

Drinking water 4.2E-19

Dermal bathing 1.2E-19

Combined DW/SH/DM 1.9E-18

75 Shower 8.1E-12

Drinking water 2.9E-12

Dermal bathing 8.4E-13

Combined DW/SH/DM 1.4E-11

90 Shower 4.7E-10

Drinking water 1.6E-10

Dermal bathing 4.6E-11

Combined DW/SH/DM 7.5E-10

95 Shower 2.9E-09

Drinking water 9.8E-10

Dermal bathing 2.6E-10

Combined DW/SH/DM 4.2E-09

99 Shower 4.2E-08

Drinking water 1.3E-08

Dermal bathing 3.3E-09

Combined DW/SH/DM 5.4E-08

Cancer Child

50 Drinking water 3.0E-19

Dermal bathing 1.2E-19

Combined DW/DM 4.3E-19

75 Drinking water 2.5E-12

Dermal bathing 9.4E-13

Combined DW/DM 3.7E-12

90 Drinking water 1.4E-10

Dermal bathing 4.6E-11

Combined DW/DM 1.9E-10

95 Drinking water 7.2E-10

Dermal bathing 2.6E-10

Combined DW/DM 9.9E-10

99 Drinking water 7.8E-09

Dermal bathing 3.2E-09

Combined DW/DM 1.1E-08

Noncancer Adult

50 Shower 5.3E-15

75 Shower 4.2E-08

90 Shower 2.3E-06

95 Shower 1.3E-05

99 Shower 1.7E-04

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Inhalation 1.2E-07

75 Inhalation 3.6E-07

90 Inhalation 8.5E-07

95 Inhalation 1.4E-06

99 Inhalation 3.4E-06

Noncancer Child

50 Inhalation 1.3E-07

75 Inhalation 3.8E-07

90 Inhalation 9.0E-07

95 Inhalation 1.4E-06

99 Inhalation 3.6E-06

Composite Liner

Noncancer Adult

50 Inhalation 1.1E-07

75 Inhalation 3.4E-07

90 Inhalation 7.9E-07

95 Inhalation 1.3E-06

99 Inhalation 3.0E-06

Noncancer Child

50 Inhalation 1.2E-07

75 Inhalation 3.6E-07

90 Inhalation 8.3E-07

95 Inhalation 1.3E-06

99 Inhalation 3.2E-06

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 

Draft Appendix A Theoretical Risk Distributions

No Liner

Noncancer Adult

50 Shower 4.4E-05

Drinking water 1.4E-06

Dermal bathing 1.0E-06

75 Shower 4.1E-04

Drinking water 1.1E-05

Dermal bathing 8.2E-06

90 Shower 2.1E-03

Drinking water 5.6E-05

Dermal bathing 3.8E-05

95 Shower 5.0E-03

Drinking water 1.2E-04

Dermal bathing 8.1E-05

99 Shower 1.9E-02

Drinking water 4.8E-04

Dermal bathing 3.2E-04

Noncancer Child

50 Drinking water 2.8E-06

Dermal bathing 2.5E-06

75 Drinking water 2.4E-05

Dermal bathing 2.0E-05

90 Drinking water 1.1E-04

Dermal bathing 9.4E-05

95 Drinking water 2.6E-04

Dermal bathing 2.0E-04

99 Drinking water 1.0E-03

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 

Draft Appendix A Theoretical Risk Distributions

Composite Liner

Noncancer Adult

50 Shower 1.1E-17

Drinking water 4.0E-19

Dermal bathing 2.7E-19

75 Shower 1.7E-08

Drinking water 5.0E-10

Dermal bathing 3.5E-10

90 Shower 1.9E-06

Drinking water 5.3E-08

Dermal bathing 3.6E-08

95 Shower 1.3E-05

Drinking water 3.4E-07

Dermal bathing 2.3E-07

99 Shower 2.2E-04

Drinking water 5.3E-06

Dermal bathing 3.8E-06

Noncancer Child

50 Drinking water 8.2E-19

Dermal bathing 6.7E-19

75 Drinking water 1.1E-09

Dermal bathing 9.3E-10

90 Drinking water 1.0E-07

Dermal bathing 9.5E-08

95 Drinking water 7.0E-07

Dermal bathing 6.0E-07

99 Drinking water 1.2E-05

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 coefficients 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: Hazardous 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

B (unitless) 2.86E-02 Calculated based on U.S. EPA, 2004

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)

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

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 6.4E-03 Calculated based on U.S. EPA, 2004

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

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

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

tb Boiling point (degC) 1.14E+02 SCDM

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

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

B (unitless) 1.50E-03 Calculated based on U.S. EPA, 2004

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)

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

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 4.2E-04 Calculated based on U.S. EPA, 2004

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

Sol Solubility (mg/L) miscible SCDM

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

tb Boiling point (degC) 1.35E+02 SCDM

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

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

B (unitless) 1.50E-03 Calculated based on U.S. EPA, 2004

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)

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

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 5.1E-04 Calculated based on U.S. EPA, 2004

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

Sol Solubility (mg/L) miscible SCDM

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

tb Boiling point (degC) 5.60E+01 SCDM

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

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

B (unitless) 5.06E-02 Calculated based on U.S. EPA, 2004

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)

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

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 1.5E-02 Calculated based on U.S. EPA, 2004

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

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

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

tb Boiling point (degC) 8.00E+01 SCDM

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

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

B (unitless) 7.30E-03 Calculated based on U.S. EPA, 2004

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)

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

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 2.2E-03 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 4.36E+01 HSDB

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

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

tb Boiling point (degC) 1.18E+02 SCDM

tc Critical temperature (degC) 2.90E+02 HSDB

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

B (unitless) 1.19E-01 Calculated based on U.S. EPA, 2004

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)

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

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 2.9E-02 Calculated based on U.S. EPA, 2004

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

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

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

tb Boiling point (degC) 1.32E+02 SCDM

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

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

B (unitless) 3.16E-02 Calculated based on U.S. EPA, 2004

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)

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

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 7.9E-03 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 4.84E+01 KDB

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

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

tb Boiling point (degC) 1.98E+02 SCDM

tc Critical temperature (degC) 4.30E+02 KDB

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

B (unitless) 5.80E-03 Calculated based on U.S. EPA, 2004

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)

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

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 1.5E-03 Calculated based on U.S. EPA, 2004

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

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

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

tb Boiling point (degC) 1.55E+02 SCDM

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

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

B (unitless) 2.08E-01 Calculated based on U.S. EPA, 2004

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)

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

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 4.5E-02 Calculated based on U.S. EPA, 2004

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

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

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

tb Boiling point (degC) 1.80E+02 SCDM

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

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

B (unitless) 5.20E-03 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 1.38E-04 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 1.4E-03 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 3.78E+01 Reid et al., 1977

Sol Solubility (mg/L) 8.03E+04 SCDM

tau Lag time per event (hr/event) 3.30E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 7.71E+01 SCDM

tc Critical temperature (degC) 2.50E+02 Reid et al., 1977

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

B (unitless) 1.92E-01 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 7.88E-03 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 4.9E-02 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 3.56E+01 Reid et al., 1977

Sol Solubility (mg/L) 1.69E+02 SCDM

tau Lag time per event (hr/event) 4.20E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 1.36E+02 SCDM

tc Critical temperature (degC) 3.44E+02 Reid et al., 1977

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

B (unitless) 6.30E-03 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 1.18E-05 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 1.9E-03 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 4.24E+01 Reid et al., 1977

Sol Solubility (mg/L) 8.50E+04 SCDM

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

tb Boiling point (degC) 1.08E+02 SCDM

tc Critical temperature (degC) 2.75E+02 Reid et al., 1977

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

B (unitless) 8.00E-04 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 4.55E-06 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 3.5E-04 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 7.99E+01 Reid et. al., 1977

Sol Solubility (mg/L) miscible SCDM

tau Lag time per event (hr/event) 1.60E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 6.46E+01 SCDM

tc Critical temperature (degC) 2.39E+02 Reid et. al., 1977

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

B (unitless) 3.10E-03 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 5.59E-05 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 9.5E-04 Calculated based on U.S. EPA, 2004

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

Sol Solubility (mg/L) 2.23E+05 SCDM

tau Lag time per event (hr/event) 2.70E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 7.95E+01 SCDM

tc Critical temperature (degC) 2.62E+02 Reid et al., 1977

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

B (unitless) 1.02E-02 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 1.38E-04 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 2.7E-03 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 3.23E+01 Reid et al., 1977

Sol Solubility (mg/L) 1.90E+04 SCDM

tau Lag time per event (hr/event) 3.90E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 1.17E+02 SCDM

tc Critical temperature (degC) 2.98E+02 Reid et al., 1977

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

B (unitless) 1.26E-02 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 2.19E-03 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 3.5E-03 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 6.02E+01 HSDB

Sol Solubility (mg/L) 1.30E+04 SCDM

tau Lag time per event (hr/event) 3.20E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 4.00E+01 SCDM

tc Critical temperature (degC) 2.37E+02 HSDB

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

B (unitless) 5.42E-02 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 1.84E-02 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 1.1E-02 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 4.40E+01 Reid et al., 1977

Sol Solubility (mg/L) 2.00E+02 SCDM

tau Lag time per event (hr/event) 9.10E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 1.21E+02 SCDM

tc Critical temperature (degC) 3.47E+02 Reid et al., 1977

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

B (unitless) 1.18E-01 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 6.64E-03 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 3.2E-02 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 4.06E+01 Reid et al., 1977

Sol Solubility (mg/L) 5.26E+02 SCDM

tau Lag time per event (hr/event) 3.50E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 1.11E+02 SCDM

tc Critical temperature (degC) 3.19E+02 Reid et al., 1977

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

B (unitless) 8.00E-02 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 1.03E-02 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 1.8E-02 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 4.85E+01 Reid et al., 1977

Sol Solubility (mg/L) 1.10E+03 SCDM

tau Lag time per event (hr/event) 5.80E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 8.72E+01 SCDM

tc Critical temperature (degC) 2.98E+02 Reid et al., 1977

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

B (unitless) 2.01E-01 Calculated based on U.S. EPA, 2004

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)

HLC Henry's law constant (atm-m3/mol) 6.73E-03 SCDM

Dermal permeability coefficient of 

compound in water

Kp (cm/hr) 5.1E-02 Calculated based on U.S. EPA, 2004

Pc Critical pressure (atm) 3.55E+01 KDB

Sol Solubility (mg/L) 1.75E+02 SCDM

tau Lag time per event (hr/event) 4.20E-01 Calculated based on U.S. EPA, 2004

tb Boiling point (degC) 1.41E+02 SCDM

tc Critical temperature (degC) 3.48E+02 KDB

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 (Da) 

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 

 Da = diffusivity in air (cm2/s) 

 T = temperature (oC) 

 P = density (g/cm3) 

 Mr = reciprocal of the reduced mass, as calculated below in Equation B-2 

 VA = molar volume of air (cm3/mol) 

 VB = constituent molar volume (mol/m3

). 

The reciprocal of the reduced mass, Mr, is calculated from the molecular weight of air 

and the molecular weight of the constituent: 

( )

( )

a b

a b

r M M

M M

M

×

+ = (Equation B-2) 

where 

 Ma = molecular weight of air (g/mol) 

 Mb = 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, VB, 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 ▵VB (cm3/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 

(cm3/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 (Dw) 

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. 

1.14 0.589

5 13.26 10

B

w

vwt V'

D

×

× =

−

 (Equation B-3) 

where 

 Dw = diffusivity in water (cm2

/s) 

 vwt = viscosity of the water (g/m-s) 

 V'B = LeBas molar volume (cm3

/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 ln(2)

1/ 2 = (Equation B-4) 

where 

 t1⁄2 = 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 

Cg = Cf × Kdg (Equation B-5) 

where 

 Cg = geomembrane concentrations (M/L3) 

 Cf = fluid concentration (M/L3) 

 Kdg = linear partition coefficient between the fluid and the geomembrane (unitless). 

Fick’s law can be used to describe diffusion through the geomembrane: 

dz

dC

f D g = − g

× (Equation B-6) 

where 

 f = mass flux (mass per area per time) (M/L2-T) 

 Dg = the geomembrane diffusion coefficient (L2/T) 

 Cg = geomembrane concentration (M/L3) 

 z = diffusion direction (L). 

Combining the above two relationships yields the following: 

dz

dC

P

dz

dC

f D K f

g

f = − g dg = − (Equation B-7) 

where 

f = mass flux (mass per area per time) (M/L2-T) 

 Dg = the geomembrane diffusion coefficient (L2/T) 

 Cf = fluid concentration (M/L3) 

 z = diffusion direction (L) 

 Pg = geomembrane permeation coefficient (L2/T) = Dg x Kdg. 

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 (Kow): 

2 log 13.4476 2.2437 log 0.3910 (log ) Pg = − + Kow − Kow (Equation B-8) 

This correlation showed an r2

 correlation of 0.84 in predicting the permeation coefficient 

for a range of chemicals (Sangam and Rowe, 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 

 Hadj = adjusted Henry’s law constant (atm-m3/mol) 

 Href = reference Henry’s law constant (atm-m3/mol) at the reference temperature 

 Tref = reference temperature (K) 

Δhv = 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 (Δhvb): 

c

b

c

b

c

vb b

T

T

T

T

P

h T

−

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ − +

Δ = ×

1.07

7.11 log ( ) 7.82 7.9 10

 (Equation B-10) 

where 

Δhvb = enthalpy of vaporization at the boiling point (cal/mol) 

 Tb = boiling point (K)

 Pc = critical pressure (atm) 

 Tc = critical Temperature (K). 

Then, the enthalpy of vaporization is estimated using the method in Lyman et al. (1990): 

n

c

b

c

v vb

T

T

T

T

h h

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎝

⎛

−

−

Δ = Δ

1

1

 (Equation B-11) 

where the exponent, n, is equal to 0.41 if T/Tc > 0.71. If T/Tc ≤ 0.71, n is calculated as follows: 
Draft Appendix B Chemical-Specific Parameters 

B-28 

0.74 − 0.116 ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =

c

b

T

T

n (Equation B-12) 

Most of the critical temperature values were 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-m3/mol. The landfill source model uses 

the dimensionless form of the Henry’s law constant, 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-m3

/mol) 

 R = universal gas constant = 8.2e-5 atm-m3/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): 

2.6

( ) 0.5 Kp MW 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 Kow andMW (U.S. EPA, 2004): 
Draft Appendix B Chemical-Specific Parameters 

B-29 

(-2.805063+ 0.6645865 logK - 0.0056118 MW) ow 10 × × Kp = (Equation B-15) 

where 

 Kp = Dermal permeability coefficient of compound in water (cm/hr) 

 Kow = 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): 

× Dsc

= 6

l 2

sc τ (Equation B-16) 

where 

τ = Chemical-specific lag time per event (cm/hr) 

lsc = Apparent thickness of the stratum corneum (cm) – set to a default value of 0.001 

 Ds = Chemical-specific effective diffusion coefficient for chemical transfer through the 

stratum corneum (cm2

/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 Manufacturer’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 mixtures containing alkoxyethanols. Part XV. 

DISQUAC characterization of systems of alkoxyethanols 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. Migration 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 Summary 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 Model 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 covered 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 landfill 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 material 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 previous ones. Lifts extending above 

the local grade (above the excavated landfill basin) are typically added with a slope of 

approximately 1 to 3. Our understanding of typical 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 Model Mathematical Formulation 

C-2 

Figure C-2 shows the waste addition pattern developed for the LFCR model, which is 

generally consistent with the typical landfill operating practices described above. Each box in the 

figure represents a daily cell, and each lift is shown in a different color. Although some of the 

details do not match typical practice (e.g., sloping side walls above and below grade), this 

approach captures critical characteristics of landfill waste addition (daily cells added in lifts). 

Additional details of the landfill-filling 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 Model 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 simplicity, the surface areas of daily and landfill 

cells were modeled as squares. The daily cell/lift height can vary from the daily cell width. 

The following input parameters characterize the waste addition algorithm for a given 

landfill: total landfill capacity (Vtot), total landfill area (Atot), landfill operating life in years (Tlf), 

number of landfill cells within the landfill (Nlfcell), the target lift height (Htarg), and the fraction of 

a day when waste is actively added to the landfill (and the active daily cell has no cover, fopen). 

The mass associated with each new daily cell is added in full at the 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 calculated 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: 

N T cells lfcell = { } (Equation C-3) 

where {⋅} denotes a rounding operator to the nearest integer (the number of cells must be an 

integer). A portion of the total landfill capacity (Vtot) is taken up by the volume of soil used for 

the liner, the final cover, and the daily covers (as determined by the landfill area and userspecified thicknesses for these layers). The adjusted total capacity (Vadj) represents the landfill 

volume after subtracting the final cover and liner volumes. Then, the total volume of each daily 

cell (inclusive of the daily cover volume) is calculated as: 

adj

celltot

lfcell cells

V

V

N N = ×

 (Equation C-4) 

The number of daily cells per landfill cell length is then calculated:1

 

 

1

 This relationship is derived from the following: Lcell = Llfcell/NL; Llfcell = (Atot/Nlfcell)

1/2; Vcell = Lcell2 × Htarg. 
Draft Appendix C Landfill Source Model 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 different from the input target height because 

the number of cells must be an integer. Any roundoff adjustment is compensated by slightly 

adjusting Hcelltot. 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 (Hcell and Vcell) can then be calculated by subtracting the height and volume of the daily 

cover. In addition, the daily cell surface area (Acell) 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 stacked daily cells with overlying daily cells added at later times. 

The model simulates vertical transport within each 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 description based on fully mixed reactors 

coupled in series and applies it within a framework consistent with typical landfill operations 

(daily cells added in lifts as depicted in Figure 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 balance 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 Model Mathematical Formulation 

C-5 

mass exiting the cell and transformed within the cell. Such a mass balance around a daily cell 

control volume can be written as the overall change in mass within the cell equal to the sum of 

source/sink terms representing each of the mass 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 represents the change in mass within daily cell i (volume 

times concentration). The right hand side of the mass balance equation is the sum of source/sink 

terms representing mass within flowing air (Sa,i), mass within flowing water (Sw,i), mass decay 

within the cell (Sλ,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 exiting 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, each 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 rearranged 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 added at a later time above existing cells become 

additional reactors in series. In the 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 total volumetric concentration within cell i, which 

includes mass in the aqueous, vapor, and solid phases. An expression for the total concentration 

can be developed by considering the total mass in the cell equal to the mass within each of the 

phases: 

m VC VC MC i w wi a ai s si = ,, , + + (Equation C-10) 

Where mi is the total chemical mass within the daily cell, Vw is the water volume, Cw,i is the 

volumetric concentration of chemical in the water (e.g., kg/m3

), Va is the air volume, Ca,i is the 

volumetric concentration of chemical in air, Ms is the mass of refuse in the daily cell, and Cs,i is 

the mass-based concentration of chemical on the solid (e.g., kg/kg). Dividing by the total waste 

volume within the daily cell (Vcell) gives an expression for the total concentration in daily cell i in 

terms of the phase specific concentrations: 

CC C C i w wi a ai b si ,,, = ε + + ε ρ (Equation C-11) 

where εw and εa are the volumetric fractions of water and air, respectively, and ρb is the dry bulk 

density. 

Air-water partitioning is characterized by linear equilibrium and described through 

Henry’s law: 
Draft Appendix C Landfill Source Model Mathematical Formulation 

C-6 

Ca,i = KH Cw,i (Equation C-12) 

where KH is the dimensionless Henry’s law constant. 

Solid-water partitioning is characterized by linear equilibrium, as described by a 

distribution coefficient (Kd): 

C KC s, , i d wi = (Equation C-13) 

For organic compounds, the distribution coefficient can be estimated from the organiccarbon fraction (foc) and the organic-carbon distribution coefficient (Koc): 

K fK d oc oc = (Equation C-14) 

C.3.2 Partition/Retardation Coefficients 

Although the model is formulated in terms of the total concentration, mass transfer and 

transformation processes are generally active within 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 concentrations are constant (Kjeldsen and Christensen, 

2001). Therefore, partition coefficients can be developed 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 (Ra): 

C RC i a ai = , (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 (Rw): 

C RC i w wi = , (Equation C-17) 

Rw w aH bd = ε + + ε ρ K K (Equation C-18) 

The concentration in the solid can be related to the total concentration using the solidtotal concentration partition/retardation coefficient (Rs): 

C RC i s si = , (Equation C-19) 

w aH

s b

d

K R

K

ε ε

ρ

+ = + (Equation C-20) 
Draft Appendix C Landfill Source Model Mathematical Formulation 

C-7 

C.3.3 Advective Gaseous Transport (Landfill Gas) 

A first-order decay model developed for EPA’s LandGEM model (U.S. EPA, 2005) 

estimates the landfill gas flow rate (Qa,i). This model uses a landfill gas generation rate, k (/T), 

and a potential methane generation capacity, Lo (methane volume per waste mass). The gas 

generation model can be expressed as follows (Bartelt-Hunt et al., 2006): 

, 2 exp( ) Q V L k kt a i cell b o i = ρ − (Equation C-21) 

where Vcell is the waste volume within the daily cell, ρb is the waste bulk density, and ti 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 current 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 has a positive sign, while the 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 qa,j is equal to [2ρbLokexp(-kti)] based on Equation C-21. 

C.3.4 Advective Aqueous Transport (Leachate) 

The leachate flow rate (Qw) is equal to the net infiltration (N) multiplied by the surface 

area (A): 

Q NA w cell = (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 vertical downward water flow, mass enters the 

current daily cell (i) from the overlying daily cell: 

wi w wi w wi , ,1 , 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 aqueous 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 Model Mathematical Formulation 

C-8 

C.3.5 Degradation/Transformation 

A first-order degradation sink term describes degradation and transformation processes 

such as biodegradation and hydrolysis: 

SVC C C λ, ,1 2 , 1 2 ,1 2 i cell a a i a a w w i w w b s i s s =− + + + + + ⎡ ⎤ ε λλ ε λ λ ρ λλ ( ) ( ) ( ) ⎣ ⎦ (Equation C-27) 

where λa1, λw1, and λs1 are the biotic first-order degradation rates in the air, water, and solid 

phases, respectively, and λa2, λw2, and λs2 are the respective abiotic first-order degradation rates. 

After expressing in terms of the total concentration, 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 approach to describe diffusion between daily 

cells in air and water. Mass transfer is dependent 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 , ( ) aDai ai ai

i

AD S CC

L = − + (Equation C-30) 

Consistent with the model’s sign convention, the diffusive source/sink term is positive if the 

concentration in the overlying cell exceeds the concentration in the current cell (which would 

result in a positive diffusive mass flow into cell i). 

Expressing the equation in terms of the total concentration yields the following: 

, 1

a a

Dai i i

ia ia

AD AD S CC

LR LR +

⎛⎞ ⎛⎞ = − ⎜⎟ ⎜⎟ ⎝⎠ ⎝⎠

 (Equation C-31) 

Diffusion coefficients are dependent on the chemical, as well as the porous medium in 

cell i. The diffusion coefficient can be estimated based on the chemical-specific diffusion rate in 

air or water and the porous medium tortuosity for air or water (Millington, 1959). Accordingly, 

the diffusion coefficient for air has the following expression: 

D D a oa = τ (Equation C-32) 
Draft Appendix C Landfill Source Model Mathematical Formulation 

C-9 

where τ is the tortuosity. The tortuosity 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): 

103

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: 

Da tot i Da i Da i , , , ,1 S SS = − − (Equation C-34) 

A similar approach yields the diffusive transport in the water phase. The following 

source/sink term describes the diffusive transport in water through the overlying cover: 

, 1

w w

Dwi i i

iw iw

AD AD S CC

LR LR = − + (Equation C-35) 

The Millington (1959) approach for estimating the diffusion coefficient and the tortuosity 

associated with the water phase yields the following: 

D D w ow = τ (Equation C-36) 

103

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 the underlying cover/liner layers: 

S Dw,tot,i = S Dw,i − S Dw,i−1 (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: 

D, , ,1 , ,1 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 based 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

dC SSSS

dt V

+ + + λ = (Equation C-41) 

Below, each of the source/sink terms is divided by the volume and expressed in terms of 

coefficients of the total concentrations within the current and overlying and underlying daily 
Draft Appendix C Landfill Source Model Mathematical Formulation 

C-10 

cells (Ci-1, Ci, and Ci+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

a i j j

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

+ −

− −

+

− −

⎡ ⎤⎡ ⎤ ⎛ ⎞ ⎛ ⎞ ⎛ ⎞⎛ ⎞ = −− − ⎢ ⎥⎢ ⎥ ⎜ ⎟ ⎜ ⎟ ⎜ ⎟⎜ ⎟ ⎣ ⎦⎣ ⎦ ⎝ ⎠ ⎝ ⎠ ⎝ ⎠⎝ ⎠

⎡ ⎤ ⎛ ⎞ ⎛ ⎞ ⎛ ⎞⎛

+ −− − ⎢ ⎥ ⎜ ⎟⎜ ⎟ ⎜ ⎟ ⎣ ⎦ ⎝ ⎠⎝ ⎠ ⎝ ⎠

Ci−1

⎡ ⎤ ⎞ ⎢ ⎥ ⎜ ⎟ ⎣ ⎦ ⎝ ⎠

(Equation C-45) 

The mass balance equation can then be expressed in terms of the total concentration in 

cell i as a function of the concentrations in the current (Ci), the overlying (Ci+1), and the 

underlying (Ci-1) daily cells: 

= 1 i−1 + 2 i + 3 i+1

i k C k C k C

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 Model Mathematical Formulation 

C-11 

3

a w

cell w i cell a i cell w

N D D 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 diffusive 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 equation presented by Carslaw and Jaeger (1947). This 

one-dimensional analytical solution describes the mass release from a system with a constant 

starting concentration, a zero-flux lower boundary, and an upper boundary at a constant 

concentration of zero. 

The underlying differential equation for the Carslaw 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 solution is shown here: 

( )

( )

( ) ( ) 2 2

2

0

4 1 21 21

( , ) exp cos 21 4 2

n

init

n

C Dn t n

Czt z

n LL

π π

π

∞

=

− ++ ⎛ ⎞ ⎡ ⎤ = −⎜ ⎟ ⎢ ⎥ + ⎣ ⎦ ⎝ ⎠

∑ (Equation C-51) 

where C is the concentration, z is the depth, t is time, Cinit 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 specified concentration of zero. Figure C-3 presents a series of 

representative concentration profiles over time. The concentration starts at the constant 

maximum value and decreases over time with zero flux from the lower boundary. 
Draft Appendix C Landfill Source Model Mathematical Formulation 

C-12 

Concentration

Depth

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 2 1

( ) exp 4

init

n

DC Dn t

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. 

Time

Diffusive Mass Flux

0

0

Figure C-4. Flux over time based on the Carslaw and Jaeger (1947) solution. 
Draft Appendix C Landfill Source Model Mathematical Formulation 

C-13 

The average flux from time t1 to t2 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 t1 and t2 is based on the definite integral between t1

and t2: 

( )

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

2 4 2 1

( , ) exp

2 1 4

j init

j

j j n

DC L Dn t

FtL

L L D n

π

π

∞

=

− ⎛ ⎞ + = −⎜ ⎟

+ ⎝ ⎠

∑ (Equation C-55) 

and Lj is the thickness of the waste 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 start of the day. In order to represent enhanced 

mass loss associated with this process, the LFCR model applies the solution presented above to 

sequential layers added to the working 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 the no-cover length (Lnc) and height (Hnc): 

( )

( )

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 Model Mathematical Formulation 

C-14 

Solution geometry 

(flux through the top surface) Actual geometry

Hnc

Hnc

Working 

Face

Angle

Lnc

Lnc

Hcell

Lcell

Figure C-6. Representation of mass loss from the open face of the active daily cell. 

The solution calculates the number of sublayers (Nsl) 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 (hinc) is then equal to Hnc divided by Nsl. The incremental time over which each sublayer 

is applied (tinc) is equal to the fraction of a day with no cover divided by Nsl. The Carslaw and 

Jaeger solution is then applied to a series of layers of increasing thickness (Hinc, 2Hinc, 3Hinc, etc.) 

to calculate the average flux over the period with no cover (Jnc): 

( )

1

0, ,

Nsl

avg inc inc

i

nc

sl

J t ih

J

N

= =

∑

 (Equation C-57) 

This no-cover flux is applied to the surface area of the working face (Lnc x Hnc), as well as 

to one-half of the daily cell top surface (on average, 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 cell top surface would be a more complex, 

multidimensional process. Uncertainty is increased through variable disposal practices (e.g., 

industrial wipes sealed in plastic bags versus open to the atmosphere, variable waste mixing and 

compaction). The approach described above provides a relatively simple and reasonable 

estimation given the complexity, uncertainty, 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 tolerance. 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 partitioning in the air, water, and solid phases. 

This effective diffusion coefficient is equal to the vapor-phase diffusion coefficient (Da,i in 

Equation C-32) divided by the vapor-phase partition/retardation coefficient (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 Model Mathematical Formulation 

C-15 

which to describe diffusive transport. The diffusive flux of interest is from the constantconcentration bottom reactor into the underlying unsaturated zone soil. Extending the domain to 

the water table (and assuming the water table is at a concentration of zero), diffusion through the 

unsaturated soil zone below the landfill can be approximated using a steady-state solution to the 

diffusion equation. The solution domain is the unsaturated zone thickness (Lu). The upper 

boundary condition (the bottom of the landfill) is a constant concentration of the bottom reactor, 

C1. The lower boundary condition (at the water table) is a constant concentration of zero. Given 

these boundary conditions, the solution for the steady-state diffusive flux is the following: 

1

D noliner u ,

u

C J D

L = (Equation C-58) 

Thus, the sink term for diffusive losses below 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 total mass transfer to groundwater. 

Diffusion through the Uppermost Cover and the Liner 

When the top cell has a cover, the formulation 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 Cn+1 term from the mass balance equation. 

Similarly, the concentration below the liner is assumed to be zero, which eliminates the Co term. 

Diffusion Through a Geomembrane-Based Liner or Final Cover 

Diffusive transport through a geomembrane behaves differently from transport through 

soil, because a geomembrane is not porous (Foose et al., 1999). Rather than diffusing through 

void spaces filled with air or water, 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 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. 

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: 

C CK g = f dg (Equation C-60) 

where Cg and Cf are the geomembrane and fluid concentrations, respectively, and Kdg is the 

linear partition coefficient between the fluid and the geomembrane. Fick’s law describes 

diffusion through the geomembrane: 
Draft Appendix C Landfill Source Model Mathematical Formulation 

C-16 

g

g

dC

f D dz = −

 (Equation C-61) 

where f is the mass flux, Dg is the geomembrane diffusion coefficient, and z is the diffusion 

direction. Combining these two relationships yields the following: 

f f

g dg g

dC dC

f DK P dz dz =− =−

 (Equation C-62) 

where the geomembrane permeation coefficient, Pg, is the product of the geomembrane diffusion 

coefficient and the partition coefficient. The landfill source model applies the permeationcoefficient formulation shown above to describe transport through geomembranes. As described 

in Appendix E, an empirical correlation and literature 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 individual diffusion/permeation 

coefficients (Foose et al., 2002): 

gm cl

eq

gm cl

gm 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 Lgm

and permeation coefficient Pgm and a clay layer of thickness Lcl and diffusion coefficient Dcl. To 

account for potential sorption within the soil layer, the diffusion coefficient can be divided by a 

retardation coefficient. For the industrial wipes analysis, no sorption was allowed within the 

cover/liner soil layers, because a generalized approach to estimate the cover/liner soil retardation 

coefficient for national conditions was not identified, 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 landfill, much of the advective water 

flux leaving the bottom cell is captured by a leachate collection system. In this situation, the 

majority of the advective water flow is captured and does not reach the groundwater zone. 

However, some fraction of the flow does migrate through the liner as a result of liner 

imperfections (e.g., holes, defective seams). In this 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-specified 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), the infiltration rate may significantly decrease after 
Draft Appendix C Landfill Source Model 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 solutions to systems of ordinary 

differential equations exist (e.g., Bulirsch-Stoer), the Runge-Kutte algorithm is effective because 

of the relatively small number of coupled equations (the number 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 generating 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 

Acell Daily cell surface area [L2] 

Atot Total landfill surface area [L2

] 

Ca,i Volumetric air-phase concentration in daily cell i [M/L3

] 

Cf Concentration in fluid adjacent to geomembrane [M/ L3

] 

Cg Concentration on geomembrane [M/ L3

] 

Ci Total volumetric concentration in daily cell i [M/L3

] 

Cs,i Mass-based, solid-phase concentration in daily cell i [M/M] 

Cw,i Volumetric water-phase concentration in daily cell i [M/L3

] 

Da Air-phase diffusion coefficient [L2

/T] 

Dcl Diffusion coefficient for the clay layer in a composite liner or cover [L2

/T] 

Deq Equivalent diffusion coefficient for a composite cover or liner [L2

/T] 

Doa Diffusivity in air [L2

/T] 

Dow Diffusivity in water [L2

/T] 

Du Diffusion coefficient in the unsaturated zone [L2

/T] 

Dw Water-phase diffusion coefficient [L2

/T] 

foc Fraction organic carbon [-] 

fopen Fraction of tcell (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 

Hcell Daily cell height, without the daily cover [L] 

Hcelltot Lift height, inclusive of daily cover [L] 

hinc Height of subcell layer in the active, open daily cell [L] 

Hnc Adjusted daily cell thickness, accounting for the working face angle [L] 

Htarg User-specified target lift height [L] 

i Subscript denoting cell i within a column of landfill cells 

Javg Average diffusive flux from a waste sublayer with no cover [M/L2 T] 

Jnc Total diffusive flux from the top cell with no cover (all sublayers) [M/L2 T] 

k Landfill gas production rate (/T] 

k1 Coefficient for Ci-1 (underlying cell concentration) in the mass balance equation 

k2 Coefficient for Ci (current cell concentration) in the mass balance equation 

k3 Coefficient for Ci+1 (overlying cell concentration) in the mass balance equation 
Draft Appendix C Landfill Source Model Mathematical Formulation 

C-18 

Kd Solid-water phase distribution coefficient [L3/M] 

Kdg Geomembrane partition coefficient [-] 

KH Henry’s law constant [-] 

Koc Organic carbon distribution coefficient [L3

/M] 

Lcell Daily cell length in the lateral dimension [L] 

Lcl Composite liner clay layer thickness [L] 

Li Thickness of the cover layer overlying cell i [L] 

Lgm Geomembrane thickness [L] 

Llfcell Length of each lateral dimension of a landfill cell [L] 

Lnc Adjusted daily cell width, accounting for the working face angle [L] 

Lo Potential methane generation capacity [volume methane/waste mass]

Lu Length of unsaturated zone [L] 

mi Chemical mass in daily cell i [T] 

Ms Mass of refuse in daily cell [T] 

n Number of cells within column [-] 

N Net infiltration rate [L/T] 

Ncells Number of daily cells within a given landfill cell [-]

NH Number of lifts within a landfill cell in the z dimension [-]

NL Number of daily cells within a landfill cell in the lateral dimension [-]

Nlfcell Number of landfill cells within a given landfill [-]

Nsl Number of sublayers within a daily cell [-] 

Pg Geomembrane permeation coefficient [L2

/T] 

qa,i Landfill gas generation rate, per landfill waste volume [/T] 

Qa,i Air flow rate for daily cell i [L3

/T] 

Qw Leachate flow rate [L3

/T] 

Ra Air-phase to total concentration partition/retardation coefficient [-] 

Rs Solid-phase to total concentration partition/retardation coefficient [-] 

Rw Water-phase to total concentration partition/retardation coefficient [-] 

Sa,i Advective gaseous transport source/sink term [M/T] 

SD ,i Total (air and water) diffusive transport source/sink term [M/T] 

SDa,i Gaseous diffusive transport source/sink term through overlying cover [M/T] 

SDa,tot,i Total gaseous diffusive transport source/sink term [M/T] 

SDw,i Aqueous diffusive transport source/sink term through overlying cover [M/T] 

SDw,tot,i Total aqueous diffusive transport source/sink term [M/T] 

Sw,i Advective aqueous transport source/sink term [M/T] 

Sλ,i Degradation source/sink term [M/T] 

SNC Diffusive source/sink term for the active daily cell with no cover [M/T] 

t Time [T] 

tcell Time increment required to fill one daily cell (typically 1 day) [T] 

Tlf Total operating life of a landfill in years [T]

Tlfcell Operating life of an active landfill cell in years [T]

tnc Time required to fill a waste subcell with refuse [T] 

Va Volume of air within a daily cell [L3

] 

Vadj Landfill volume after subtracting the final cover and liner volumes [L3

] 

Vcell Daily cell volume, without the daily cover [L3

] 

Vcelltot Daily cell volume, inclusive of the daily cover volume [L3

] 
Draft Appendix C Landfill Source Model Mathematical Formulation 

C-19 

Vlfcell Volume of a landfill cell [L3]

Vtot Total landfill volume [L3] 

Vw Volume of water within a daily cell [L3

] 

εa Air-phase volumetric fraction [L3/L3] 

εaC Air-phase volumetric fraction in overlying cover [L3/L3] 

εC Porosity in overlying cover [L3/L3] 

εw Water-phase volumetric fraction [L3/L3] 

εwC Aqueous-phase volumetric fraction in overlying cover [L3/L3] 

λa1 First-order biodegradation rate in the air phase [/T] 

λs1 First-order biodegradation rate in the solid phase [/T] 

λw1 First-order biodegradation rate in the water phase [/T] 

λa2 First-order abiotic degradation rate in the air phase [/T] 

λs2 First-order abiotic degradation rate in the solid phase [/T] 

λw2 First-order abiotic degradation rate in the water phase [/T] 

ρb Dry bulk density of the waste [solid mass/total volume, M/L3] 

θ Working face angle [deg] 

τ Tortuousity [-] 

C.5 References 

Aivaliotis, V., I. Dokas, M. Hatzigiannakou, and D. Panagiotakopoulos. 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 development and parameterization of the LFCR landfill 

source model.” Multiple phone and email communications from Dr. Morton Barlaz, 

Professor, Water Resources/Environmental Engineering, North Carolina State University, 

to Michael I. Lowry, RTI. July through December. 

Bartelt-Hunt, S. L., D. R. U. Knappe, P. Kjeldsen, 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 Composite Geosynthetic Clay 

Liners as a Barrier to Volatile 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 Solute Transport in Three 

Composite Liners. Journal of Geotechnical and Geoenvironmental Engineering

128(5):391–403. 
Draft Appendix C Landfill Source Model 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 Scientific Computing. Second Edition. New York: Cambridge 

University Press. 

Sangam, H. P., and R. K. Rowe. 2001. Migration 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 reliability 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 verification testing includes test 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 results vary linearly with input 

concentrations. The industrial wipes risk modeling was performed using a single input 

concentration. If results scale linearly with the input concentration, 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 concentration. Linearity verification is described in Section D.2. 

 Robustness testing evaluates the model’s effectiveness and reliability in simulating the 

range of conditions anticipated for the industrial wipes risk assessment. Robustnesstesting scenarios explore the model behavior using specific chemicals and scenarios 

representing the extremes of the anticipated parameter space (e.g., most/least volatile 

chemicals, maximum/minimum gas advection). The robustness testing consists 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 robustness testing considers two chemicals 

representing the maximum and minimum Henry’s law constant. Robustness testing is 

described in Section D.3. 

A series of test cases were developed using average input parameter values to compare 

modeled landfill gas and leachate concentrations with 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 LFCR 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 operations and transport mechanisms along with 

tests used to verify the accuracy of each model implementation. The verification of several of 

these transport mechanisms relies on comparisons between analytical solutions and a model 

simulation where the landfill is represented as a single landfill cell. 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 simulations include a single cell representing an 

operating landfill life of 40 years. The total simulation 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 industrial wipes risk analysis. Many of the chemical 

parameters are representative of tetrachloroethylene, which has the 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 significantly adjusted (e.g., degradation rates, diffusivities) to verify 

specific transport mechanisms rather than to represent the behavior of particular chemicals or 

scenarios. Figures D-1 through D-14 (at the end of this appendix) present the graphical 

comparisons between model results and the analytical 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 diffusive 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 diffusive 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 m3 4,232,637 

Total landfill area m2 360,150 

Landfill cell volume m3 4,232,637 

Landfill cell area m2 360,150 

Target cell/lift height m 11.75 

Time before permanent cover installed on landfill cell yr 17.8 

Daily cell waste sublayer period hr 8 

Working face angle to horizontal deg 19.6 

Initial concentration kg/m3 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 truncation 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 cm3/mol 111 

Le Bas molar volume cm3/mol 128 

Molecular weight g/mol 165.83 

Henry's law constant atm-m3/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 0 
Draft Appendix D Landf

Table D-4. Input Parameters Varied for the Verification Testing 

Verification Testing Cases 

Parameter Unit Base 1 2 3a 4 5 6 7 8b 9c 10 11 12 1

Fraction 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 0.0 0.0 0.0 0.Landfill gas generation rate /yr 0.04 0.04 0.04 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0Infiltration rate before permanent cover 

m/yr 0.109 0.109 0.109 0 0.109 0 0 0 0 0 0 0 0 0 

Infiltration rate with permanent cover 

m/yr 0.109 0.109 0.109 0 0.109 0 0 0 0 0 0 0 0 0 

Liner leakage rate before permanent cover 

m/yr 0.000219 0.000219 0.000219 0 0.000219 0 0 0 0 0 0 0 0 0 

Liner leakage rate after permanent cover 

m/yr 0.000219 0.000219 0.000219 0 0.000219 0 0 0 0 0 0 0 0 0 

Abiotic decay half-life in water day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 Biotic decay half-life in water day 19.3 19.3 19.3 0 0 20 0 0 0 0 0 0 0 0 Biotic decay half-life in air day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 Abiotic decay half-life in air day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 Biotic decay half-life in solid day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 Abiotic decay half-life in solid day 0 0 0 0 0 20 0 0 0 0 0 0 0 0 Daily cover moisture 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 0.4Intermediate cover moisture 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 0.4

Permanent cover soil moisture 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 0.4

Liner moisture content - 0.284 0.284 0.284 0.284 0.284 0.284 0.43 0.284 0.43 0.43 0.284 0.284 0.284 0.2Geomembrane permeation coefficient 

cm2/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 

Liner configuration: 0=no liner; 1=soil liner; 2=composite liner 

- 2 2 2 2 2 2 2 1 2 2 1 2 2 0 

Permanent cover configuration 0=soil only; 1=composite 

- 1 1 1 1 1 1 0 0 1 1 1 1 1 1 

Diffusivity in aird cm2/sec -9999 -9999 -9999 0 0 0 -9999 0 -9999 -9999 -9999 -9999 0 -99Diffusivity in waterd cm2/sec -9999 -9999 -9999 0 0 0 0 -9999 0 0 0 0 -9999 0 Water diffusivity reference temperature (C) 

C 25 25 25 25 25 25 25 25 25 25 25 25 25 25 

Notes: 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 p

Lyman 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 (Kd) and linear equilibrium air-water partitioning 

described by a Henry’s law constant (KH). According to these relationships, the ratios between 

phase concentrations (solid, water, and air) are constant. Thus, the concentration within a given 

phase can be related to the concentration 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 Ra, Rw, and Rs. According to the relationships 

outlined above, the following phase fractions are valid for the verification case 1 scenario 

(calculated in a spreadsheet using parameter 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 from 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 exponential 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 generation rate over time predicted using a 

spreadsheet and from a model simulation using the input parameter values in Tables D-3 and D4. Note that the waste mass (W) is the product of the bulk density 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 over 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 migration of mass within the flowing air phase. 

The following analytical solution describes 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 the 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 working version of the model with a constant gas production rate. 

The gas production rate was constant and equal to the rate at time zero as specified by the input 

parameters in Tables D-3 and D-4. Transport pathways other than advection in the gas phase 

were disabled for this comparison (infiltration, degradation 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 spreadsheet using the solution presented above. 

D.1.4 Verification Case 4: Advective Aqueous Transport 

Advective aqueous transport describes 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 HR Ct Ce−

= (Equation D-5) 

Evaluation of advective transport within the aqueous phase involved comparison between 

a single cell model and the analytical solution presented above. Transport pathways other than 

advection in the aqueous phase were disabled for 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-order 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 for first-order decay shown above. Other transport pathways were 

disabled for this verification exercise (infiltration, gas production rates, and diffusivities set to 

zero). Figure D-4 shows the successful comparison between the concentration predicted by the 

model and that generated by a spreadsheet 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 atmosphere. Vapor diffusion can also transfer mass to 

groundwater (Verification Cases 10, 11, and 13). The following analytical solution describes the 

total concentration over time with diffusive transport in the air phase through an overlying cover: 

0 ( )

a

a

D t LHR Ct Ce−

= (Equation D-7) 

Note that the diffusion coefficient (Da) is calculated from the air volume fraction, porosity, and 

air diffusivity using the tortuosity formulation described in Appendix C. 

The formulation of diffusive transport in the air phase was evaluated by comparing 

single-cell model results with results from the analytical solution in Equation D-7. Other 

transport pathways were disabled for this verification exercise (infiltration, degradation, air 

production rates, and water diffusivity set to zero). The parameter values for daily, interim, and 

permanent covers were identical. Note that testing of diffusion through a geomembrane-based 

composite permanent cover occurs under Verification 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 the 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 verification test case involves a single cell, aqueous diffusive 

transport through a soil liner was evaluated (there is no aqueous 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 (infiltration, 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 representative exponential decay curve for comparison. 

D.1.8 Verification Case 8: Vapor Diffusive 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 geomembrane 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 transport 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, degradation, air production rates, and water 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 simulation (including before closure). Vapor diffusion 

through the bottom of the cell was disabled by setting the moisture content equal to the porosity. 

Figure D-7 shows the successful comparison between the 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 decay 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) using a Carslaw and Jaeger solution to the diffusion 

equation as presented in Appendix C. This approach produces an average flux with no cover 

(Javg). 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 from the analytical solution in Equation D-10. 

Other transport pathways were disabled for this verification exercise (infiltration, degradation, 

air production rates, and water diffusivity set to zero). As required 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 predicted 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 mass. 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-cover mass loss is significantly lower than in this 

verification scenario. 

D.1.10 Verification Case 10: Vapor Diffusive 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 LHR Ct Ce−

= (Equation D-11) 
Draft Appendix D Landfill Source Model Testing 

D-10 

The formulation of diffusive transport in air through a soil liner was verified by 

comparing single-cell simulation results with results generated from the analytical solution in 

Equation D-11. Other transport pathways were disabled for this verification exercise (infiltration, 

degradation, and air production rates 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 Diffusive Transport through a Composite 

Liner 

The model can simulate vapor diffusion through a composite liner made up of a 

geomembrane and a soil layer. The analytical solution 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 the harmonic mean of the geomembrane permeation 

coefficient and the soil diffusion coefficient. 

The formulation of diffusive transport in air through a composite liner was verified by 

comparing single-cell simulation results with results generated from the analytical solution in 

Equation D-12. Other transport pathways were disabled for this verification exercise (infiltration, 

degradation, air production rates, and water diffusivity set to zero). Diffusion through the top of 

the cell was disabled by setting the moisture content equal to the porosity for all cover types. 

Figure D-10 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 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 through a composite landfill 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 the harmonic mean of the geomembrane permeation 

coefficient and the soil diffusion coefficient. 

The formulation of diffusive transport in water through a composite liner was verified by 

comparing single-cell simulation results with results generated using the analytical solution in 

Equation D-13. Other transport pathways were disabled 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. Given 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 the diffusion equation presented in 

Appendix C. The analytical solution below describes the change in total concentration over time 

with no liner due to diffusion in air through the underlying unsaturated zone: 

0 ( )

a

u a

D t L HR Ct Ce−

= (Equation D-14) 

The formulation of diffusive transport in air with no liner was verified by comparing 

single-cell simulation results with results generated 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 zero). Diffusion through the top of 

the cell was disabled by setting the moisture content equal to the porosity for all cover types. 

Figure D-12 shows the successful comparison between the 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 decay curve for comparison. 

D.1.14 Verification Case 14: Aqueous 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 analytical solution to the diffusion equation presented in 

Appendix C. The analytical solution below describes the 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 water with no liner was verified by comparing 

single-cell simulation results with results generated 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 increase the mass loss attributable to 

aqueous diffusion (without the increase, the concentration change would be too small for 

effective comparison with the analytical solution). Figure D-13 shows the successful comparison 

between the 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 decay curve for comparison. 

D.1.15 Verification Case 15: Base Case Simulation/Simultaneous Mechanisms 

The verification cases above consider different transport mechanisms in independent 

simulations. Verification Case 15 considers multiple transport mechanisms acting 

simultaneously. The analytical solution below describes the change in total 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 rate; degradation in the 

solid, gas, and aqueous phases; diffusion in air through an overlying soil cover and an underlying 

soil liner; and diffusion in water through an underlying 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 cover and liner input parameters are 

the same and are consistent between cover types. 

Verification Case 15 involved comparing single-cell simulation results with results 

generated from the analytical solution in Equation D-16. A working version of the model was 

used to hold the gas production rate 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 predicted by the model and that generated by a spreadsheet using the 

solution presented above. 

D.1.16 Verification Case 16: Accuracy of the Landfill Waste Addition Algorithm 

The landfill waste addition algorithm describes the 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 location and timing. For example, the algorithm 

maintains information about whether 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, column ID, whether the cell is a top cell, whether 

the cell is a bottom cell, and the top configuration (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 corresponding mass loading rate). The industrial wipes risk modeling 

was performed using a single input concentration. If results scale linearly with the input 

concentration, 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 concentration. 

Model linearity verification involved a series of test cases with different initial 

concentrations. The input parameter values corresponded to the base case values in Table D-4. 

Five simulations were performed with input concentrations of 0.01, 0.1, 1, 10, and 100. The 

results were compared, and all mass loss results scaled linearly with the input concentration. 

D.3 Model Robustness and Sensitivity Testing 

The robustness testing evaluates the model effectiveness and reliability in simulating the 

range of conditions anticipated for the industrial wipes risk assessment. Robustness testing 

scenarios explore the model behavior using specific chemicals and conditions representative of 
Draft Appendix D Landfill Source Model Testing 

D-13 

the extremes of anticipated parameter space (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 testing requirements, and Table D-6

provides a summary of the robustness tests and 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 across 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 constituent 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 robustness testing was to select parameter combinations that 

would maximize and minimize the transport process under consideration. For example, Test 

Cases 1 and 2 respectively maximize and minimize 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 constant for the robustness testing. Table D-8 lists the range of 

variable parameter values within the risk assessment database and the parameterization scheme 

for each robustness test. As the table indicates, the robustness tests will use the maximum, 

minimum, or median values within the parameter space. The chemicals with the maximum and 

minimum volatility are tetrachloroethylene 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/m3 1 

Total simulation time yr 200 

Initial timestep day 0.33 

RK truncation error tolerance - 1.00E-12 

Infinite sum truncation 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 cm2/sec -9999 

Air diffusivity reference temperature C 25 

Diffusivity in water cm2/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 0.0015 
Draft Appendix D Landf

Table D-8. Robustness Testing Variable Input Parameter Values 
Draft Appendix D Landfill Source Model Testing 

D-17 

Each robustness test included evaluations for simulation runtime, mass conservation, and 

numerical accuracy (Robustness Requirements 1 through 3). These evaluations ensure that 

Requirements 1 through 3 are maintained throughout 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 required, a short simulation runtime is critical 

to implementing the Monte Carlo–based risk assessment. The industrial 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 single 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 balance 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 balance 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 the 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 decreases. Preliminary simulations suggest that an 

error tolerance of 1e-11 provides 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 value for the range of parameter space anticipated 

for the risk assessment. 

This section describes the design and results of specific robustness tests. Documentation 

of the robustness testing includes the total mass loss per pathway 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 results 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 air, 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 (landfill 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: Maximum/Minimum Vapor-Phase Advection 

The model should reliably simulate the scenarios 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 waste properties (Henry’s law constant, organic 

carbon distribution coefficient, fraction organic carbon, moisture 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 values 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 relative 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 overlying 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; the rate decreases because an increasing 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 constant 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); however, the no-cover flux only applies to the active 

daily cell, so that the no-cover mass loss contribution is smaller relative to the entire landfill 

waste. Diffusion to groundwater is the primary mechanism for 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). Figure D-16b shows that no-cover mass loss is the 

dominant mechanism for transfer of mass to the atmosphere. The decrease in diffusion through 

the cover at 17.8 years occurs when the permanent cover is placed over the landfill cell. These 

results collectively show the expected model behavior associated with maximizing and 

minimizing vapor-phase advection. The relevant robustness requirements are satisfied. 
Draft Appendix D Landf

Table D-9a. Robustness Testing Summary Results (Median and Test Cases 1–4) 

Robustness Testing Ca

Median Value Cases 1 2 3 

No Liner Composite Liner Vapor Advection Aq

Total 

Mass 

Loss per 

Pathway 

(total g) Max H Min H Max H Min H Max Min Max 

Vapor advection to atmosphere 

2.74E+08 72.72% 351313 0.16% 2.62E+08 73.91% 333963 0.16% 2.92E+08 79.20% 77734.9 0.04% 50806.4 

Diffusion to atmosphere 

9.55E+07 25.33% 433212 0.20% 7.67E+07 21.63% 321316 0.15% 7.39E+07 20.07% 107262 0.06% 339075 

Loss with no cover (also included in diffusion to air) 

1.26E+07 3.35% 268443 0.12% 1.22E+07 3.44% 258913 0.12% 2.91E+07 7.89% 78788.9 0.04% 292153 

Decay in water 

2.51E+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 

Aqueous advection to bottom 

1.20E+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 

Loss to liner leakage 

1.20E+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 

Diffusion to groundwater 

3.65E+06 0.97% 177406 0.08% 1.23E+07 3.47% 805101 0.38% 2.50E+06 0.68% 525356 0.27% 109077 

Total loss to air 

3.70E+08 98.05% 784528 0.36% 3.39E+08 95.54% 655275 0.31% 3.66E+08 99.27% 184996 0.10% 389881 

Total loss to groundwater 

4.84E+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 

Mass released from system 

3.77E+08 2.19E+08 3.55E+08 2.09E+08 3.68E+08 1.94E+08 3.79E+08 

Mass added to system 

3.89E+08 3.89E+08 3.69E+08 3.69E+08 3.69E+08 3.69E+08 3.89E+08 

Mass remaining within landfill 

1.08E+07 1.70E+08 1.31E+07 1.59E+08 366713 1.74E+08 8.32E+06 

% mass balance error 

0.37% 0.29% 0.36% 0.30% 0.15% 0.21% 0.52% 

Mass remaining within landfill (%) 

2.77% 43.57% 3.56% 43.00% 0.10% 47.22% 2.14% 
Draft Appendix D Landf

Robustness Testing Ca

Median Value Cases 1 2 3 

No Liner Composite Liner Vapor Advection Aq

Total 

Mass 

Loss per 

Pathway 

(total g) Max H Min H Max H Min H Max Min Max 

Simulation stopped by mass loss criterion 

No No No No Yes No No 

Final time 200.18 201.362 201.855 201.362 191.226 202.11 200.241 Simulation runtime 

0.1 0.0833333 0.1 0.1 0.15 0.083333 0.1 

Table D-9b. Robustness Testing Summary Results (Test Cases 5–12) 

Robustness Testing Cases 

5 6 7 8 9 10 11 

Vapor Diffusion Aqueous Diffusion Degradation No-L

Total 

Mass 

Loss per 

Pathway 

(total g) Max Min Max Min Max Min Max 

Vapor advection to atmosphere 

1.06E+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 

Diffusion to atmosphere 

2.82E+08 72.39% 84108.4 0.05% 0 0.00% 0.00E+00 0.00% 393561 0.11% 7.00E+07 20.34% 9.74E+07 

Loss with no cover (also included in diffusion to air) 

3.01E+07 7.75% 78788.9 0.04% 0 0.00% 0.00E+00 0.00% 369723 0.10% 1.09E+07 3.16% 3.01E+07 

Decay in water 

231510 0.06% 1.73E+08 98.08% 2.34E+08 96.26% 3671160 1.28% 3.64E+08 99.52% 868861 0.25% 280682 

Aqueous advection to bottom 

197908 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 

Loss to liner leakage 

197908 0.05% 80281 0.05% 109826 0.05% 5.24E+03 0.00% 2538.87 0.00% 1.23E+06 0.36% 102897 

Diffusion to groundwater 

860833 0.22% 533853 0.30% 993495 0.41% 3.13E+04 0.01% 20024.6 0.01% 1.35E+07 3.93% 8.38E+07 

Total loss to air 

3.88E+08 99.67% 262437 0.15% 659188 0.27% 2.82E+08 98.52% 459453 0.13% 3.28E+08 95.46% 3.04E+08 

Total loss to groundwater 

1.06E+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 
Draft Appendix D Landf

Robustness Testing Cases 

5 6 7 8 9 10 11 

Vapor Diffusion Aqueous Diffusion Degradation No-L

Total 

Mass 

Loss per 

Pathway 

(total g) Max Min Max Min Max Min Max 

Mass released from system 

3.89E+08 1.76E+08 2.43E+08 2.86E+08 3.66E+08 3.44E+08 3.88E+08 

Mass added to system 

3.89E+08 3.69E+08 3.69E+08 3.69E+08 3.69E+08 3.69E+08 3.89E+08 

Mass remaining within landfill 

389018 1.92E+08 1.24E+08 8.06E+07 364705 2.37E+07 388612 

% mass balance error 

0.02% 0.21% 0.48% 0.63% 0.80% 0.37% 0.26% 

Mass remaining within landfill (%) 

0.10% 52.08% 33.59% 21.83% 0.10% 6.43% 0.10% 

Simulation stopped by mass loss criterion 

Yes No No No Yes No Yes 

Final time 50.0011 201.781 201.362 202.222 21.6581 201.655 38.3756 Simulation runtime 

0.16667 0.083333 0.083333 0.066667 0.1 0.1 0.1 

Table D-9c. Robustness Testing Summary Results (Test Cases 13–18) 

Robustness Testing Cases 

13 14 15 16 17 

No-Liner Aqueous Diffusion No-Cover Diffusion Land

 (total g Total 

Mass Loss 

per Pathway 

) Max Min Max Min Max 

Vapor advection to atmosphere 

663007 0.23% 2.47E+08 72.71% 2.42E+08 65.91% 176191 0.10% 1.82E+09 94.31% 

Diffusion to atmosphere 

795626 0.28% 8.71E+07 25.67% 1.17E+08 31.77% 93268 0.05% 8.30E+07 4.30% 

Loss with no cover (also included in diffusion to air) 

499906 0.17% 9.42E+06 2.77% 4.01E+07 10.93% 61181.7 0.03% 3.88E+07 2.01% 

Decay in water 2.24E+08 77.87% 2.98E+06 0.88% 651765 0.18% 1.72E+08 96.95% 1.85E+07 0.96% 
Draft Appendix D Landf

Robustness Testing Cases 

13 14 15 16 17 

No-Liner Aqueous Diffusion No-Cover Diffusion Land

 (total g Total 

Mass Loss 

per Pathway 

) Max Min Max Min Max 

Aqueous advection to bottom 

5.18E+07 18.03% 2.20E+06 0.65% 353037 0.10% 4.60E+06 2.60% 2.68E+05 0.01% 

Loss to liner leakage 

5.18E+07 18.03% 2.20E+06 0.65% 1002.7 0.00% 80162.5 0.05% 1500.24 0.00% 

Diffusion to groundwater 

1.03E+07 3.60% 3.02E+05 0.09% 7.49E+06 2.04% 533066 0.30% 8.18E+06 0.42% 

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% Total loss to groundwater 

6.22E+07 21.63% 2.51E+06 0.74% 7.50E+06 2.04% 613228 0.35% 8.18E+06 0.42% 

Mass released from system 

2.87E+08 3.39E+08 3.67E+08 1.77E+08 1.93E+09 

Mass added to system 

3.89E+08 3.89E+08 3.69E+08 3.69E+08 2.09E+09 

Mass remaining within landfill 

9.93E+07 4.85E+07 1.22E+06 1.91E+08 1.51E+08 

% mass balance error 

0.65% 0.38% 0.19% 0.21% 0.24% 

Mass remaining within landfill (%) 

25.51% 12.44% 0.33% 51.85% 7.25% 

Simulation stopped by mass loss criterion 

No No No No No 

Final time 201.362 200.426 200.148 201.362 202.406 Simulation runtime 0.083333 0.083333 0.1166667 0.083333 0.1 
Draft Appendix D Landfill Source Model Testing 

D-23 

D.3.2 Robustness Tests 3 and 4: Maximum/Minimum Aqueous-Phase Advection 

The model should reliably simulate the scenarios 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 carbon distribution coefficient, fraction organic 

carbon, moisture content, porosity, and bulk density). These parameters were set to values that 

maximize and minimize the infiltration and liner leakage rates and the mass partitioning to water, 

as described in Table D-8 under Test Cases 3 and 4. The parameter values selected were the 

endpoint values 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 relative contribution of aqueous-phase advection follows the 

expected pattern (68 percent versus 0 percent 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 significant, which appears to be a general pattern 

as the significance of vapor-phase loss decreases. Also, no-cover loss is the most dominant 

vapor-phase loss mechanism, although the relative significance of vapor losses is small. As 

expected by the input parameters, aqueous advection 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 advection is relatively insignificant. These results collectively show 

the expected model behavior associated with maximizing and minimizing aqueous-phase 

advection. The relevant robustness requirements are satisfied. 

D.3.3 Robustness Tests 5 and 6: Maximum/Minimum Vapor-Phase Diffusion 

The model should reliably simulate scenarios and constituents with the maximum and 

minimum potential chemical diffusion rates in air. Parameters controlling the vapor-phase 

diffusion rate include air diffusivity, phase partitioning waste properties (moisture content, 

porosity, bulk density, organic carbon distribution coefficient, and fraction organic carbon), 

cover/liner properties (type, thickness, moisture content, porosity), and the 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 under 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 parameter space associated with the industrial wipes 

risk assessment. 

Table D-9 shows that the relative 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 dominates the mass loss. The influence of vaporphase fluxes can even be seen in groundwater losses 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 results collectively show the expected model 
Draft Appendix D Landfill Source Model Testing 

D-24 

behavior associated with maximizing and minimizing vapor-phase diffusion. The relevant 

robustness requirements are satisfied. 

D.3.4 Robustness Tests 7 and 8: Maximum/Minimum Aqueous-Phase Diffusion 

The model should reliably simulate the scenarios and constituents with the maximum and 

minimum potential chemical diffusion rates in water. Parameters controlling the aqueous-phase 

diffusion rate include the water diffusivity, phase partitioning waste properties (moisture content, 

porosity, bulk density, organic carbon distribution coefficient, and fraction organic carbon), and 

cover/liner properties (type, thickness, moisture content, porosity). These parameters were set to 

values that maximize and minimize the diffusion coefficients and the phase partitioning to water, 

as described in Table D-8 under Test Cases 7 and 8. The parameter values selected were the 

endpoint values 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 relative contribution of diffusion 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 diffusion 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 dominated by degradation, because the vapor-phase 

partitioning and transport parameters were minimized 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 aqueous-phase diffusion. The relevant robustness 

requirements are satisfied. 

D.3.5 Robustness Tests 9 and 10: Maximum/Minimum Degradation Rate 

The model should reliably simulate the scenarios and constituents with the maximum and 

minimum potential mass loss through first-order degradation. Parameters controlling mass loss 

through degradation include the decay rates and phase-partitioning waste properties (moisture 

content, porosity, bulk density, organic carbon distribution coefficient, and fraction organic 

carbon). These parameters were set to values that maximize and minimize the degradation rate, 

as described in Table D-8 under Test Cases 9 and 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 degradation occurs for the risk assessment). The parameter values 

selected were the endpoint values 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 relative contribution of degradation 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 particular pathways over time for Test 

Case 9. Test Case 9 is dominated 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 pathways over time for Test Case 10. Test Case 10 

is dominated by vapor advection rather than degradation, as expected. These results collectively 

show the expected model behavior associated with maximizing and minimizing aqueous-phase 

degradation. The relevant robustness 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 scenarios and constituents with the maximum and 

minimum potential mass loss through diffusion with no liner. Parameters controlling diffusive 

mass loss with no liner include unsaturated zone parameters (depth to water, moisture content, 

and porosity), diffusivities, and phase-partitioning waste parameters (moisture content, porosity, 

bulk density, organic carbon distribution coefficient, and fraction organic carbon). These 

parameters were set to values that maximize and 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 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 relative contribution of diffusion 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 diffusive loss to groundwater is much more significant 

in Test Case 11 than Test Case 12, as expected. These results collectively show the expected 

model behavior associated with maximizing and 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 scenarios and constituents with the maximum and 

minimum potential chemical diffusion rates in water with no liner. Parameters controlling the 

aqueous-phase diffusion rate with no liner include the water diffusivity, phase partitioning waste 

properties (moisture content, porosity, bulk density, organic carbon distribution coefficient, and 

fraction organic carbon), and unsaturated 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 parameter values selected were 

the endpoint values 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 relative contribution of diffusion 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 degradation, 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 particular pathways over time for Test 

Case 14. Test Case 14 is dominated by vapor advection, because the chemical is the more 
Draft Appendix D Landfill Source Model Testing 

D-26 

volatile tetrachloroethylene. These results collectively show the expected model behavior 

associated with maximizing and minimizing aqueous-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 scenarios 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 partitioning waste properties (moisture 

content, porosity, bulk density, organic carbon distribution coefficient, and fraction organic 

carbon), daily cell geometry information, the working 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 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 relative 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 particular 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 Test 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 robustness requirements are satisfied. 

D.3.9 Robustness Tests 17 and 18 Maximum/Minimum Landfill Geometry 

The model should reliably simulate scenarios with the maximum and minimum landfill 

geometry characteristics. The primary geometric characteristic controlling transport is landfill 

height. Thus, parameters controlling height were set to maximum and minimum values, as 

described in Table D-8 under Test Cases 17 and 18. The parameter values selected were the 

endpoint values 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 the relative contribution of different mass loss pathways. Also, the mass 

balance and simulation time results meet the requirements. 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 volatile cresols for Test Case 18. Nevertheless, 

these simulations demonstrate that the model successfully simulates the endpoint geometries 

anticipated for the industrial wipes risk assessment. The relevant 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 field experiment with extensive control and 

monitoring of the landfill, including initial contaminant 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 developed 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 et al. (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 landfill behavior reported in the literature. 

Table D-10 shows the initial chemical concentrations used in the comparison 

simulations. Although there is a large degree of uncertainty in the initial contaminant 

concentrations, order of magnitude estimates are possible using assumed fractions of household 

hazardous waste (HHW) and chemicals within landfill waste. In California, HHW is estimated to 

comprise 0.2 percent (2,000 mg/kg) of landfilled waste (California Integrated Waste 

Management Board, 2004). This waste fraction includes containers of paint, vehicle fluids, used 

oil, batteries, and mixed residential HHW. Further 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/m3

(see Table D-10), the volumetric initial chemical concentration in the waste would range from 16 

to 16,000 mg/m3

. (HHW concentration in landfill waste × chemical concentration in HHW × wet 

density of waste). The assumed LFCR input concentrations 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/m3 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 volumetric concentration divided by the density of 

wet waste (795 kg/m3

). 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 landfill 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 measured landfill behavior using 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 results. All robustness tests use the standard version of the model. 

Some of the verification test cases used working versions of the model with specific processes 

disabled, as described above. Due to budget and schedule constraints, test packages will not be 

prepared and archived for this project. 

D.6 Summary 

The testing results documented in this appendix provide a comprehensive demonstration 

of the computational accuracy of transport mechanisms and pathways in the model. A series of 

verification test cases successfully verify the 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 ensured the model’s reliability throughout the anticipated range of 

parameter space for the industrial wipes risk assessment. The numerical accuracy, mass balance, 

and runtime satisfied the requirements for all robustness tests. The documentation of the tests 

would allow independent parties to reproduce the test results, if necessary. 

Due to resource and data availability constraints, we have not attempted 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 landfill via multiple pathways have been measured over long time 

scales (years). Should resources and data be available, model validation could be pursued. 

D.7 Symbols 

Ca Air-phase concentration [M/L3] 

Cs Solid-phase concentration [M/M] 

C Total concentration [M/L3

] 

C0 Initial total concentration [M/L3] 

Cw Water-phase concentration [M/L3

] 

Da Vapor-phase diffusion coefficient [L2

/T] 

Deq Equivalent diffusion coefficient for a composite geomembrane and soil layer [L2

/T] 

Dw Aqueous-phase diffusion coefficient [L2

/T] 

fa Fraction of total mass in the air phase [-] 

fw Fraction of total mass in the water phase [-] 

fs Fraction of total mass in the solid phase [-] 

H Cell/landfill height [L3

] 

Hcalc The domain height used for the no-cover flux, based on the angle to horizontal and the 

daily cell geometry [L] 

Javg Average no-cover flux [M/L2

T] 

k Landfill gas generation rate [/T] 

KH Henry’s law constant [-] 

Kd Solid-water phase distribution coefficient [L3

/M] 

L Length of the diffusive layer [L] 
Draft Appendix D Landfill Source Model Testing 

D-29 

Lo Methane generation capacity [L3/M] 

Lu Unsaturated zone thickness [L] 

Min,tot Cumulative total mass entering the landfill during a simulation [M] 

Min(i) Mass entering the landfill over time step i [M] 

Mlf Mass stored within the landfill [M] 

Mlf(i) Mass stored within the landfill over time step i [M] 

Mout,tot Cumulative total mass leaving the landfill during a simulation [M] 

Mout(i) Mass leaving the landfill over time step i [M] 

N Net infiltration rate [L/T] 

qa Landfill gas generation rate, per landfill waste volume [/T] 

Ra Air-phase to total concentration partition coefficient [-] 

Rs Solid-phase to total concentration partition coefficient [-] 

Rw Water-phase to total concentration partition coefficient [-] 

t Time [T] 

V Cell/landfill volume [L3

] 

W Mass of waste [M] 

εa Air-phase volumetric fraction [L3/L3] 

εw Water-phase volumetric fraction [L3/L3] 

λa1 Biotic first-order degradation rate in the air phase [/T] 

λw1 Biotic first-order degradation rate in the water phase [/T] 

λs1 Biotic first-order degradation rate in the solid phase [/T] 

λa2 Abiotic first-order degradation rate in the air phase [/T] 

λw2 Abiotic first-order degradation rate in the water phase [/T] 

λs2 Abiotic first-order degradation rate in the solid phase [/T] 

ρb Solid-phase bulk density [solid mass/total volume M/L3] 

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. Kjeldsen, 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 Board, 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 Environmental Science and Technology 32(4):297–336. 

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. 

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 (LandGEM) Version 3.02 User’s Guide. 

EPA-600/R-05/047. U.S. EPA, Office of Research 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

Years

Gas 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

Years

C/Co

Analytical

LFCR

Draft Appendix D Landfill Source Model Testing

D-31
Figure D-3

LFCR Verification Case 4

Advective Aqueous Transport

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 2000000 4000000 6000000 8000000 10000000 12000000 14000000

Years

C/Co

Analytical

LFCR

Figure D-4

LFCR Verification Case 5

Degradation/Transformation

0

0.1

0.2

0.3

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

Years

C/Co

Analytical

LFCR

Draft Appendix D Landfill Source Model Testing

D-32
Figure D-5

LFCR Verification Case 6

Vapor Diffusive Transport

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

Years

C/Co

Analytical

LFCR

Figure D-6.

LFCR Verification Case 7

Aqueous Diffusive Transport

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 20000 40000 60000 80000 100000 120000 140000 160000 180000 200000

Years

C/Co

Analytical

LFCR

Draft Appendix D Landfill Source Model Testing

D-33
Figure 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

Years

C/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

Years

C/Co

Analytical

LFCR

Draft Appendix D Landfill Source Model Testing

D-34
Figure 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

m3

 Initial concentration

Do 0.705894 m2

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

Porosity2 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 L2 



e

D ( ) 2 n 1 2  S

2  t

4 L2 





=



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  ( ) 0.07795 t_inc kg

m2day

 

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

Years

C/Co

Analytical

LFCR

Draft Appendix D Landfill Source Model Testing

D-35
Figure 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

Years

C/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

Years

C/Co

Analytical

LFCR

Draft Appendix D Landfill Source Model Testing

D-36
Figure 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

Years

C/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

Years

C/Co

Analytical

LFCR

Draft Appendix D Landfill Source Model Testing

D-37
Figure 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

Years

C/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

Years

Mass Loss (g/day)

Aqueous Degradation

Vapor Advection

Diffusion With Cover

No Cover Loss

Aqueous Advection

Diffusion to Groundwater

Draft Appendix D Landfill Source Model Testing

D-38
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Groundwater

Diffusion to Groundwater

Leaching

Draft Appendix D Landfill Source Model Testing

D-39
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Atmosphere

Vapor Advection

Diffusion With Cover

No Cover Loss

Draft Appendix D Landfill Source Model Testing

D-40
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Aqueous Degradation

Vapor Advection

Diffusion With Cover

No Cover Loss

Aqueous Advection

Diffusion to Groundwater

Draft Appendix D Landfill Source Model Testing

D-41
Figure D-17b.

Mass Loss to Atmosphere

Robustness Testing Case 3

0

50

100

150

200

250

0 10 20 30 40 50 60

Years

Mass 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

Years

Mass Loss (g/day)

Total to Groundwater

Diffusion to Groundwater

Leaching

Draft Appendix D Landfill Source Model Testing

D-42
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Atmosphere

Vapor Advection

Diffusion With Cover

No Cover Loss

Draft Appendix D Landfill Source Model Testing

D-43
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Aqueous Degradation

Vapor Advection

Diffusion With Cover

No Cover Loss

Aqueous Advection

Diffusion to Groundwater

Draft Appendix D Landfill Source Model Testing

D-44
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Groundwater

Diffusion to Groundwater

Leaching

Draft Appendix D Landfill Source Model Testing

D-45
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Atmosphere

Vapor Advection

Diffusion With Cover

No Cover Loss

Draft Appendix D Landfill Source Model Testing

D-46
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Aqueous Degradation

Vapor Advection

Diffusion With Cover

No Cover Loss

Aqueous Advection

Diffusion to Groundwater

Draft Appendix D Landfill Source Model Testing

D-47
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Groundwater

Diffusion to Groundwater

Leaching

Draft Appendix D Landfill Source Model Testing

D-48
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Atmosphere

Vapor Advection

Diffusion With Cover

No Cover Loss

Draft Appendix D Landfill Source Model Testing

D-49
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Aqueous Degradation

Vapor Advection

Diffusion With Cover

No Cover Loss

Aqueous Advection

Diffusion to Groundwater

Draft Appendix D Landfill Source Model Testing

D-50
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Groundwater

Diffusion to Groundwater

Leaching

Draft Appendix D Landfill Source Model Testing

D-51
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Atmosphere

Vapor Advection

Diffusion With Cover

No Cover Loss

Draft Appendix D Landfill Source Model Testing

D-52
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Aqueous Degradation

Vapor Advection

Diffusion With Cover

No Cover Loss

Aqueous Advection

Diffusion to Groundwater

Draft Appendix D Landfill Source Model Testing

D-53
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Groundwater

Diffusion to Groundwater

Leaching

Draft Appendix D Landfill Source Model Testing

D-54
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Atmosphere

Vapor Advection

Diffusion With Cover

No Cover Loss

Draft Appendix D Landfill Source Model Testing

D-55
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Aqueous Degradation

Vapor Advection

Diffusion With Cover

No Cover Loss

Aqueous Advection

Diffusion to Groundwater

Draft Appendix D Landfill Source Model Testing

D-56
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Groundwater

Diffusion to Groundwater

Leaching

Draft Appendix D Landfill Source Model Testing

D-57
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Atmosphere

Vapor Advection

Diffusion With Cover

No Cover Loss

Draft Appendix D Landfill Source Model Testing

D-58
Figure 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

Years

Mass 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 10 20 30 40 50 60

Years

Mass Loss (g/day)

Aqueous Degradation

Vapor Advection

Diffusion With Cover

No Cover Loss

Aqueous Advection

Diffusion to Groundwater

Draft Appendix D Landfill Source Model Testing

D-59
Figure 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

Years

Mass 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 10 20 30 40 50 60

Years

Mass Loss (g/day)

Total to Groundwater

Diffusion to Groundwater

Leaching

Draft Appendix D Landfill Source Model Testing

D-60
Figure 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

Years

Mass 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

Years

Mass Loss (g/day)

Total to Atmosphere

Vapor Advection

Diffusion With Cover

No Cover Loss

Draft Appendix D Landfill Source Model Testing

D-61
Figure 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

Years

Mass 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

Years

mg/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)

Draft Appendix D Landfill Source Model Testing

D-62
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

Years

mg/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

Years

mg/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)

Draft Appendix D Landfill Source Model Testing

D-63
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

Years

mg/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

Years

mg/m3

Leachate

Landfill Gas

Reported range in measured 

MEK concentrations in 

leachate (110 - 6600 mg/m3)

No reported concentrations in landfill gas

Draft Appendix D Landfill Source Model Testing

D-64
Draft Appendix E Landfill Source Modeling Parameters 

E-1 

Appendix E 

Landfill Source Modeling Parameters 

This appendix presents input parameter values and distributions used by the landfill 

source model, and includes a table with the parameter name, unit, value, and reference 

information. 
Parameter Units Value Reference/Notes

 Draft Appendix E Source Modeling Parameters

Table E-1. Source Model Variables for Landfills

Cover/Liner Characterization (See Section 3.1.2.2)

6", consistent with Subtitle D 

regulations.

Ldc Daily cover thickness m 0.152

60 mil, consistent with Subtitle D 

regulations

Lgm Geomembrane thickness m 0.0015

12", consistent with Subtitle D 

regulations

Lic Interim cover thickness m 0.305

2 ft, consistent with Subtitle D 

regulations

Liner thickness No Liner scenario: NA

Composite liner 

Scenario: 0.61

Ll m

2 ft, consistent with Subtitle D 

regulations

Lpc Final cover thickness 0.61 m

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 Units Value Reference/Notes

 Draft Appendix E Source Modeling Parameters

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)

Lu Depth to watertable EPACMTP DSOIL m See Appendix F.

The effective porosity for the specific 

EPACMTP regional soil type 

(ISTYPE1). See Appendix F.

Unsaturated zone porosity unitless EPACMTP WCS

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)

Inf_post m/yr

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)

Inf_pre m/yr

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)

Leach_post m/yr

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)

Leach_pre m/yr

E-3
Parameter Units Value Reference/Notes

 Draft Appendix E Source Modeling Parameters

Table E-1. Source Model Variables for Landfills

Landfill Characterization (See Section 3.1.2.4)

Landfill cell area Total landfill area / Calculated

number of landfill cells. 

(Number of landfill cells 

= total landfill active life 

/ landfill cell active life).

Alfc m2

Atot Total landfill area m2 EPACMTP AREA Based on EPA-WBJ data.

Barlaz (2006). Typical industry 

practice.

Fraction of day without a 

cover

Fnc unitless 0.33

Aivaliotis et al. (2004) and Barlaz 

(2006).

Daily cell/lift height Uniform distribution, 

min=1.2, max=6.1

Htarg m

Barlaz (2006). Typical industry 

practice.

Daily cell waste sublayer 

period

SubLayT hr 1

Based on EPA-WBJ data. Adjusted to 

be evenly divisible by the landfill cell 

active life.

Tlf Landfill active life yr EPACMTP Active Life

Barlaz (2006). Typical industry 

practice.

Landfill cell active life Uniform distribution, 

min=3, max=5

Tlfc yr

Barlaz (2006). Typical industry 

practice.

Time before final cover 

installed on landfill 

cell/section

Triangular distribution, 

min=10, max=30, 

mode=15

Tpc yr

Landfill cell volume total landfill volume / Calculated

number of landfill cells. 

(Number of landfill cells 

= total landfill active life 

/ landfill cell active life).

Vlfc m3

Calculated. Depth and area based on 

EPA-WBJ data.

Total landfill volume EPACMTP DEPTH x 

EPACMTP AREA

Vtot m3

Working face angle to Aivolatis et al. (2004)

horizontal

Triangular distribution, 

min=12, max=30, 

mode=18

Wfangle deg

Simulation Parameters (See Section 3.1.2.5)

Setting equal to Fnc provides runtime 

efficiency.

dt_init Initial timestep day Set to Fnc: 0.33

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)

FracStop unitless 0.001

E-4
Parameter Units Value Reference/Notes

 Draft Appendix E Source Modeling Parameters

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

InfSum_tol unitless 1e-12

Liner type (0=no liner, 

2=composite liner)

LinerType Scenario specific

1 day is inherent to the source model. 

Varied only for testing.

Tcell Daily cell period day 1

Adjusted to maintain a mass balance 

error < 1% for all robustness testing 

simulations (See Appendix D).

RK truncation error 

tolerance

TruncErr_tol unitless 1e-11

In all testing simulations, the mass loss 

after 200 years was insignificant (see 

Appendix D).

Tsim Total simulation time yr 200

Waste Characterization (See Section 3.1.2.6)

Average waste temperature Triangular distribution, Barlaz (2006)

min=30, max=45, 

mode=37.5

AvgT deg C

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

BD kg/L

The input concentration was 

normalized to 1. (Note that the results 

were normalized to a constant mass 

loading rate for risk modeling.)

Cin Initial concentration kg/m3 1

Organic carbon fraction in Bartelt-Hunt (2006) and Barlaz (2006).

waste

Uniform distribution, 

min=0.4, max=0.6

focW unitless

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

Lo L/kg

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 Units Value Reference/Notes

 Draft Appendix E Source Modeling Parameters

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. Panagiotakopoulos. 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 development and parameterization of the LFCR landfill 

source model.” Multiple phone and email communications from Dr. Morton Barlaz, 

Professor, Water Resources/Environmental Engineering, North Carolina State University, 

to Michael I. Lowry, RTI. July through December. 

Bartelt-Hunt, S. 2006. “Topics relevant to development and parameterization of the LFCR 

landfill source model.” Multiple phone and email communications from Dr. Shannon L. 

Bartelt-Hunt, Assistant Professor, 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. Kjeldsen, 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 Geoenvironmental 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 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. 

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. 
[This page intentionally left blank.] 
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 Ref

Table F-1. Groundwater Model Variables

Comments

 Draft Appendix F GroAquiferAL Longitudinal dispersivity 

(aquifer)

m Empirical Calculated from a national distribution 

and radial distance to well (RADIS)

See a

ANGLE Angle of well off plume 

centerline

Degrees Uniform Randomly selected from uniform 

distribution

U.S. 

ANIST Anisotropy ratio Unitless Constant 1 No anisotropy U.S. AT Transverse dispersivity m Derived Calculated by EPACMTP U.S. 

Derived from longitudinal dispersivity

AV Vertical dispersivity m Derived Calculated by EPACMTP U.S. 

Derived from longitudinal dispersivity

BULKD Bulk density g/cm3 Derived Calculated by EPACMTP U.S. 

Derived from porosity

DIAM Avg. particle diameter cm Empirical Randomly selected from national 

distribution

See a

FOC Fraction organic carbon (FOC) g/g Johnson SB Randomly selected from national 

distribution

Mean = 0.000432; stdev = 0.0456; min = 0; max U.S. = 0.0638

GRADNT Hydraulic gradient m/m Empirical 

correlated

Aquifer-specifc See a

Randomly selected based on aquifer code (IGWR) using EPACMTP

PH Groundwater pH std. Units Empirical Randomly selected from national 

distribution

Assumed equal to average soil pH for 20-mi See aradius around location

POR Effective porosity Unitless Derived Calculated by EPACMTP U.S. 

Derived from particle diameter

RADIS Radial distance to well (R) m Empirical Randomly selected from national 

distribution

EPA OSW survey of landfills See a

RETARD Retardation coefficient Unitless Derived Calculated by EPACMTP U.S. 

Derived from bulk density, Kd, and porosity

TEMP Groundwater temperature DegreesC Constant Site-specific Todd

Groundwater temperature map; average for 20-mi radius around location

VXCS Groundwater seepage velocity m/yr Derived Calculated by EPACMTP U.S. 

Derived from conductivity and gradient

XKX Longitudinal hydraulic 

conductivity (K)

m/yr Empirical 

correlated

Aquifer-specifc See a

Randomly selected based on aquifer code (IGWR) using EPACMTP

XWELL Longitudinal distance to well m Derived Calculated by EPACMTP U.S. 

Derived from radial distance (R) and angle to the well

YWELL Distance from plume 

centerline to well

m Derived Calculated by EPACMTP U.S. 

Derived from radial distance (R) and angle to the well and constrained to lay within the areal plume extent

ZB Aquifer thickness m Empirical 

correlated

Aquifer-specifc See a

Randomly selected based on aquifer code (IGWR) using EPACMTP

ZWELL Depth of well below water table Fraction Uniform Randomly selected from uniform distr. 

within ZB or within upper 10 m of aquifer if ZB>10 m

U.S. 
Variable ID Parameter Units Type Value Ref

Table F-1. Groundwater Model Variables

Comments

 Draft Appendix F GroChemicalAHYDR 2nd order acid hydrolysis rate 1/mol/yr Constant Chemical-specific KolliBHYDR 2nd order base hydrolysis rate 1/mol/yr Constant Chemical-specific KolliBIOS Biodegradation rate in aquifer 1/yr Constant 0 No biodegradationBIOU Biodegradation rate in vadose 

zone

1/yr Constant 0 No biodegradation

CSLAM Chemical decay rate in aquifer 1/yr Derived Calculated by EPACMTP U.S. 

Derived from dissolved and sorbed rates for organics only

CZERO Leachate concentration mg/L Derived Calculated by LFCR Transient mass fluxes generated by LFCR and 

read by EPACMTP, converted to transient concentrations

DSTAR Molecular diffusion coefficient m2/yr Constant Chemical-specific U.S. 

attac

KOC Organic carbon distribution 

coefficient (KOC)

mL/g Constant Chemical-specific Kolli

NHYDR Neutral hydrolysis rate 1/yr Constant Chemical-specific KolliRLAM1 Dissolved hydrolysis rate 1/yr Derived Calculated by EPACMTP U.S. 

Derived from rate constants

RLAM2 Sorbed hydrolysis rate 1/yr Derived Calculated by EPACMTP U.S. 

Derived from rate constants

RTEMP Reference temperature C Constant Chemical-specific KolliSFCOF Freundlich isotherm 

coefficient (Kd) in aquifer

cm3/g Derived or 

empirical isotherm

Chemical-specific U.S. 

Function of KOC and POM

SFEXP Freundlich isotherm exponent 

in aquifer

Unitless Constant 1 Linear sorption

UCLAM Chemical decay rate 1/yr Derived Calculated by EPACMTP U.S. 

Derived from dissolved and sorbed rates

UFCOF Freundlich isotherm 

coefficient (Kd) in vadose zone

cm3/g Derived or 

empirical isotherm

Chemical-specific U.S. 

Function of KOC and POM

UFEXP Freundlich isotherm exponent 

vadose zone

Unitless Constant 1 Linear sorption

ExposureCARC Groundwater averaging time yr Empirical Distributions of Child and Adult 

exposure times

Used to represent long-term concentration for chronic exposure
Variable ID Parameter Units Type Value Ref

Table F-1. Groundwater Model Variables

Comments

 Draft Appendix F GroVadoseALPHA Moisture retention parameter 

(a)

1/cm Constant Site-specific U.S. 

Randomly selected value from distribution for a given soil texture (ISTYPE1)

BETA Moisture retention parameter 

(b)

Unitless Constant Site-specific U.S. 

Randomly selected value from distribution for a given soil texture (ISTYPE1)

DISPR Longitudinal dispersivity 

(vadose)

m Derived Calculated by EPACMTP U.S. 

Derived from unsaturated zone thickness

DSOIL Unsaturated zone thickness m Empirical 

correlated

Aquifer-specifc See a

Randomly selected based on aquifer code (IGWR)

POM Percent organic matter (POM) % Constant Site-specific U.S. 

Randomly selected value from distribution for a given soil texture (ISTYPE1)

RHOB Soil bulk density g/cm3 Constant Site-specific U.S. 

Randomly selected value from distribution for a given soil texture (ISTYPE1)

SATK Saturated hydraulic 

conductivity

cm/hr Constant Site-specific U.S. 

Randomly selected value from distribution for a given soil texture (ISTYPE1)

WCR Residual water content L/L Constant Site-specific U.S. 

Randomly selected value from distribution for a given soil texture (ISTYPE1)

WCS Saturated water content L/L Constant Site-specific U.S. 

Randomly selected value from distribution for a given soil texture (ISTYPE1)

WMUAREA WMU area m2 Empirical Randomly selected from a national 

distribution

EPA

DBGS Depth of WMU base below 

ground surface

m Constant 0 Constant value of 0 used for groundwater 

modeling

DEPTH WMU depth m Derived Randomly selected from a national 

distribution

EPA

ICLR Climate Center Integer Constant Site-specific U.S. 

and F

Nearest appropriate climate center to WMU locations

IGWR Hydrogeologic Environment Integer Constant Site-specific See a

Derived using state-specific aquifer maps

ISTYPE1 Regional soil type Integer Constant WMU-Specific U.S. 

Random selection from frequency distribution

ISTYPE2 Landfill cover soil type Integer Constant Calculated by EPACMTP U.S. 

Randomly selected from frequency distributions for landfills

RECH Recharge rate m/yr Derived Site-specific See a

Selected based on climate center (ICLR) and regional soil type (ISTYPE1) for all scenarios

SINFIL Infiltration rate (no liner 

scenario)

m/yr Derived Calculated by EPACMTP See a

Selected based on climate center (ICLR) and cover soil type (ISTYPE2)

SINFIL Infiltration rate (composite 

liner scenario)

m/yr Empirical Randomly selected from empirical 

distribution

Random selection from empirical distribution See a
Variable ID Parameter Units Type Value Ref

Table F-1. Groundwater Model Variables

Comments

 Draft Appendix F GroTSOURCE Duration of leaching period yr Derived Calculated by LFCR Calculated based on transient mass fluxes read 

by EPACMTP

XY WMU length m Derived Calculated by EPACMTP U.S. 

Square root of area

YD WMU width m Derived Calculated by EPACMTP U.S. 

Square root of area
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

Draft Appendix F Groundwater Modeling Parameters

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

Draft Appendix F Groundwater Modeling Parameters

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

Draft Appendix F Groundwater Modeling Parameters

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

Draft Appendix F Groundwater Modeling Parameters

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

Draft Appendix F Groundwater Modeling Parameters

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

Draft Appendix F Groundwater Modeling Parameters

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

Draft Appendix F Groundwater Modeling Parameters

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

Draft Appendix F Groundwater Modeling Parameters

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

Draft Appendix F Groundwater Modeling Parameters

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

Draft Appendix F Groundwater Modeling Parameters

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 Parameter [Reference] Value Units CDF

Table F-3. Empirical Distributions for Groundwater Modeling

Draft Appendix F Groundwater Modeling Parameters

ActiveLife Active life of the landfill [b] yrs 8.18 0

22.95 0.1

29.54 0.25

38.73 0.5

51.36 0.75

65.44 0.9

194.17 1

AL Longitudinal dispersivity (aquifer) [a] m 0.1 0

1 0.1

10 0.7

100 1

AREA Landfill area [b] m^2 4072 0

67650 0.1

150300 0.25

360100 0.5

846200 0.75

1860000 0.9

16810000 1

DEPTH Landfill depth [b] m 2.9 0

3.93 0.1

5.84 0.25

10.94 0.5

22.42 0.75

42.61 0.9

114.8 1

DIAM Avg. particle diameter [d] cm 0.00039 0

0.00078 0.038

0.0016 0.104

0.0031 0.171

0.0063 0.262

0.0125 0.371

0.025 0.56

0.05 0.792

0.1 0.904

0.2 0.944

0.4 0.976

0.8 1

PH Groundwater pH [d] std. Units 3.2 0

3.6 0.01

4.5 0.05

5.2 0.1

6.07 0.25

6.8 0.5

7.4 0.75

7.9 0.9

8.2 0.95

8.95 0.99

9.7 1

RADIS Radial distance to well [d] m 0.6 0

13.7 0.03

F-17
VariableID Parameter [Reference] Value Units CDF

Table F-3. Empirical Distributions for Groundwater Modeling

Draft Appendix F Groundwater Modeling Parameters

RADIS Radial distance to well [d] m 19.8 0.04

45.7 0.05

103.6 0.1

152.4 0.15

182.9 0.2

243.8 0.25

304.8 0.3

304.8 0.35

365.7 0.4

396.2 0.45

426.7 0.5

457.2 0.55

609.6 0.6

762 0.65

804.6 0.7

868.6 0.75

914.4 0.8

1158.2 0.85

1219.1 0.9

1371.5 0.95

1523.9 0.98

1609.3 1

SINFIL Landfill composite liner infiltration rate [c] m/yr 0 0

0 0.26

0.0000365 0.28

0.0000365 0.3

0.000073 0.32

0.000073 0.38

0.0001095 0.4

0.000146 0.42

0.00021353 0.44

0.000219 0.46

0.000219 0.5

0.0003285 0.52

0.0004015 0.54

0.000876 0.56

0.000876 0.58

0.000949 0.6

0.001022 0.62

0.0011315 0.64

0.0012045 0.66

0.001241 0.68

0.001314 0.7

0.001533 0.72

0.002263 0.74

0.002336 0.76

0.002555 0.78

0.0026645 0.8

0.0031755 0.82

0.0038325 0.84

0.0043435 0.86

F-18
VariableID Parameter [Reference] Value Units CDF

Table F-3. Empirical Distributions for Groundwater Modeling

Draft Appendix F Groundwater Modeling Parameters

SINFIL Landfill composite liner infiltration rate [c] m/yr 0.0049275 0.88

0.005475 0.9

0.0055845 0.92

0.005986 0.94

0.0060955 0.96

0.006351 0.98

0.0116435 1

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
TEMP IGWR

Table F-4. Offsite Industrial Landfill Database

Appendix F Groundwater Modeling Parameters

SiteID ICLR

Draft

1 22.5 5 92

2 12.5 12 85

3 12.5 5 51

4 7.5 2 32

5 12.5 12 42

6 17.5 2 36

7 12.5 1 71

8 12.5 9 32

9 12.5 12 49

10 12.5 12 71

11 22.5 12 93

12 17.5 4 29

13 17.5 2 89

14 12.5 2 28

15 22.5 4 96

16 12.5 1 63

17 7.5 13 49

18 12.5 5 74

19 12.5 12 87

20 12.5 5 74

21 17.5 12 89

22 17.5 12 85

23 22.5 4 81

24 12.5 13 26

25 22.5 5 21

26 12.5 5 3

27 17.5 5 21

28 17.5 4 79

29 12.5 12 54

30 12.5 5 87

31 17.5 5 12

32 12.5 12 49

33 17.5 4 79

34 7.5 13 50

35 17.5 4 93

36 7.5 2 31

37 7.5 8 41

38 7.5 2 50

39 7.5 4 45

40 7.5 2 50

41 7.5 1 62

42 12.5 8 32

43 7.5 1 44

44 22.5 12 78

45 12.5 13 24

46 12.5 8 32

47 22.5 2 21

48 22.5 2 22

49 12.5 6 89

F-20
TEMP IGWR

Table F-4. Offsite Industrial Landfill Database

Appendix F Groundwater Modeling Parameters

SiteID ICLR

Draft

50 22.5 12 91

51 12.5 2 52

52 12.5 12 71

53 17.5 1 77

54 17.5 5 13

55 17.5 12 85

56 12.5 4 66

57 17.5 4 20

58 17.5 4 29

59 22.5 4 92

60 12.5 8 46

61 17.5 4 20

62 17.5 4 93

63 12.5 2 52

64 12.5 8 32

65 12.5 4 72

66 17.5 1 79

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 for Landfill Recharge and No-liner Infiltration

Draft Appendix F Groundwater Modeling Parameters

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 for Landfill Recharge and No-liner Infiltration

Draft Appendix F Groundwater Modeling Parameters

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 for Landfill Recharge and No-liner Infiltration

Draft Appendix F Groundwater Modeling Parameters

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

CAS DSTAR

Draft

67561 Methanol 0.08 0 0 0 0.052

67641 Acetone 0.26 0 0 0 0.0363

71363 Butanol n- 3.18 0 0 0 0

71432 Benzene 63.10 0 0 0 0.0325

75092 Methylene Chloride 8.51 0 0.001 0.6 0.0394

78831 Isobutyl alcohol 2.75 0 0 0 0

78933 Methyl ethyl ketone 0.93 0 0 0 0.0322

79005 Trichloroethane 1,1,2- 53.70 0 2.73E-05 49500 0.0315

79016 Trichloroethylene 125.89 0 0 0 0.0322

95501 Dichlorobenzene 1,2- 1202.26 0 0 0 0.0281

100414 Ethylbenzene 1000.00 0 0 0 0.0267

108101 Methyl isobutyl ketone 7.41 0 0 0 0.0264

108883 Toluene 269.15 0 0 0 0.0291

108907 Chlorobenzene 378.44 0 0 0 0.0299

108941 Cyclohexanone 66.07 0 0 0 0

110805 Ethoxyethanol 2- 0.29 0 0 0 0.0308

127184 Tetrachloroethylene 162.18 0 0 0 0.0298

141786 Ethyl acetate 2.24 3500 0.0048 3400000 0

1319773 Cresols 131.83 0 0 0 0.0299

1330207 Xylenes (total) 1198.55 0 0 0 0.0268

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 Research Laboratory, Office of Research and 

Development, Athens, GA. 

Newell, C.J., L.P. Hopkins, and P.B Bedient. 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 interpolation methods used to develop unitized air 

concentrations (UACs) used in the solvent industrial wipes analysis. The approach 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 Industrial Waste Air (IWAIR) model (U.S. EPA, 

2002). This approach, which includes the interpolation 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 Industrial Source Complex – Short Term model, 

version 3 (ISCST3). Modeling was conducted for many different locations, landfill surface areas, 

distances, and directions designed 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 meteorological regions were 

identified. 

 Surface Area. Nineteen surface areas for landfills 

ranging from 4,000 m2

 to approximately 17,000,000 

m

2

 were modeled (see box). 

 Distance. Eight receptor distances 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 selects two UACs for the same location, distance, and direction that 

reflect the modeled surface areas that bracket the actual landfill surface area, and interpolates to 

the actual surface area for the specific landfill using standard linear interpolation: 

( ) j i i

j i

i UAC UAC UAC

A A

A A UAC × − + ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

−

− = (Equation G-1) 

Landfill Areas Modeled 

4,000 m2 420,000 m2

6,045 m2 607,000 m2

8,090 m2

 906,528 m2

14,145 m2

 1,157,442 m2

20,200 m2

 1,408,356 m2

40,450 m2

 3,146,678 m2

60,700 m2

 4,885,000 m2

127,350 m2

 9,350,000 m2

194,000 m2

 17,000,000 m2

307,000 m2

 

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 ([Fg/m3

]/[Fg/m2-s]) 

A = area of specific landfill (m2) 

Ai = modeled surface area immediately below area of specific landfill (m2

) 

Aj = modeled surface area immediately above area of specific landfill (m2

) 

UACi = UAC for area i ([Fg/m3]/[Fg/m2-s]) 

UACj = UAC for area j ([Fg/m3]/[Fg/m2-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 areas in achieving a goal of less 

than 5 percent interpolation error. Modeling was performed for three 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 compute 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 interpolation algorithm was applied to estimate the 

ISCST3 output value using the initial set of areas. These are the interpolated values.

3. The percentage interpolation error was computed as follows: 

( )

( ) ×100 −

true value

true value interpolated value (Equation G-2) 

Results from the analysis indicated that the goal of less than 5 percent 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, ambient air and groundwater pathway exposures, and 

human health risks for cancer and noncancer endpoints. These equations are grouped as follows: 

 Calculation of ambient air concentrations (Table H1-1) 

 Calculation of shower indoor 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 concentrations 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 Description Value

Cair

Draft Appendix H Equations

Calculation of Ambient Air Concentrations

C =UAC×1,000,000×[ ] Q /86400 ×0.001 air

UAC Unitized Air Concentration (ug/m^3) per (ug/s-m^2) Calculated from dispersion modeling

1000000 Conversion factor (ug/g)

Q Emission rate from source (g/d-m^2) Calculated from source modeling

86400 Conversion factor (sec/day)

0.001 Conversion factor (mg/ug)

This equation is used to calculate ambient air concentration 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 Description Value

Cairindoor

Draft Appendix H Equations

Calculation of Shower Indoor Air Concentrations

( )( )

1440

airShower Shower airBathroom bathroom

airIndoor

C T C T C× + × =

[ ] ( )

s

s t ts s t

airShower

n

y y C , + , 2 ×1000 = ∑ +

[ ] ( )

b

b t ts b t

airBathroom

n

y y C , + , 2 ×1000 = ∑ +

CairBathroom Average concentration in bathroom (mg/m^3) Calculated above

CairShower Average concentration in shower (mg/m^3) Calculated above

Tshower Total time spent in shower stall (min) Calculated; see Table H2-10

Vapor-phase constituent concentration in the shower at the end Calculated; see Table H2-2

of time step (mg/L)

ys, t+ts

Vapor-phase constituent concentration in the bathroom at the Calculated; see Table H2-3

end of time step (mg/L)

yb, t+ts

Vapor-phase constituent concentration in the bathroom at the Calculated from last time step

beginning of time step (mg/L)

yb, t

Vapor-phase constituent concentration in the shower at the Calculated from last time step

beginning of time step (mg/L)

ys, t

Tbathroom Time spent in bathroom, not in shower (min) Exposure data; see Appendix I

Number of time steps corresponding to time spent in the Calculated as Tshower divided by ts

shower (unitless)

ns

Number of time steps corresponding to time spent in the Calculated as Tbathroom divided by ts

bathroom (unitless)

nb

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 assumes that receptors are only exposed to contaminants 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 Description Value

ys, t+ts

Draft Appendix H Equations

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

Es Mass emitted in the shower for a given time step (mg) Calculated; see Table H2-4

Vapor-phase constituent concentration in the bathroom at the Calculated from last time step

beginning of time step (mg/L)

yb, t

Vapor-phase constituent concentration in the shower at the Calculated from last time step

beginning of time step (mg/L)

ys, 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)

Qsb

Vs Volume of shower stall (m^3) 2

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 Description Value

yb, t+ts

Draft Appendix H Equations

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

Vapor-phase constituent concentration in the shower at the end Calculated; see Table H2-2

of time step (mg/L)

ys, t+ts

Vapor-phase constituent concentration in the bathroom at the Calculated from last time step

beginning of time step (mg/L)

yb, 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)

Qbh

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)

Qsb

Vb Volume of bathroom (m^3) 10

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)

yh,t

The above equations are used to calculate the time-weighted average daily indoor air concentration to which a 

receptor is exposed. The equation assumes that receptors are only exposed to contaminants in the shower and 

bathroom.

H-5
Table H2-4. Contaminant Mass Emitted in the Shower for a Given Time Step (mg)

Name Description Value

Es

Draft Appendix H Equations

Calculation of Shower Indoor Air Concentrations

 For Et > Emax, 

Es = Emax

For Et ≤ Emax, 

Es = Et

Where, 

t in em E = C × ShowerRate×ts× f

= − , × ×1000 s eq s t Emax (y y ) V

Potential mass of constituent emitted from shower during time Calculated above

step (mg)

Et

Maximum possible mass of constituent emitted from shower Calculated above

during time step (mg)

Emax

fem Fraction of constituent emitted from a droplet (unitless) Calculated; see Table H2-5

H’ Dimensionless Henry's law constant (unitless) Calculated; see Table H2-9

Vapor-phase constituent concentration in the shower at the Calculated from last time step

beginning of time step (mg/L)

ys, t

Vapor-phase contaminant concentration in equilibrium H' x Cin

between water and air (mg/L)

yeq

Cin Constituent concentration in incoming water (mg/L) Exposure data; see Appendix I

ShowerRate 5.5; calculated based on droplet 

diameter and nozzle velocity.

Rate of flow from showerhead (L/min)

Vs Volume of shower stall (m^3) 2

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 Constituent Emitted from a Droplet (unitless)

Name Description Value

fem

Draft Appendix H Equations

Calculation of Shower Indoor Air Concentrations

f ( f ) ( e ) N

em sat

− = 1 − × 1−

fsat Fraction of gas-phase saturation (unitless) Calculated; see Table H2-6

N Dimensionless overall mass transfer coefficient (unitless) Calculated; see Table H2-7

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 Description Value

fsat

Draft Appendix H Equations

Calculation of Shower Indoor Air Concentrations

eq

s t ts

sat y

y f +

= ,

Vapor-phase constituent concentration in the shower at the end Calculated; see Table H2-2

of time step (mg/L)

ys, t+ts

Vapor-phase constituent concentration in the shower at the Calculated from last time step

beginning of time step (mg/L)

ys, t

Vapor-phase contaminant concentration in equilibrium H' x Cin

between water and air (mg/L)

yeq

This equation is used to calculate the fraction of a given 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 Description Value

N

Draft Appendix H Equations

Calculation of Shower Indoor Air Concentrations

N K AVRatio DropResTime = ol × ×

DropDiam

AVRatio 6 =

DropVel

NozHeight DropResTime×100 =

AVRatio Area-to-volume ratio for a sphere (cm^2/cm^3) Calculated above

DropResTime Residence time for falling drops (s) Calculated above

Kol Overall mass transfer coefficient (cm/s) Calculated; see Table H2-8

DropDiam Drop diameter (cm) Exposure data; see Appendix I

DropVel Drop terminal velocity (cm/s) Exposure data; see Appendix I

NozHeight Nozzle height (m) Exposure data; see Appendix I

100 Conversion factor (cm/m)

This equation is used to calculate the fraction of a given 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 Description Value

Kol

Draft Appendix H Equations

Calculation of Shower Indoor Air Concentrations

1

2 / 3 2 / 3

2.5 1 −

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

× ′ = × +D D H

K

w a

ol β

H’ Dimensionless Henry's law constant (unitless) Calculated; see Table H2-9

Da Diffusivity of chemical in air (cm^2/s) Chemical data; see Appendix B

Dw Diffusivity in water (cm^2/s) Chemical data; see Appendix B

β Proportionality constant (cm-s)^-1/3 216

This equation calculates the dimensionless overall mass transfer coefficient. The above equation is based on Little 

(1992).

H-10
Table H2-9. Dimensionless Henry's Law Constant (unitless)

Name Description Value

H’

Draft Appendix H Equations

Calculation of Shower Indoor Air Concentrations

H ′ = HLCcoef × HLC

R Temp

HLCcoef × = 1

HLCcoef Coefficient to Henry's law constant (unitless) Calculated above

HLC Henry's law constant (atm-m^3/mole) Chemical data; see Appendix B

R Ideal Gas Constant; R=0.00008205 (atm-m^3/K-mole)

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 Description Value

Tshower

Draft Appendix H Equations

Calculation of Shower Indoor Air Concentrations

Tshower = Tshowerstall + Tshowering

Tshowering Duration of shower (min) Exposure data; see Appendix I

Tshowerstall Time in shower stall after showering (min) Exposure data; see Appendix I

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 Description Value

ADDdw

Draft Appendix H Equations

Calculation of Ingestion Dose

×1000

× × = BWC CR F ADD water dw dw

dw

Cwater Total concentration in the water (mg/L) Calculated from groundwater model

CRdw Consumption rate of water (mL/day) Exposure data; see Appendix I

BW Body weight (kg) Exposure data; see Appendix I

Fraction of drinking water ingested that is contaminated Set to 1

(unitless)

Fdw

1000 Conversion factor (mL/L)

Source: U.S. EPA, 2005.

H-13
Table H3-2. Lifetime Average Daily Dose (mg/kg/d)

Name Description Value

LADD

Draft Appendix H Equations

Calculation of Ingestion Dose

× 365

× × = ATADD ED EF LADD dw

ADD Average daily dose (mg/kg/day) Calculated; see Table H3-1

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 frequency (d/yr) Exposure data; see Appendix I

ED Exposure duration (yr) Exposure data; see Appendix I

SA Start age (yr) Set to 1yr for child and 20yrs for adult

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 Description Value

DAevent

Draft Appendix H Equations

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

FA Fraction absorbed water (unitless) Set to 1

Kp Dermal permeability coefficient of compound in water (cm/hr) Calculated (U.S. EPA, 2004)

Dimensionless ratio of the permeability coefficient of a Calculated (U.S. EPA, 2004)

compound through the stratum corneum relative to its 

permeability coefficient across the viable epidermis (unitless)

B 

tevent Event duration (hr/event) Exposure data; see Appendix I

tau Lag time per event (hr/event) Calculated (U.S. EPA, 2004)

t* Time to reach steady-state (hr) 2.4 * tau (U.S. EPA, 2004)

Cw Chemical concentration in water (mg/cm3) Calculated from groundwater model

H-15
Table H4-2. Dermal Absorbed Dose - Water Content (mg/kg-day)

Name Description Value

DAD 

Draft Appendix H Equations

Calculation of Dermal Dose

DAD DA EV ED EF SA

BW AT

event = ××××

×

DAevent Absorbed dose per event (mg/cm2-event) Calculated; see Table H4-1

EF Exposure frequency (d/yr) Exposure data; see Appendix I

EV Event frequency (events/day) Exposure data; see Appendix I

AT Averaging time (day) Exposure data; see Appendix I

BW Body weight (kg) Exposure data; see Appendix I

ED Exposure duration (yr) Exposure data; see Appendix I

SA Skin surface area available for contact (cm2) Exposure data; see Appendix I

H-16
Table H5-1. Cancer Risk Due to Inhalation (unitless)

Name Description Value

Riskair

Draft Appendix H Equations

Calculation of Risk

AT

C URF ED Risk air Inhal

air

× × × = 1000

1000 Conversion factor (ug/mg)

URFinhal Inhalation unit risk factor (ug/m^3)^-1 Toxicity data; see Table 6-1

LADD Lifetime average daily dose (mg/kg/day) Calculated; see Table H3-2

Cair Concentration in air (mg/m^3) Calculated; see Table H1-1

ED Exposure duration (yr) Exposure data; see Appendix I

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 Description Value

Riskoral

Draft Appendix H Equations

Calculation of Risk

Risk oral = LADD ×CSForal

CSForal Oral cancer slope factor (mg/kg/day)-1 Toxicity data; see Table 6-1

LADD Lifetime average daily dose (mg/kg/day) Calculated; see Table H3-2

Source: U.S. EPA, 2005.

H-18
Table H5-3. Dermal Cancer Risk (unitless)

Name Description Value

Riskdermal

Draft Appendix H Equations

Calculation of Risk

Risk DAD SF dermal ABS = ×

SFABS Absorbed cancer slope factor (mg/kg-day)^-1 Applied oral cancer slope factor

DAD Dermal absorbed dose (mg/kg-day) Calculated; see Table H4-2

H-19
Table H5-4. Noncancer Hazard Quotient Due to Inhalation (unitless)

Name Description Value

HQair

Draft Appendix H Equations

Calculation of Risk

RfC

C HQ air

air =

RfC Noncancer reference concentration (mg/m^3) Toxicity data; see Table 6-1

Cair Total concentration in air (mg/m^3) Calculated; see Table H1-1

Source: U.S. EPA, 2005.

H-20
Table H5-5. Noncancer Hazard Quotient Due to Ingestion (unitless)

Name Description Value

HQoral

Draft Appendix H Equations

Calculation of Risk

RfD

ADD HQoral =

RfD Noncancer reference dose (mg/kg/day) Toxicity data; see Table 6-1

ADD Average daily dose (mg/kg/day) Calculated; see Table H3-1

Source: U.S. EPA, 2005.

H-21
Table H5-6. Dermal Noncancer Hazard Quotient (unitless)

Name Description Value

HQdermal

Draft Appendix H Equations

Calculation of Risk

HQ DAD

RfD dermal

ABS

=

RFDABS Absorbed reference dose (mg/kg-day) Applied noncancer reference dose

DAD Dermal absorbed dose (mg/kg-day) Calculated; see Table H4-2

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 two resistance theory to contaminant 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. September. 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 versus 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). 
Draft Appendix I H

Table I-1. Summary of Exposure Parameters Used in Probabilistic Analysis 

Parameter Units 

Variable 

 Type Constants

Mean 

(or shape)a

Std Dev 

(or scale)a Minimum Maximum 

Averaging time for carcinogens yr Constant 7.00E+01 U.SBody weight (adult) kg Lognormal 7.12E+01 1.33E+01 1.50E+01 3.00E+02 U.S

7-4

Body weight (child 1) kg Lognormal 1.55E+01 2.05E+00 4.00E+00 5.00E+01 U.S

7-6

Body weight (child 2) kg Lognormal 3.07E+01 5.96E+00 6.00E+00 2.00E+02 U.S

7-6

Body weight (child 3) kg Lognormal 5.82E+01 1.02E+01 1.30E+01 3.00E+02 U.S

7-6

Event frequency (shower/bath) event/d Constant 1.00E+00 U.S

17Tb

Exposure duration (adult resident) yr Weibull 1.34E+00 1.74E+01 1.00E+00 Cappedb U.SExposure duration (child) yr Weibull 1.32E+00 7.06E+00 1.00E+00 Cappedb U.SExposure frequency (adult resident) d/y Constant 3.50E+02 U.SFraction contaminated: drinking water 

Fraction Constant 1.00E+00 U.S

Ingestion rate: drinking water (adult resident) 

mL/d Gamma 3.88E+00 3.57E+02 1.04E+02 1.10E+04 U.S

Ingestion rate: drinking water (child 1 resident) 

mL/d Gamma 2.95E+00 2.37E+02 2.60E+01 3.84E+03 U.S

Ingestion rate: drinking water (child 2 resident) 

mL/d Gamma 3.35E+00 2.35E+02 3.40E+01 4.20E+03 U.S

Ingestion rate: drinking water (child 3 resident) 

mL/d Gamma 2.82E+00 3.42E+02 3.30E+01 5.40E+03 U.S

Time spent showering min Gamma 2.83E+00 5.89E+00 1.00E+00 6.00E+01 U.S

21 

Time spent in shower stall after showering 

min Weibull 9.60E-01 8.36E+00 1.00E+00 6.00E+01 U.S

23 

Time spent in bathroom immediately following shower 

min Weibull 9.80E-01 9.75E+00 1.00E+00 1.20E+02 U.S

32 

Bathing contact time (child resident) min/ 

event 

Lognormal 2.68E+01 1.41E+01 1.00E+00 6.00E+01 U.S

(ch
Draft Appendix I H

Parameter Units 

Variable 

 Type Constants

Mean 

(or shape)a

Std Dev 

(or scale)a Minimum Maximum 

Ratio of surface area to body weight (child 1) 

m2/kgc Lognormal 4.18E-02 1.17E-02 3.00E-02 1.10E-01 U.S

U.S

Ratio of surface area to body weight (child 2 and 3) 

m2/kgc Weibull 3.63E-02 7.7E-03 1.00E-02 6.00E-02 U.S

U.S

Ratio of surface area to body weight (adult resident) 

m2/kgc Weibull 7.27 E+00 1.730E-02 2.00E-02 4.00E-02 U.S

a Mean and std dev for lognormal distributions, and shape and scale for gamma and Weibull distributions. b Exposure duration was capped so that the maximum value would not exceed the 70-year lifetime assumption implicit in the averaging time used. For ex

for adults was capped at 50 years. This is the maximum exposure duration, starting at age 20, that will not exceed the 70-year lifetime assumption implic

c Converted 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 distributed 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 more 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 different 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 exposure 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 them1

 and allow for a 

likelihood ratio test of the fit of the two-parameter 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 fraction 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 Factor Data Used in Modeling: Constants 

Description Value Units Source 

Fraction contaminated: drinking 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 resident, child resident) 70 yr U.S. EPA (1989) 

Source: EFH (U.S. EPA, 1997a,b,c) 

The fraction contaminated for drinking water was 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 value based on McKone (1987) 

data 

Volumetric exchange rate between the 

shower and the bathroom 

100 L/min RTI-derived value 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 m3 McKone (1987) 

Volume of shower 2 m3 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. 
Draft Appendix I H

Table I-4. Drinking Water Intake Data and Distributions 

EFH Data (mL/d) 

Age 

Cohort N 

Data 

Mean 

Data 

SDev P01 P05 P10 P25 P50 P75 P90 P95 P99 Distribu

1–5 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 6–11 2,405 787 417 68 241 318 484 731 1,016 1,338 1,556 1,998 Gamma 12–19 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 20+ 13,394 1,384 721.6 207.6 457.5 607.3 899.6 1,275 1,741 2,260 2,682 3,737 Gamma N = Number of samples; P01-P99 = Percentiles; Pop-Estd = Population-estimated; SDev = Standard deviation. 
Draft Appendix I H

Table I-5. Shower and Bathing Parameter Data and Distributions 

EFH Data 

Parameter 

Age 

Cohort N 

P02/ 

P05a P10 P25 P50 P75 P90 P95 P98 P99 

Distribu

tion 

Time spent showering (adult) (minutes) 

all ages 3,547 4 5 10 15 20 30 35 50 60 Gamma 

Time spent in shower stall after showering (adult) (minutes) 

all ages 3,533 1 3 5 10 20 30 40 50 Weibull 

Time spent in bathroom after shower (adult) (minutes) 

all ages 4,182 1 4 5 15 20 30 40 60 Weibull 

Time spent bathing (child)c (minutes) 

1-5 20 60 Lognorm1-5 0.047 0.00507 0.0563 0.0617 0.0719 0.0784 0.0846 Lognorm6-11 0.0291 0.0328 0.0376 0.0422 0.0454 0.0501 0.0594 Weibull 12-19 0.0291 0.0328 0.036 0.0422 0.0454 0.0501 0.0594 Weibull 

Ratio of surface area to body weight (SA/BW ratio) (m2/kg) d

20+ 0.0238 0.0244 0.0270 0.0286 0.0302 0.0316 0.0329 Weibull 

N = number of samples; P02-P99 = percentiles; Pop-Estd = population-estimated. a Data are P02 for time spent showering and P05 for ratio of surface area to body weight. b Mean and std dev for lognormal distributions, and shape and scale for gamma and Weibull distributions. c Bathing 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 yed The data for SA/BW ratio in the EFH was presented for somewhat different age ranges than the cohorts used here. For child 1 (ages 1-5), we used EFH 

(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 

modeling. 
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). The 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 through 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. 
Draft Appendix I H

Table I-6. Body Weight Data and Distributions 

EFH Data (kg) 

Age 

Cohort N 

Data 

Mean 

Data 

SDev P05 P10 P15 P25 P50 P75 P85 P90 P95 Distribu

1–5 3,762 15.52 3.719 12.5 13.1 13.45 14.03 15.26 16.67 17.58 18.32 19.45 Lognorm6–11 1,725 30.84 9.561 22.79 24.05 25.07 26.44 29.58 33.44 36.82 39.66 43.5 Lognorm12–19 2,615 58.45 13.64 43.84 46.52 48.31 50.94 56.77 63.57 68.09 71.98 79.52 Lognorm20+ 12,504 71.41 15.45 52.86 55.98 58.21 61.69 69.26 78.49 84.92 89.75 97.64 LognormN = Number of samples; P05-P95 = Percentiles; Pop-Estd = Population-estimated; SDev = Standard deviation. 

Table I-7. Exposure Duration Data and Distributions 

EFH Data Distributions 

Age 

Cohort 

Data Mean 

(yr) Distribution 

Pop-Estd Shape 

(yr)a

Pop-Estd Scale 

(yr) 

1–5 6.5 Weibull 1.32 7.059 Adult 16.0 Weibull 1.34 17.38 Pop-Estd = Population-estimated; SDev = Standard deviation.a Distributions used in analysis. 
Draft Appendix I Human Exposure Factors 

I-11 

I.2 References

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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, Office 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, Office of Research and Development, 

Washington, DC. 
Draft Appendix I Human Exposure Factors 

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.