Response to External Peer Review 

Comments: Human and Ecological 

Risk Assessment for Coal Combustion 

Residuals 

Final 

December 2014 

U.S. Environmental Protection Agency 

Office of Solid Waste and Emergency Response 

Office of Resource Conservation and Recovery 

Regulation Identifier Number: 2050-AE81 
Submitted to: 

Office of Resource Conservation and Recovery 

Office of Solid Waste and Emergency Response 

U.S. Environmental Protection Agency 

Submitted by: 

RTI International 

EPA Work Assignment 4-25 

EPA Contract No. EP-W-09-004 
Responses to Public Review Comments

i 

Table of Contents

1. Introduction and Background ............................................................................................. 1-1

2. Ground Water Modeling ..................................................................................................... 2-1

2.1. 10,000-Year Risk Duration ........................................................................................ 2-1

2.2. Ground Water Transport Modeling Approach ........................................................... 2-3

2.3. Site-Specific Analysis and Comparisons with Measured Data ................................ 2-10

2.4. Well-Related Issues ................................................................................................. 2-12

3. Source Modeling ................................................................................................................. 3-1

3.1. Use of TCLP Data and the Availability of the Vanderbilt Study .............................. 3-1

3.2. 2006 DOE Facility Data and Liner Scenarios............................................................ 3-5

3.3. Alternative Waste/Codisposal Scenarios ................................................................... 3-7

3.4. Liner Leakage ............................................................................................................ 3-9

3.5. Treatment of Nondetect Values ............................................................................... 3-12

3.6. Effect of Waste Compaction .................................................................................... 3-13

3.7. HELP Infiltration Rates/Cover Assumptions........................................................... 3-14

3.8. Water Table above the Disposal Unit ...................................................................... 3-14

3.9. Impact of Increased Mercury Capture with New Future Air Emission Control 

Regulations .............................................................................................................. 3-15

3.10. Use of Pore water Data for Surface Impoundment Source Concentrations ............. 3-16

3.11. Modeling Surface Impoundments Only Before Closure ......................................... 3-18

3.12. Modeling Landfills Only After Closure ................................................................... 3-18

4. Exposure Scenarios ............................................................................................................. 4-1

4.1. Direct Surface Impoundment Exposure ..................................................................... 4-1

4.2. Indirect Exposure through Game Species .................................................................. 4-3

4.3. Exposure to Surface Impoundment Effluent.............................................................. 4-4

4.4. Exposure during Landfill Operation (Before Closure) .............................................. 4-6

4.5. Elimination of Pathways During Screening Analysis ................................................ 4-7

5. Comments Related to Human Exposure and Toxicity ....................................................... 5-1

5.1. Combined Chemical Effects, Additive Risk, and Multiple Pathway Exposures ....... 5-1

5.2. Toxicity Values .......................................................................................................... 5-4

5.3. Target Cancer Risk .................................................................................................... 5-5

5.4. Defining the Exposed Population .............................................................................. 5-6

5.5. Exposure Factor Assumptions ................................................................................... 5-7

5.6. Child/Infant Exposure Assumptions .......................................................................... 5-8

5.7. Correlations in Input Variables ................................................................................ 5-10

6. Comments Related to Ecological Exposure and Toxicity .................................................. 6-1

6.1. Cumulative Ecological Risk ...................................................................................... 6-1

6.2. Sensitive Habitats/Sensitive Species.......................................................................... 6-2

6.3. Indirect Effects ........................................................................................................... 6-3

6.4. Ecological Benchmarks, Ecological Toxicity ............................................................ 6-4

7. Comments about the Monte Carlo Analysis Approach ...................................................... 7-1

7.1. Use of Conservative Parameter Estimates ................................................................. 7-1
Responses to Peer Review Comments Table of Contents

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7.2. Variability versus Uncertainty ................................................................................... 7-2

7.3. Calculation of Percentile Probabilities as Opposed to an Overall Probability .......... 7-3

7.4. The Numerical Stability of Monte Carlo Results ...................................................... 7-4

7.5. Impacts on Ground water as a Resource .................................................................... 7-5

8. Comments Related to the Documentation and Miscellaneous Comments ......................... 8-1

8.1. Insufficient Documentation to Reproduce the Analysis Independently .................... 8-1

8.2. Graphical Input/Output Distributions, Truncation Values......................................... 8-3

8.3. Documentation of Sensitivity Analysis ..................................................................... 8-4

8.4. Discussion of General Risk-Susceptibility Patterns such as Climate-Specific 

Risk ............................................................................................................................ 8-4

8.5. Discussion of Worst-Case Scenarios ......................................................................... 8-6

8.6. Discussion of Sulfate, Phosphate, and Chloride ........................................................ 8-6

8.7. Background Concentrations ....................................................................................... 8-7

9. References ........................................................................................................................... 9-1

List of Tables and Figures

Table 1. Comparison of Per Capita Beef, Dairy and Wild Game Consumption Rates ........... 4-4 

Figure 1. Example showing convergence of Monte Carlo simulations of up to 10,000 

realizations. ................................................................................................................ 7-5

List of Abbreviations and Acronyms 

Al Aluminum 

As Arsenic 

 

CCL Compacted clay liner 

CCR Coal combustion residual 

Cd Cadmium 

 

DOE U.S. Department of Energy 

 

Eco-SSL Ecological Soil Screening Levels 

EFH Exposure Factors Handbook 

EPA U.S. Environmental Protection Agency 

EPACMTP EPA’s Composite Model for Leachate Migration with Transformation Products

EPRI Electric Power Research Institute 

 

FBC Fluidized-bed combustion 

Fe Iron 

FGD Flue gas desulfurization 
Responses to Peer Review Comments Table of Contents

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GCL Geosynthetic clay liner 

 

HELP Hydrologic Evaluation of Landfill Performance 

HFO Hydrous ferric oxide 

Hg Mercury 

HQ Hazard quotient 

 

IEUBK Integrated Exposure and Uptake Biokinetic Model 

IRIS Integrated Risk Information System 

IWEM Industrial Waste Evaluation Model 

 

Kd Soil-water partition coefficient 

 

MCL Maximum Concentration Limit 

MINTEQA2 Metal Speciation Equilibrium Model for Surface and Ground Water 

Mn Manganese 

MSW Municipal solid waste 

 

NODA Notice of Data Availability 

 

ORCHESTRA Objects Representing Chemical Speciation and Transport Model 

OSWER Office of Solid Waste and Emergency Response 

 

Pb Lead 

PRA Probabilistic risk assessment 

PPRTV Provisional Peer-Reviewed Toxicity Values 

 

RA Risk assessment 

RCRA Resource Conservation and Recovery Act 

RfD Reference Dose 

RME Reasonable maximum exposure 

 

Se Selenium 

SPLP Synthetic Precipitation Leaching Procedure 

 

TCLP Toxicity Characteristic Leaching Procedure 

 

WMU Waste management unit 
Responses to Peer Review Comments Table of Contents

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Response to Peer Review Comments

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1. Introduction and Background 

To ensure protection of human health and the environment, the U.S. Environmental Protection 

Agency (EPA or the Agency) has completed a risk assessment to evaluate potential risks to human 

health and the environment from exposure to coal combustion residuals (CCRs) in landfills and 

surface impoundments. The risk assessment, originally entitled Human and Ecological Risk 

Assessment of Coal Combustion Wastes, was renamed to reflect the terminology used in EPA’s 

2010 proposed regulation. Although the name has changed, the new document is merely a revision 

of the version independently peer reviewed after the 2007 Notice of Data Availability (NODA). 

A peer review is a process for enhancing a scientific or technical work product so that the decision 

or position taken by the Agency based on that product has a sound, credible basis. The Agency 

contracted with Industrial Economics, Incorporated (IEc), to conduct a letter peer review of the 

draft Human and Ecological Risk Assessment of Coal Combustion Wastes. This document provides 

responses to peer review comments received on the CCR risk assessment. There were five peer 

reviewers with the following focus areas: 

 Dr. Nicholas Basta, Ohio State University: overall risk assessment approach, including the 

use of methods and parameters used in geochemical modeling 

 Dr. Charles Harvey, Massachusetts Institute of Technology: use of probabilistic 

approaches used in the analysis in the context of fate and transport of contaminants in the 

environment 

 Dr. William Hopkins, Virginia Polytechnic Institute and State University: ecological 

impacts as they were addressed in the analysis 

 Dr. Kerry Rowe, Queens University: relationship between the use of landfill liners and the 

analytical approach 

 Dr. Donna Vorhees, The Science Collaborative: adequacy of the human health risk 

assessment approach in the context of requirements for proper conduct of probabilistic risk 

assessments. 

EPA has established a docket for this action (Docket ID No. EPA-HQ-RCRA-2006-0796). All 

documents in the docket are listed on www.regulations.gov. The public can view the peer 

reviewers’ comments in their entirety on the docket Web site. The docket is located at the EPA 

Docket Center, Public Reading Room, EPA West Building, 1301 Constitution Avenue, NW, 

Washington, D.C. This Peer Review Response to Comments document has been revised to reflect 

the modifications completed in the most current CCR risk assessment. 
Responses to Peer Review Comments Introduction and Background

1-2 

This comment review and response report focuses on the technical themes initially presented by 

the peer reviewers of the CCR risk assessment. For each comment category, the comments are 

provided by each peer reviewer, followed by the response. Please note that this document does not 

respond to public comments received from the 2010 proposed rule or the 2007, 2011 and 2013 

NODAs. Rather, these public comments are addressed in a separate Response to Comments 

Document. 1 

 

1

 All NODAs from the federal register for the CCR proposed rule from 2010 to present are available at 

www.epa.gov/solidwaste/nonhaz/industrial/special/fossil/ccr-rule/index.htm 
Response to Peer Review Comments

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2. Ground Water Modeling 

The peer review comments relating to modeling of the ground water pathway are grouped into 

four subcategories: 

 The 10,000-year maximum ground water simulation time 

 Ground water transport modeling assumptions 

 The need for more site-specific analysis and comparisons with measured data 

 The number of wells contaminated, realistic risk of exposure, well placement within the 

plume, and other well-related issues. 

2.1. 10,000-Year Risk Duration 

Comment Summary 

Both Dr. Basta and Dr. Rowe questioned the use of a risk assessment model that assumes current 

conditions will be maintained for 10,000 years and wondered how realistic the results may be. 

Specifically, Dr. Basta requested that the limitations of this assumption be better explained and 

questioned the assumption that contaminant concentrations in the leachate remain constant 

throughout the timeframe. Dr. Rowe questioned the assumption that well use and climate 

conditions will remain constant for 10,000 years. 

Dr. Nicholas Basta, Ohio State University 

One limitation that is not discussed is the validity of modeling risk over a 10,000-

year period. Shifting land use, geological and climate phenomena, and human and 

ecological populations will dramatically change exposure scenarios for CCR from 

surface impoundments and landfills. The time period for modeling risk should be 

discussed as a limitation and justified. 

The assumption made that the contaminant concentration in the leachate data 

remains constant throughout the 10,000-year modeling period is not realistic. 

Leaching of contaminants will likely occur in much shorter time periods and 

decrease after reaching a maximum. The peak contaminant concentration will not 

remain constant throughout the modeling period. The assumption that 100% of the 

contaminant mass will be leached out of the CCR is unlikely. Only a fraction of the 

contaminant will leach from a solid waste such as CCR. The remainder of the 

contaminant will remain insoluble and “unleachable.” 

Dr. Kerry Rowe, Queens University 

It appears to be assumed that the current hydrogeologic and climatic conditions will 

prevail over the next 10,000 years. While it is difficult to do otherwise, the 
Response to Peer Review Comments Ground Water Modeling

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implications of this assumption have not been adequately discussed. For example, 

it is assumed that well usage will correspond to that which exists today down 

gradient of Subtitle D MSW [municipal solid waste] landfills (RA [Risk 

Assessment] pg. 2-11) however global warming may result in the need for much 

greater reliance than at present on ground water resources; if that were to be the 

case then the risks may be (considerably) higher than implied by the present study 

in even 30-100 years from now – let alone in 10,000 years time! The issue of time 

is also discussed in response to Question # 8. 

The time period examined (10,000 years) is VERY long for the surficial 

hydrogeologic environments being considered – it is only about 10,000 years ago 

that glaciers retreated from much of Canada and northern USA. Thus the landscape 

that we see today is very different from that 10,000 years ago and we can expect it 

to be very different 10,000 years from now. Also the climate is likely to change 

substantially over this period. Thus considerable skepticism needs to be applied to 

predicted impacts that are thousands of years from now – however it is not clear 

which results fall into this category (except for composite–lined sites where it is 

indicated that many impacts had not occurred in 10,000 years (RA, pg. 4-7)). 

EPA Response 

EPA acknowledges that the 10,000-year modeling time horizon required further clarification in 

the revised risk assessment. Thus, the text has been updated to make it clear that the selection of a 

maximum 10,000-year time horizon does not mean that all model simulations continue for the full 

10,000 years. Specifically, Section 4 states: 

EPA ran the model until either the observed ground water concentration of a 

constituent at the receptor point reached a peak and then fell below a modelspecified minimum concentration (10-16 mg/L), or the model had been run for a time 

period of 10,000 years. 

Although ground water concentrations are modeled beyond the observed peak or maximum 

average concentrations, these postpeak or postmaximum average predictions are not used in 

estimates of risk. In many cases the leachate plume reaches the receptor point much sooner than 

10,000 years. As discussed in Section 5 of the revised risk assessment, on a national scale, both 

unlined and clay-lined surface impoundments consistently pose peak risks within 100 years. 

Composite liners show much higher peak arrival times, close to 10,000 years for most surface 

impoundment runs. Peak arrival times are longer for landfills. Under such timeframes EPA 

acknowledges that surface conditions may change significantly, compounding the uncertainty 

associated with the predicted exposures and risks. However, EPA also notes that the time to first 

exceedance of selected risk criteria is typically considerably less than the time to the greatest 

exceedance. 
Response to Peer Review Comments Ground Water Modeling

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EPA acknowledges that the leaching profile described by Dr. Basta is more realistic. Empirical 

evidence reported in U.S. EPA (2009b) indicates that constituents can exhibit a leaching profile 

that changes over time. In the particular case of washout controlled constituents, the leaching 

profile is characterized by an initial high-concentration pulse followed by a lower concentration 

pulse that continues until the leachable content is depleted. However, the nonlinear fate and 

transport solution used for inorganic constituents in the unsaturated zone module of EPA’s 

Composite Model for Leachate Migration with Transformation Products (EPACMTP) requires 

constituent concentrations leached from the bottom of waste management units (WMUs) to remain 

constant for the entire duration of leaching (see Section 3.3.5.3 of U.S. EPA, 2003b). EPA 

conducted a sensitivity analysis to estimate the potential magnitude of this error in Appendix K 

of the revised risk assessment. 

EPA agrees that there may be some constituent mass that is not available to be leached from the 

waste. For surface impoundments, this leachable fraction was not considered because the relatively 

short leaching duration (compared to landfills) makes it unlikely that the leachable fraction would 

be fully depleted for any constituent. For landfills, the data collected using SW-846 Method 1313 

provided an empirically derived estimate of the leachable mass of each constituent, which were 

used in the revised risk assessment. There is some uncertainty associated with the measured values 

because long-term leachate studies have shown that short-term test methods may underestimate 

the total mass of constituents that can leach over longer periods of time. EPA conducted a 

sensitivity analysis to estimate the potential magnitude of this error, which is discussed in Section 

5 of the revised risk assessment. 

EPA acknowledges that future ground water use patterns may shift as the number and location of 

receptors changes. However, no known data exist that would allow EPA to do more than speculate 

about future population dynamics. Thus, the Agency relied on the best available data on the current 

population to conduct the revised risk assessment as discussed in Section 4 and Appendix B of 

the revised risk assessment. Discussion of the associated uncertainties has been added to Section 

5. 

2.2. Ground Water Transport Modeling Approach 

Comment Summary 

Comments related to the specifics of the ground water transport modeling were received from Dr. 

Basta and Dr. Harvey. Issues covered in their comments included the following: 

 The way that aquifer soil-water partition coefficient (Kd) values were determined and 

used, including the fact that the risk assessment did not model precipitation-dissolution 

processes that probably control several of the CCR chemical constituents 

 The approach used to determine the value of pH in the aquifer for selecting Kd

 The subsequent calculation of the retardation factor. 
Response to Peer Review Comments Ground Water Modeling

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The comments also addressed the general need for more transparency in the data and methods used 

in the analysis and the need for validation and/or comparison of model inputs and results to sitespecific field data. 

Dr. Nicholas Basta, Ohio State University 

Another major source of uncertainty is the ability of the MINTEQA2 [Metal 

Speciation Equilibrium Model for Surface and Ground Water] model-generated Kd

values used in EPACMTP to determine realistic contaminant transport at field CCR 

facilities. Kd values for arsenic and other select contaminants should be determined 

for a set of soils with a range of soil chemical properties critical to chemical 

processes values. This could be conducted using column studies under controlled 

laboratory conditions. Modeled Kd values used in the Draft must be validated by 

comparison to Kd values derived from real soil and/or geomedia to assure that the 

EPACMTP model captures the major chemical process critical to transport. 

Realistic Kd values will greatly affect the transport and risk calculation of As in 

ground water. Kd values from soil or geomedia from CCR sites with a range of 

chemical properties will significantly reduce uncertainty associated with risk from 

As in ground water (a risk driver) and significantly improve the risk assessment. 

In general, all of the chemical processes are lumped into one value, Kd, calculated 

by MINTEQA2. This is a common modeling approach, although this grossly 

oversimplifies and is likely not an accurate approach for several CCR chemical 

constituents that are controlled by precipitation-dissolution processes in soil that 

cannot be accurately modeled using Kd values. 

Chemical processes are mainly described through determination of a partitioning 

coefficient, Kd, from nonlinear isotherms for each contaminant. The generation and 

use of an accurate Kd value is absolutely critical because it controls the amount of 

contaminant that is dissolved in the leachate and capable of being transported. The 

contaminant is not transported if it is not dissolved. Kd is very sensitive to 

adsorbents selected for inclusion in MINTEQA2. The type of sorbent varies with 

contaminant. In general, soil organic matter and clay minerals (especially Fe [iron], 

Al [aluminum], Mn [manganese] oxides) sorb metal cations and oxyanions (i.e., 

arsenate and arsenite). Soils vary greatly in the type and amount of these sorbents. 

The MINTEQA2 model is very limited in its ability to model sorption. 

MINTEQA2’s database is limited to three sorbents: Fe sorbent as the mineral 

goethite, Fe sorbent as hydrous ferric oxide, and organic matter. Fe sorbent as 

goethite and organic matter were selected to calculate nonlinear isotherms and 

subsequent Kd values in the Draft. The choice of Fe sorbent is important because 

goethite is a much poorer adsorbent than hydrous ferric oxide and will result in 

larger leachate contaminant concentration. No explanation for the choice of 

goethite over hydrous ferric oxide is provided in the Draft. In addition to the type 
Response to Peer Review Comments Ground Water Modeling

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of adsorbent, the amount of adsorbent (i.e., adsorption sites) will greatly affect the 

calculated Kd value. The adsorption site density for the two sorbents is not specified 

in the draft. This is critical because we do not know if the sorption site density 

represents the normal range found in soils. 

It is not possible to determine if the approach used by MINTEQA2 provides Kd

values for the EPACMTP model that is representative of chemical processes in soils 

or geomedia at any of the CCR locations from information presented in the Draft. 

Soil has many more sorbents than the two sorbents used in the MINTEQA2 model 

in the Draft. Except for organic matter content, soil sorbents were not measured in 

soils collected from CCR facilities sites. The only soil data collected and reported 

was pH, organic carbon content, and soil texture. However, very important sorption 

of hydrous Fe, Al, and Mn oxides soil minerals were not reported. 

Arsenic solubility and transport in soil is greatly affected by soil sorbents and Kd

inputs into transport models. It is well known that the major chemical process that 

affects transport of As is adsorption of As(V) or As(III) to hydrous Fe, Al, and Mn 

oxide minerals. The amount of As transported will depend on the type and amount 

of these minerals in soil. These mineral sorbent phases were not measured in the 

soils from CCR facility sites and most are not in the MINTEQA2 model. Because 

one of the most critical chemical processes (sorption to oxides) affecting As 

transport was not used to calculate Kd values for input into EPACMTP, As 

solubility and subsequent transport is overestimated. Soil content of hydrous Fe, 

Al, and Mn oxide minerals ranges from < 0.5% for sandy soils to > 50% for 

weathered clay soils of the southeastern U.S., Hawaii, and Puerto Rico. The 

overestimation of As transport in soils with moderate to high levels of hydrous Fe, 

Al, and Mn oxides could be orders of magnitude. 

However, some insight into impact of exclusion of hydrous Fe, Al, and Mn oxides 

on As in leachate is provided from the Draft: “Sensitivity analysis results indicate 

that for most of the scenarios evaluated (over 75 percent), the risk assessment model 

was most sensitive to parameters related to ground water flow and transport: WMU 

infiltration rate, leachate concentration, and aquifer hydraulic conductivity and 

gradient. For strongly sorbing contaminants (such as lead and cadmium), variables 

related to sorption and travel time (adsorption coefficient, depth to ground water, 

receptor well distance) are most important.” This statement implies that As is not a 

strongly sorbing contaminant in the EPACMTP model. Arsenic is strongly 

adsorbed in soil and environmental media. Arsenic is more strongly adsorbed than 

those identified by EPACMTP as “strongly sorbing contaminants (such as lead and 

cadmium).” A likely reason for the poor sensitivity of the EPACMTP model for 

arsenic sorption is an inaccurate input Kd value generated from MINTEQA2. 
Response to Peer Review Comments Ground Water Modeling

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One approach to answer the question posed, “Do the models capture the major 

physical and chemical processes and mass transport mechanisms that are important 

for the chemical contaminants and exposure scenarios studied?” is comparing Kd

used for transport modeling using EPACMTP in the Draft with Kd values for select 

soils from CCR facilities. Kd values for As and other select contaminants should be 

determined for a set of soils with a range of soil chemical properties critical to 

chemical processes values. This could be conducted using column studies under 

controlled laboratory conditions. Modeled Kd values used in the Draft must be 

validated by comparison to Kd values derived from real soil and/or geomedia to 

assure that the EPACMTP model captures the major chemical process critical to 

transport. 

Arsenic speciation was considered in the Draft as a source of uncertainty. In the 

Draft (p. 4-30): 

“Because the soil and ground water models assume one form for each model run, 

the risk results presented for arsenic are based on arsenic(III), which is a 

conservative, protective assumption (i.e., arsenic(III) has higher risks than 

arsenic(V)). Although arsenic is generally thought to occur in the +3 form in 

leachate, there is evidence from damage cases at CCR disposal sites that suggests 

that arsenic(III) is rapidly converted to arsenic(V) during subsurface transport, with 

the result that drinking water standards are rarely exceeded in offsite ground water 

in spite of high landfill leachate concentrations (see, for example, U.S. EPA, 2000b; 

U.S. EPA, 2003e; Lang and Schlictmann, 2004; Zillmer and Fauble, 2004). To 

address this uncertainty (i.e., how much an arsenic III assumption might overpredict 

offsite well concentrations) the models were run assuming arsenic V as the arsenic 

species in soil and ground water. Figure 4-4 compares the risk results for arsenic 

III and arsenic V. Arsenic V has lower risks than arsenic III by about a factor of 

two, As (III) vs. As(V)...” 

The scientific literature has many examples showing As(V) has much lower 

solubility and mobility than As(III) in soil and environmental media. Arsenic(V) 

which occurs as arsenate, is strongly adsorbed to clay / oxide fractions in soil and 

geomedia, whereas As(III) has a much lower adsorption capacity. Also, As(V) is 

more likely to form insoluble precipitates (i.e., scorodite) than As(III). Thus, As(V) 

is often magnitudes less soluble than As(III). It is striking that the differences in 

modeled risk reported in the Draft were less than a factor of 2. These results suggest 

that the models used were insensitive to changes in As speciation (V vs. III). This 

would not be the case under real soil / environmental conditions where much lower 

mobility of As(V) from CCR compared to As(III) would result in reduced risk 

(much greater than a factor of 2) for As. The differences in As transport could be 

overestimated in orders of magnitude because As(III) was used instead of As(V). 
Response to Peer Review Comments Ground Water Modeling

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The results should be modeled using As(V). The Kd values for As(V) and As(III) 

used for inputs into EPACMTP should be reported. The MINTEQA2 outputs used 

to calculate Kd values should be reported also. 

Dr. Charles Harvey, Massachusetts Institute of Technology 

Numerical modeling of reactive transport is a challenging area of research. 

Constructing an accurate reactive transport model for a single site is a very 

ambitious research goal, even with abundant site-specific data. So, of course, 

calculating reactive transport over a wide variety of possible sites requires extensive 

simplifications. 

The models employed here simplify many geochemical processes, and it is easy to 

construct a list of biogeochemical processes that are not included. This list could 

contain processes that would either reduce or increase retardation. Geochemists 

who study surface reactions may criticize the choice of metal oxides and the 

parameterization of their surface characteristics; Geochemists who study organic 

matter may criticize the modeled source of organic matter and its reactivity; 

Geochemists who are interested in redox transformations may criticize the lack of 

redox transformations, such as As(III)/As(V), and the lack of realistic models of 

microbial metabolisms. All of these concerns, and many others, are likely valid at 

some sites, but not others, for some contaminants, but not for others. In other words, 

our ability to model reactive transport may not be sufficiently developed to 

construct good models over a wide range of conditions without constraining these 

models with a very large data set of field measurements. 

So, does is this assessment over-reach by employing a reactive transport model? Is 

constructing an assessment across many sites a hopeless task? Perhaps, but we 

know some simple constraints on the spread of contaminants. First, contamination 

is not transported farther than a conservative tracer. Second, the spread of most 

contaminants is considerably less than for a tracer because they adsorb to the 

aquifer material, and perhaps precipitate. Thus, it seems to me, the tact taken here, 

of reducing the effects of reaction to a set of different simple isotherms, and then 

using these isotherms to model contaminant immobilization and retardation of 

transport, may be the only realistic approach to this problem. 

Perhaps my biggest concern about the reactive transport model is that that it appears 

to use parameters that would represent a mixture of the leachate and ambient 

conditions. For example, Appendix D describes how the pH was calculated as “The 

volume of leachate released from the WMU was mixed with the volume of the 

aquifer that was likely to be impacted by the plume”. This approach misses an 

important fact about solute transport in aquifers: the volume of mixed water may 

be very small; most of the ground water is either in the plume, or out of the plume. 

The mixing zone may be very thin. Correctly modeling a reacting plume is very 
Response to Peer Review Comments Ground Water Modeling

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difficult, but the simple approach taken here would likely be more realistic if the 

conditions within the plume were used to calculate the retardation factor. 

One simple, but important, aspect of the model should be clarified. With the 

retardation approach, not only is the residence time of a solute increased by its 

retardation factor, but the concentration must also be decreased by the retardation 

factor. I suspect that the models used in this study correctly reduced the 

concentration by the retardation factor, but I found the text confusing on this issue. 

If this simple effect was not included it would be a serious error. 

EPA Response 

Geochemical Modeling 

EPA recognizes that explicit reactive/geochemical modeling would be more realistic than using 

linear and nonlinear partitioning coefficients. EPA considered the use of the Objects Representing 

Chemical Speciation and Transport (ORCHESTRA) model because it can account for geochemical 

interactions such as aqueous complexation, precipitation, surface complexation, and ion exchange 

(Meeussen, 2003). However, such modeling is not a practical approach for a nationwide analysis 

because the data collection effort necessary to populate such a model on a nationwide, site-based 

level would be prohibitively expensive. Even assuming such data were available to populate the 

ORCHESTRA model, the level of complexity to account for highly variable geochemical and 

hydrogeologic conditions nationwide and time necessary to run such a model would also be 

impractical. Furthermore, the use of Kd as a surrogate for dilution/precipitation processes is a 

widely used and accepted method in both the scientific literature and the ground water modeling 

community, provided the values of Kd used are appropriate to account for the range of potential 

attenuation processes (U.S. EPA, 1999). Therefore, for a nationwide analysis, Dr. Harvey is correct 

in stating that the use of Kd values is a practical and necessary simplification. 

Selection of Sorbents 

In recent years, databases of equilibrium sorption reactions have been compiled in the literature 

for two forms of iron oxide, hydrous ferrous oxide (HFO) and goethite (Dzombak and Morel, 

1990; Mathur, 1995). Because of the availability of these data and the prevalence of iron oxides in 

the environment, these are the hydrous oxide sorbents available for MINTEQA2 modeling. Other 

common hydrous oxides that can sorb chemicals include hydrous oxides of aluminum, manganese, 

and silicon (Dzombak and Morel, 1990); however, there were insufficient data to incorporate these 

sorbents. 

Furthermore, EPA chose goethite as the most appropriate form of iron oxide for the risk assessment 

to avoid an underestimation of risk. While both goethite and HFO are common forms of iron oxide 

in soils, goethite is a much poorer adsorbent than HFO, thereby leading to relatively greater ground 

water plume concentrations. However, there is still the potential for HFO or other sorbents to be 

present at some CCR disposal sites. Thus, to reach a conclusion, EPA consulted experts who had 

published on this subject (Dr. David Dzombak and Dr. Samir Mathur) and the developer of 
Response to Peer Review Comments Ground Water Modeling

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MINTEQA2 (Dr. Jerry Allison). As pointed out by Dr. Harvey in his peer review, the approach is 

“likely valid at some sites, but not others,” yet “using these isotherms to model contaminant 

immobilization and retardation of transport, may be the only realistic approach to this problem.” 

EPA agrees that this was a necessary assumption. 

Nevertheless, EPA has added discussion to the risk assessment to clarify issues raised by the 

commenters. Appendix H of the revised risk assessment discusses the development of Kd values 

using MINTEQA2 as well as the associated uncertainties. Furthermore, Attachment H-1 

graphically presents the full isotherms for each constituent modeled and Attachment H-2 displays 

select percentiles of the Kd values selected in the analysis. These values were derived from the 

isotherm sampling performed by EPACMTP and used in the modeling. A listing of all individual 

Kd values available in the MINTEQA2 isotherms used in these analyses would not be practicable. 

Instead, the full input and output files are available to the public in the docket. 

Comparing to Real-World Kd Values 

As suggested by Dr. Basta, EPA considered comparing the modeled Kd values to available 

estimates in the published literature, but did not do so for two reasons. First, there are many 

individual values within each Kd isotherm that depend both on constituent concentrations and 

master variables, such as pH, organic carbon, and iron oxide concentrations. Second, there is 

generally limited information available about the conditions under which published values were 

measured. Therefore, not only would this comparison be complicated to perform, it would also be 

subject to numerous uncertainties, making it unlikely to provide a basis for definitive conclusions. 

Instead, EPA notes that the results of the risk assessment are generally in agreement with damage 

cases, as discussed in Section 5. 

Leachate-Aquifer Mixing 

The approach adopted in the risk assessment to determine the value of pH in the aquifer (used to 

select Kd) and the subsequent calculation of the retardation factor assumed that, after entering the 

aquifer, the leachate plume would thoroughly mix with the ambient, uncontaminated ground water. 

One reviewer stated that the mixing zone would only be present at the periphery of the ground 

water plume. This is consistent with the general conceptual model used in this risk assessment of 

uniform subsurface flow with recharge. However, EPACMTP requires a constant ground water 

pH to model transport with nonlinear sorption isotherms. EPA assumed full mixing as a more 

conservative approach because, for most metals, sorption/precipitation tends to increase (i.e., Kd

goes up) with higher pH, which is characteristic of certain types of CCR leachate (i.e., assuming 

full mixing lowers the ground water pH and, thus, decreases sorption). To characterize the potential 

effect of this simplifying assumption on calculated risk results, EPA conducted uncertainty 

sensitivity analysis that is presented in Section 5 of the revised risk assessment. 

Arsenic Speciation 

Dr. Basta also pointed out that literature on arsenic (V) often shows it to be orders of magnitude 

less soluble than arsenic (III), which appears inconsistent with the results of the draft risk 
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assessment that found similar exposure concentrations for both arsenic species. As a result of 

revisions to the risk assessment, the modeled concentrations of arsenic (III) and arsenic (V) are 

now generally an order of magnitude different, although the specific results vary between 

pathways. A primary cause of this difference is likely the increased distances to receptors in the 

revised risk assessment. The increased distance would lead to additional arsenic (V) attenuation 

because it generally has greater Kd values, consistent with the comments provided by Dr Basta. 

Retardation Factor 

Finally, with respect to Dr. Harvey’s comment, the contaminant transport formulations in both the 

unsaturated and saturated modules of EPACMTP correctly include a sorption term that represents 

the transfer of dissolved contaminants from the liquid phase to the solid phase by way of a 

retardation factor or an isotherm describing the change in sorbed concentration with respect to 

dissolved concentration. Further discussion of the retardation factor can be found in Section 4.4.3.1 

of U.S. EPA (2003b). Since the documentation for EPACMTP already discusses this issue, no 

changes were made in response to this specific comment. 

2.3. Site-Specific Analysis and Comparisons with 

Measured Data 

Comment Summary 

Three reviewers (Dr. Basta, Dr. Harvey, and Dr. Vorhees) submitted comments that fall into this 

subcategory. Dr. Basta and Dr. Vorhees recommended conducting more detailed, site-specific 

analysis to increase confidence in the risk assessment results. They expressed concern that the 

results are difficult to evaluate given the significant variability and uncertainty associated with the 

national scope of the analysis. 

Dr. Nicholas Basta, Ohio State University 

EPA is to be commended on the great effort expended to conduct a nationwide 

assessment of risks posed by CCR disposal practices. However, is it possible to 

model human and ecological risks across the wide range of scenarios found 

nationwide at different CCR facilities? Confidence in such an all-encompassing 

model can only be achieved with (1) verification or “ground-truthing.” There is a 

wealth of field leachate and impact data from CCR disposal facilities. Because of 

the great uncertainty in the model, the model should be validated on a case-by-case 

basis with the CCR field data to gain acceptance for the EPA CCR risk assessment 

model. Perhaps a subset of CCR facilities can be selected for verification of the risk 

assessment model output. This validation of model results must be performed 

before any decisions on CCR waste management are required of specific CCR 

facilities. 
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Dr. Charles Harvey, Massachusetts Institute of Technology 

The model described in this report predicts the distribution of contaminant 

concentrations downstream of WMUs. The obvious next step is to test the model 

by comparing it to measurements. This is easily accomplished by simply (2) 

collecting and analyzing some water samples, then testing the hypothesis that the 

measured values come from the same distribution predicted by the model. This is 

the scientific method. 

Dr. Donna Vorhees, The Science Collaborative 

Need for More Site-Specific Analysis. The primary challenge in conducting this 

review was to interpret results of this ambitious, national-scale PRA [probabilistic 

risk assessment] in light of the myriad sources of uncertainty associated with the 

exposure scenarios and risk models. The national scale of this assessment 

introduces complexity and uncertainty that perhaps could be reduced if EPA 

examined a representative subset of WMUs in more detail to better understand the 

technical strengths and weaknesses of its nationwide approach. One starting point 

might be those WMUs that are represented in existing surveys of WMUs (i.e., 

EPRI, 1997 and [U.S.] DOE, 2006) and in EPA’s CCR constituent database. For 

example, I am aware of one site referenced in Figure 4-5 that was the subject of a 

relatively recent risk assessment that was submitted to the Massachusetts 

Department of Environmental Protection. Public commentary submitted from 

industry and government (State of Wisconsin) representatives noted the availability 

of additional data, and these leads should be explored to determine if high quality 

data are available beyond what is already included in the risk assessment. EPA does 

make reference to WMUs involved in damage cases, but these WMUs are not 

necessarily representative of all WMUs. EPA’s risk assessment embodies an 

enormous amount of work and creative, thoughtful modeling. But, at a minimum, 

EPA needs to provide a compelling reason for not attempting some site-specific 

analyses, which is the most effective way to reduce uncertainty in the PRA. 

EPA reports that it has data for antimony, cobalt, mercury, and thallium from, at 

most, “a few” sites and with “only a few measurements” (page 4-32). EPA should 

explain why this is the case (e.g., elevated detection limits, not included on analyte 

lists at surface impoundment WMUs). Screening results in Table 2-3 suggest that 

it would be worthwhile to resolve whether these constituents are present and at what 

concentrations. 

EPA Response 

EPA agrees with the reviewers that confidence in the results of an environmental fate and transport 

model increase significantly when model predictions can be compared favorably with measured 

field results. However, site-specific modeling involves extensive data collection and detailed 
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modeling (representing site-specific conditions and processes), which was not possible with the 

available resources for the assessment. Instead, EPA compared the results of the national 

probabilistic, Monte Carlo analysis to proven and potential damage cases from across the United 

States. These damage cases represent real-world instances of contamination from CCR WMUs 

that provide the best available comparison for the results of the risk assessment. This comparison 

is presented in Section 5 of the revised risk assessment. 

With respect to constituents that EPA did not model for the codisposed ash and coal refuse 

scenario, EPA acknowledges that this was due to low sample sizes and high detection limits. 

Cobalt was mistakenly placed on this list since it was modeled in both the draft and revised risk 

assessments. For mercury, EPA has incorporated additional data with lower detection limits in the 

revised risk assessment, allowing EPA to conduct probabilistic modeling. However, for antimony, 

beryllium and thallium, EPA did not have sufficient data on codiposed ash and coal refuse. Thus, 

it was not possible to develop values for these constituents for codisposed ash and coal refuse. This 

is noted in Appendix H of the revised risk assessment. 

2.4. Well-Related Issues 

Comment Summary 

Comments relating to the number of wells contaminated, the realistic risk of exposure, well 

placement within the plume, and other well-related issues were received from Dr. Harvey, Dr. 

Rowe, and Dr. Vorhees. Dr. Harvey’s comments focused on the assumption that the wells used in 

this assessment are contaminated (i.e., located within the plume), even if the well location used 

reflects a deeper well that may be screened in an uncontaminated aquifer; the manner in which the 

assessment handles uncontaminated wells, plume characteristics, ground water–surface water 

interactions and vertical contaminant concentration across a screened interval in an aquifer; and 

the values used for plume dispersivity. Drs. Rowe and Dr. Vorhees commented on this 

assessment’s use of water well distances from MSW landfills and EPA’s belief that these distances 

would be protective for CCR waste. 

Dr. Charles Harvey, Massachusetts Institute of Technology

At the heart of this assessment is a Monte Carlo simulation that first generates 

realizations of contaminant breakthrough curves at a well that has been 

contaminated by a WMU. These realizations provide a set of exposures that are 

then used to determine a distribution of health risks. This approach does not attempt 

to calculate a probabilistic description of the number of wells that are contaminated. 

Rather, this Monte Carlo approach characterizes the distribution of breakthrough 

curves assuming that a well is contaminated. 

This approach has merits, but it also presents puzzling conceptual problems 

stemming from the fact that the calculated health risks are independent of the 

probability that the contaminated well actually exists. The following example 
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illustrates the difficulty. In comment II.B. below, I will discuss how, wherever there 

is a river or stream between the source and the well, ground water will likely 

discharge into the river, preventing the plume from reaching more distant wells. 

Consequentially, wells far from the source cannot be contaminated and health risks 

are reduced. However, in the framework used in this report, the calculated health 

risks would actually increase for a shorter plume – reducing the plume length forces 

the Monte-Carlo model to select a well closer to the source where concentrations 

are higher and arrival times are quicker. Since every realization of the ground water 

exposure pathway must generate a well position, short plumes will actually have 

worse adverse health effects because the wells generated by the Monte Carlo study 

will be closer to the source where contamination concentrations are worse. Thus, a 

reduction in the probability of exposure does not necessarily reduce the probability 

of adverse health outcomes in this model. This problem also exists when defining 

plume width (see II.B below). It is a fundamental problem of the framework of this 

assessment that extends beyond these examples. The difficulty arises because this 

assessment does not attempt to characterize the number of wells contaminated, and 

hence does not consider the size of the population that would suffer adverse health 

effects. 

This report would benefit from a candid discussion of these issues – a 

straightforward explanation that the calculated health dangers are conditioned on a 

well being contaminated, but that in fact many wells, or few wells, could be 

contaminated. After reading the public comments, I believe that this discussion 

would be valuable – it appears that the authors of these public comments may not 

have understood this issue. 

Public understanding of the dangers of contaminated ground water down-gradient 

of potential sources of contamination has grown over the last decades so that it is 

unusual to site new wells, or to leave existing wells, in the flow-paths downgradient of obvious contaminant sources such as a waste site. Because studies such 

as this have documented the serious health dangers of contaminated ground water, 

and because severe contamination has often been found down-gradient of waste 

sites, people and local government are aware of the dangers and have taken action 

to avoid the use of contaminated water. Although the risk to people drinking 

contaminated ground water certainly still exists, it has receded. Again, this report 

would be improved by a discussion of the issue of contaminated wells actually 

being used for water supply. 

The report nicely integrates the few available national data sets of hydrogeolgic 

parameters. My comments largely concern the interaction of the choice of well 

position with the solute transport model. The Monte Carlo simulation places a well 

at random (uniformly distributed) angular offset from the plume center line, at a 
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depth generated from a uniform distribution of depth between the aquifer top and 

bottom, and at a distance from the source generated from a distribution of distances 

measured in 1988 for WMUs. This framework is basically reasonable. However, 

the implementation is not fully explained and there may be some opportunities for 

improvement. 

(A) Definition of the Plume Width 

The definition of the plume size is very important for this assessment, but it is not 

clear how the margin of the plume is defined. Contaminant concentrations typically 

fall-off gradually away from the center of a plume. Therefore, the choice of the 

width of the plume is somewhat arbitrary – it depends on the minimum 

concentration used to define the extent. The margin could be defined as the 

outermost flow path that originates from the waste site. (i.e. the plume that would 

be simulated with zero dispersion) However, this definition would exclude 

contamination that disperses out of this flow path. So, a better definition of the 

plume extent would use a minimum concentration – but what concentration should 

be used? 

This problem of plume definition plays directly into the conceptual problem 

described above in comment I.A. If a low concentration is chosen to define the 

plume margin, then the well may be placed in a much larger area of low 

concentrations, and hence the calculated health risks will be small. If the plume 

margin is defined by a high concentration, then the well will be placed in a high 

concentration region, and the calculated health risks will be worse. In either case, 

the simulated plume is the same – but defining the margins with a low concentration 

such that the plume is larger will lower the health risks. 

(B) Transverse Dispersion 

In a steady-state flow model, such as used in this study, the lateral spread of the 

plume is largely controlled by the transverse dispersivity. Consequentially, the 

transverse dispersivity is the key aquifer parameter for determining both the width 

of the plume and the dilution of contaminants. Recent field and laboratory 

experiments show that there is much less spreading in the transverse direction than 

in the direction of flow, and hence the actual values of transverse dispersivity are 

very small, so small that is difficult to simulate solute transport accurately with 

many numerical techniques that attempt to model dispersion. I find no mention in 

the report of the values used for transverse dispersivity. This report should: (1) Give 

the values used in the transport simulations, (2) Describe how this value was 

chosen, and (3) Describe the sensitivity of the results to the chosen dispersivity 

value. 

(C) Depth of the Plume 
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Vertical spreading is much like transverse spreading – little spreading occurs in the 

vertical direction. Realistic dispersivities are so small that they are difficult to 

include in simulation models. So, again, one wonders what values were used, and 

how the simulation was performed. 

However, the effects of vertical spreading on contamination of wells differs from 

horizontal spreading because wells are often screened over large vertical 

increments so wells often extract water that contains a mix of concentrations over 

a vertical extent of the contaminated aquifer. Wells can be screened over 10m, and, 

depending on the pumping rate, can draw water from the full thickness of the 

aquifer. Thus, the vertical concentrations might be better approximated by 

averaging concentrations vertically. 

Finally, geologic formations are often layered with deep confined aquifers 

separated from shallow unconfined aquifers by low permeability layers. Wells are 

often placed in the deeper aquifer, but local contamination is often restricted to the 

upper aquifer. Some of the data used to construct the distribution of well locations 

may reflect wells that tap deeper aquifers that will remain uncontaminated by 

WMUs. 

(D) Rivers May Limit the Distance from the Source 

I suspect that many waste sites are near rivers because power plants are often along 

rivers. Except in arid regions, rivers are typically gaining, meaning that ground 

water discharges into the river. Indeed the mean distance to surface water calculated 

in this report is less than the mean distance to a well. Consequentially, contaminant 

plumes discharge into rivers, and hence the maximum length of a plume is limited 

by the distance to a river. It is not clear from Figure 3-7 that plumes are constrained 

by the distance to surface water, although these distances are used for the 

calculation of risks to fishermen and ecological risks. 

Dr. Kerry Rowe, Queens University 

In the absence of an actual survey of water well usage around existing CCR 

facilities, I am not aware of a better source of data than that available for MSW 

landfills. EPA recognized this as “one of the larger uncertainties in this analysis” 

(RA, pg. 4-37) however the statement that “EPA believes that the MSW well 

distance distribution used is protective for CCR landfills and surface 

impoundments” (RA, pg. 4-37) appears to be nothing more than that – a belief – 

with no justification being given for this article of faith. Also, as noted in response 

to Question #5, the analysis extends for 10,000 years but no consideration appears 

to have been given to likelihood of increased demand for the use of ground water 

in the next 30-100 years (let alone the next 10,000 years) which presumably means 

more wells and makes the protection of ground water likely even more important 
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for the future than it is now. It would have been good to have examined the 

implications of wells being closer than that indicated by the MSW survey to assess 

how sensitive the RA is to that assumption (one can infer that it will be important 

– but not how important in terms of risk). 

Dr. Donna Vorhees, The Science Collaborative 

Distribution for Distance to Drinking Water Wells. This distribution is the subject 

of one of our charge questions: 

 Charge Question #11: The CCR risk assessment used a distribution of well distances 

measured at MSW landfills. Is this distribution appropriate for CCR disposal 

facilities? Are there better or more representative sources of well-distance data for 

CCR disposal facilities that should be used instead? 

It might be appropriate, but it is hard to say in the absence of any real measurements 

from WMU locations. One public comment on this distribution refers to its bias, 

which EPA describes as conservatism. I agree that such bias should be avoided in 

conducting PRA. EPA does not explain why it could not obtain measurements from 

at least a representative sample of WMUs. 

EPA explains that: 

“...the MSW well distance distribution is a conservative representation of actual 

well distances at CCR disposal sites. However, data on residential well distances 

from CCR landfills or surface impoundments will be needed to verify this 

hypothesis” (Appendix C, Section C.2). 

This sentence seems to suggest that EPA will perform additional analyses at some 

point and possibly update the risk assessment. This would indeed be a useful step, 

and EPA’s intentions should be clarified. 

EPA assumes that the drinking water pathway exists at all WMU locations, using 

the distance between municipal landfills and drinking water wells as surrogate 

measures for the distance between WMUs and drinking water wells. EPA 

appropriately cites the uncertainty associated with this surrogate information but 

does not explain the specific impediments to obtaining data specific to at least a 

representative subset of WMUs. Because everyone must drink water, presumably 

everyone served by these hypothetical wells would be exposed, although EPA 

correctly notes that people are likely to get some or all of their water from other 

sources. This exposure pathway might not occur near every WMU and assuming 

so contributes to the uncertainty in the risk output distribution of risk for this 

pathway. 
Response to Peer Review Comments Ground Water Modeling

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EPA Response 

In cases where receptor wells are located downgradient from a surface water body that intersects 

the ground water table, some or all of the ground water, along with the mass of constituents 

contained therein, is intercepted by the water body before it can reach the well. This interception 

was not modeled in the draft risk assessment. However, a review of the input database for the draft 

risk assessment found that such a water body was present in approximately two-thirds of the Monte 

Carlo runs. Furthermore, ignoring the loss of constituent mass had the effect of overestimating 

exposures. Thus, in the revised risk assessment an EPACMTP model postprocessor was created to 

account for surface water interception by removing constituent mass flowing into the water body 

from the ground water plume, and leaving only the remaining ground water available to migrate 

to a drinking water receptor. The approach used to account for interception is discussed in further 

detail in Section 4 and Appendix J of the revised risk assessment and the uncertainties associated 

with this approach discussed in Section 5. 

The reviewer comments regarding placement of receptor wells “within the contaminant plume” in 

the Monte Carlo framework are the result of a fundamental misunderstanding about the constraints 

placed on ground water receptor location. Maximum lateral plume extent is selected prior to each 

model iteration rather than based on the result of that iteration. This constraint is more fully 

explained in Section 4.4.3.6 of U.S. EPA (2003b). Since the comment resulted from a 

misunderstanding, EPA does not find the sensitivity analysis suggested by the commenter to be 

necessary. 

With respect to Dr. Harvey’s comment on the placement of wells within deeper aquifers, EPA has 

policy of erring in the direction of protecting human health and environmental quality when 

addressing uncertainties. Consistent with this practice, wells screened within vulnerable, surficial 

aquifers (i.e., the top 10 meters of the saturated zone) will continue to be the primary focus the 

Agency’s national-scale modeling efforts. Dr. Harvey also highlighted the possibility that modeled 

receptor well concentrations may incorrectly represent actual exposures by sampling from a single 

aquifer depth. Wells may be screened across an extended depth, and may capture both 

contaminated and pristine ground water, depending on factors identified in Dr. Harvey’s comment. 

Thus, a discussion of the uncertainties associated with this approach has been added to Section 5

of the revised risk assessment. 

Dr. Harvey’s comment on dispersivity partially highlighted the need for greater transparency. The 

documentation for the draft risk assessment did not include comprehensive tables detailing 

modeling input parameters, their values or distributional characteristics, and the source of the data 

used. These values are, in many cases, publicly available in the EPACMTP Background and 

Parameters/Data Background documents (U.S. EPA, 2003a,b). EPA still finds it unnecessary to 

duplicate this large amount of data. Instead, the revised risk assessment includes an increased 

number of references to these documents, and directs readers to refer to these documents for further 

information. Further discussion of the inputs and outputs used in the risk assessment can be found 
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in Section 8.1 of this response to comments document. Additionally, the full input and output files 

are available to the public in the docket. 

In response to Dr. Rowe’s and Dr. Vorhees comments on the use of MSW landfill data to predict 

the distance to private wells, EPA has eliminated the use of the MSW data in the revised risk 

assessment. Instead, EPA used synthetic population data derived from the U.S. Census to place 

each household and its occupants at discrete points across the landscape. Synthetic populations are 

a representation of households and individual residents in a given area and are based on methods 

to identify more realistic locations using LandScan USA 90-meter gridded population dataset 

(Bhaduri, 2007). This is discussed in more detail in Appendix B of the revised risk assessment.
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3. Source Modeling 

The comments relating to source modeling are divided into 12 subcategories: 

1. The use of leachate concentrations based on toxicity characteristic leaching procedure 

(TCLP) data and the availability of more representative results from EPA’s research with 

Vanderbilt University 

2. The use of 2006 U.S. Department of Energy (DOE) facility data and liner scenarios 

3. Alternative waste disposal/codisposal scenarios 

4. Updates on liner leakage assumptions 

5. Treatment of nondetect CCR constituent values 

6. The effect of waste compaction on infiltration and leaching 

7. Hydrologic Evaluation of Landfill Performance (HELP) model infiltration rates and 

landfill cover assumptions 

8. Scenarios where the water table is above the disposal unit 

9. The impact of increased mercury capture under future air emission control regulations 

10. The use of pore water data for surface impoundment source concentrations 

11. Modeling surface impoundments only before closure 

12. Modeling landfills only after closure. 

3.1. Use of TCLP Data and the Availability of the 

Vanderbilt Study 

Comment Summary 

This subcategory addresses comments from Dr. Basta, Dr. Hopkins, Dr. Rowe, and Dr. Vorhees. 

These reviewers expressed concern about the hierarchical process of choosing data from different 

leaching methods and the predominant use of TCLP data to derive source concentrations for the 

risk assessment, because the TCLP laboratory method is intended to mimic conditions in municipal 

landfills rather than CCR monofills. In the presence of organic acids associated with municipal 

waste degradation, the mobility of metals can be significantly impacted by the more acidic 

conditions and complexing organic acid molecules. Because organic acids are not present in CCR, 

leachate concentration estimates based on TCLP results may differ significantly from leachate 

concentrations under actual CCR field conditions. The reviewers also suggested that the 

availability of a new leachate study by Vanderbilt University would provide useful data. 
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Dr. Nicholas Basta, Ohio State University 

In the Draft (p. 4-32), the importance of leachate data is acknowledged in the quote 

“...waste leachate concentration is arguably the most important data set in terms of 

driving the risk assessment results.” Therefore, additional information that 

improves the waste leachate data set would be expected to significantly reduce key 

uncertainties. Selection of appropriate analyte data for landfills in the CCR 

constituent database (p. A-4) is a hierarchical process of data from different 

leaching methods. The hierarchy is described as (a) landfill leachate or pore water 

data given greater preference than TCLP or SPLP [Synthetic Precipitation Leaching 

Procedure], and (b) selection of the highest concentration between SPLP and TCLP. 

The Draft recognizes the quality of the data is much greater for pore water than 

TCLP. Then, the Draft uses mostly TCLP data as input. 

The TCLP method used to generate most of the input leachate data in the Draft is 

improper for determining leachate concentration from CCR. Improved leachate 

methods, designed for CCR, should be used to generate data in the Risk 

Assessment. 

TCLP was developed to characterize waste behavior in municipal landfills. It is not 

a predictive method. TCLP extracts are acidic (pH < 5), buffered with acetic acid, 

and designed to simulate decaying organic waste (i.e., food, etc.). However, 

conditions are very different in CCR landfills where organic acids from municipal 

solid waste are absent and conditions are more likely to be neutral to alkaline than 

acidic. TCLP is a gross extraction to classify disposal of waste materials in either 

hazardous or nonhazardous landfills. TCLP was not designed to model specific 

physiochemical processes such as leachate from CCR landfills. Therefore, TCLP 

data should not have been used to perform risk assessment calculations of CCR. 

The following is stated in the Draft (p. 4-32) recognizing the limitations of the 

TCLP method: “The available landfill data are largely derived from the TCLP, a 

laboratory test designed to estimate leachate concentrations in MSW landfills.” The 

use of TCLP data in the risk assessment is justified as follows: 

“The TCLP has been shown to both over and under predict leachate concentrations 

for other waste disposal scenarios, so the use of the TCLP data to represent CCR 

leachate is another source of uncertainty. However, as noted below, this does not 

appear to be a significant source of uncertainty for this analysis.” 

To support this contention, limited results of leachate data from CCR material from 

a study conducted at Vanderbilt University (U.S. EPA, 2006b) were compared with 

extraction data used in the CCR Risk Assessment for As and Se [selenium] (Fig. 4-

5). Overlap of the ranges of As concentration reported in Vanderbilt (2006) [U.S. 

EPA, 2006b] and the Draft CCR for 5 of the 6 CCR facilities is used to conclude: 
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“Although the Vanderbilt Study does not cover all of the metals addressed in the 

CCR analysis, its general agreement with the CCR arsenic and selenium levels does 

help allay concerns that the TCLP CCR leachate values used in the analysis 

markedly overestimate or underestimate the concentration’s actual CCR leachate” 

(4-34). 

This is not a sufficient justification for use of TCLP data as acceptable data because: 

(a) A comparison of results from six CCR facilities is inadequate. To accept TCLP 

data as an acceptable data, a comparison should be made between TCLP data and 

actual leachate for all CCR materials. 

(b) The comparison between TCLP and actual leachate data would have to be 

extended to include all the input data used in the risk assessment. 

Accurate input data is critical to determine risk for a specific site. For example, data 

present in the Draft from Vanderbilt (2006) [U.S. EPA, 2006b] for the St. Clair 

facility of 0.001 mg/L for As is 60 times lower than ca. 0.06 mg/L used in the Draft 

Risk Assessment (Fig. 4-5). 

Recently, research has improved the scientific understanding of the generation of 

leachate from CCR, in particular for mercury, arsenic, and selenium (USEPA, 

2006[b]) and development of new CCR-specific leaching methods (USEPA, 

2006[b]; Kosson et al., 2002) Improved leachate methods, designed for CCR, 

should be used to generate data in the Risk Assessment. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

It is widely recognized that TCLP data are not adequate for characterizing how coal 

combustion wastes will behave in a field setting. There are a number of serious 

problems with using this test to predict long-term behavior of these wastes, some 

of which were highlighted in the National Academy of Sciences [National Research 

Council] 2006 report (pages 143-152). Unfortunately, TCLP data may simply be 

the best available for the time being, but when better alternatives are developed 

(there are ongoing, active efforts to do so) the EPA should determine whether the 

outcome of those tests suggest a re-evaluation of this risk assessment. 

Dr. Kerry Rowe, Queens University 

The use of landfill data largely based on TCLP is potentially subject to criticism. 

An attempt is made to address this issue (e.g. RA, pgs. 4-32 to 4-34). At least for 

arsenic and selenium a good case is made that the parameters used in the RA are 

reasonable for arsenic and or potentially unconservative for selenium. However it 

is not clear from the documentation how one can validly distinguish between the 

leachate from conventional CCR and CCRs co-disposed with coal refuse if data is 

based on the TCLP. One would anticipate that potentially higher concentrations of 
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metals in the more acidic leachate associated with co-disposal than for conventional 

CCR. There may be data in the Vanderbilt study that provides insight regarding this 

matter however it is not addressed in the current RA. 

The use of landfill data largely based on TCLP is potentially subject to criticism, 

especially for the CCR given the pH used in the TCLP test. However the report 

does address this concern (pgs. 4-32 to 4-34) and at least for arsenic and selenium 

a good case is made that the parameters used in the RA are reasonable for arsenic 

and or potentially unconservative for selenium. 

If more work were to be done today there is at least the data from the Vanderbilt 

study however it would appear that if more work is to be done it should also look 

at the implications of flue gas mercury controls. 

Dr. Donna Vorhees, The Science Collaborative 

Specifically, EPA describes and partially analyzes data that have been collected 

recently by EPA and DOE (DOE 2006) that reflect changing practices at WMUs. 

EPA also refers to findings from its study of CCR chemistry and leaching behavior 

([U.S.] EPA 2006b). EPA explains that these data were not included because the 

risk assessment was performed in 2003 (page 1-1). EPA acknowledges that 

inclusion of these data might result in lower risk estimates. Without reviewing them 

in detail, it is not possible to say whether inclusion of these data would 

“significantly improve” the risk assessment, but I see no logic to excluding them. 

Without inclusion of data that represent more recent conditions such that the 

database as a whole is representative of WMUs used for CCR disposal, EPA’s data 

set is not of sufficient quality and quantity to support the objectives of the risk 

assessment. EPA reports that it “is currently evaluating how to best incorporate and 

address the results and findings of these studies in future efforts to address CCR 

management practices” (page 1-1). This statement raises another question: how will 

the results of this risk assessment be used? Are they just interim calculations that 

EPA plans to supplement with future analyses that include these more recent data? 

EPA appropriately acknowledges limitations associated with TCLP data and 

compares it to higher quality data that it collected more recently (See Figure 4-5). 

EPA argues that the data sets are similar but this figure suggests otherwise. It would 

be interesting to see how risk estimates change with the exclusion of TCLP data, 

assuming this can be done while maintaining a representative dataset. 

EPA Response 

For surface impoundments, only pore water and impoundment water data were used. Therefore, 

this issue is not relevant for the surface impoundment scenario. For landfills, EPA agrees that 

TCLP may not be the most appropriate leachate extraction method for all waste streams and all 

disposal scenarios. The draft risk assessment relied on a hierarchy of dissolved concentration data, 
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ranging from field leachate data to TCLP, to characterize leaching from landfills. Because new 

data collected using the Leaching Environmental Assessment Framework (LEAF) test methods 

has been made available through a series of EPA reports (U.S. EPA 2006b, 2008b, 2009b), EPA 

no longer relies on TCLP to model landfill leachate. These new data account for the range of pH 

values that are typically seen in CCRs, as well as the liquid to solid ratio of the pore water. The 

data were collected with three LEAF methods, specifically: 

 SW-846 Method 1313 (and its predecessor, Method SR02); 

 SW-846 Method 1314; and 

 SW-846 Method 1316 (and its predecessor, Method SR03).2

The data from these three methods were used in conjunction to effectively characterize landfill 

leaching. All three methods are summarized in Appendix C, with the leachate data provided in 

Attachment C-5 of the revised risk assessment. Additionally, the interlaboratory validation for 

these methods are described in U.S. EPA (2012a,b), lab to field comparisons are presented in U.S. 

EPA (2014a), and Kosson et al. (2002) provides the detailed test methodology for SR02 and SR03. 

3.2. 2006 DOE Facility Data and Liner Scenarios 

Comment Summary 

Dr. Rowe pointed out that the risk assessment results represent outdated conditions, because the 

U.S. DOE (2006) study indicated that the proportion of lined versus unlined landfills had increased 

since the 1995 EPRI data (EPRI, 1997) that were used in the risk assessment. 

Dr. Kerry Rowe, Queens University 

Objectives 2 and 3 are generally considered to have been met, particularly in the 

context of the stated intent (RA, §4.4.1, pg. 4-27) to “characterize current 

conditions by estimating risks from actual CCR disposal sites across the country” 

based on data relating to facilities that existed in 1995 as identified in the EPRI 

(1997) report. However, as acknowledged in the RA at various points (e.g. RA, 

§4.4.1, pg. 4-28), the proportion of lined landfills appears to have changed 

significantly between the 1995 data and the subsequent U.S. DOE (2006) study. 

This does not affect the assessment of the risk associated with the facilities that 

existed in 1995 but the data does need to be carefully interpreted if it is to be used 

to assess the risk of future facilities and for developing future management options 

(Objective 2). For example the combination of data (“All Units Combined”) to 

evaluate 90th and 50th percentile risks (e.g. RA Tables 4-5 to 4-10) makes sense in 

assessing the general risk associated with the 1995 facilities but does not represent 

the risk associated with facilities constructed post 1995. On the other hand the 

 

2 Methods SR02 and SR03 are predecessor methods to SW-846 Methods 1313 and 1316. 
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separately evaluated risks for “unlined”, “clay-lined” and “composite-lined” units 

can be considered to be useful to the EPA for the development of management 

options for future CCR facilities (Objective 2). 

The limitations associated with the CCR management data being based on the EPRI 

(1997) sites is acknowledged in the RA (e.g. pg. 4-28). However, this could have 

warranted a little greater discussion to acknowledge the issues raised above in 

response to Question #1. 

As discussed in response to Question #1 (and repeated here for completeness), the 

proportion of lined landfills appears to have changed significantly between the 1995 

data and the subsequent U.S. DOE (2006) study. This does not affect the assessment 

of the risk associated with the facilities that existed in 1995 but the data does need 

to be carefully interpreted if it is to be used to assess the risk of future facilities for 

developing future management options. 

The combination of data (“All Units Combined”) to evaluate 90th and 50th 

percentile risks (e.g. RA Tables 4-5 to 4-10) makes sense in assessing the general 

risk associated with the 1995 facilities but does not represent the risk associated 

with facilities constructed post 1995. On the other hand the separately evaluated 

risks for “unlined”, “clay-lined” and “composite-lined” units can be considered to 

be useful to the EPA for the development of management options for future CCR 

facilities. 

While the information in RA Tables 4-5 to 4-10 for “unlined”, “clay-lined” and 

“composite-lined” units is useful for the development of management options for 

future CCR facilities, it only considers the specific liner conditions at the specific 

sites where those conditions actually exist (e.g. the evaluation of risks for “claylined” is only done for sites that are clay-lined). This is appropriate for evaluating 

the risk associated with these facilities, however even better insight regarding the 

effect of the three liner conditions (“unlined”, “clay-lined” and “composite-lined”) 

could have been obtained by examining all three liner possibilities for all sites used 

in the Monte Carlo study (irrespective of what is currently used) thereby giving an 

assessment of the risk associated with the three lining conditions over a wider range 

of hydrogeologic and climatic environments. While it is unlikely that this would 

change the overall conclusions regarding the relative risk associated with the three 

liner conditions (unlined having the highest risk and clay-lined sites having a 

substantially higher risk than composite-lined sites; RA pgs. 4-39 to 440), it would 

provide a better indication of the benefits to be gained by installing/mandating 

different liners. 

While the information in RA Tables 4-5 to 4-10 for “unlined”, “clay-lined” and 

“composite-lined” units is useful for the development of management options for 

future CCR facilities, it only considers the specific liner conditions at the specific 
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sites where those conditions actually exist (e.g. the evaluation of risks for “claylined” is only done for sites that are clay-lined). This is appropriate for evaluating 

the risk associated with these facilities, however even better insight regarding the 

effect of the three liner conditions (“unlined”, “clay-lined” and “composite-lined”) 

could have been obtained by examining all three liner possibilities for all sites used 

in the Monte Carlo study (irrespective of what is currently used) thereby giving an 

assessment of the risk associated with the three lining conditions over a wider range 

of hydrogeologic and climatic environments. While it is unlikely that this would 

change the overall conclusions regarding the relative risk associated with the three 

liner conditions, it would provide a better indication of the benefits to be gained by 

installing/mandating different liners. 

EPA Response 

Since the purpose of the risk assessment was to evaluate baseline risks for the universe of currently 

operating facilities and WMUs, EPA generally agrees with the reviewer that the 1995 Electric 

Power Research Institute (EPRI) survey may be outdated. Thus, EPA collected data from several 

new sources of information on both the facilities and WMUs that are in operation today. Further 

discussion of these data sources is available in Section 2 and Appendix A of the revised risk 

assessment. However, to the extent that the commenter suggests modeling liners that are not 

representative of current practice, EPA agrees with the commenter that it would not change the 

overall conclusions of the risk assessment, and further notes that this is outside the scope of the 

risk assessment provided in Section 1. However, uncertainties resulting from liner type are 

discussed further in Section 5 of the revised risk assessment. 

3.3. Alternative Waste/Codisposal Scenarios 

Comment Summary 

Dr. Rowe expressed concern about whether the risk assessment considered alternative CCR 

disposal scenarios. Specifically, codisposal with wastes generating more acidic conditions may 

significantly impact the mobility of metals. Dr. Hopkins suggested that the risk assessment should 

consider CCR beneficial reuse options such as structural fill. 

Dr. Kerry Rowe, Queens University 

However as previously indicated in response to Question #2, it is not clear from the 

documentation how one can validly distinguish between the leachate from 

conventional CCR and CCRs co-disposed with coal refuse if data is based on the 

TCLP. One would anticipate that there would be concentrations of metals in the 

more acidic leachate associated with co-disposal than in the leachate from a 

conventional CCR where the pH is expected to be higher. 
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Dr. William Hopkins, Virginia Polytechnic Institute and State University 

Once revised, the risk assessment will be an important document for determining 

what management options for coal combustion wastes are most protective of human 

and ecological health. With this in mind, it seems odd that one of the most attractive 

management options, recycling and reuse, is not considered in the risk assessment. 

While it would clearly be far beyond the scope of this risk assessment to evaluate 

“beneficial uses” of coal combustion wastes on a broad scale (e.g., wallboard, 

cement, etc.), this risk assessment not only serves as an important tool for guiding 

state policies and procedures for disposing of the wastes, but also for using these 

materials for structural fills. 

An increasing number of states consider the use of coal combustion wastes as 

structural fill material to be a “beneficial use”. The National Academy of Sciences 

encouraged using coal combustion wastes as fill material, but not at the expense of 

environmental health or in the name of “beneficial use”. To be clear, I believe it is 

highly desirable to use these wastes for structural fill and as fill material in mines 

in some circumstances. However, it is clear from documented damage cases (which 

include at least one superfund site), this draft risk assessment document, and the 

National Academy of Sciences [National Research Council] 2006 report that 

placement of these materials in landfills can produce undesirable risks if not 

managed properly. These risks can be mitigated by using appropriate safeguards 

such as liners. Similarly, use of these wastes as a structural fill, particularly in large 

monofills without safeguards, could have adverse effects on the environment. 

Because structural fills are often categorized as a “beneficial use”, they are often 

exempt from standards and regulations (no liners or monitoring requirements, etc.) 

that provide safeguards from undesirable outcomes. In light of the findings of this 

risk assessment, the EPA and state regulatory agencies should consider under what 

circumstances structural filling with coal combustion wastes is safe, and under what 

circumstances it poses unacceptable risks that outweigh any perceived benefits. 

EPA Response 

Beneficial use is outside the scope of the risk assessment, as discussed in Section 1. However, EPA 

points Dr. Hopkins to the Agency’s recent work beneficial uses of CCRs, including a peerreviewed methodology for evaluating encapsulated uses (U.S. EPA, 2013b) as well as a document 

applying that methodology to evaluate two of the largest encapsulated uses (U.S. EPA, 2014b). 

EPA plans to develop a conceptual framework for evaluating unencapsulated CCR beneficial uses 

in the future. EPA is also working with the US Department of Agriculture to assess the use of flue 

gas desulfurization gypsum in agriculture. 

With regard to the evaluation of CCRs codisposed with coal refuse, EPA notes that the pore water 

data used to characterize surface impoundments were broken out separately for this waste type. 

The development and application of these waste types is discussed in Section 3, Section 4 and 
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Appendix H of the revised risk assessment, while the associated uncertainties are discussed in 

Section 5. For landfills, waste pH, which is the major driver of variations in Kd values used to 

distinguish waste types, was known with great accuracy for CCRs nationwide because U.S. EPA 

(2009b) compiled a full, nationwide distribution of CCR pH. In this distribution, disposal of ash 

with coal refuse is reflected is the acidic tail of the distribution. For the national probabilistic 

analysis, EPA aggregated model runs for codisposed ash and coal refuse (surface impoundments) 

and acidic waste (landfills) with other wastes so that risks reflected the prevalence of these disposal 

practices. However, EPA also performed sensitivity analyses to understand the extent that the 

lower pH of comanaged wastes could affect risks, which is discussed in Section 5 of the revised 

risk assessment. 

3.4. Liner Leakage 

Comment Summary 

Dr. Rowe submitted a comment addressing the liner leakage assumptions used in the CCR risk 

assessment. The composite liner leakage distribution used in the risk assessment was based on 

empirical data from industrial liners compiled by Tetra Tech (2001). The leakage distribution 

excluded Tetra Tech data from landfills with composite liners containing compacted clay layers. 

The original justification for excluding these types of liners was that water is released from these 

liners through consolidation and may not represent actual leakage. However, Dr. Rowe argues that 

this was an incorrect assumption, because compacted clay layers do not release significant volumes 

of water due to subsequent compaction. 

Dr. Kerry Rowe, Queens University 

The leakage through composite-lined CCR sites was based on data for a limited 

number of existing industrial landfill cells (RA Pg. 3-11). Leakage can vary 

substantially depending on the level of construction quality control and 

construction quality assurance, the wrinkling of the geomembrane when covered, 

and whether the clay liner component is a compacted clay liner or geosynthetic clay 

liner (GCL). Finally the service life of a geomembrane is finite (albeit that it may 

be many hundreds or even a thousand or more years) yet it appears from the 

documentation that the geomembrane was likely to have been intact for the entire 

period modeled (up to 10,000 years). It is expected that if these factors had been 

considered the risks associated with the composite-lined sites would have been 

higher than reported in the RA (Tables 4-5 to 4-10). However this would not change 

the conclusion that composite-lined sites are superior to clay-lined sites and that 

these are superior to unlined sites in terms of reducing risk. 

In the past few years there has been considerable research suggesting that (a) 

geomembranes have a finite service life and (b) leakage through composite liners 

depends significantly on both the nature of the clay component of the composite 
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liner (CCL [compacted clay liner] or GCL) and the presence of wrinkles when the 

liners is covered (which may cover up to 25% of the liner area and hence this 

removes composite action from up to a quarter of the total area). Consideration of 

these factors (see response to Questions #1 above) would improve the RA and 

increase the calculated risk associated with composite-lined sites compared to that 

predicted by the RA. However as already noted above, this would not change the 

conclusion that composite-lined sites are superior to clay-lined sites and that they 

are substantially superior to unlined sites in terms of reducing risk. 

The exclusion of data relating to composite liners with a CCL (RA, pg.3-11) is 

NOT considered reasonable. The amount of water related to consolidation can be 

shown to be small. Also, composite liners with a CCL can be expected to leak much 

more than those with GCLs because of the poorer interface transmissivity (many 

orders of magnitude higher) for CCLs. This approach adopted introduces an 

unconservative bias to the corresponding risk assessment for composite lined sites. 

Furthermore, the results for composite-lined sites do not appear to adequately 

recognize a finite service life for the geomembrane component of the liner (as noted 

earlier). This will result in a consistent underestimate of risk associated with these 

liners (and hence represents a bias). However this would not change the conclusion 

that composite-lined sites are superior to clay-lined sites and that they are 

substantially superior to unlined sites in terms of reducing risk. 

The assumption of a clay liner hydraulic conductivity of 1x10-9 m/s (1x10-7 cm/s; 

RA pg. 3-20) is reasonable provided that the liner had appropriate (a) specifications 

(in terms of clay content, plasticity, compacted water content and density etc.), (b) 

construction quality control and assurance during construction, and (c) it was kept 

moist (to avoid desiccation) prior to covering with waste. Indeed if these conditions 

are all met and provided the typically specified hydraulic conductivity of 1x10-9 

m/s was achieved at the time of covering (as any well-designed and constructed 

clay liner will) then, following loading by waste in a landfill, consolidation will 

likely result in a significant reduction in hydraulic conductivity (to say 1x10-10 m/s 

or possibly as low as 5x10-11 if there is significant applied stress). Thus I consider 

that the value of 1x10-9 m/s used is actually conservative and likely overestimates 

the risk associated with well-designed and constructed clay-lined sites. 

On the other hand, public comments claim that current practice involves the use of 

“compacted CCR as liner materials, if any liner is installed” and that “the few CCR 

landfills that are constructed with clay liners are generally designed with only 2-

feet of 10-7 cm/s compacted clay rather than the 3 feet that are assumed ...” (GeoHydro, pg.4). If CCR material is used and it does not meet typical clay liner 

specification, then this should not be modeled as a clay-lined but rather as an 

unlined site. If, for a CCR landfill, the clay liner meets specification and has an a 
Response to Peer Review Comments Source Modeling

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constructed hydraulic conductivity of 1x10-9 m/s then the fact that it may only be 

2-feet thick (as opposed to the 3-feet assumed) will likely be off-set by the decrease 

in hydraulic conductivity due to consolidation under the weight of the CCR and the 

predicted risk is still likely to range between reasonable and conservative (i.e. erring 

on the high side for clay-lined sites). 

As previously noted above, the leakage calculated as described in the RA (pg. 3-

20) is likely to underestimate the leakage through composite liners and hence 

underestimate the risk associated with these liners. That said, properly constructed 

composite liners are still going to substantially reduce the risks associated with 

CCR disposal compared to unlined and clay-lined sites and this refinement will not 

change the general conclusions of the RA. 

... as discussed in response to earlier questions above, while variability was 

considered with respect to WMU characteristics, there does not appear to have been 

adequate consideration of uncertainty associated with composite-lined sites. 

EPA Response 

The composite liner leakage rates used for this risk assessment correspond to leakage rates 

developed for the peer-reviewed Industrial Waste Management Evaluation Model (IWEM) (U.S. 

EPA, 2002b). The exclusion of data from composite liners containing compacted clay layers was 

based on an assumption that significant volumes of water can be released from clay due to 

consolidation from mechanical compaction from the weight of overlying waste. The fraction of 

leakage attributable to consolidation has not been quantified accurately to date, although the 

potential for clay liners to release consolidation water has been demonstrated. Due to the absence 

of an approach for estimating consolidation flow rates versus leakage, EPA excluded data on 

composite liners constructed with clay from the estimated distribution of composite liner leakage 

rates. Although there is clear literature support for the assumed liner leakage distribution, EPA 

also considered the effect that incorporating these additional data would have on the risk results. 

This sensitivity analysis is presented in Section 5 of the revised risk assessment. However, EPA 

agrees with the commenter that these considerations would not change the overall risk assessment 

conclusions that composite liners are the most protective. 

With respect to the evaluation of liners constructed with compacted CCRs, EPA treated these 

WMUs as unlined. The approach of assigning liner types is discussed in Appendix A of the revised 

risk assessment, while a discussion of the uncertainties associated with liner assignment, as well 

as clay liner thickness and conductivity, has also been added to Section 5. 
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3.5. Treatment of Nondetect Values 

Comment Summary 

Dr. Basta and Dr. Rowe provided comments on the treatment of nondetect values in the CCR risk 

assessment. Dr. Basta’s comments focused on the assessment’s use of half of the detection limit 

when a constituent’s concentration was not detected. He felt that lower values should have been 

used, especially for arsenic and mercury, which were frequently not detected but drive exposure 

pathways. Dr. Rowe suggested that the analysis could use the mercury concentration distribution 

(as shown in Figure 4-6 in the 2007 CCR risk assessment document) to assess the risks while 

acknowledging the shortcomings (the likely overly conservative nature) of such an analysis. 

Dr. Nicholas Basta, Ohio State University

The “Calculation of average constituent concentrations by site for landfill leachate, 

surface impoundment pore water, and total ash concentrations” (p. A-5) in the Draft 

states: 

“During site averaging, any separate waste disposal scenarios occurring at a site 

(e.g., non-fluidized-bed combustion [FBC] and FBC ash) were treated as separate 

“sites” and were averaged independently. This approach is consistent with that used 

in the 1998 CCR risk analysis. A large number of CCR samples report “below 

detection limit” values. As in 1998, nondetects were averaged at one-half the 

reported detection limit.” 

However, a large number of CCR samples reported “below detection limits” for 

many samples and elements. Two critical elements, As and Hg [mercury], had an 

excessive number of “nondetects” reported. Therefore, there is great uncertainty in 

the input data for the risk assessment of these elements. This is critical because As 

drives the Human Health drinking water exposure pathway standard, and it is very 

possible that Hg would have driven the Ecological Risk exposure pathway. The 

analytical laboratory instrumental detection limits are not reported. Cursory 

inspection of the data in Appendix A-2 suggests improved analytical methods 

should have been used to achieve lower detection levels that would have decreased 

or eliminated the large number of nondetects. Analytical methods that achieve 

lower detection limits can have an impact on the risk calculation for As. It is very 

possible that leachate concentration could be much lower (tenfold or more) than 

half the high detection levels reported. Modern analytical methods can achieve 

detection limits of < 0.001 mg/L for As. These methods should be used to analyze 

CCR leachate or extract data for CCR landfill risk assessment. 

Dr. Kerry Rowe, Queens University 

It is acknowledged that a large number of nondetects, as observed for mercury, 

poses a considerable challenge for a risk assessment. The use of half the detection 
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limit as the concentration for “nondetects” (RA, pg. 4-34) to represent the 

concentration may give unrealistically high impacts (as is suggested by the data in 

Figure 4-6). However to ignore mercury altogether, especially given that 

concentration may increase in the future (RA, pg. 4-34) is also questionable. At the 

time the study was conducted, an alternative to ignoring mercury would have been 

to do analyses with their concentration distribution (as shown on Fig. 4-6) and 

assess the risks while acknowledging the shortcomings (likely over-conservative 

nature) of the analysis. If the risk was low (below criteria) then one could easily 

conclude that mercury was not a problem. If the risks were significantly above 

criteria then this would highlight the need for more study of this issue. 

EPA Response

Additional constituent data measured with lower detection limits have been made available to EPA 

since completion of the draft risk assessment. However, the overall CCR constituent database still 

contains nondetect data for some constituents. EPA continues to use half the reported detection 

limit to account for these nondetects. A detailed rationale for this approach is provided in Section 

3 of the revised risk assessment. Much of the pre-2010 mercury data has high detection limits 

resulting in a large proportion of nondetects. In this instance, EPA relied only on the newer data 

made available to the Agency since the 2010 risk assessment, which was collected through newer 

methods with significantly lower detection limits. A more detailed rationale for this approach is 

provided in Section 3 along with further discussion of the uncertainty in Section 5. 

3.6. Effect of Waste Compaction 

Comment Summary 

Dr. Hopkins suggests considering how waste compaction would reduce water infiltration. He feels 

that this would be a useful comparison with the current assessment. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

5) Consideration of how compaction of wastes in the landfill would reduce water 

infiltration. The report does a good job of demonstrating the importance of liners 

in preventing undesirable migration of constituents from the site. However, 

compaction technologies reduce water penetration through the materials, rendering 

them less likely to produce leachate. If the data are available, this would be a useful 

comparison (similar to the lined vs. unlined comparison) to demonstrate how 

compaction reduces risks by reducing leachate production. 

EPA Response 

EPA acknowledges that the landfill source model does not consider the compaction of CCR waste 

that may occur over time as a result of anthropogenic activities, gravity, or infiltrating water. A 

discussion of this uncertainty has been added to Section 5 of the revised risk assessment. 
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3.7. HELP Infiltration Rates/Cover Assumptions 

Comment Summary 

Dr. Rowe questioned the use of the HELP model in light of recent criticisms and expressed 

concerns that the limitations of this model and the potential implications of its use have not been 

adequately addressed in the document. 

Dr. Kerry Rowe, Queens University 

The use of HELP to model infiltration for landfills has been the subject of some 

recent criticism in the literature however the limitations of this model, and the 

potential implications of its use, have not been adequately addressed in the 

document. 

Any assessment of infiltration through a landfill cover must consider the long-term 

performance of the cover (after the effects of many seasons of climatic exposure 

are considered). Thus, for example, the bulk hydraulic conductivity of a compacted 

clay liner in a cover is likely to increase by orders of magnitude due to desiccation 

as a result of temperature cycles in most climates (both hot and cold). If a GCL is 

used as an alternative, its hydraulic conductivity may also increase (in some cases 

by several orders of magnitude) due to cation exchange with the adjacent “soils” 

and desiccation. It is not clear that either of these issues were considered. 

EPA Response 

EPA has adopted the use of the HELP model, which was subject to both peer and administrative 

review, as the source of unlined and clay-lined infiltration rates for landfill for nearly two decades. 

EPA acknowledges that there are limitations in using HELP. However, the model has been tested 

and verified as discussed in the EPACMTP Parameter/Data Background Document (U.S. EPA, 

2003a). To the extent that the performance of the cap will decrease over time, EPA acknowledges 

that unlined and clay-lined infiltration rates calculated by HELP may be underestimated; however, 

the degree of that underestimate is unknown. Discussion of this uncertainty has been added to 

Section 5 of the revised risk assessment. 

3.8. Water Table above the Disposal Unit 

Comment Summary 

Dr. Rowe expressed concern about the disconnect between the fact that the assessment modeled 

only disposal sites above the water table and the statement in the report that many CCR disposal 

sites are constructed within the saturated zone. The commenter did acknowledge that modeling 

disposal sites below the water table would only strengthen the assessment’s conclusion rather than 

change it. 
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Dr. Kerry Rowe, Queens University 

Concern was raised in the public comments about the modeling only considering 

disposal sites where the bottom of the facility is above the water table while 

claiming that CCR landfills are “often constructed in mines and quarries ... within 

the saturated zone” which “will have the effect of expediting leaching of 

contaminants from the waste to levels consistent with levels found in surface 

impoundments” (Geo-Hydro, pg. 4). If this is indeed the case and if active measures 

are not enforced to control the head in the landfill to below that outside the landfill 

(hydraulic containment), then the risk of these sites will indeed be higher than 

modeled. However given that the general conclusions from the study are that the 

risks for unlined and clay-lined sites already exceed the risk criteria, this would 

only serve to emphasize that point and would not change the general conclusions. 

EPA Response 

EPA acknowledges that EPACMTP is not designed to handle the scenario where the water table 

is above the bottom of the WMU, and has added a discussion of this uncertainty to Section 5 of 

the revised risk assessment. However, as stated by Dr. Rowe, this uncertainty would not affect the 

ultimate conclusion that composite-lined impoundments present the lowest risks. 

3.9. Impact of Increased Mercury Capture with New 

Future Air Emission Control Regulations 

Comment Summary 

Dr. Hopkins, Dr. Rowe, and Dr. Vorhees recommended that EPA address the future increase in 

mercury levels in CCR that will result from mercury capture from flue gas under new emission 

control regulations. Dr. Rowe and Dr. Vorhees pointed out that the recent Vanderbilt study should 

provide data that could be used to expand the risk assessment in this area. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

Because Hg is volatilized during combustion, it is not surprising that Hg was not 

detected in many circumstances in the solid wastes. However, this question raises 

an important point: Will the conclusions of the risk assessment remain similar once 

Hg is more effectively captured and introduced into the solid wastes? This will not 

only be a tremendous challenge for the power industry and for the corporations that 

recycle these materials, but also for the USEPA as they reconsider the risks from a 

very different waste stream. Importantly, the amount of Hg that will be captured in 

the future and introduced into the solid waste stream should be predictable. Based 

on these predictions, I recommend that these risk assessment models be run based 

on current as well as projected waste composition (by manipulating Hg 
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concentrations in the models). This will be invaluable for addressing management 

of coal combustion wastes when Hg concentrations increase in the near future. 

Dr. Kerry Rowe, Queens University 

If more work were to be done today there is at least the data from the Vanderbilt 

study however it would appear that if more work is to be done it should also look 

at the implications of flue gas mercury controls. 

Dr. Donna Vorhees, The Science Collaborative 

EPA’s approach to treating the high frequency of concentrations reported below 

detection limits is reasonable, particularly given its acknowledgement that more 

work is needed to resolve questions about mercury because of its tendency to 

bioaccumulate in fish and because mercury concentrations in CCR might increase 

as flue gas mercury controls are installed on coal-fired power plants. EPA indicates 

that mercury concentration and leachability from CCR can vary as a function of 

flue gas controls and that “additional work is underway in this area” (page 4-41). 

What is not made clear is when this additional work will be completed and how it 

will be used to reassess risk from WMUs used to dispose of CCR? 

EPA Response 

The risk assessment was designed to evaluate the risks associated with current management 

practices and, as such, draws no conclusions about the potential for future air pollution 

technologies to alter the composition or leaching behavior of CCR wastes. However, it has been 

shown that newer mercury pollution control technologies currently in place may affect leaching 

(U.S. EPA, 2006b, 2008b, 2009b). EPA considered the risks associated with these select units 

through an uncertainty analysis presented in Section 5 of the revised risk assessment. 

3.10. Use of Pore water Data for Surface Impoundment 

Source Concentrations 

Comment Summary 

Dr. Rowe expressed concern about estimating surface impoundment source concentrations using 

measured concentrations in pore water collected from underlying sediments. The pore water 

concentrations are likely lower than concentrations in the bulk surface impoundment water, 

because they reflect any attenuation between the surface impoundment and the measurement point. 

Dr. Kerry Rowe, Queens University

While I would have preferred leachate data for the surface impoundments based on 

analysis of the actual leachate itself, the data obtained from pore water sampling of 

soil from below the impoundments (RA, pg. 4-32) is considered as a reasonable 

alternative as long as the limitations are recognized. It should be recognized that 
Response to Peer Review Comments Source Modeling

3-17 

the pore water squeeze chemistry may have been impacted by geochemical 

reactions (e.g. precipitation, sorption) during migration through the “soil” above 

the sample from which the pore water was extracted. Since these interactions will 

vary from one “soil” to another (depending on the mineralogy of the soil), the pore 

squeeze data will reflect this variability but will have a bias to lower values. Thus 

while the modeling does consider retardation mechanism as contaminants migrate 

through the soil, the use of a source term that is artificially low because of 

sorption/precipitation that occurred in the soil above which the sample was taken 

would lead to a potential underestimate of impact. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

The quantity of data is not sufficient. Surface water concentrations need to be 

considered 1) within the impoundments and 2) downstream from impoundments 

(i.e., direct surface water contamination, independent of subsurface flow). 

For surface impoundments, pore water data seem appropriate for estimating 

subsurface risks, but not for the two most important exposure pathways (direct 

exposure in surface impoundments and downstream from surface impoundments). 

To complete these analyses, a minimum of two other types of information are 

required. First, actual concentrations of trace elements in coal combustion wastes 

are needed to assess risk to animals (deer, dabbling ducks, grazing amphibian 

larvae, certain invertebrates) that directly ingest the solid waste materials when 

foraging in or around the margins of impoundments. These data are readily 

available, making this portion of the risk assessment highly feasible. Second, 

surface water concentrations in the impoundments themselves should be used to 

assess risks to animals that drink water from impoundments (a wide array of 

invertebrates and vertebrates [especially birds and mammals]) or deposit their eggs 

directly in the water (amphibians, invertebrates). These data are likely available, at 

least from discharge points which should represent the low end of actual 

concentrations in the impoundments. To assess risks in downstream sites affected 

by discharge, different dilution factors can be applied to represent a range of sitespecific scenarios. In addition to calculating resultant concentrations after dilution, 

continual loading and deposition need to be considered in downstream habitats 

based on the duration of site operation and discharge. 

EPA Response 

The use of pore water data is still considered the most appropriate approach to estimate constituent 

fluxes to ground water. This is because pore water better represent the leachate seeping from the 

bottom of the impoundment than impoundment water samples. Therefore, no changes were made 

in response to these comments. 
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3-18 

The use of whole waste and impoundment water concentrations to analyze alternative pathway is 

discussed in Section 4 of this response to comments document. 

3.11. Modeling Surface Impoundments Only Before 

Closure 

Comment Summary 

Dr. Hopkins pointed out that many surface impoundment wastes are left in place at the time of 

closure, so that the waste behaves more as a landfill than a surface impoundment. The risk 

assessment considered releases from surface impoundments only during active operation. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

Consideration of how surface impoundments are actually managed. In many cases 

the coal combustion wastes are left in place at the time of closure (analogous to 

filling a landfill). Thus, risk does not end when the slurry pumping ceases, which 

is in direct contrast to the assumptions of the current risk assessment model. Instead, 

the type of risk transitions from that modeled in the surface impoundment to that 

which is more analogous to a capped landfill. Again, this inaccurate assumption 

underestimates risk. 

EPA Response 

Dr. Hopkins is correct that not all surface impoundments will clean closed. However, the majority 

of ponds are believed to be continually dredged based on the 2009/2010 EPA surveys. Because 

these facilities have other units (whether onsite or offsite) established for disposition, it likely that 

the majority of waste in the dredged impoundments would be removed by the end of the unit’s 

operating life. Regardless, an uncertainty analysis provided in Appendix K demonstrates that the 

risks during the operating life of surface impoundments are greater because the higher hydraulic 

head that drives leachate into underlying soils has greater force than those present after closure. 

Therefore, EPA did not explicitly model the postclosure phase of surface impoundments. The 

uncertainties resulting from this decision are discussed in Section 5 of the revised risk assessment. 

3.12. Modeling Landfills Only After Closure 

Comment Summary 

Dr. Hopkins suggested that risk from operating landfills should have been considered, because the 

greatest risks may occur during site operations when the waste products are directly exposed to 

wind and rain. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

It is incorrect to assume that risk begins when the landfill closes. In reality, the 

greatest risks likely occur during site operations when the waste products are 
Response to Peer Review Comments Source Modeling

3-19 

directly exposed to wind and rain. This is a simple, yet serious flaw in the risk 

assessment that obviously underestimates overall risk. 

EPA Response 

The landfill source model used in this risk assessment is not able to address landfills during 

operation because the nonlinear sorption isotherms used require a constant, annualized infiltration 

rate throughout the duration of leaching. Instead, the revised risk assessment assumes that the full 

footprint of the landfill is filled to capacity and a cap no less permeable than the soil or liner 

underlying the WMU is present at the start of leaching. EPA acknowledges that this approach 

introduces some uncertainty into the analysis, the potential impacts of which are discussed in 

Section 5 of the revised risk assessment. 
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Response to Peer Review Comments

4-1 

4. Exposure Scenarios 

The peer review comments relating to exposure scenarios are grouped into five subcategories: 

1. Direct surface impoundment exposure 

2. Indirect exposure through game species (e.g., deer, waterfowl) 

3. Exposure to surface impoundment effluent 

4. Exposure during landfill operation (before closure) 

5. Elimination of pathways during screening analysis. 

4.1. Direct Surface Impoundment Exposure 

Comment Summary 

Dr. Hopkins pointed out that the risk assessment does not consider direct exposure to active surface 

impoundments. Such exposure can occur, for example, when wildlife are attracted to 

impoundments for uses such as drinking, feeding, and swimming, can lead to exposure through 

transdermal or direct ingestion pathways. There is also a potential for trophic exposure increases 

as other organisms eat animals or plants exposed to surface impoundment waste. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

The National Academy of Sciences concluded that coal combustion wastes pose 

the greatest risk to humans and the environment when they contact water in the 

disposal environment. Thus, by definition, surface impoundments should pose 

greater risks than most landfills because the use of surface impoundments requires 

that the wastes be mixed with water before being pumped into the impoundments. 

Overall, the findings of the risk assessment are consistent with this. That is, risks 

are higher for surface impoundments than for landfills. However, the risk 

assessment grossly underestimates risks from surface impoundments to humans 

and the environment because it fails to consider the two most important exposure 

pathways for invertebrates, fish, wildlife, and humans. For surface impoundments, 

the risk assessment only recognizes leaching as a release mechanism and 1) ground 

water-to-drinking water and 2) ground water-to-surface water as exposure 

pathways. This is incorrect. While leaching into ground water is clearly a concern 

at these sites, the predominant exposure pathways relate to 3) direct exposure to the 

slurried wastes in the impoundments and to 4) direct exposure to the effluent from 

the impoundments discharged offsite. I highlight the problems with overlooking 

these routes of exposure below. 

Direct Exposure Onsite. Plants and animals can experience direct exposure to coal 

combustion wastes when they inhabit or periodically utilize surface impoundments. 
Response to Peer Review Comments Source Modeling

4-2 

Surface impoundments often attract wildlife from adjacent areas for a variety of 

purposes, including foraging, drinking water, and reproduction. Examples include 

game (e.g., deer, migratory waterfowl, and raccoons) and non-game species 

(migratory passerine birds, wading birds, amphibians, and reptiles). For these 

animals, exposure to trace elements in coal combustion wastes can occur by at least 

four mechanisms: 

A) Drinking water from the impoundments, 

B) Direct ingestion of the wastes, 

C) Trophic exposure caused by eating other animal inhabitants or ingesting plants 

growing in or around the impoundment, and/or 

D) Transdermal exposure. 

Drinking water is a widespread mechanism of exposure and is a significant risk to 

most taxonomic groups since the impoundments can contain large quantities of 

fine, suspended particulate matter (e.g., fly ash) and high concentrations of 

dissolved trace elements resulting from the slurry. Several important groups of 

organisms ingest sediments from the bottom of impoundments, perhaps most 

notably, dabbling ducks (e.g., mallards, teal, pintails, etc.) and larval amphibians 

(i.e., frogs and toads). Aquatic plants and algae often comprise a significant portion 

of the diet for a variety of these animals, as well as aquatic turtles which frequently 

become residents of surface impoundments. Transdermal exposure is possible for 

all species that come in contact with the water and coal combustion wastes in and 

around surface impoundments, but is especially problematic for species with highly 

permeable skin (e.g., amphibians). 

From an ecological perspective, all of the groups of organisms mentioned above 

are important. It is possible that such sites act as population sinks in the landscape 

for species such as amphibians and certain birds (e.g., green herons and red-winged 

blackbirds) that use them in large numbers for reproductive purposes. In other 

cases, animals that drink or forage at the sites can transport accumulated pollutants 

to adjacent habitats where their body burden becomes a bioavailable exposure risk 

to their predators. 

EPA Response 

Direct exposure of ecological receptors to CCR surface impoundment wastewater in the 

impoundments themselves is evaluated during the screening-level modeling (described in Section 

3 of the revised risk assessment). With respect to direct discharges, see the discussion in Section 

4.3 of this response to comments document. 
Response to Peer Review Comments Source Modeling

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4.2. Indirect Exposure through Game Species 

Comment Summary 

Dr. Hopkins expressed concern that the risk assessment does not consider potential indirect 

exposure to humans through game species that may have been exposed to surface impoundment 

waste (e.g., deer drinking surface impoundment water). 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

From a human health perspective, game species are particularly concerning. For 

example, a study on landfilled coal combustion wastes with improper cover 

demonstrated that deer are attracted to the wastes (and ingest it), presumably 

because of its salt content (Sample and Suter, 2002). Thus, in a surface 

impoundment setting, deer not only drink from the impoundments, but may also 

ingest the materials directly from the impoundment margins. While it may be 

possible to regulate hunting in areas near surface impoundments to protect humans 

from such exposure, it is less likely that hunters (and their families) could be 

protected from the hazards of eating waterfowl that have used surface 

impoundments. Migratory waterfowl often use surface impoundments and in some 

cases (depending on where the impoundment is located along their migratory range) 

could remain on site for considerable periods of time. When these waterfowl leave 

the impoundment, they become a route of exposure for hunters in other (perhaps 

distant) localities. 

EPA should consider this important mechanism of exposure in their risk evaluation 

so that appropriate guidance can be provided to the power industry. If a landfill was 

left uncapped and a wide variety of wildlife species used the site (e.g., eating plant 

material growing in the wastes, burrowing in the wastes, nesting in the wastes), it 

would not be acceptable. Minimum cover standards are in place to prevent such 

ecological problems. Paradoxically, surface impoundments can actually attract 

wildlife and promote exposure to high concentrations of trace elements in 

bioavailable forms. These exposure scenarios are not considered in the current draft 

risk assessment and as a result, the assessment grossly underestimates exposure and 

resultant risks. 

EPA Response 

EPA acknowledges that this human exposure scenario was not addressed in either the screening 

analysis or the full-scale CCR risk assessment, and that risks could exist if humans consume 

wildlife contaminated by CCR constituents. The screening analysis, presented in Section 3 of the 

revised risk assessment, shows that consumption of contaminated beef and dairy from cows that 

consume contaminated soil and produce grown in contaminated soil may pose risks to human 

health for thallium. Although EPA did not collect biotransfer factors for deer, the following 
Response to Peer Review Comments Source Modeling

4-4 

considerations make this pathway less of a concern than the beef and dairy pathways evaluated. 

First, as shown in Table 1, only 1.2% of the population consumes game species. Second, the table 

also shows that the consumption rates for game species are consistently orders of magnitude below 

the consumption rates of beef and dairy. Finally, beef and dairy cattle are assumed to get 100% of 

their diet from contaminated soil, forage, silage and grains, whereas game species would forage 

throughout their natural habitat range, with direct ingestion of CCRs the only exposure pathway 

available. Thus, EPA does not consider the exclusion of this pathway to be a significant 

uncertainty. 

Table 1. Comparison of Per Capita Beef, Dairy and Wild Game Consumption Rates

Food 

Percent of 

Population 

Consuming 

Consumption Rate (g/kg-day) 

1st 5th 10th 25th 50th 75th 90th 95th 99th 

Beef 91% 0 0 0.06 0.27 0.63 1.2 1.8 2.3 3.5 

Dairy 97% 0 0.16 0.40 1.4 3.6 8.2 18.7 29.7 72.2 

Game 1.2% 0 0 0 0 0 0 0 0 0.1 

Rounded values drawn from Exposure Factors Handbook (EFH) (U.S. EPA, 1997) Tables 11-2, 11-3, and 11-6. 

4.3. Exposure to Surface Impoundment Effluent 

Comment Summary 

Dr. Hopkins emphasized that the risk assessment does not consider potential exposure to surface 

impoundment effluent even though many CCR waste management systems continuously release 

wastewater into downstream habitats. Such exposure could be direct for animals living 

downstream (e.g., fish) or indirect (e.g., humans catching fish downstream). 

Dr. William Hopkins, Virginia Polytechnic Institute and State University

Direct Exposure Offsite. Plants and animals can experience direct exposure to coal 

combustion wastes downstream from surface impoundments. Depending on how 

the site is engineered, surface water in impoundments can be recirculated or 

discharged downstream. Discharge of surface waters into reservoirs can result in 

significant adverse ecological impacts such as the classic case study at Belews 

Lake, NC where most fish species (19 of 20) were extirpated. Today, contaminated 

surface waters are commonly discharged into streams and rivers where dilution 

factors are large and offsite transport is typical. While concentrations of trace 

elements in surface water are required to meet discharge permit standards, continual 

loading of trace elements to downstream habitats is a significant concern for human 

health and the environment. In addition, if not managed properly, rain events can 

result in resuspension of coal combustion wastes and the direct discharge of 

suspended particulates into downstream habitats. These problems can be further 

exacerbated in large rivers that receive discharge from surface impoundments at 
Response to Peer Review Comments Source Modeling

4-5 

multiple power plants, creating cumulative exposure risks in downstream habitats 

for human and ecological receptors. 

Although the environmental impacts of offsite discharge into lakes/reservoirs are 

well known, the impacts to streams and rivers have received less attention. 

However, recent work near Atlanta, GA demonstrated that surface impoundments 

represent an important source of bioavailable trace elements including As, Se, and 

Cd [cadmium] to the Chattahoochee River, an important water source and exposure 

pathway for humans and wildlife (Loeffler Peltier, 2008). The biological effects of 

such discharge to rivers and streams are not well studied, but invertebrates and 

microbial communities have been adversely impacted by surface impoundment 

discharge (Reviewed in National Academy of Sciences [National Research 

Council] 2006 Report, pg 89-90). Likewise, discharge of trace elements from 

impoundments to rivers can result in artificial selection for more antibiotic-resistant 

communities of micro-organisms (Stepanauskas et al., 2005). This latter finding 

has far-reaching human health implications. 

Because many surface impoundments continually release contaminated surface 

waters into downstream habitats, direct discharge is an important release 

mechanism that must be considered in EPA’s risk assessment process. For humans, 

the most likely exposure pathway will be ingestion of fish or other commonly eaten 

vertebrates (e.g., turtles, ducks, or muskrats) that inhabit downstream sites. 

However, recreational use of impacted streams and rivers could also result in 

significant contact with water and sediments, creating multiple exposure pathways. 

For fish and wildlife, particular attention should be devoted to species that utilize 

areas that favor deposition of trace elements and fine particulates, including areas 

of reduced flow (deep holes, oxbows, etc.) that are also commonly used for 

recreation by humans (fishing, swimming, etc.). 

This represents the greatest flaw in the risk assessment. Direct exposure in surface 

impoundments and downstream from surface impoundments represents the greatest 

risk pathway for humans and the environment, yet they are not considered in the 

assessment. In other words, subsurface flow predicted based on physical and 

chemical processes only represents a small portion of the total risks posed by these 

waste management units. Direct surface transport from impoundments and dilution 

factors need to be considered. See comments above (Major Criticism). 

EPA Response 

Resource Conservation and Recovery Act (RCRA) waste disposal risk assessments do not address 

direct discharges from impoundments to surface waters because they are regulated as permitted 

point source discharges under the Clean Water Act by EPA’s Office of Water. Therefore, this 

pathway is outside the scope of the proposed rule and this risk assessment, so the revised risk 
Response to Peer Review Comments Source Modeling

4-6 

assessment does not consider this pathway for human or ecological receptors. However, this 

pathway was evaluated in a separate risk assessment, documented in Environmental Assessment 

for the Proposed Effluent Limitation Guidelines and Standards for the Steam Electric Power 

Generating Point Source Category (U.S. EPA (2013a), which will be revised in support of final 

effluent limitation guidelines due to be released in September of 2015. 

4.4. Exposure during Landfill Operation (Before 

Closure) 

Comment Summary 

Dr. Hopkins pointed out that the risk assessment considered landfill conditions only after closure. 

This approach excludes potential pathways such as exposure to airborne contaminants associated 

with dry handled waste and direct ingestion of waste by wildlife. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

... the risk assessment should include the following: 

1) Consideration of the two most important release mechanisms and resulting 

exposure pathways associated with surface impoundments (see comments [Major 

Criticism] above regarding exposure to contaminants in surface impoundments and 

in downstream sites). 

2) Consideration of the inhalation pathway for human health risks in a landfill 

setting. This is a significant problem when the wastes are being predominately dry 

handled, and can be remedied by adding modest amounts of moisture to the wastes 

and by limiting the amount of the materials that are exposed to air over the 

protracted life of an open landfill. Failure to control airborne transport of the wastes 

during site operations will result in increased risks for workers and residents in the 

areas adjacent to transport routes and landfills. Although this concern was raised 

repeatedly to the National Academy of Sciences by concerned citizens who could 

provide concrete evidence of airborne transport (e.g., thin layers of ash covering 

their cars, homes, etc.), the committee did not evaluate this because it was beyond 

the scope of their study. However, it is within the scope of this comprehensive risk 

assessment and should be included. 

The exposure distributions do not include the wide array of organisms that are 

exposed onsite while the waste management units (especially surface 

impoundments) are active. Because these sites can be active for decades and this 

period may represent the greatest exposure risk to wildlife (especially in surface 

impoundments), the current distributions grossly underestimate actual exposures. 

Consideration of the starting point for the source term in the landfill model. It is 

incorrect to assume that risk begins when the landfill closes. In reality, the greatest 
Response to Peer Review Comments Source Modeling

4-7 

risks likely occur during site operations when the waste products are directly 

exposed to wind and rain. This is a simple, yet serious flaw in the risk assessment 

that obviously underestimates overall risk. 

EPA Response 

As previously discussed in Section 3.12 of this comment response document, the simple landfill 

model used in the CCR risk assessment does not handle variable infiltration rates required to model 

leaching during landfill operation. 

With respect to fugitive dust, EPA acknowledges that the draft risk assessment did not fully 

evaluate the inhalation pathway. To correct this deficiency, Section 3 and Appendix F of the 

revised risk assessment now include a more complete analysis of the air pathway, including both 

long-term and short-term exposures. 

The direct contact risks for CCRs in surface impoundments are discussed above in Section 4.1 of 

this document. 

4.5. Elimination of Pathways During Screening 

Analysis 

Comment Summary 

Dr. Vorhees requested more documentation of the screening analysis and justification for 

eliminating certain exposure pathways from the risk assessment. 

Dr. Donna Vorhees, The Science Collaborative 

EPA’s Screening Analysis. EPA conducted a 2002 screening analysis in which it 

determined the subset of exposure pathways and CCR constituents that would 

undergo full-scale evaluation in the risk assessment. Figure ES-1 summarizes 

results of the exposure pathway screening, and Table 2-3 summarizes results of the 

CCR constituent screening. No discussion is provided about why exposure 

pathways were eliminated. I tried to determine the reason, but I could not find the 

screening analysis document on the website provided in the risk assessment (i.e., 

www.epa.gov/epaoswer/other/fossil/index.htm). The risk assessment needs to 

include at least a summary of these analyses. Also, why is poultry not among the 

possible animal product pathways? Why is there no dermal contact with drinking 

water, e.g., during showering? EPA provides guidance for assessing dermal 

exposure to metals in water (See Chapter 3 in [U.S.] EPA 2004[b]). 

EPA Response 

The 2002 Constituent Screening for Coal Combustion Wastes (U.S. EPA, 2002a) report was not 

available to the peer reviewers. However, it has been made available in the docket at 

www.regulations.gov (Document #: EPA-HQ-RCRA-2006-0796-0470). Furthermore, to increase 
Response to Peer Review Comments Source Modeling

4-8 

transparency, the revised risk assessment now includes a detailed presentation of the screening 

assessment in Section 3, which describes the methodology used to eliminate exposure media and 

pathways from the full-scale risk assessment modeling. 
Response to Peer Review Comments

5-1 

5. Comments Related to Human 

Exposure and Toxicity 

The peer review comments relating to human exposure and toxicity are grouped into seven 

subcategories: 

1. Combined chemical effects, additive risk, and multiple pathway exposures 

2. Toxicity values 

3. Target cancer risk 

4. Defining the exposed population 

5. Exposure factor assumptions 

6. Child/infant exposure assumptions 

7. Correlations in input variables. 

5.1. Combined Chemical Effects, Additive Risk, and 

Multiple Pathway Exposures 

Comment Summary 

Dr. Rowe questioned whether the possible interaction of people consuming both contaminated fish 

and drinking water from the same waterbody source was considered and where this was 

documented. 

Dr. Vorhees questioned why a cumulative risk evaluation was not attempted for simultaneous 

exposure to CCR constituents. Specifically, she suggests that potential cumulative exposures of 

concern could be identified by a review of EPA’s existing data related to relative proportion of 

CCR constituents at WMU locations combined with predictions of CCR constituent concentrations 

in drinking and surface water near WMU locations. Additionally, she noted that cumulative risk 

needs to be reported from the perspective of the receptor and that cumulative exposure should be 

considered for all 21 constituents with risks exceeding chosen benchmark values. 

Dr. Hopkins noted that it is not appropriate to treat each constituent separately because they exist 

in a mixture in the waste stream and some constituents are known to interact. He suggests that this 

at least be addressed by modeling additivity, although this would underestimate synergistic 

interactions. Additionally, he notes that multiple exposure routes should be considered, with the 

most likely combinations used for the risk assessment. 
Response to Peer Review Comments Human Exposure and Toxicity

5-2 

Dr. Kerry Rowe, Queens University 

The study considered people consuming fish from the water body and drinking 

water from ground water (without considering interaction). It is not clear why the 

potential for people both consuming fish and drinking water from the water body 

was not considered. This would seem entirely possible especially if people had a 

residence/cottage adjacent to the water body. Was this possibility examined and if 

so where is the documentation? 

Dr. Donna Vorhees, The Science Collaborative 

Cumulative risk refers to the combined risk from exposure to multiple stressors, in 

this case, CCR constituents. Given that exposure to CCR constituents might occur 

simultaneously and some might jointly cause similar toxicity, it is important to 

evaluate the potential for cumulative risk. EPA has tackled this topic repeatedly in 

recent guidance ([U.S.] EPA 2000[a], 2003[c], and 2007), so it is puzzling that EPA 

provides no reason for why it did not attempt a cumulative risk evaluation except 

to say that such an evaluation is difficult. 

In Superfund risk assessments, cumulative risk is often addressed by summing HQs 

[hazard quotients] across constituents and if the sum is greater than 1, examining 

the underlying assumption of additivity more closely. However, as noted in at least 

one set of public commentary, one cannot simply sum 90th percentile HQs across 

different CCR constituents because this sum might reflect a cumulative exposure 

to which no one is exposed in reality. Specifically, the 90th percentile exposure 

level for one CCR constituent might not occur in the same place and time as the 

90th percentile level for another CCR constituent. However, EPA does have data 

that indicate the relative proportion of CCR constituents at individual WMU 

locations and predictions of CCR constituent concentrations in surface water and 

drinking water near each WMU over time, so it could review these results to check 

for potential cumulative exposures of concern. In its evaluation of cumulative risk, 

it is important that EPA report findings from the perspective of the receptor: what 

combination of CCR constituents will he or she be exposed to within a timeframe 

where they might collectively cause harm? This approach is particularly important 

given the 10,000 year modeling timeframe – for both the assessment of individual 

chemical risk and cumulative risk. Also, in reaching a decision about cumulative 

risk, EPA should consider cumulative exposure to all 21 constituents associated 

with risks that exceed selected benchmarks, not just the 12 that underwent full-scale 

analysis. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

Consideration of the combined effects of individual elements within the waste 

stream. Because this is a complex mixture of wastes, it is inappropriate to treat each 
Response to Peer Review Comments Human Exposure and Toxicity

5-3 

constituent separately from one another. Some of the elements in coal combustion 

wastes are known to interact with one another, which could lead to a very different 

outcome in the risk models. The risk assessment document acknowledges this 

shortfall, but it should be corrected in the next draft. At the very least, additivity 

(which is an underestimate because it does not consider synergistic interactions) 

should be modeled. 

Consideration of multiple exposure routes. Human and ecological receptors may be 

exposed via diet, water, contact, and/or inhalation and the most likely combinations 

should be considered in a full scale risk assessment. This is discussed below 

(answer to #6) in more detail. 

... the risk assessment does not include some of the uncertainties that could be 

addressed with the data currently available. For example, the risk assessment only 

considers single exposure pathways. Yet in reality, multiple exposure pathways are 

important for both humans and wildlife. In many cases the analytical results are in 

place for individual scenarios, but the outcomes may be quite different if multiple 

exposure pathways are simultaneously considered. 

A simple scenario would be local citizens who use a stream that receives discharge 

from surface impoundments for recreational purposes (swimming) and sustenance 

(fishing, trapping, and hunting), while also using ground water sources for drinking. 

EPA Response 

EPA acknowledges that this risk assessment considered potential risks to human health from 

individual constituents and individual pathways. Although it is possible that an individual could 

be exposed to risks from drinking contaminated ground water, as well as eating contaminated fish 

from a local surface water body, EPA does not believe that this overlap is likely to occur in 

significant numbers in the real world due to, for example, the average distance anglers travel to 

fish. A full list of the reasons EPA did not evaluate cumulative risk from multiple pathways, as 

well as the resulting uncertainties, is included in Section 5 of the revised risk assessment. 

In addition, it may be possible for an individual to be exposed to multiple constituents through a 

single pathway. This is a more likely scenario because, as demonstrated by the available data, 

CCRs may leach multiple inorganic constituents. Where exposure to multiple constituents is likely 

to occur, EPA policy is to assume that the risks resulting from these exposures are additive (U.S. 

EPA, 2000a). However, the current risk assessment did not consider additivity due to, for example, 

the difference in transit times of the constituents. A full list of the reasons EPA did not evaluate 

cumulative risk from multiple constituents, as well as the resulting uncertainties, is included in 

Section 5 of the revised risk assessment. 

EPA acknowledges that the failure to evaluate cumulative risk is a source of uncertainty that may 

result in an underestimation of risks for certain individuals. However, because the risks for 
Response to Peer Review Comments Human Exposure and Toxicity

5-4 

individual constituents were found to be above levels of concern, the magnitude of the uncertainty 

introduced into the final conclusions of the risk assessment is likely to be small. 

5.2. Toxicity Values 

Comment Summary 

Dr. Vorhees corrected several toxicity values and suggested the use of the Integrated Exposure 

Uptake Biokinetic (IEUBK) model for calculating risks to human health from lead. Additionally, 

she noted that EPA should include a discussion of the uncertainty associated with the toxicity 

values in the risk assessment. 

Dr. Donna Vorhees, The Science Collaborative 

Several toxicity values require correction: 

1. The PPRTV [Provisional Peer-Reviewed Toxicity Value] RfD [reference dose] for 

aluminum is 1 mg/kg-d, not 2 mg/kg-d (PPRTV). 

2. The IRIS [Integrated Risk Information System] RfD for boron is 0.2 mg/kg-d; not 0.09 

mg/kg-d as indicated on Table G-1. 

3. The IEUBK model should be used to quantify risk for a young child exposed to lead. 

4. New July 2008 PPRTV documentation is available for cobalt: 

 a. Unit Risk of 2.8E-3 (μg/m3)

-1

 

 b. Data insufficient to derive an oral Cancer Slope Factor 

 c. Reference Dose of 0.02 mg/kg-d (EPA reports this value in the risk assessment) 

 d. Reference Concentration of 2E-5 mg/m3 

For some reason, EPA does not provide PPRTV documentation on-line. Instead, it 

must be requested by “registered” users. I did not make such a request for all CCR 

constituents, but EPA should update the risk assessment to include the latest 

toxicity values. This should not be labor intensive because the toxicity values were 

treated as point estimates in the PRA. 

EPA’s PRA guidance: 

“does not propose probabilistic approaches for dose-response in human health 

assessment and, further, discourages undertaking such activities on a site-by-site 

basis” ([U.S.] EPA 2001). I assume that this is why EPA chose not to quantify 

uncertainty in toxicity values. But EPA should at least discuss uncertainty 

associated with chemical toxicity values in the risk assessment to facilitate 

interpretation of risk results. 
Response to Peer Review Comments Human Exposure and Toxicity

5-5 

EPA Response 

Human health benchmarks were chosen based on the Office of Solid Waste and Emergency 

Response (OSWER) hierarchy (OSWER Directive 9285.7-53). EPA reviewed the benchmarks to 

confirm their accuracy and determine whether newer values have become available from EPA or 

other sources used by EPA since the CCR draft risk assessment was conducted. The current, 

updated list of human health benchmarks is provided in Appendix E of the revised risk 

assessment. The underlying source documents include thorough discussions of the uncertainties 

associated with these values. 

For lead, EPA had used the drinking water maximum contaminant level (MCL) to estimate risks 

from drinking water exposure in the draft risk assessment. In the revised risk assessment, EPA 

continued to rely on the MCL, but also used the IEUBK model for comparison in a sensitivity 

analysis described in Section 5 of the revised risk assessment. 

With respect to PPRTVs, documentation is now available online at hhpprtv.ornl.gov/. 

5.3. Target Cancer Risk 

Comment Summary 

Dr. Vorhees questioned why EPA chose a target cancer risk of 10-5 when other EPA programs use 

a range of 10-4 to 10-6. She suggested that an explanation is necessary. 

Dr. Donna Vorhees, The Science Collaborative 

Why did EPA select a cancer risk benchmark of 10E-5? Some other EPA programs 

use a range of 10E-4 to 10E-6 range. This topic warrants some discussion; 

otherwise, how does one explain to a person living on or near a Superfund site that 

it is acceptable for them to incur a higher cancer risk than someone living near a 

WMU used for CCR disposal? 

EPA Response 

Section 2 of the revised risk assessment has been updated with the following text to clarify EPA’s 

cancer criteria: 

EPA considered excess lifetime cancer risks within the OSWER risk range of 

between a 1 in 1,000,000 (1×10-6) and a 1 in 10,000 (1×10-4) excess cancer risk. 

EPA has historically used a 1×10-5 excess cancer risk as the point of departure for 

RCRA hazardous waste listings (59 FR 66075). Thus, in determining whether to 

retain constituents for further analysis, EPA used a 1×10-5 excess lifetime cancer 

risk. 

Although EPA uses a 1×10-5 cancer risk to select which constituents continue forward for further 

analysis, the full OSWER risk range is considered and discussed for each cancer risk result 

presented throughout the revised risk assessment. 
Response to Peer Review Comments Human Exposure and Toxicity

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5.4. Defining the Exposed Population 

Comment Summary 

Dr. Vorhees questioned the evaluation of only the reasonable maximum exposure (RME) scenario. 

Specifically, she noted that this does not represent the entire exposure distribution. She suggests 

that EPA clearly define the exposed population of interest in the evaluation based upon the 

requirements of applicable laws and regulations. Additionally, she notes that the use of exposure 

data and distributions relevant to the population of interest needs to be demonstrated. 

Dr. Donna Vorhees, The Science Collaborative 

EPA reports that: 

“the recreational fisher scenario was used to estimate risks to recreational fishers 

(and their children) who live near the CCR landfills and surface impoundments and 

catch and consume fish from a waterbody located adjacent to the [WMU] buffer” 

(page 2-12). 

EPA selected the recreational fisher because: 

“they represent the reasonable maximum exposed individuals and because the 

streams, lakes, or rivers that are near CCR plants are not likely to be used by 

commercial fishing operations” (page 2-12). 

In the context of a PRA, it is illogical to evaluate only the reasonable maximum 

exposure (RME) scenario because this exposure level represents only part of the 

entire exposure distribution, albeit the portion of the distribution generally of 

greatest interest within regulatory contexts. The population that should be the 

subject of an exposure evaluation presumably is dictated by requirements of the 

applicable laws and regulations, so I do not attempt to define this population. 

However, EPA must clearly do so. Is this population everyone who lives near 

WMUs or just recreational fishers and their families who live near WMUs and also 

consume fish from water bodies contaminated by WMU constituents? The 90th 

percentile exposure level will differ depending on how the exposed population is 

defined. EPA must clearly define the exposed population of interest and 

demonstrate that it is using exposure data and distributions relevant to that exposed 

population (see related commentary under EPA Condition #5 and Charge Question 

#4). 

EPA Response 

EPA acknowledges that the recreational fisher scenario was used as a RME scenario for the draft 

risk assessment, and has clarified that this fisher is assumed to be consuming fish from water 

bodies contaminated by constituents from CCR WMUs. Exposure data used for the recreational 

fisher are described in Appendix D of the revised risk assessment. However, EPA policy states 
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that decision-makers should be given a range of risk estimates from at least two points on a 

distribution of risk estimates; a central tendency estimate, and a “high-end” estimate (U.S. EPA,

1992). In risk assessments used to develop regulations under RCRA, EPA traditionally assesses 

potential risks resulting from an RME scenario in order to ensure that the resulting regulation be 

adequately protective of human health without being excessively conservative. In this case, data 

are not available on the populations of recreational fishers living near CCR WMUs and whether 

or not they are consuming fish from CCR-contaminated waterbodies. EPA believes that the RME 

assumption is a reasonable and protective alternative given this data gap. 

5.5. Exposure Factor Assumptions 

Comment Summary 

Dr. Vorhees questioned the use of data from the 1997 Exposure Factors Handbook in the 

development of intake rate distributions for various exposures, because more current data are 

available. Additionally, she questioned why the variability of fish consumption rates was not 

considered and suggests that EPA determine rates from the bodies of water affected by WMUs. 

Minimally, she suggests that more current fish consumption data could be discussed with regard 

to the implications for interpreting risk results. 

Dr. Donna Vorhees, The Science Collaborative 

Drinking Water Intake Rate Distribution. EPA used data from its three-volume 

Exposure Factors Handbook (1997a-c) to develop many exposure input 

distributions. EPA asserts that this handbook “provides the current state of the 

science concerning exposure assumptions” (page 438). However, exposure studies 

have been performed since 1997, and the EPA website acknowledges this fact by 

indicating that the handbook “is being revised to incorporate new data available 

since 1997” (cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=12464). 

Fish Consumption Rate. To truly describe the variability in fish consumption rates, 

EPA needs to identify water bodies affected by WMUs and determine fish 

consumption rates from these locations. There is no reason to believe that data from 

Maine apply to the whole country, and, as noted above, studies have been 

conducted and published in the scientific literature since publication of the 

Exposure Factors Handbook. Moya (2004) reviews these data, plus EPA will likely 

find more studies published since this 2004 review. I recognize that all of the cited 

studies do not require detailed percentile data that EPA favors, but that is not a 

reason to ignore fish consumption rate variability among regions and water body 

types. At a minimum, EPA could discuss these other fish consumption data and 

implications for interpreting risk results (of course, the fish consumption rate 

distribution first must be included in EPA’s sensitivity analyses). 
Response to Peer Review Comments Human Exposure and Toxicity

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EPA Response 

EPA agrees that newer exposure factor data are available in the 2008 Child-Specific Exposure 

Factors Handbook (U.S. EPA, 2008a). The 2008 data, in addition to the 1997 EFH data used in 

the draft risk assessment, were used to as the primary information on human exposure factors for 

the U.S. population in the revised risk assessment. These data are discussed in Section 2 and 

Appendix D of the revised risk assessment. 

Data on site-specific fish consumption rates were not available for use in this analysis. Instead, 

fish consumption rates were drawn from a study of Maine anglers that fished from streams, rivers, 

and ponds. Additionally, data were available only for adult anglers. Because age-specific data for 

children were not available, all child cohorts were assumed to consume the same amount of fish 

as the adult cohort. Finally, all fish consumed is assumed to be contaminated. These issues are 

discussed in Appendix D of the revised risk assessment. However, these issues do introduce 

uncertainty into the analysis, which is discussed in Section 5 of the revised risk assessment. 

5.6. Child/Infant Exposure Assumptions 

Comment Summary 

Dr. Vorhees commented that no reference is made to EPA guidance regarding the evaluation of 

exposure during childhood. Additionally, the exposure assessment does not address infant 

exposure to tap water. She noted that tap water consumption rates are available for infants. Also, 

because infants are less likely to consume recreationally caught fish, they should be excluded from 

the evaluation of this exposure pathway. Dr. Vorhees suggests that data are available for tap water 

consumption rates among children that are more recent than the 1997 Exposure Factors Handbook, 

and because the newer data set contains more data for infants, it should be used even though it will 

not likely affect the risk calculations. She noted that the infant age range was excluded from the 

documentation without explanation. She also suggests that the child fish consumption rates are 

unnecessarily conservative and other rates should be considered. Additionally she thought it would 

be useful to include a summary of the more recent literature since the 1997 Exposure Factors 

Handbook. Dr. Vorhees questions why the maximum value for child exposure duration is 50 years 

and suggested that an explanation of how the age distributions are used in modeling is necessary. 

Dr. Donna Vorhees, The Science Collaborative 

The problem formulation discusses the importance of evaluating children 

separately from adults, given their potentially higher intake to body weight ratios. 

The exposure assessment includes four age groups for individuals younger than 20 

to account for variation in exposure over this time interval [Note: EPA has not 

documented how it accounted for correlations among exposure across these age 

groupings. See commentary under EPA Condition #4.] However, the risk 

assessment includes no references to EPA guidance regarding the evaluation of 

exposure during childhood (e.g., EPA 2006a, EPA 2005a), and infant exposure to 
Response to Peer Review Comments Human Exposure and Toxicity

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tap water is not examined. Tap water consumption rates for infants are summarized 

by EPA (2006a) and discussed under EPA Condition #5. Infants are less likely to 

consume recreationally caught fish; therefore, it is reasonable to exclude this age 

range from the evaluation of the fish consumption pathway. 

EPA’s external review draft of its Child-Specific Exposure Factors Handbook 

(EPA 2006a) includes some more recent data that are relevant to the evaluation of 

the drinking water pathway. It summarizes data on tap water intake among children 

([U.S.] EPA 2004[a]) that were collected more recently than the tap water 

consumption rates used in the PRA. These rates were calculated from the combined 

1994, 1995, 1996, and 1998 Continuing Survey of Food Intakes by Individuals, 

conducted by the United States Department of Agriculture. In addition to being 

more recent than the data set in the exposure factor handbook (EPA 2007a), the 

2004 data set contains more data for the infant age range (0-1 year old), which was 

excluded from the PRA without explanation. Including an infant will likely have 

minimal effect on risk calculations, but exposure during this life stage should be 

acknowledged in the risk assessment. 

EPA assumed that the child fish consumption rate was the same as the adult fish 

consumption rate. This assumption is unnecessarily conservative for many but not 

necessarily all U.S. subpopulations. EPA should consider reducing the fish 

consumption rate for a child, using the ratio of adult to child fish consumption rates 

from various sources, e.g., 

EPA’s 2002 Estimated Per Capita Fish Consumption in the United States [U.S. 

EPA, 2002c]; or West PC, Fly JM, Marans R, Larkin F, Rosenblatt D. 1993. 1991-

92 Michigan sport anglers fish consumption study. Prepared by the University of 

Michigan, School of Natural Resources for the Michigan Department of Natural 

Resources, Ann Arbor, MI. Technical Report No. 6; May 1993. 

It would also be useful to include a summary of recent literature beyond what is 

described in the 1997 Exposure Factors Handbook. 

Exposure Duration Distributions. Why is the maximum value for the child exposure 

duration 50 years? This value makes no sense given the four child age categories 

that EPA selected. Perhaps if EPA explained how these distributions were used in 

the modeling, the rationale for this maximum value would be clear. Regardless, a 

50-year exposure duration is long but might be appropriate at some sites, depending 

on the size and productivity of water bodies near WMUs. 

EPA Response 

Dr. Vorhees comments refer to the Child-Specific Exposure Factors Handbook (U.S. EPA, 2008a). 

The revised risk assessment makes use of both these newer exposure factors, as well as the 

suggested child age groups. These revisions also include evaluation of infants drinking formula 
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made with contaminated water. Since Dr. Vorhees is correct that exposure factors such as body 

weight are correlated to the receptor’s age, EPA used separate exposure factor distributions for 

each age cohort. A discussion of the exposure factors is available in Section 2 and Appendix D

of the revised risk assessment, and the uncertainties associated with their use is discussed in 

Section 5. 

With respect to the aging of receptors, EPA has added discussion of this process to Section 3 of 

the revised risk assessment. 

5.7. Correlations in Input Variables 

Comment Summary 

Dr. Vorhees commented that correlations were only discussed in Appendix C as related to how 

they were accounted for among inputs in the EPACMTP model. No discussion of correlations 

among other inputs (e.g., fish consumption rate and body weight) was provided. 

Dr. Donna Vorhees, The Science Collaborative 

The authors do not mention the presence or absence of correlations except in 

appendix C where they discuss how they accounted for correlations among inputs 

to the EPACMTP model. There is no discussion of correlations among other input 

distributions, such as fish consumption rate and body weight or among age-specific 

distributions for multiple child age groups that are analyzed in a single Monte Carlo 

simulation. Only one constituent was modeled at a time; therefore, EPA does not 

need to consider correlations among CCR constituent concentrations in drinking 

water or fish. Also, with the exclusion of the dermal exposure pathway, EPA does 

not need to consider the correlation between body surface area and body weight. 

EPA Response 

Although exposure factors were selected for specific age groups, the distributions for each 

exposure factor were not correlated with each other within each of these age groups. Instead, for 

each modeling run, each exposure factor was selected from its age group–based distribution 

independently. This introduces some uncertainty into the evaluation because some combinations 

of exposure factors, such as a high fish consumption rate combined with small body weight, while 

possible, may be less frequent. However, sufficient data are not available to develop these 

correlations. Therefore, this remains an uncertainty in the analysis that may under- or overestimate 

exposures for given model iterations. The magnitude of this uncertainty is unknown, but is 

discussed in Section 5 of the revised risk assessment. 
Response to Peer Review Comments

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6. Comments Related to Ecological 

Exposure and Toxicity 

The peer review comments relating to ecological exposure and toxicity are grouped into four 

subcategories: 

1. Cumulative ecological risk 

2. Sensitive habitats/sensitive species 

3. Indirect effects 

4. Ecological benchmarks, ecological toxicity. 

6.1. Cumulative Ecological Risk 

Comment Summary 

Dr. Hopkins emphasized the potential importance of cumulative ecological risk, whereby an 

ecological receptor may be exposed to multiple constituents and/or pathways. For example, 

amphibians may be subject to both dermal and ingestion exposure. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

Ecological scenarios can be even more complex and consideration needs to be 

given to the full lifecycle of receptors in the analysis. Take for example amphibians 

that use surface impoundments for reproductive purposes. Adults can be exposed 

transdermally because most of the water they acquire crosses the skin (they don’t 

typically drink). Concomitantly, they can be exposed trophically because the 

invertebrates they ingest accumulate trace elements from the site. Their eggs are 

deposited in the water, where developing embryos are directly exposed to dissolved 

concentrations in the impoundment. Larvae that successfully hatch from these eggs 

are then exposed to not only the water, but also the contaminated plant material and 

coal combustion wastes that they ingest directly. 

EPA Response 

EPA acknowledges that cumulative effects can be important for ecological receptors. However, 

just as EPA did not consider cumulative human health risks from exposures to ground water 

(discussed in Section 6.1 of this document), they were not modeled for ecological receptors. In 

Section 4 of the revised risk assessment, risks for all constituents fell below the ecological criteria. 

Even the sum of modeled risks for all constituents fell below the ecological criteria. To the extent 

that cumulative risk was not evaluated, EPA acknowledges that ecological risk could be 

underestimated to some degree for surface water exposures. However, these uncertainties are 

unlikely to affect the principal findings of the risk assessment. In addition, EPA also notes that all
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surface water risks are orders of magnitude lower than the risks resulting from direct discharges 

modeled in U.S. EPA (2013).

In contrast to the surface water and sediment exposures, ecological risks for individual constituents 

were appreciably above risk criteria for direct exposure to impoundment wastewater. As a result, 

it is clear that CCR disposal in surface impoundments have the potential to pose risk to ecological 

receptors, even without consideration of cumulative exposures. 

6.2. Sensitive Habitats/Sensitive Species 

Comment Summary 

Dr. Hopkins commented that the risk assessment does not consider sensitive habitats or species. 

Rather, this is listed as an uncertainty to be dealt with on a site-specific basis. Dr. Hopkins 

requested additional discussion of this issue, including “how it can be dealt with on a site specific 

basis” and “specific steps to be taken to determine what habitats and species deserve special 

consideration.” 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

The only other major comment I have relates to the exclusion of sensitive habitats 

and sensitive species from the analysis. This is listed as an uncertainty that will 

need to be dealt with on site-specific basis. I agree with this conclusion, but it would 

be useful to see this idea receive more prominence in the conclusions of the 

document. How can it be dealt with on a site-specific basis? What specific steps 

should be taken to determine what habitats and species deserve special 

consideration (besides the obvious threatened and endangered species)? 

EPA Response 

EPA did not evaluate sensitive habitats and sensitive/endangered ecological receptors because the 

presence of such habitats and receptors is inherently a site-specific issue, and data on potential 

impacts are often not available and can be difficult to ascertain, even on a site-specific basis. 

Although these classes of receptors and potential ecological hazards are not explicitly considered 

in the analysis, conditions represented by simulations in the upper end of the risk distribution 

(higher risk scenarios) and based on benchmarks for the most sensitive ecological receptors for 

which data are available should characterize many situations with such sensitive species or 

habitats. EPA acknowledges that the inability to quantitatively evaluate the potential for these 

adverse effects represents a source of uncertainty. Discussion of these uncertainties is presented in 

Section 5 of the revised risk assessment. 
Response to Peer Review Comments Ecological Exposure and Toxicity

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6.3. Indirect Effects 

Comment Summary 

Dr. Hopkins emphasized the potential importance of indirect ecological effects (e.g., depletion of 

food resources), suggesting that exclusion of indirect effects from the risk assessment 

underestimates risk. He requested at a minimum discussion of indirect effects as a major 

uncertainty. Dr. Harvey requested additional discussion of “how ecosystems can be adversely 

affected by discharges of solutes in unexpected ways” and how this issue is uncertain due to 

insufficient scientific understanding. 

Dr. William Hopkins, Virginia Polytechnic Institute and State University 

Consideration of indirect effects of toxic constituents in coal combustion wastes on 

ecological systems. Currently, the risk assessment is based on the assumption that 

all effects of contaminants are direct (i.e., direct toxicity). In reality, when 

contaminants are discharged into ecological systems, they have community wideeffects that are often mediated through ecological interactions. Indirect effects 

include responses such as depletion of food resources, alteration of predator-prey 

interactions, and modified host-pathogen interactions. It is well known that the 

indirect effects of contaminants can be just as important, and in some cases more 

important, than direct effects. This has been demonstrated for a wide variety of 

organic pollutants and metals (e.g., Fleeger, et al., 2003). Similarly, a variety of 

ecological effects have been documented from coal combustion wastes that could 

have broad, indirect effects on other community constituents (e.g., Reviewed in 

National Academy of Sciences [National Resources Council] Report, pages 89-90). 

Failure to consider indirect effects in the models (at the very least, as a major 

uncertainty) underestimates risk. 

Dr. Charles Harvey, Massachusetts Institute of Technology 

I recognize that the hazard quotient approach may be the only workable method for 

attempting to quantify ecological risks. However, I think the report would be 

strengthened by a candid discussion of how aquatic ecosystems can be adversely 

affected by discharges of solutes in unexpected ways. The state of the science is 

simply not sufficient to predict how different species, let alone ecosystems, will 

respond to an input of a mixture of solutes. Many examples exist of how aquatic 

environments are impacted in surprising ways by shifts in water chemistry. 

EPA Response 

EPA has expanded the report discussion on indirect ecological effects and the associated 

uncertainty in Section 5 of the revised risk assessment. 
Response to Peer Review Comments Ecological Exposure and Toxicity

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6.4. Ecological Benchmarks, Ecological Toxicity 

Comment Summary 

Dr. Basta was concerned that the ecological benchmarks used in the risk assessment may have 

been overly conservative and that many are at or below background soil concentrations, 

mentioning lead in particular (specifically, that the 95th percentile of the natural background of 

lead in soils in the United States is 38.8 mg/kg [Smith et al., 2005], higher than the value of 28 

mg/kg used in the risk assessment). He suggested EPA Ecological Soil Screening levels (EcoSSLs) as an alternative. In the example of lead, the Eco-SSL of 1,700 mg/kg is 60 times higher 

than the value used in the risk assessment. 

Dr. Nicholas Basta, Ohio State University 

The ecological database used to generate ecological benchmarks and calculate 

ecological HQs is overly conservative, and at times, unrealistic. Many of the 

ecological benchmarks are at or below background soil concentrations. 

Ecotoxicological data were identified from summary documents prepared at the 

Oak Ridge National Laboratory (Efroymson et al., 1997a,b). 

Many of the Soil Criteria Ecological Benchmarks in the Draft are well below 

natural background levels in soil. Natural background soil levels of the constituents 

considered in Table H-3 of the Draft Ecological risk assessment are not phytotoxic. 

Contaminant soil concentrations must be much greater than natural background 

concentrations to observe ecotoxicity at Draft Benchmark effects levels. For 

example, the Soil Criteria of 28 mg/kg Pb [lead] was used in the risk assessment 

(Table H-3) for soil invertebrates as the terrestrial receptor. However, the 95th 

percentile of the natural background of Pb in soils in the United States is 38.8 mg/kg 

(Smith, 2005). The Soil Criteria is below background soil Pb levels. We do not 

observe phytotoxicity to soil invertebrates at 28 mg/kg Pb in natural soils. 

USEPA has established Eco-SSLs of contaminants in soil that are protective of 

ecological receptors that commonly come into contact with and/or consume biota 

that live in or on the soil. The derivation procedures for the Eco-SSLs represent the 

collaborative effort of a multi-stakeholder team consisting of federal, state, 

consulting, industry, and academic participants led by the USEPA, Office of Solid 

Waste and Emergency Response. The Eco-SSL values were derived separately for 

four groups of ecological receptors: plants, soil invertebrates, birds, and mammals. 

These values are presumed to provide adequate protection of terrestrial ecosystems. 

Eco-SSLs are derived to be protective of the conservative end of the exposure and 

effects species distribution and are intended to be applied at the screening stage of 

an ecological risk assessment. The detailed procedures used to derive Eco-SSL 

values are described in separate documentation (U.S. EPA, 2003[d]). 
Response to Peer Review Comments Ecological Exposure and Toxicity

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The USEPA Pb Eco-SSL for soil invertebrates is 1,700 mg/kg Pb (U.S. EPA, 

2005[c]). Thus, the Eco-SSL of 1,700 mg/kg is considered to be protective of the 

conservative end of the exposure and effects species distribution. The Eco-SSL is 

60 times higher than the Soil Criteria Ecological Benchmark of 28 mg/kg used in 

the Draft. Why the difference? The Eco-SSL values are based on an exhaustive 

review of previously published peer-reviewed literature from soil invertebrate 

studies that included natural soils and soil invertebrate toxicity endpoints (U.S. 

EPA, 2003[d]). Because of its scope, Eco-SSL values are better indicators for 

ecotoxicity screening than the study used to establish Ecological Benchmarks in the 

Draft. 

The Ecological Benchmarks in Table H-3 should be compared with (a) the 95th 

percentile concentration of natural soils for each constituent, and (b) the USEPA 

Eco-SSL values. The Soil Criteria should be reevaluated and justified if the 

Benchmark is below natural soil concentrations (Smith, 2005) where we know 

toxicity does not occur. At a minimum, a table comparing the three should be 

reported in the Draft. 

EPA Response 

EPA agrees with Dr. Basta’s comments that the most recent ecological data, such as the Eco-SSLs, 

should be used when appropriate. When the ecological benchmarks used in the draft CCR risk 

assessment were developed, EPA used a very different methodology to establish benchmarks for 

the soil community relative to the Eco-SSL effort. The 1998 methodology for the generation of 

constituent stressor concentration limits was intentionally conservative and was based on species 

sensitivity distributions that include a wide range of soil fauna. In the 10 years since the CCR 

ecological benchmarks were developed, there has been a considerable effort by EPA and others to 

improve the data and methods used in benchmark derivation. In the revised risk assessment, EPA 

makes use of newer ecological benchmarks, including the Eco-SSLs, where available. Further 

discussion on EPA’s selection of ecological benchmarks is available in Appendix E of the revised 

risk assessment, while uncertainty surrounding these benchmarks is presented in Section 5. 

Dr. Basta’s suggestion that the benchmark used for lead is below background is no longer relevant 

because the current screening assessment in Section 3 of the revised risk assessment shows that 

lead is not present at levels of concern for soil biota. Thus, no further response to this comment 

was necessary. However, Dr. Basta’s broader implication that ecological screening levels are 

below background is slightly misleading. The expression of toxicity with regards to soil biota (as 

well as plants and other flora and fauna) for any constituent is inherently a site-specific 

phenomenon. Areas with high natural concentrations of a given constituent tend to be colonized 

by more tolerant species and have those constituents in more stable, less bioavailable forms. In 

areas with relatively low background concentrations, the introduction of higher constituent levels 

may result in a significant change in the soil community that could adversely affect the ecosystem. 
Response to Peer Review Comments Ecological Exposure and Toxicity

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These are valid considerations for site-specific analyses, but due to their site-specific nature, they

were not incorporated into the nationwide analysis conducted here. 
Response to Peer Review Comments

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7. Comments about the Monte 

Carlo Analysis Approach 

The peer review comments relating to the Monte Carlo analysis approach are grouped into four 

subcategories: 

1. Use of conservative parameter estimates 

2. Variability versus uncertainty 

3. The calculation of percentile probabilities as opposed to an overall probability 

4. Comments related to the numerical stability of Monte Carlo results 

5. Impacts on ground water as a resource. 

7.1. Use of Conservative Parameter Estimates 

Comment Summary 

Dr. Harvey expressed concern about the use of conservative estimates for some parameters. He 

emphasized that the ideal approach would be to estimate the actual risk and associated uncertainty 

rather than weighting the results conservatively. “From a decision making point of view, it is much 

cleaner if the distribution of risks represents a best estimate. Then attitudes towards risk (i.e., being 

“protective”) can be considered when using this distribution to make a decision.” 

Dr. Charles Harvey, Massachusetts Institute of Technology 

The logic of this assessment also skates on thin ice when “conservative” or 

“protective” values of parameters are selected. The idea of a Monte Carlo model is 

to generate a best estimate of the actually probability distribution. While there is a 

clear motivation to use protective values of a parameter when assessing 

environmental contaminants, choosing a value that gives an upper bound on risk, 

rather than the best estimate of risk, may be an easy way out of the difficult job of 

assessing probabilities and this approach may muddle the overall assessment. It is 

often easier to say, “I know that this parameter can’t possibly be beyond the value 

A” than to support the claim that a parameter has a value B with a certain standard 

deviation. The problem with this approach is that it moves risk aversion into the 

characterization of the distribution of outcomes. From a decision making point of 

view, it is much cleaner if the distribution of risks represents a best estimate. Then 

attitudes towards risk (i.e. being “protective”) can be considered when using this 

distribution to make a decision. (Note: for the cancer risk from arsenic the 

distribution may be best collapsed into a single probability, as discussed in above 

in C.) 
Response to Peer Review Comments Monte Carlo Analysis Approach

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EPA Response 

The revised risk assessment conducted full-scale probabilistic Monte Carlo analysis to quantify 

human and ecological risks. EPA agrees in the ideal of producing best estimates of actual risk. All 

input data distributions (e.g., aquifer data, soil type, WMU data, climate data, distance to ground 

water wells, distance to surface water bodies, constituent concentrations, water flow data, human 

exposure factors) were developed in line with this objective. However, these distributions were 

developed from available data and are subject to the limitations of these data. In cases where data 

were not sufficient to fully characterize the input distribution, conservative values and assumptions 

were used to fill data gaps to remain protective of human health and the environment. Further 

discussion of the resulting uncertainties has been added to Section 5 of the revised risk assessment. 

7.2. Variability versus Uncertainty 

Comment Summary 

Dr. Vorhees pointed out that the risk assessment does not formally separate variability from 

uncertainty, which makes it challenging to identify opportunities to reduce uncertainty. 

Dr. Donna Vorhees, The Science Collaborative 

The authors discuss variability and uncertainty. Distinguishing between them 

quantitatively is important for determining opportunities to reduce uncertainty in 

risk estimates. EPA’s input distributions are intended to represent national 

variability. In addition EPA reports that “Uncertainty also was considered in the 

analysis by using reasonable ranges and distributions when variables were not 

known exactly. For example, when a soil texture or ground water flow conditions 

could not be precisely assigned at a site, multiple soil types or hydrogeologic 

environments would be sampled based on the soil and aquifer types that are likely 

to be present at the site.” (page 4-27) As a result, EPA has not separated uncertainty 

and variability quantitatively but has instead blended them in some input 

distributions. To the extent possible, EPA guidance recommends separating them 

to help in identifying opportunities to reduce uncertainty. 

Simulation inputs were not defined in a manner that would allow for a clear 

quantitative distinction between the contribution of variability and uncertainty to 

the simulation output. This limitation of the Monte Carlo simulations is discussed 

below under Condition #5. 

EPA Response 

EPA acknowledges the ideal of separating variability from uncertainty when possible in a 

probabilistic risk assessment. EPA was able to reduce a substantial number of the uncertainties in 

the revised risk assessment through the acquisition of additional data on facilities, environmental 

parameters, and constituent concentrations. Variability and uncertainty are still comingled in a 
Response to Peer Review Comments Monte Carlo Analysis Approach

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large number of cases due to remaining data gaps; however, EPA conducted multiple sensitivity 

analyses to determine the potential for different inputs to affect risk results. Additional discussion

of the differences between parameter variability, data uncertainty, and model error, as well as 

discussions of the sensitivity and uncertainty analyses, is presented in Section 5 of the revised risk 

assessment. 

7.3. Calculation of Percentile Probabilities as Opposed 

to an Overall Probability 

Comment Summary 

Dr. Harvey stated that the distributions of cancer risk estimated in the risk assessment can be 

reduced to a single probability and that this result can provide particular insight into the results. 

Dr. Charles Harvey, Massachusetts Institute of Technology 

For the cancer risks from arsenic, the Monte Carlo model generates probability 

distributions of cancer probabilities. A probability distribution of binary 

probabilities can be reduced to a single probability. For example, consider the case 

where you are adverse to tails in a coin toss. If there is a 0.6 probability that the 

coin is fair and 0.4 probability that the coin is weighted so that it lands tails with 

0.75 probability, then the probability of getting tails is: 0.6*0.5 + 0.4*0.75 = 0.6. 

What you really care about is the 0.6 chance of tails, and the distribution of 

probabilities used to calculate this risk is of little value to you. Likewise, for the 

cancer risks one could simply calculate the final cancer risk (the probability of 

cancer) over the Monte Carlo generated distribution of risks. This calculated 

probability may be the most important estimate, more useful than the 0.5 and 0.9 

quantiles of probability provided in this report. The assessment should certainly 

report this probability, and it would also be useful if the report discussed how 

distributions of probabilities should be considered. For the hazard quotients, the full 

distribution is necessary because hazard quotients are not probabilities. A clear 

explanation of the use of estimated distributions would help the reader understand 

the conditions for which distributions are useful, and the conditions under which 

they may be converted to a single probability without losing important information. 

EPA Response 

EPA acknowledges that such a simplification may be possible. However, EPA policy states that 

decision-makers should be given a range of risk estimates from at least two points on a distribution 

of risk estimates; a central tendency estimate, and a “high-end” estimate (U.S. EPA, 1992). This 

is consistent with EPA policy, and provides more useful information to the decision-makers than 

what would effectively be an unweighted average. Therefore, no changes were made in response 

to this comment. 
Response to Peer Review Comments Monte Carlo Analysis Approach

7-4 

7.4. The Numerical Stability of Monte Carlo Results 

Comment Summary 

Dr. Vorhees requested an evaluation of the stability of the Monte Carlo results. In other words, is 

the number of simulations sufficient, so that the results do not change significantly with more 

simulations? 

Dr. Donna Vorhees, The Science Collaborative 

EPA performed Monte Carlo simulations of 10,000 iterations per waste type/WMU 

type/constituent combination. However, they do not provide quantitative evidence 

of numerical stability of 50th and 90th percentile estimates using this number of 

iterations. This information needs to be in the report. In addition, when EPA reports 

results by liner type, e.g., Table 4-1, it is reporting results from fewer than 10,000 

iterations, with the number of iterations per liner type a function of how frequently 

WMUs with each liner type were selected in the Monte Carlo simulation. 

EPA Response 

Figure 1 shows average risk versus the number of simulations for arsenic under selected CCR 

disposal scenarios in the draft risk assessment. The lower two lines depict landfill risks for the 

10,000 model iterations of ash and ash mixed with coal mill rejects, respectively. Similarly, the 

upper two lines depict surface impoundment risks for the 10,000 model iterations of ash and ash 

mixed with coal mill rejects, respectively. In each case, the averages of the model results converge 

as the number of simulations increases. Consistent with other probabilistic risk analyses conducted 

by EPA, around three to five thousand simulations are necessary for convergence in most cases. 

Thus, the over 30,000 simulations for landfills and over 70,000 simulations for surface 

impoundments in the revised risk assessment are more than sufficient for all modeled cases. 
Response to Peer Review Comments Monte Carlo Analysis Approach

7-5 

Figure 1. Example showing convergence of Monte Carlo simulations of up to 

10,000 realizations. 

7.5. Impacts on Ground water as a Resource 

Comment Summary 

Dr. Harvey requested a discussion of the potential for ground water contamination to impact the 

availability of ground water as a resource in the future. Similarly, Dr. Rowe questioned whether 

ground water use patterns would change in the future, thus affecting the potentially exposed 

population (e.g., higher population density leading to more wells closer to the source). Dr. Rowe 

requested an evaluation of the sensitivity of the results to the well placement assumptions. 

Dr. Charles Harvey, Massachusetts Institute of Technology 

The report would also benefit from a discussion of the non-health and nonecological costs of polluting ground water: namely, the loss of ground water as a 

resource to future generations. Even with no adverse health impacts, there is an 

important adverse effect of contaminating ground water. The ground water 

downgradient of a WMU may be lost as a useable source of water. This adverse 

effect of WMUs could be assessed by characterizing the volume of ground water 

lost as a potential resource near WMUs. The volume of this lost resource is 

1E-07

1E-06

1E-05

1E-04

1E-03

1E-02

1E-01

1E+00

1 10 100 1,000 10,000

Average Risk

Number of realizations

Landfill, ash Landfill, ash and coal

Surface impoundment, ash Surface impoundment, ash and coal
Response to Peer Review Comments Monte Carlo Analysis Approach

7-6 

substantially larger than the volume of ground water that is actually contaminated 

because the pattern of ground water contamination downstream of a source is nearly 

impossible to completely characterize, so the ground water over a large area will 

not be used. 

Completely ignoring health effects because of the belief that no one will drink 

contaminated water, and shifting the analysis to purely protection of water 

resources, would be an extreme approach, and I would not support such a limited 

analysis. However, I think that the report would benefit from a candid discussion 

of the actual effects on the population near a WMU, a discussion of the possible 

numbers of people who would really drink contaminated well water and the 

detrimental effects of loosing valuable water supplies. 

Dr. Kerry Rowe, Queens University 

In the absence of an actual survey of water well usage around existing CCR 

facilities, I am not aware of a better source of data than that available for MSW 

landfills. EPA recognized this as “one of the larger uncertainties in this analysis” 

(RA, pg. 4-37) however the statement that “EPA believes that the MSW well 

distance distribution used is protective for CCR landfills and surface 

impoundments” (RA, pg. 4-37) appears to be nothing more than that – a belief – 

with no justification being given for this article of faith. Also, as noted in response 

to Question #5, the analysis extends for 10,000 years but no consideration appears 

to have been given to likelihood of increased demand for the use of ground water 

in the next 30-100 years (let alone the next 10,000 years) which presumably means 

more wells and makes the protection of ground water likely even more important 

for the future than it is now. It would have been good to have examined the 

implications of wells being closer than that indicated by the MSW survey to assess 

how sensitive the RA is to that assumption (one can infer that it will be important 

– but not how important in terms of risk). 

EPA Response 

EPA acknowledges Dr. Harvey’s comments on future ground water resources. However, this issue 

is beyond the scope of the risk assessment, as stated in Section 1 of the revised risk assessment, 

and therefore the risk assessment did not explicitly consider potential impacts on the availability 

of ground water in the future. Nevertheless EPA notes that the results do clearly indicate that there 

can be a reduction in resource availability if ground water contaminated by CCRs becomes 

unsuitable for consumption. 

Dr. Rowe’s comments on the changing location of wells and the appropriateness of the MSW well 

distances have been addressed in Sections 2.1 and 2.4 of this response to comment document, 

respectively. 
Response to Peer Review Comments

8-1 

8. Comments Related to the 

Documentation and 

Miscellaneous Comments 

The peer review comments relating to documentation are grouped into seven subcategories: 

1. Insufficient documentation to reproduce the analysis independently 

2. Graphical input/output distributions, truncation values 

3. Documentation of sensitivity analysis 

4. Discussion of general risk-susceptibility patterns (e.g., climate-specific risk) 

5. Discussion of worst-case scenarios 

6. Discussion of sulfate, phosphate, and chloride 

7. Background concentrations. 

8.1. Insufficient Documentation to Reproduce the 

Analysis Independently 

Comment Summary 

Dr. Basta, Dr. Rowe, and Dr. Vorhees stated that the documentation is incomplete and that an 

independent reviewer could not reproduce the analysis. For example, Kd values generated by 

MINTEQA2 used for EPACMTP are not presented in the documentation. 

Dr. Nicholas Basta, Ohio State University 

The parameterization of the risk models is clear but the inputs and outputs of several 

modeling components are absent and must be provided. A thorough review of the 

CCR risk assessment was not possible because input data used or data generated 

for the risk assessment was not provided. The inputs and outputs for each step of 

the risk assessment should be provided. For example, Kd values generated by using 

MINTEQA2 (used as input data for EPACMTP) are critical but are not reported. 

The Kd value selected can greatly influence the outcome of the risk assessment. 

Review of Kd values, and other intermediate modeled outputs, is critical. The 

reviewer cannot determine whether Kd values used were “reasonable.” Similarly, 

modeled ground water concentration used as input data for the risk assessment 

should be provided for review. In short, the modeling methodology should be more 

transparent. 
Response to Peer Review Comments Documentation and Miscellaneous Comments

8-2 

The parameterization of the risk models is clear, but the inputs and outputs of 

several modeling components are absent and must be provided. The inputs and 

outputs for each step of the risk assessment should be provided. In short, the 

modeling methodology should be more transparent. 

Dr. Kerry Rowe, Queens University 

The documentation of the parameterization is at a variable but generally high level. 

It is adequate to give a general idea of how the RA was conducted and, except for 

the limitations as noted in response to other questions, appears reasonable at the 

level provided. However the level of detail is insufficient for a reviewer to comment 

in detail on the distributions that were input to the Monte Carlo simulations and 

hence it is also not possible to reproduce the RA based on the documentation 

provided for review. Thus, except at a very high level, it is not possible to comment 

on the completeness or reasonableness of the distributions that were input to the 

Monte Carlo simulations. This is a significant short-coming if the objective of the 

documentation is to allow a complete review of the approach that was adopted in 

arriving at the results. That said, it is also recognized, that full documentation will 

likely be quite voluminous and would take much longer to review than has been 

allocated. 

Dr. Donna Vorhees, The Science Collaborative 

My general comment is that the risk assessment does not provide sufficient 

information to allow results of the analysis to be independently reproduced. My 

more detailed comments follow. 

EPA describes the foundation of the Monte Carlo simulation as the source data 

derived from the EPRI survey, explaining that these data were combined with data 

from EPA’s CCR constituent database to conduct a simulation of 10,000 iterations 

per waste type/WMU type/constituent combination. EPA also should provide the 

name of any software program and/or annotated computer code that it used to 

perform these simulations. 

EPA Response 

EPA acknowledges that the documentation of the inputs and intermediate outputs could have been 

more transparent. In the revised risk assessment, EPA notes that many of the inputs EPA used are 

directly discernible from the appendices. A summary of the data available in each appendix is 

presented in Section 1 of the revised risk assessment. 

With respect to Kd values, these comments are addressed in Section 2.1 of this response to 

comments document. 

Finally, EPA acknowledges that the additions and discussions of inputs in the document are not 

sufficient for duplication of the results. Thus, the input and output files for the draft risk assessment 
Response to Peer Review Comments Documentation and Miscellaneous Comments

8-3 

were made available in the docket of the proposed rule via an FTP site,3 and final input and output 

files are being placed in the docket for the final rule concurrently with this response to comments 

document. 

8.2. Graphical Input/Output Distributions, Truncation 

Values 

Comment Summary 

Dr. Vorhees requested graphical presentation of input and output distributions. She also requested 

further explanation of the minimum and maximum truncating values. 

Dr. Donna Vorhees, The Science Collaborative 

EPA provides much of the documentation required for a PRA, including exposure 

input distributions, models used to predict surface water, fish, and ground water 

concentrations, and models used to predict noncancer hazard quotients and cancer 

risks. EPA discusses many of the most important assumptions inherent in their 

choices of input distributions. However, EPA does not include input distributions 

and output distributions in graphical format, which would aid interpretation and use 

of results, particularly given the relatively large differences between some 

corresponding 50th and 90th percentile results. It would be useful to see plots that 

include the input distributions and the data used to construct the distributions as a 

supplement to goodness-of-fit statistical test results. EPA does not explain why it 

chose the minimum and maximum values for truncating input distributions or 

whether truncation affected parameter estimates for the distributions. 

EPA explains that HQs for the child resident were consistently higher than HQs for 

the adult resident; therefore, only child HQs are presented. This is a reasonable 

choice, but it would be helpful to define which of the four childhood age groups 

corresponded to the child resident and to label tables accordingly. 

EPA Response 

Although EPA did not provide a graphical presentation of the risk results, this information is more 

clearly discernible from the full input and output files discussed in Section 8.3 above. 

With regard to truncation, EPA no longer manually truncates input distributions for the human 

exposure factors. Instead, exposure factor distributions in the revised risk assessment were 

generated with the @Risk software (Palisade Co., Newfield, NY)4 as described in Appendix D of 

the revised risk assessment. 

 

3 Available online at: ftp://ftp.epa.gov/coal-combustion-residues 

4 Available online at: http://www.palisade.com/risk/ 
Response to Peer Review Comments Documentation and Miscellaneous Comments

8-4 

EPA has also added further discussion of the cohorts to the body of the risk analysis, with tables 

comparing each cohort’s risk presented in Section 5 of the revised risk assessment. 

8.3. Documentation of Sensitivity Analysis 

Comment Summary 

Dr. Vorhees requested more complete documentation of the sensitivity analysis. She also stated 

that she could not find the report that originally presented the sensitivity analysis (U.S. EPA, 

2005[b]). 

Dr. Donna Vorhees, The Science Collaborative 

EPA briefly summarizes the sensitivity analyses that it describes in another report 

(EPA 2005[b]). I was unable to find this report online. The sensitivity analyses are 

an integral part of the PRA, vital to proper interpretation and use of results, and 

should not be reported in a separate document. 

EPA’s summary is not sufficient to understand the full scope of the sensitivity 

analysis effort, the procedures that EPA used, and extent to which EPA was able to 

distinguish influential sources of variability from influential sources of uncertainty. 

EPA excluded human exposure factors from the sensitivity analysis, describing 

them as sources of variability that could not be changed or managed in anyway. 

Nevertheless, if one of these inputs strongly influenced risk results, this might 

indicate that EPA needs to take additional steps to determine how well its input 

distributions accurately reflect variability on a national level. The fish consumption 

rate distribution is based on data from only one region, so it will be particularly 

important to determine its relative influence on risk estimates. 

EPA Response 

EPA acknowledges the omission of the original sensitivity analysis from the docket. EPA updated 

the sensitivity analysis (U.S. EPA, 2009a) and placed it in the docket for the proposed rule. A 

summary of the methodology and results is also presented in Section 5 of the revised risk 

assessment. 

8.4. Discussion of General Risk-Susceptibility Patterns 

such as Climate-Specific Risk 

Comment Summary 

Dr. Rowe and Dr. Harvey requested an analysis of risk susceptibility patterns—i.e., what 

conditions lead to more or less relative risk. Dr. Rowe focused on potential climate patterns (e.g., 

less risk in dry conditions). 
Response to Peer Review Comments Documentation and Miscellaneous Comments

8-5 

Dr. Charles Harvey, Massachusetts Institute of Technology 

This report misses the opportunity to describe which WMU are the most dangerous. 

It would be useful to know the conditions where the risks are the highest, and then 

to map where these locations are most likely to exist. This could be accomplished 

simply by taking the top, say 20%, of realizations with the worst risk and analyzing 

what these realizations have in common. Some characteristics will be trivial, such 

as a short distance to the well or water body, but others, such as the geochemical 

and hydrologic parameters, might provide useful insight into where high-quality 

liners are particularly important. 

Dr. Kerry Rowe, Queens University 

While it is understood that the objective was to do a RA for the entire US using the 

distributions of sites in the ERPI (1997) report, it needs to be recognized that (a) 

climate and (b) composite-liner design and construction have a profound impact on 

the WMU infiltration rate for landfills (correctly identified as a key parameter 

affecting the RA, e.g. pg. 4-40). These are discussed below. 

The potential risk of a disposal facility in an arid climate may be substantially 

different to those in a humid climate and hence the nature of, for example, the level 

of liner that is needed to meet risk criteria may vary from one climatic region to 

another. The current RA may underestimate risk for humid zones and overestimate 

risk in arid zones. Thus for the purposes of developing management options for 

CCR (Objective 2), more cost effective management strategies may be developed 

by considering what is required for different climatic regions rather than adopting 

a one-size-fits-all approach. 

EPA Response 

EPA refers Dr. Harvey to Section 5 of the risk assessment, where a summary of the sensitivity 

analysis is provided. EPA finds that across constituents and pathways, the most sensitive drivers 

of risk appear to be leachate concentration and infiltration rate. To the extent that infiltration rate 

is affected by the precipitation rate, the sensitivity analysis suggests that the risk results may be 

sensitive to the particular climate variable that the commenter suggests. 

Other parameters that appear to be sensitive for specific constituents and pathways include aquifer 

hydraulic conductivity and gradient, adsorption isotherm coefficient, depth to ground water, 

receptor well distance, and waterbody flow rate. Although EPA did not analyze the top 20 percent 

of model runs as the commenter suggests, the sensitivity analysis results confirm that higher input 

values for these variables are likely to lead to higher risk results. 
Response to Peer Review Comments Documentation and Miscellaneous Comments

8-6 

8.5. Discussion of Worst-Case Scenarios 

Comment Summary 

Dr. Rowe emphasized that worst-case scenarios may exceed the risks modeled in the risk 

assessment. 

Dr. Kerry Rowe, Queens University 

The discussion of receptor populations is considered reasonable given the broad 

scope of the study. However it should be acknowledged that there may be special 

cases where the assessment may underestimate risk. Under these circumstances, 

site specific studies would be warranted. These situations are unlikely to occur often 

but the possibility should be recognized in the development of any regulations 

based on the RA. For example, the consumption of fish assumes recreational fishing 

and this is, in most cases, likely to be reasonable. However if the receptor water 

body was used by subsistence fish consumers (native harvesters as identified in the 

comments by Dr. Foran) then the risks could be substantially higher than modeled. 

EPA Response 

EPA acknowledges that a range of outcomes may occur. The risk assessment has been expanded 

to include discussion of specific subsets of current disposal practices in Section 5 that may be 

closer to the “worst-case” scenarios discussed by Dr. Rowe than the reported national results from 

the risk assessment. 

8.6. Discussion of Sulfate, Phosphate, and Chloride 

Comment Summary 

Dr. Rowe questioned why sulfate, phosphate, and chloride were excluded from the analysis. He 

requested more justification. 

Dr. Kerry Rowe, Queens University 

Although it is acknowledged that some of the contaminants not considered (e.g. 

sulfate, phosphate and chloride; RA pg. 2-3) could “pose an ecological hazard if 

concentrations are high enough”, there is inadequate discussion of the justification 

of this exclusion and its rationalization. 

EPA Response 

The revised risk assessment no longer excludes constituents from the analysis if they pass through 

the hazard identification in Section 2. The hazard identification results present the availability of 

toxicity benchmarks for each constituent for which concentration data were available. This now 

includes sulfate for human health and chloride for both human health and ecological risk. 
Response to Peer Review Comments Documentation and Miscellaneous Comments

8-7 

Phosphate, due to the lack of concentration data, is not evaluated. However, discussion of this 

uncertainty has been included in Section 5 of the revised risk assessment. 

8.7. Background Concentrations 

Comment Summary 

Dr. Vorhees requested discussion of background concentrations of constituents in CCR. 

Dr. Donna Vorhees, The Science Collaborative 

EPA did not discuss results in light of background concentrations of CCR 

constituents in the absence of a release from WMUs. Such discussion would 

improve the risk assessment. 

EPA Response 

EPA acknowledges that a discussion of background concentrations of CCR constituents would be 

helpful to a risk manager, especially if a CCR facility is conducting ground water monitoring or 

undergoing corrective action. However, the scope of the analysis was specifically to analyze the 

potential impacts of releases associated with CCR management. Although background 

concentrations certainly may contribute to risk when present, or can be higher than some of the 

media concentrations calculated in the CCR risk assessment, EPA generally considers only the 

incremental increase in risk associated with constituents in wastes when conducting risk 

assessments under RCRA. 
Response to Peer Review Comments Documentation and Miscellaneous Comments

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Response to Peer Review Comments

9-1 

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EPA530-R-15-002