# 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-AE81Submitted 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-09-004Responses 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 Measure d 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 Vander bilt 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 Sour ce 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 Multi ple 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 Toxicit y ................................................. . 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 ...........

................................................... ... 7-1Responses to Peer Review Comments Table of Contents

ii 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 Miscellan eous Comments ......................... 8-1 8.1. Insufficient Documentation to Reproduce the Analysi s Independently .................... 8-1 8.2. Graphical Input/Output Distributions, Truncation Va lues......................................... 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 W ild Game Consumption Rates ........... 4-4

Figure 1. Example showing convergence of Monte Carl o 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 Migratio n with Transformation Products EPRI Electric Power Research Institute

FBC Fluidized-bed combustion Fe Iron FGD Flue gas desulfurizationResponses to Peer Review Comments Table of Contents

iii 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 Mod el IRIS Integrated Risk Information System IWEM Industrial Waste Evaluation Model

K d Soil-water partition coefficient

MCL Maximum Concentration Limit MINTEQA2 Metal Speciation Equilibrium Model for Sur face and Ground Water Mn Manganese MSW Municipal solid waste

NODA Notice of Data Availability

ORCHESTRA Objects Representing Chemical Speciation and Transp ort 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 unitResponses to Peer Review Comments Table of Contents

iv [This page intentionally left blank.]Response to Peer Review Comments

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# 1. Introduction and Background

To ensure protection of human health and the enviro nment, the U.S. Environmental Protection Agency (EPA or the Agency) has completed a risk ass essment to evaluate potential risks to human health and the environment from exposure to coal co mbustion residuals (CCRs) in landfills and surface impoundments. The risk assessment, original ly entitled Human and Ecological Risk Assessment of Coal Combustion Wastes , was renamed to reflect the terminology used in EP A’s 2010 proposed regulation. Although the name has cha nged, the new document is merely a revision of the version independently peer reviewed after th e 2007 Notice of Data Availability (NODA). A peer review is a process for enhancing a scientif ic or technical work product so that the decision or position taken by the Agency based on that produ ct 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 Combus tion Wastes. This document provides responses to peer review comments received on the C CR 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 m odeling

 Dr. Charles Harvey, Massachusetts Institute of Tech nology: use of probabilistic approaches used in the analysis in the context of f ate 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 an d 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 (Docke t 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 Buildi ng, 1301 Constitution Avenue, NW, Washington, D.C. This Peer Review Response to Comme nts 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 res ponse. Please note that this document does not respond to public comments received from the 2010 p roposed 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 pr oposed rule from 2010 to present are available at www.epa.gov/solidwaste/nonhaz/industrial/special/fo ssil/ccr-rule/index.htmResponse to Peer Review Comments

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# 2. Ground Water Modeling

The peer review comments relating to modeling of th e ground water pathway are grouped into four subcategories:

 The 10,000-year maximum ground water simulation tim e

 Ground water transport modeling assumptions

 The need for more site-specific analysis and compar isons 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 limitati ons of this assumption be better explained and questioned the assumption that contaminant concentr ations in the leachate remain constant throughout the timeframe. Dr. Rowe questioned the a ssumption 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 validit y of modeling risk over a 10,000- year period. Shifting land use, geological and clim ate phenomena, and human and ecological populations will dramatically change exp osure 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 concentrat ion in the leachate data remains constant throughout the 10,000-year modelin g period is not realistic. Leaching of contaminants will likely occur in much shorter time periods and decrease after reaching a maximum. The peak contami nant 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 C CR. The remainder of the contaminant will remain insoluble and “unleachable. ” 

### Dr. Kerry Rowe, Queens University It appears to be assumed that the current hydrogeol ogic and climatic conditions will prevail over the next 10,000 years. While it is dif ficult to do otherwise, theResponse to Peer Review Comments Ground Water Modeling

2-2 implications of this assumption have not been adequ ately discussed. For example, it is assumed that well usage will correspond to th at which exists today down gradient of Subtitle D MSW [municipal solid waste] landfills (RA [Risk Assessment] pg. 2-11) however global warming may re sult in the need for much greater reliance than at present on ground water re sources; if that were to be the case then the risks may be (considerably) higher th an 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 lon g for the surficial hydrogeologic environments being considered – it is only about 10,000 years ago that glaciers retreated from much of Canada and nor thern USA. Thus the landscape that we see today is very different from that 10,00 0 years ago and we can expect it to be very different 10,000 years from now. Also th e climate is likely to change substantially over this period. Thus considerable s kepticism 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 c omposite–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 bee n updated to make it clear that the selection of a maximum 10,000-year time horizon does not mean that all mo del 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 an d 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 be yond the observed peak or maximum average concentrations, these postpeak or postmaxim um 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 consist ently pose peak risks within 100 years. Composite liners show much higher peak arrival time s, 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 sig nificantly, 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 c onsiderably less than the time to the greatest exceedance.Response to Peer Review Comments Ground Water Modeling

2-3 EPA acknowledges that the leaching profile describe d by Dr. Basta is more realistic. Empirical evidence reported in U.S. EPA (2009b) indicates tha t constituents can exhibit a leaching profile that changes over time. In the particular case of w ashout controlled constituents, the leaching profile is characterized by an initial high-concent ration 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 Transfo rmation Products (EPACMTP) requires constituent concentrations leached from the bottom of waste management units (WMUs) to remain constant for the entire duration of leaching (see S ection 3.3.5.3 of U.S. EPA, 2003b). EPA conducted a sensitivity analysis to estimate the po tential 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 fra ction was not considered because the relatively short leaching duration (compared to landfills) mak es it unlikely that the leachable fraction would be fully depleted for any constituent. For landfill s, the data collected using SW-846 Method 1313 provided an empirically derived estimate of the lea chable 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 magn itude of this error, which is discussed in Section 5 of the revised risk assessment. EPA acknowledges that future ground water use patte rns may shift as the number and location of receptors changes. However, no known data exist tha t 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 a s discussed in Section 4 and Appendix B of the revised risk assessment. Discussion of the asso ciated uncertainties has been added to Section 5

. 

## 2.2. Ground Water Transport Modeling Approach Comment Summary Comments related to the specifics of the ground wat er transport modeling were received from Dr. Basta and Dr. Harvey. Issues covered in their comme nts included the following:

 The way that aquifer soil-water partition coefficie nt (K d ) values were determined and used, including the fact that the risk assessment d id not model precipitation-dissolution processes that probably control several of the CCR chemical constituents

 The approach used to determine the value of pH in t he aquifer for selecting K d

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

2-4 The comments also addressed the general need for mo re 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 K d values used in EPACMTP to determine realistic conta minant transport at field CCR facilities. K d values for arsenic and other select contaminants s hould be determined for a set of soils with a range of soil chemical pr operties critical to chemical processes values. This could be conducted using col umn studies under controlled laboratory conditions. Modeled K d values used in the Draft must be validated by comparison to K d values derived from real soil and/or geomedia to a ssure that the EPACMTP model captures the major chemical process c ritical to transport. Realistic K d values will greatly affect the transport and risk calculation of As in ground water. K d values from soil or geomedia from CCR sites with a range of chemical properties will significantly reduce uncer tainty associated with risk from As in ground water (a risk driver) and significantl y improve the risk assessment. In general, all of the chemical processes are lumpe d into one value, K d , calculated by MINTEQA2. This is a common modeling approach, al though this grossly oversimplifies and is likely not an accurate approa ch for several CCR chemical constituents that are controlled by precipitation-d issolution processes in soil that cannot be accurately modeled using K d values. Chemical processes are mainly described through det ermination of a partitioning coefficient, K d , from nonlinear isotherms for each contaminant. Th e generation and use of an accurate K d value is absolutely critical because it controls t he amount of contaminant that is dissolved in the leachate and c apable of being transported. The contaminant is not transported if it is not dissolv ed. K d is very sensitive to adsorbents selected for inclusion in MINTEQA2. The type of sorbent varies with contaminant. In general, soil organic matter and cl ay minerals (especially Fe [iron], Al [aluminum], Mn [manganese] oxides) sorb metal ca tions and oxyanions (i.e., arsenate and arsenite). Soils vary greatly in the t ype and amount of these sorbents. The MINTEQA2 model is very limited in its ability t o model sorption. MINTEQA2’s database is limited to three sorbents: F e sorbent as the mineral goethite, Fe sorbent as hydrous ferric oxide, and o rganic matter. Fe sorbent as goethite and organic matter were selected to calcul ate nonlinear isotherms and subsequent K d values in the Draft. The choice of Fe sorbent is i mportant because goethite is a much poorer adsorbent than hydrous fe rric oxide and will result in larger leachate contaminant concentration. No expla nation for the choice of goethite over hydrous ferric oxide is provided in t he Draft. In addition to the typeResponse to Peer Review Comments Ground Water Modeling

2-5 of adsorbent, the amount of adsorbent (i.e., adsorp tion sites) will greatly affect the calculated K d value. The adsorption site density for the two sor bents is not specified in the draft. This is critical because we do not kn ow if the sorption site density represents the normal range found in soils. It is not possible to determine if the approach use d by MINTEQA2 provides K d values for the EPACMTP model that is representative of chemical processes in soils or geomedia at any of the CCR locations from inform ation presented in the Draft. Soil has many more sorbents than the two sorbents u sed in the MINTEQA2 model in the Draft. Except for organic matter content, so il 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. H owever, 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 K d inputs into transport models. It is well known that the major chemical process that affects transport of As is adsorption of As(V) or A s(III) to hydrous Fe, Al, and Mn oxide minerals. The amount of As transported will d epend on the type and amount of these minerals in soil. These mineral sorbent ph ases were not measured in the soils from CCR facility sites and most are not in t he MINTEQA2 model. Because one of the most critical chemical processes (sorpti on to oxides) affecting As transport was not used to calculate K d values for input into EPACMTP, As solubility and subsequent transport is overestimate d. Soil content of hydrous Fe, Al, and Mn oxide minerals ranges from < 0.5% for sa ndy soils to > 50% for weathered clay soils of the southeastern U.S., Hawa ii, and Puerto Rico. The overestimation of As transport in soils with modera te to high levels of hydrous Fe, Al, and Mn oxides could be orders of magnitude. However, some insight into impact of exclusion of h ydrous Fe, Al, and Mn oxides on As in leachate is provided from the Draft: “Sens itivity analysis results indicate that for most of the scenarios evaluated (over 75 p ercent), the risk assessment model was most sensitive to parameters related to ground water flow and transport: WMU infiltration rate, leachate concentration, and aqui fer hydraulic conductivity and gradient. For strongly sorbing contaminants (such a s lead and cadmium), variables related to sorption and travel time (adsorption coe fficient, depth to ground water, receptor well distance) are most important.” This s tatement implies that As is not a strongly sorbing contaminant in the EPACMTP model. Arsenic is strongly adsorbed in soil and environmental media. Arsenic i s more strongly adsorbed than those identified by EPACMTP as “strongly sorbing co ntaminants (such as lead and cadmium).” A likely reason for the poor sensitivity of the EPACMTP model for arsenic sorption is an inaccurate input K d value generated from MINTEQA2.Response to Peer Review Comments Ground Water Modeling

2-6 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 scenario s studied?” is comparing K d used for transport modeling using EPACMTP in the Dr aft with K d values for select soils from CCR facilities. K d 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 K d values used in the Draft must be validated by comparison to K d values derived from real soil and/or geomedia to assure that the EPACMTP model captures the major ch emical 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 on e 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 CC R 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; Zillme r and Fauble, 2004). To address this uncertainty (i.e., how much an arsenic III assumption might overpredict offsite well concentrations) the models were run as suming arsenic V as the arsenic species in soil and ground water. Figure 4-4 compar es the risk results for arsenic III and arsenic V. Arsenic V has lower risks than a rsenic 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 en vironmental media. Arsenic(V) which occurs as arsenate, is strongly adsorbed to c lay / oxide fractions in soil and geomedia, whereas As(III) has a much lower adsorpti on capacity. Also, As(V) is more likely to form insoluble precipitates (i.e., s corodite) than As(III). Thus, As(V) is often magnitudes less soluble than As(III). It i s 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 / environment al conditions where much lower mobility of As(V) from CCR compared to As(III) woul d result in reduced risk (much greater than a factor of 2) for As. The diffe rences 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

2-7 The results should be modeled using As(V). The K d values for As(V) and As(III) used for inputs into EPACMTP should be reported. Th e MINTEQA2 outputs used to calculate K d values should be reported also. 

### Dr. Charles Harvey, Massachusetts Institute of Techno logy Numerical modeling of reactive transport is a chall enging area of research. Constructing an accurate reactive transport model f or a single site is a very ambitious research goal, even with abundant site-sp ecific 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 a re not included. This list could contain processes that would either reduce or incre ase retardation. Geochemists who study surface reactions may criticize the choic e 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 transformat ions may criticize the lack of redox transformations, such as As(III)/As(V), and t he lack of realistic models of microbial metabolisms. All of these concerns, and m any 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 conditio ns without constraining these models with a very large data set of field measurem ents. So, does is this assessment over-reach by employing a reactive transport model? Is constructing an assessment across many sites a hope less task? Perhaps, but we know some simple constraints on the spread of conta minants. First, contamination is not transported farther than a conservative trac er. 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 dif ferent simple isotherms, and then using these isotherms to model contaminant immobili zation and retardation of transport, may be the only realistic approach to th is problem. Perhaps my biggest concern about the reactive trans port 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 t he 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 i n the plume, or out of the plume. The mixing zone may be very thin. Correctly modelin g a reacting plume is veryResponse to Peer Review Comments Ground Water Modeling

2-8 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 shou ld be clarified. With the retardation approach, not only is the residence tim e 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 stud y correctly reduced the concentration by the retardation factor, but I foun d 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 m odeling 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, precipit ation, surface complexation, and ion exchange (Meeussen, 2003). However, such modeling is not a p ractical approach for a nationwide analysis because the data collection effort necessary to pop ulate such a model on a nationwide, site-based level would be prohibitively expensive. Even assumi ng 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 necess ary to run such a model would also be impractical. Furthermore, the use of K d as a surrogate for dilution/precipitation processe s is a widely used and accepted method in both the scienti fic literature and the ground water modeling community, provided the values of K d used are appropriate to account for the range of p otential attenuation processes (U.S. EPA, 1999). Therefore, for a nationwide analysis, Dr. Harvey is correct in stating that the use of K d 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 sorben ts available for MINTEQA2 modeling. Other common hydrous oxides that can sorb chemicals inclu de hydrous oxides of aluminum, manganese, and silicon (Dzombak and Morel, 1990); however, the re were insufficient data to incorporate these sorbents. Furthermore, EPA chose goethite as the most appropr iate form of iron oxide for the risk assessment to avoid an underestimation of risk. While both goe thite 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 ofResponse to Peer Review Comments Ground Water Modeling

2-9 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 devel opment of K d values using MINTEQA2 as well as the associated uncertaint ies. Furthermore, Attachment H-1 graphically presents the full isotherms for each co nstituent modeled and Attachment H-2 displays select percentiles of the K d 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 K d values available in the MINTEQA2 isotherms used in these analyses would not be practicable. Instead, the full input and output files are availa ble to the public in the docket. Comparing to Real-World K d Values As suggested by Dr. Basta, EPA considered comparing the modeled K d values to available estimates in the published literature, but did not do so for two reasons. First, there are many individual values within each K d isotherm that depend both on constituent concentra tions and master variables, such as pH, organic carbon, and i ron oxide concentrations. Second, there is generally limited information available about the c onditions 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 unlike ly to provide a basis for definitive conclusions. Instead, EPA notes that the results of the risk ass essment are generally in agreement with damage cases, as discussed in Section 5

. Leachate-Aquifer Mixing The approach adopted in the risk assessment to dete rmine the value of pH in the aquifer (used to select K d ) and the subsequent calculation of the retardation factor assumed that, after entering the aquifer, the leachate plume would thoroughly mix wi th 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 co nceptual model used in this risk assessment of uniform subsurface flow with recharge. However, EPA CMTP requires a constant ground water pH to model transport with nonlinear sorption isoth erms. EPA assumed full mixing as a more conservative approach because, for most metals, sor ption/precipitation tends to increase (i.e., K d 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, d ecreases 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 arsen ic (V) often shows it to be orders of magnitude less soluble than arsenic (III), which appears inco nsistent with the results of the draft riskResponse to Peer Review Comments Ground Water Modeling

2-10 assessment that found similar exposure concentratio ns for both arsenic species. As a result of revisions to the risk assessment, the modeled conce ntrations of arsenic (III) and arsenic (V) are now generally an order of magnitude different, alth ough the specific results vary between pathways. A primary cause of this difference is lik ely the increased distances to receptors in the revised risk assessment. The increased distance wou ld lead to additional arsenic (V) attenuation because it generally has greater K d values, consistent with the comments provided by D r Basta.

Retardation Factor Finally, with respect to Dr. Harvey’s comment, the contaminant transport formulations in both the unsaturated and saturated modules of EPACMTP correc tly include a sorption term that represents the transfer of dissolved contaminants from the liq uid phase to the solid phase by way of a retardation factor or an isotherm describing the ch ange 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 EP ACMTP already discusses this issue, no changes were made in response to this specific comm ent.


## 2.3. Site-Specific Analysis and Comparisons with Measured Data Comment Summary Three reviewers (Dr. Basta, Dr. Harvey, and Dr. Vor hees) 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 assessm ent results. They expressed concern that the results are difficult to evaluate given the signifi cant variability and uncertainty associated with th e 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 ra nge 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 d isposal facilities. Because of the great uncertainty in the model, the model shoul d be validated on a case-by-case basis with the CCR field data to gain acceptance fo r the EPA CCR risk assessment model. Perhaps a subset of CCR facilities can be se lected for verification of the risk assessment model output. This validation of model r esults must be performed before any decisions on CCR waste management are re quired of specific CCR facilities.Response to Peer Review Comments Ground Water Modeling

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### Dr. Charles Harvey, Massachusetts Institute of Techno logy The model described in this report predicts the dis tribution of contaminant concentrations downstream of WMUs. The obvious next step is to test the model by comparing it to measurements. This is easily acc omplished by simply (2) collecting and analyzing some water samples, then t esting the hypothesis that the measured values come from the same distribution pre dicted by the model. This is the scientific method. 

### Dr. Donna Vorhees, The Science Collaborative Need for More Site-Specific Analysis. The primary c hallenge 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 sc ale of this assessment introduces complexity and uncertainty that perhaps could be reduced if EPA examined a representative subset of WMUs in more de tail to better understand the technical strengths and weaknesses of its nationwid e approach. One starting point might be those WMUs that are represented in existin g surveys of WMUs (i.e., EPRI, 1997 and [U.S.] DOE, 2006) and in EPA’s CCR c onstituent database. For example, I am aware of one site referenced in Figur e 4-5 that was the subject of a relatively recent risk assessment that was submitte d to the Massachusetts Department of Environmental Protection. Public comm entary submitted from industry and government (State of Wisconsin) repres entatives noted the availability of additional data, and these leads should be explo red 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, bu t these WMUs are not necessarily representative of all WMUs. EPA’s risk assessment embodies an enormous amount of work and creative, thoughtful mo deling. But, at a minimum, EPA needs to provide a compelling reason for not at tempting 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 measuremen ts” (page 4-32). EPA should explain why this is the case (e.g., elevated detect ion limits, not included on analyte lists at surface impoundment WMUs). Screening resul ts in Table 2-3 suggest that it would be worthwhile to resolve whether these con stituents are present and at what concentrations. 

### EPA Response EPA agrees with the reviewers that confidence in th e 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 invo lves extensive data collection and detailedResponse to Peer Review Comments Ground Water Modeling

2-12 modeling (representing site-specific conditions and processes), which was not possible with the available resources for the assessment. Instead, EP A compared the results of the national probabilistic, Monte Carlo analysis to proven and p otential damage cases from across the United States. These damage cases represent real-world ins tances 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 addi tional data with lower detection limits in the revised risk assessment, allowing EPA to conduct pr obabilistic 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 con stituents 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 contaminat ed, 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 focuse d on the assumption that the wells used in this assessment are contaminated (i.e., located wit hin the plume), even if the well location used reflects a deeper well that may be screened in an u ncontaminated aquifer; the manner in which the assessment handles uncontaminated wells, plume char acteristics, 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 a nd Dr. Vorhees commented on this assessment’s use of water well distances from MSW l andfills and EPA’s belief that these distances would be protective for CCR waste. 

### Dr. Charles Harvey, Massachusetts Institute of Techno logy

At the heart of this assessment is a Monte Carlo si mulation 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 ris ks. This approach does not attempt to calculate a probabilistic description of the num ber 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 puzz ling conceptual problems stemming from the fact that the calculated health r isks are independent of the probability that the contaminated well actually exi sts. The following exampleResponse to Peer Review Comments Ground Water Modeling

2-13 illustrates the difficulty. In comment II.B. below, I will discuss how, wherever there is a river or stream between the source and the wel l, ground water will likely discharge into the river, preventing the plume from reaching more distant wells. Consequentially, wells far from the source cannot b e 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 th e source where concentrations are higher and arrival times are quicker. Since eve ry realization of the ground water exposure pathway must generate a well position, sho rt plumes will actually have worse adverse health effects because the wells gene rated by the Monte Carlo study will be closer to the source where contamination co ncentrations are worse. Thus, a reduction in the probability of exposure does not n ecessarily reduce the probability of adverse health outcomes in this model. This prob lem also exists when defining plume width (see II.B below). It is a fundamental p roblem of the framework of this assessment that extends beyond these examples. The difficulty arises because this assessment does not attempt to characterize the num ber 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 hea lth dangers are conditioned on a well being contaminated, but that in fact many well s, 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 ove r the last decades so that it is unusual to site new wells, or to leave existing wel ls, in the flow-paths downgradient of obvious contaminant sources such as a w aste site. Because studies such as this have documented the serious health dangers of contaminated ground water, and because severe contamination has often been fou nd 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 th e risk to people drinking contaminated ground water certainly still exists, i t has receded. Again, this report would be improved by a discussion of the issue of c ontaminated wells actually being used for water supply. The report nicely integrates the few available nati onal data sets of hydrogeolgic parameters. My comments largely concern the interac tion of the choice of well position with the solute transport model. The Monte Carlo simulation places a well at random (uniformly distributed) angular offset fr om the plume center line, at aResponse to Peer Review Comments Ground Water Modeling

2-14 depth generated from a uniform distribution of dept h 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 basica lly 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. Conta minant 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 depen ds 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 de finition would exclude contamination that disperses out of this flow path. So, a better definition of the plume extent would use a minimum concentration – bu t what concentration should be used? This problem of plume definition plays directly int o the conceptual problem described above in comment I.A. If a low concentrat ion 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 ris ks 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 ris ks 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 dispe rsivity. Consequentially, the transverse dispersivity is the key aquifer paramete r for determining both the width of the plume and the dilution of contaminants. Rece nt 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 valu es of transverse dispersivity are very small, so small that is difficult to simulate solute transport accurately with many numerical techniques that attempt to model dis persion. I find no mention in the report of the values used for transverse disper sivity. This report should: (1) Give the values used in the transport simulations, (2) D escribe how this value was chosen, and (3) Describe the sensitivity of the res ults to the chosen dispersivity value. (C) Depth of the PlumeResponse to Peer Review Comments Ground Water Modeling

2-15 Vertical spreading is much like transverse spreadin g – little spreading occurs in the vertical direction. Realistic dispersivities are so small that they are difficult to include in simulation models. So, again, one wonder s what values were used, and how the simulation was performed. However, the effects of vertical spreading on conta mination of wells differs from horizontal spreading because wells are often screen ed over large vertical increments so wells often extract water that contai ns a mix of concentrations over a vertical extent of the contaminated aquifer. Well s 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 p ermeability layers. Wells are often placed in the deeper aquifer, but local conta mination is often restricted to the upper aquifer. Some of the data used to construct t he distribution of well locations may reflect wells that tap deeper aquifers that wil l remain uncontaminated by WMUs. (D) Rivers May Limit the Distance from the Source I suspect that many waste sites are near rivers bec ause power plants are often along rivers. Except in arid regions, rivers are typicall y gaining, meaning that ground water discharges into the river. Indeed the mean di stance 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 Fi gure 3-7 that plumes are constrained by the distance to surface water, although these di stances are used for the calculation of risks to fishermen and ecological ri sks. 

### Dr. Kerry Rowe, Queens University In the absence of an actual survey of water well us age around existing CCR facilities, I am not aware of a better source of da ta than that available for MSW landfills. EPA recognized this as “one of the large r uncertainties in this analysis” (RA, pg. 4-37) however the statement that “EPA beli eves that the MSW well distance distribution used is protective for CCR la ndfills 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 yea rs but no consideration appears to have been given to likelihood of increased deman d 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 importantResponse to Peer Review Comments Ground Water Modeling

2-16 for the future than it is now. It would have been g ood to have examined the implications of wells being closer than that indica ted 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 app ropriate 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 t he absence of any real measurements from WMU locations. One public comment on this dist ribution refers to its bias, which EPA describes as conservatism. I agree that s uch bias should be avoided in conducting PRA. EPA does not explain why it could n ot obtain measurements from at least a representative sample of WMUs. EPA explains that:

“...the MSW well distance distribution is a conserv ative 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 perfor m 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 drinki ng 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 obtain ing data specific to at least a representative subset of WMUs. Because everyone mus t drink water, presumably everyone served by these hypothetical wells would b e 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 outpu t 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 downgradi ent from a surface water body that intersects the ground water table, some or all of the ground w ater, 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. Howev er, a review of the input database for the draft risk assessment found that such a water body was pr esent in approximately two-thirds of the Monte Carlo runs. Furthermore, ignoring the loss of const ituent 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 r emaining 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 uncertaintie s associated with this approach discussed in Section 5

. The reviewer comments regarding placement of recept or wells “within the contaminant plume” in the Monte Carlo framework are the result of a funda mental misunderstanding about the constraints placed on ground water receptor location. Maximum l ateral 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). S ince 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 placeme nt of wells within deeper aquifers, EPA has policy of erring in the direction of protecting hum an health and environmental quality when addressing uncertainties. Consistent with this prac tice, 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. Harve y also highlighted the possibility that modeled receptor well concentrations may incorrectly repres ent actual exposures by sampling from a single aquifer depth. Wells may be screened across an exte nded depth, and may capture both contaminated and pristine ground water, depending o n 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 high lighted the need for greater transparency. The documentation for the draft risk assessment did not include comprehensive tables detailing modeling input parameters, their values or distribu tional characteristics, and the source of the data used. These values are, in many cases, publicly ava ilable in the EPACMTP Background and Parameters/Data Background documents (U.S. EPA, 200 3a,b). EPA still finds it unnecessary to duplicate this large amount of data. Instead, the r evised risk assessment includes an increased number of references to these documents, and direct s readers to refer to these documents for further information. Further discussion of the inputs and o utputs used in the risk assessment can be foundResponse to Peer Review Comments Ground Water Modeling

2-18 in Section 8.1 of this response to comments document. Additionall y, 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 t he 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 resid ents 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 i n Appendix B of the revised risk assessment.Response to Peer Review Comments

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# 3. Source Modeling

The comments relating to source modeling are divide d into 12 subcategories: 1. The use of leachate concentrations based on toxi city characteristic leaching procedure (TCLP) data and the availability of more representa tive 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 a nd leaching 7. Hydrologic Evaluation of Landfill Performance (H ELP) model infiltration rates and landfill cover assumptions

8. Scenarios where the water table is above the dis posal unit 9. The impact of increased mercury capture under fu ture air emission control regulations 10. The use of pore water data for surface impoundm ent source concentrations 11. Modeling surface impoundments only before closu re 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 hierarc hical process of choosing data from different leaching methods and the predominant use of TCLP da ta 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 presenc e of organic acids associated with municipal waste degradation, the mobility of metals can be si gnificantly impacted by the more acidic conditions and complexing organic acid molecules. B ecause organic acids are not present in CCR, leachate concentration estimates based on TCLP resu lts may differ significantly from leachate concentrations under actual CCR field conditions. T he reviewers also suggested that the availability of a new leachate study by Vanderbilt University would provide useful data.Response to Peer Review Comments Source Modeling

3-2 

### 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, ad ditional information that improves the waste leachate data set would be expec ted to significantly reduce key uncertainties. Selection of appropriate analyte dat a for landfills in the CCR constituent database (p. A-4) is a hierarchical pro cess 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 [Sy nthetic Precipitation Leaching Procedure], and (b) selection of the highest concen tration between SPLP and TCLP. The Draft recognizes the quality of the data is muc h greater for pore water than TCLP. Then, the Draft uses mostly TCLP data as inpu t. The TCLP method used to generate most of the input leachate data in the Draft is improper for determining leachate concentration fro m CCR. Improved leachate methods, designed for CCR, should be used to genera te data in the Risk Assessment. TCLP was developed to characterize waste behavior i n 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 wher e organic acids from municipal solid waste are absent and conditions are more like ly to be neutral to alkaline than acidic. TCLP is a gross extraction to classify disp osal of waste materials in either hazardous or nonhazardous landfills. TCLP was not d esigned to model specific physiochemical processes such as leachate from CCR landfills. Therefore, TCLP data should not have been used to perform risk asse ssment calculations of CCR. The following is stated in the Draft (p. 4-32) reco gnizing the limitations of the TCLP method: “The available landfill data are large ly derived from the TCLP, a laboratory test designed to estimate leachate conce ntrations in MSW landfills.” The use of TCLP data in the risk assessment is justifie d as follows: “The TCLP has been shown to both over and under pre dict leachate concentrations for other waste disposal scenarios, so the use of t he 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 fo r this analysis.” To support this contention, limited results of leac hate data from CCR material from a study conducted at Vanderbilt University (U.S. EP A, 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 repor ted in Vanderbilt (2006) [U.S. EPA, 2006b] and the Draft CCR for 5 of the 6 CCR fa cilities is used to conclude:Response to Peer Review Comments Source Modeling

3-3 “Although the Vanderbilt Study does not cover all o f the metals addressed in the CCR analysis, its general agreement with the CCR ar senic and selenium levels does help allay concerns that the TCLP CCR leachate valu es used in the analysis markedly overestimate or underestimate the concentr ation’s actual CCR leachate” (4-34). This is not a sufficient justification for use of T CLP 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 f or a specific site. For example, data present in the Draft from Vanderbilt (2006) [U.S. E PA, 2006b] for the St. Clair facility of 0.001 mg/L for As is 60 times lower tha n ca. 0.06 mg/L used in the Draft Risk Assessment (Fig. 4-5). Recently, research has improved the scientific unde rstanding of the generation of leachate from CCR, in particular for mercury, arsen ic, and selenium (USEPA, 2006[b]) and development of new CCR-specific leachi ng methods (USEPA, 2006[b]; Kosson et al., 2002) Improved leachate met hods, designed for CCR, should be used to generate data in the Risk Assessm ent. 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd State University It is widely recognized that TCLP data are not adeq uate for characterizing how coal combustion wastes will behave in a field setting. T here 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 o f Sciences [National Research Council] 2006 report (pages 143-152). Unfortunately , TCLP data may simply be the best available for the time being, but when bet ter alternatives are developed (there are ongoing, active efforts to do so) the EP A should determine whether the outcome of those tests suggest a re-evaluation of t his risk assessment. 

### Dr. Kerry Rowe, Queens University The use of landfill data largely based on TCLP is p otentially 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 p arameters used in the RA are reasonable for arsenic and or potentially unconserv ative for selenium. However it is not clear from the documentation how one can val idly 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 potent ially higher concentrations ofResponse to Peer Review Comments Source Modeling

3-4 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 R A. The use of landfill data largely based on TCLP is p otentially subject to criticism, especially for the CCR given the pH used in the TCL P test. However the report does address this concern (pgs. 4-32 to 4-34) and a t 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 leas t 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 cha nging practices at WMUs. EPA also refers to findings from its study of CCR c hemistry and leaching behavior ([U.S.] EPA 2006b). EPA explains that these data we re not included because the risk assessment was performed in 2003 (page 1-1). E PA acknowledges that inclusion of these data might result in lower risk estimates. Without reviewing them in detail, it is not possible to say whether inclus ion of these data would “significantly improve” the risk assessment, but I see no logic to excluding them. Without inclusion of data that represent more recen t 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 su pport the objectives of the risk assessment. EPA reports that it “is currently evalu ating how to best incorporate and address the results and findings of these studies i n future efforts to address CCR management practices” (page 1-1). This statement ra ises another question: how will the results of this risk assessment be used? Are th ey just interim calculations that EPA plans to supplement with future analyses that i nclude these more recent data? EPA appropriately acknowledges limitations associat ed with TCLP data and compares it to higher quality data that it collecte d 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 wit h the exclusion of TCLP data, assuming this can be done while maintaining a repre sentative dataset. 

### EPA Response For surface impoundments, only pore water and impou ndment water data were used. Therefore, this issue is not relevant for the surface impoundm ent scenario. For landfills, EPA agrees that TCLP may not be the most appropriate leachate extra ction method for all waste streams and all disposal scenarios. The draft risk assessment relie d on a hierarchy of dissolved concentration data,Response to Peer Review Comments Source Modeling

3-5 ranging from field leachate data to TCLP, to charac terize leaching from landfills. Because new data collected using the Leaching Environmental Ass essment Framework (LEAF) test methods has been made available through a series of EPA rep orts (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, specif ically:

 SW-846 Method 1313 (and its predecessor, Method SR0 2);

 SW-846 Method 1314; and

 SW-846 Method 1316 (and its predecessor, Method SR0 3). 2

The data from these three methods were used in conj unction 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 resul ts 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 use d 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 disp osal sites across the country” based on data relating to facilities that existed i n 1995 as identified in the EPRI (1997) report. However, as acknowledged in the RA a t various points (e.g. RA, §4.4.1, pg. 4-28), the proportion of lined landfill s appears to have changed significantly between the 1995 data and the subsequ ent U.S. DOE (2006) study. This does not affect the assessment of the risk ass ociated with the facilities that existed in 1995 but the data does need to be carefu lly interpreted if it is to be used to assess the risk of future facilities and for dev eloping future management options (Objective 2). For example the combination of data (“All Units Combined”) to evaluate 90th and 50th percentile risks (e.g. RA Ta bles 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 pos t 1995. On the other hand the

2 Methods SR02 and SR03 are predecessor methods to SW -846 Methods 1313 and 1316.Response to Peer Review Comments Source Modeling

3-6 separately evaluated risks for “unlined”, “clay-lin ed” and “composite-lined” units can be considered to be useful to the EPA for the d evelopment 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 acknowledg e the issues raised above in response to Question #1. As discussed in response to Question #1 (and repeat ed here for completeness), the proportion of lined landfills appears to have chang ed 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 exi sted 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 e valuate 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 n ot represent the risk associated with facilities constructed post 1995. On the other hand the separately evaluated risks for “unlined”, “clay-lined” and “composite-li ned” units can be considered to be useful to the EPA for the development of managem ent 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 developme nt of management options for future CCR facilities, it only considers the specif ic liner conditions at the specific sites where those conditions actually exist (e.g. t he 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”, “c lay-lined” and “composite-lined”) could have been obtained by examining all three lin er possibilities for all sites used in the Monte Carlo study (irrespective of what is c urrently used) thereby giving an assessment of the risk associated with the three li ning conditions over a wider range of hydrogeologic and climatic environments. While i t is unlikely that this would change the overall conclusions regarding the relati ve risk associated with the three liner conditions (unlined having the highest risk a nd clay-lined sites having a substantially higher risk than composite-lined site s; RA pgs. 4-39 to 440), it would provide a better indication of the benefits to be g ained 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 developme nt of management options for future CCR facilities, it only considers the specif ic liner conditions at the specificResponse to Peer Review Comments Source Modeling

3-7 sites where those conditions actually exist (e.g. t he 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”, “c lay-lined” and “composite-lined”) could have been obtained by examining all three lin er possibilities for all sites used in the Monte Carlo study (irrespective of what is c urrently used) thereby giving an assessment of the risk associated with the three li ning conditions over a wider range of hydrogeologic and climatic environments. While i t is unlikely that this would change the overall conclusions regarding the relati ve risk associated with the three liner conditions, it would provide a better indicat ion of the benefits to be gained by installing/mandating different liners. 

### EPA Response Since the purpose of the risk assessment was to eva luate 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 outda ted. Thus, EPA collected data from several new sources of information on both the facilities a nd 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 comment er 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 fur ther 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 a ssessment considered alternative CCR disposal scenarios. Specifically, codisposal with w astes generating more acidic conditions may significantly impact the mobility of metals. Dr. Ho pkins suggested that the risk assessment should consider CCR beneficial reuse options such as struc tural fill. 

### Dr. Kerry Rowe, Queens University However as previously indicated in response to Ques tion #2, it is not clear from the documentation how one can validly distinguish betwe en the leachate from conventional CCR and CCRs co-disposed with coal ref use if data is based on the TCLP. One would anticipate that there would be conc entrations of metals in the more acidic leachate associated with co-disposal th an in the leachate from a conventional CCR where the pH is expected to be hig her.Response to Peer Review Comments Source Modeling

3-8 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd State University Once revised, the risk assessment will be an import ant 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 con sidered in the risk assessment. While it would clearly be far beyond the scope of t his risk assessment to evaluate “beneficial uses” of coal combustion wastes on a br oad 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 mat erial, 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 do cumented damage cases (which include at least one superfund site), this draft ri sk assessment document, and the National Academy of Sciences [National Research Cou ncil] 2006 report that placement of these materials in landfills can produ ce undesirable risks if not managed properly. These risks can be mitigated by u sing appropriate safeguards such as liners. Similarly, use of these wastes as a structural fill, particularly in large monofills without safeguards, could have adverse ef fects 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 agenc ies should consider under what circumstances structural filling with coal combusti on wastes is safe, and under what circumstances it poses unacceptable risks that outw eigh any perceived benefits. 

### EPA Response Beneficial use is outside the scope of the risk ass essment, as discussed in Section 1. However, EPA points Dr. Hopkins to the Agency’s recent work bene ficial uses of CCRs, including a peerreviewed methodology for evaluating encapsulated us es (U.S. EPA, 2013b) as well as a document applying that methodology to evaluate two of the la rgest encapsulated uses (U.S. EPA, 2014b). EPA plans to develop a conceptual framework for eva luating unencapsulated CCR beneficial uses in the future. EPA is also working with the US Depa rtment of Agriculture to assess the use of flue gas desulfurization gypsum in agriculture. With regard to the evaluation of CCRs codisposed wi th 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 type s is discussed in Section 3

, Section 4 andResponse to Peer Review Comments Source Modeling

3-9 Appendix H of the revised risk assessment, while the associat ed uncertainties are discussed in Section 5 . For landfills, waste pH, which is the major drive r of variations in K d values used to distinguish waste types, was known with great accur acy 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 t hat risks reflected the prevalence of these disposa l practices. However, EPA also performed sensitivity analyses to understand the extent that the lower pH of comanaged wastes could affect risks, wh ich is discussed in Section 5 of the revised risk assessment.



## 3.4. Liner Leakage Comment Summary Dr. Rowe submitted a comment addressing the liner l eakage assumptions used in the CCR risk assessment. The composite liner leakage distributio n used in the risk assessment was based on empirical data from industrial liners compiled by T etra Tech (2001). The leakage distribution excluded Tetra Tech data from landfills with compos ite liners containing compacted clay layers. The original justification for excluding these type s 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 b ased on data for a limited number of existing industrial landfill cells (RA Pg . 3-11). Leakage can vary substantially depending on the level of constructio n quality control and construction quality assurance, the wrinkling of th e 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 geomembr ane 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 ha ve 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 super ior to clay-lined sites and that these are superior to unlined sites in terms of red ucing risk. In the past few years there has been considerable r esearch suggesting that (a) geomembranes have a finite service life and (b) lea kage through composite liners depends significantly on both the nature of the cla y component of the compositeResponse to Peer Review Comments Source Modeling

3-10 liner (CCL [compacted clay liner] or GCL) and the p resence 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 th e total area). Consideration of these factors (see response to Questions #1 above) would improve the RA and increase the calculated risk associated with compos ite-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 term s 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 rela ted to consolidation can be shown to be small. Also, composite liners with a CC L can be expected to leak much more than those with GCLs because of the poorer int erface transmissivity (many orders of magnitude higher) for CCLs. This approach adopted introduces an unconservative bias to the corresponding risk asses sment 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 underest imate 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-lin ed sites and that they are substantially superior to unlined sites in terms of reducing risk. The assumption of a clay liner hydraulic conductivi ty 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 wa ter content and density etc.), (b) construction quality control and assurance during c onstruction, 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 hy draulic conductivity of 1x10 -9 m/s was achieved at the time of covering (as any we ll-designed and constructed clay liner will) then, following loading by waste i n a landfill, consolidation will likely result in a significant reduction in hydraul ic conductivity (to say 1x10 -10 m/s or possibly as low as 5x10 -11 if there is significant applied stress). Thus I co nsider that the value of 1x10 -9 m/s used is actually conservative and likely overe stimates the risk associated with well-designed and construc ted clay-lined sites. On the other hand, public comments claim that curre nt 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 ar e assumed ...” (GeoHydro, pg.4). If CCR material is used and it does n ot 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 line r meets specification and has an aResponse to Peer Review Comments Source Modeling

3-11 constructed hydraulic conductivity of 1x10-9 m/s th en the fact that it may only be 2-feet thick (as opposed to the 3-feet assumed) wil l likely be off-set by the decrease in hydraulic conductivity due to consolidation unde r the weight of the CCR and the predicted risk is still likely to range between rea sonable and conservative (i.e. erring on the high side for clay-lined sites). As previously noted above, the leakage calculated a s 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 r educe the risks associated with CCR disposal compared to unlined and clay-lined sit es and this refinement will not change the general conclusions of the RA. ... as discussed in response to earlier questions abo ve, while variability was considered with respect to WMU characteristics, the re does not appear to have been adequate consideration of uncertainty associated wi th composite-lined sites. 

### EPA Response The composite liner leakage rates used for this ris k assessment correspond to leakage rates developed for the peer-reviewed Industrial Waste Ma nagement Evaluation Model (IWEM) (U.S. EPA, 2002b). The exclusion of data from composite l iners 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 w eight 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 ra tes versus leakage, EPA excluded data on composite liners constructed with clay from the est imated distribution of composite liner leakage rates. Although there is clear literature support f or 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 prot ective. With respect to the evaluation of liners constructe d with compacted CCRs, EPA treated these WMUs as unlined. The approach of assigning liner ty pes is discussed in Appendix A of the revised risk assessment, while a discussion of the uncertai nties associated with liner assignment, as well as clay liner thickness and conductivity, has also been added to Section 5

.Response to Peer Review Comments Source Modeling

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## 3.5. Treatment of Nondetect Values Comment Summary Dr. Basta and Dr. Rowe provided comments on the tre atment of nondetect values in the CCR risk assessment. Dr. Basta’s comments focused on the ass essment’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 wer e frequently not detected but drive exposure pathways. Dr. Rowe suggested that the analysis coul d use the mercury concentration distribution (as shown in Figure 4-6 in the 2007 CCR risk assess ment document) to assess the risks while acknowledging the shortcomings (the likely overly c onservative nature) of such an analysis. 

### Dr. Nicholas Basta, Ohio State University The “Calculation of average constituent concentrati ons by site for landfill leachate, surface impoundment pore water, and total ash conce ntrations” (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 a sh) were treated as separate “sites” and were averaged independently. This appro ach is consistent with that used in the 1998 CCR risk analysis. A large number of CC R samples report “below detection limit” values. As in 1998, nondetects wer e averaged at one-half the reported detection limit.” However, a large number of CCR samples reported “be low detection limits” for many samples and elements. Two critical elements, A s and Hg [mercury], had an excessive number of “nondetects” reported. Therefor e, there is great uncertainty in the input data for the risk assessment of these ele ments. This is critical because As drives the Human Health drinking water exposure pat hway standard, and it is very possible that Hg would have driven the Ecological R isk exposure pathway. The analytical laboratory instrumental detection limits are not reported. Cursory inspection of the data in Appendix A-2 suggests imp roved analytical methods should have been used to achieve lower detection le vels that would have decreased or eliminated the large number of nondetects. Analy tical methods that achieve lower detection limits can have an impact on the ri sk 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 ana lytical methods can achieve detection limits of < 0.001 mg/L for As. These meth ods 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 nondetect s, as observed for mercury, poses a considerable challenge for a risk assessmen t. The use of half the detectionResponse to Peer Review Comments Source Modeling

3-13 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 ign oring mercury would have been to do analyses with their concentration distributio n (as shown on Fig. 4-6) and assess the risks while acknowledging the shortcomin gs (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 ris ks were significantly above criteria then this would highlight the need for mor e study of this issue. 

### EPA Response

Additional constituent data measured with lower det ection limits have been made available to EPA since completion of the draft risk assessment. Howe ver, 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 r ationale for this approach is provided in Section 3 of the revised risk assessment. Much of the pre-201 0 mercury data has high detection limits resulting in a large proportion of nondetects. In t his instance, EPA relied only on the newer data made available to the Agency since the 2010 risk as sessment, 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 i n Section 5

. 

## 3.6. Effect of Waste Compaction Comment Summary Dr. Hopkins suggests considering how waste compacti on would reduce water infiltration. He feels that this would be a useful comparison with the cur rent assessment. 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd State University 5) Consideration of how compaction of wastes in the landfill would reduce water infiltration. The report does a good job of demonst rating the importance of liners in preventing undesirable migration of constituents from the site. However, compaction technologies reduce water penetration th rough the materials, rendering them less likely to produce leachate. If the data a re available, this would be a useful comparison (similar to the lined vs. unlined compar ison) to demonstrate how compaction reduces risks by reducing leachate produ ction. 

### EPA Response EPA acknowledges that the landfill source model doe s not consider the compaction of CCR waste that may occur over time as a result of anthropogen ic activities, gravity, or infiltrating water. A discussion of this uncertainty has been added to Section 5 of the revised risk assessment.Response to Peer Review Comments Source Modeling

3-14 

## 3.7. HELP Infiltration Rates/Cover Assumptions Comment Summary Dr. Rowe questioned the use of the HELP model in li ght 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 limi tations of this model, and the potential implications of its use, have not been ad equately addressed in the document. Any assessment of infiltration through a landfill c over 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 hydrau lic conductivity of a compacted clay liner in a cover is likely to increase by orde rs 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 excha nge with the adjacent “soils” and desiccation. It is not clear that either of the se issues were considered. 

### EPA Response EPA has adopted the use of the HELP model, which wa s subject to both peer and administrative review, as the source of unlined and clay-lined inf iltration rates for landfill for nearly two decades

. EPA acknowledges that there are limitations in usin g 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 c ap will decrease over time, EPA acknowledges that unlined and clay-lined infiltration rates calc ulated by HELP may be underestimated; however, the degree of that underestimate is unknown. Discus sion 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 bet ween the fact that the assessment modeled only disposal sites above the water table and the s tatement in the report that many CCR disposal sites are constructed within the saturated zone. Th e commenter did acknowledge that modeling disposal sites below the water table would only str engthen the assessment’s conclusion rather than change it.Response to Peer Review Comments Source Modeling

3-15 

### 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 wi th 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 landfil l to below that outside the landfill (hydraulic containment), then the risk of these sit es 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 exce ed the risk criteria, this would only serve to emphasize that point and would not ch ange the general conclusions. 

### EPA Response EPA acknowledges that EPACMTP is not designed to ha ndle the scenario where the water table is above the bottom of the WMU, and has added a dis cussion 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 impoundmen ts 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 point ed 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 a nd 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 ris k 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 indust ry 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 amoun t of Hg that will be captured in the future and introduced into the solid waste stre am should be predictable. Based on these predictions, I recommend that these risk a ssessment models be run based on current as well as projected waste composition ( by manipulating HgResponse to Peer Review Comments Source Modeling

3-16 concentrations in the models). This will be invalua ble for addressing management of coal combustion wastes when Hg concentrations in crease in the near future. 

### Dr. Kerry Rowe, Queens University If more work were to be done today there is at leas t 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 co ncentrations reported below detection limits is reasonable, particularly given its acknowledgement that more work is needed to resolve questions about mercury b ecause of its tendency to bioaccumulate in fish and because mercury concentra tions in CCR might increase as flue gas mercury controls are installed on coal- fired power plants. EPA indicates that mercury concentration and leachability from CC R can vary as a function of flue gas controls and that “additional work is unde rway 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 dis pose of CCR? 

### EPA Response The risk assessment was designed to evaluate the ri sks 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 b ehavior of CCR wastes. However, it has been shown that newer mercury pollution control technolo gies 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 fro m underlying sediments. The pore water concentrations are likely lower than concentrations in the bulk surface impoundment water, because they reflect any attenuation between the su rface 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 ob tained 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 recogniz ed. It should be recognized thatResponse to Peer Review Comments Source Modeling

3-17 the pore water squeeze chemistry may have been impa cted by geochemical reactions (e.g. precipitation, sorption) during mig ration 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 m ineralogy 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 mechan ism 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 ab ove which the sample was taken would lead to a potential underestimate of impact. 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd State University The quantity of data is not sufficient. Surface wat er concentrations need to be considered 1) within the impoundments and 2) downst ream from impoundments (i.e., direct surface water contamination, independ ent of subsurface flow). For surface impoundments, pore water data seem appr opriate for estimating subsurface risks, but not for the two most importan t exposure pathways (direct exposure in surface impoundments and downstream fro m surface impoundments). To complete these analyses, a minimum of two other types of information are required. First, actual concentrations of trace ele ments in coal combustion wastes are needed to assess risk to animals (deer, dabblin g 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 assessme nt highly feasible. Second, surface water concentrations in the impoundments th emselves should be used to assess risks to animals that drink water from impou ndments (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 app lied to represent a range of sitespecific scenarios. In addition to calculating resu ltant concentrations after dilution, continual loading and deposition need to be conside red in downstream habitats based on the duration of site operation and dischar ge. 

### 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 sa mples. Therefore, no changes were made in response to these comments.Response to Peer Review Comments Source Modeling

3-18 The use of whole waste and impoundment water concen trations 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 impoundme nt wastes are left in place at the time of closure, so that the waste behaves more as a landfi ll than a surface impoundment. The risk assessment considered releases from surface impound ments only during active operation. 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd State University Consideration of how surface impoundments are actua lly 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 t he slurry pumping ceases, which is in direct contrast to the assumptions of the cur rent risk assessment model. Instead, the type of risk transitions from that modeled in t he 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 impound ments will clean closed. However, the majority of ponds are believed to be continually dredged bas ed on the 2009/2010 EPA surveys. Because these facilities have other units (whether onsite o r offsite) established for disposition, it likely t hat the majority of waste in the dredged impoundments w ould 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 impoundm ents 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 postclo sure phase of surface impoundments. The uncertainties resulting from this decision are disc ussed in Section 5 of the revised risk assessment.



## 3.12. Modeling Landfills Only After Closure Comment Summary Dr. Hopkins suggested that risk from operating land fills should have been considered, because the greatest risks may occur during site operations whe n the waste products are directly exposed to wind and rain. 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd 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 areResponse 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 ri sk. 

### EPA Response

The landfill source model used in this risk assessm ent 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 leach ing. 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.Response to Peer Review Comments Source Modeling

3-20 [This page intentionally left blank.]Response to Peer Review Comments

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# 4. Exposure Scenarios

The peer review comments relating to exposure scena rios are grouped into five subcategories: 1. Direct surface impoundment exposure 2. Indirect exposure through game species (e.g., de er, waterfowl) 3. Exposure to surface impoundment effluent 4. Exposure during landfill operation (before closu re) 5. Elimination of pathways during screening analysi s. 

## 4.1. Direct Surface Impoundment Exposure Comment Summary Dr. Hopkins pointed out that the risk assessment do es 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, an d 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 a nd State University The National Academy of Sciences concluded that coa l combustion wastes pose the greatest risk to humans and the environment whe n they contact water in the disposal environment. Thus, by definition, surface impoundments should pose greater risks than most landfills because the use o f surface impoundments requires that the wastes be mixed with water before being pu mped into the impoundments. Overall, the findings of the risk assessment are co nsistent with this. That is, risks are higher for surface impoundments than for landfi lls. However, the risk assessment grossly underestimates risks from surfac e impoundments to humans and the environment because it fails to consider th e two most important exposure pathways for invertebrates, fish, wildlife, and hum ans. For surface impoundments, the risk assessment only recognizes leaching as a r elease mechanism and 1) ground water-to-drinking water and 2) ground water-to-surf ace water as exposure pathways. This is incorrect. While leaching into gr ound water is clearly a concern at these sites, the predominant exposure pathways r elate to 3) direct exposure to the slurried wastes in the impoundments and to 4) direc t exposure to the effluent from the impoundments discharged offsite. I highlight th e problems with overlooking these routes of exposure below. Direct Exposure Onsite. Plants and animals can expe rience 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 ad jacent areas for a variety of purposes, including foraging, drinking water, and r eproduction. Examples include game (e.g., deer, migratory waterfowl, and raccoons ) and non-game species (migratory passerine birds, wading birds, amphibian s, and reptiles). For these animals, exposure to trace elements in coal combust ion 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 i nhabitants or ingesting plants growing in or around the impoundment, and/or D) Transdermal exposure. Drinking water is a widespread mechanism of exposur e and is a significant risk to most taxonomic groups since the impoundments can co ntain 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 impou ndments, perhaps most notably, dabbling ducks (e.g., mallards, teal, pint ails, etc.) and larval amphibians (i.e., frogs and toads). Aquatic plants and algae o ften 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. Transderm al 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 prob lematic for species with highly permeable skin (e.g., amphibians). From an ecological perspective, all of the groups o f organisms mentioned above are important. It is possible that such sites act a s 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 repr oductive purposes. In other cases, animals that drink or forage at the sites ca n transport accumulated pollutants to adjacent habitats where their body burden become s a bioavailable exposure risk to their predators. 

### EPA Response Direct exposure of ecological receptors to CCR surf ace impoundment wastewater in the impoundments themselves is evaluated during the scr eening-level modeling (described in Section 3 of the revised risk assessment). With respect to di rect 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 assessm ent does not consider potential indirect exposure to humans through game species that may ha ve been exposed to surface impoundment waste (e.g., deer drinking surface impoundment wate r). 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd State University From a human health perspective, game species are p articularly concerning. For example, a study on landfilled coal combustion wast es 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 i mpoundments, 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 locate d along their migratory range) could remain on site for considerable periods of ti me. When these waterfowl leave the impoundment, they become a route of exposure fo r hunters in other (perhaps distant) localities. EPA should consider this important mechanism of exp osure 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 specie s used the site (e.g., eating plant material growing in the wastes, burrowing in the wa stes, nesting in the wastes), it would not be acceptable. Minimum cover standards ar e in place to prevent such ecological problems. Paradoxically, surface impound ments can actually attract wildlife and promote exposure to high concentration s of trace elements in bioavailable forms. These exposure scenarios are no t considered in the current draft risk assessment and as a result, the assessment gro ssly 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 scre ening 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 cont aminated soil may pose risks to human health for thallium. Although EPA did not collect b iotransfer factors for deer, the followingResponse 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 spec ies are consistently orders of magnitude below the consumption rates of beef and dairy. Finally, b eef and dairy cattle are assumed to get 100% of their diet from contaminated soil, forage, silage a nd 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 exclusio n 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 doe s not consider potential exposure to surface impoundment effluent even though many CCR waste man agement systems continuously release wastewater into downstream habitats. Such exposure could be direct for animals living downstream (e.g., fish) or indirect (e.g., humans c atching fish downstream). 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd State University Direct Exposure Offsite. Plants and animals can exp erience direct exposure to coal combustion wastes downstream from surface impoundme nts. Depending on how the site is engineered, surface water in impoundmen ts 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 ex tirpated. 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 disc harge permit standards, continual loading of trace elements to downstream habitats is a significant concern for human health and the environment. In addition, if not man aged properly, rain events can result in resuspension of coal combustion wastes an d the direct discharge of suspended particulates into downstream habitats. Th ese problems can be further exacerbated in large rivers that receive discharge from surface impoundments atResponse 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 disch arge 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 importa nt 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 s tudied, 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, discharg e of trace elements from impoundments to rivers can result in artificial sel ection 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 relea se contaminated surface waters into downstream habitats, direct discharge i s an important release mechanism that must be considered in EPA’s risk ass essment process. For humans, the most likely exposure pathway will be ingestion of fish or other commonly eaten vertebrates (e.g., turtles, ducks, or muskrats) tha t inhabit downstream sites. However, recreational use of impacted streams and r ivers could also result in significant contact with water and sediments, creat ing multiple exposure pathways. For fish and wildlife, particular attention should be devoted to species that utilize areas that favor deposition of trace elements and f ine 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 asses sment. Direct exposure in surface impoundments and downstream from surface impoundmen ts represents the greatest risk pathway for humans and the environment, yet th ey are not considered in the assessment. In other words, subsurface flow predict ed based on physical and chemical processes only represents a small portion of the total risks posed by these waste management units. Direct surface transport fr om 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 wate rs because they are regulated as permitted point source discharges under the Clean Water Act b y EPA’s Office of Water. Therefore, this pathway is outside the scope of the proposed rule a nd this risk assessment, so the revised riskResponse 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 suppor t of final effluent limitation guidelines due to be released i n September of 2015.



## 4.4. Exposure during Landfill Operation (Before Closure) Comment Summary Dr. Hopkins pointed out that the risk assessment co nsidered landfill conditions only after closure. This approach excludes potential pathways such as e xposure to airborne contaminants associated with dry handled waste and direct ingestion of wast e by wildlife. 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd 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 impoundme nts (see comments [Major Criticism] above regarding exposure to contaminants in surface impoundments and in downstream sites). 2) Consideration of the inhalation pathway for huma n health risks in a landfill setting. This is a significant problem when the was tes are being predominately dry handled, and can be remedied by adding modest amoun ts of moisture to the wastes and by limiting the amount of the materials that ar e exposed to air over the protracted life of an open landfill. Failure to con trol airborne transport of the wastes during site operations will result in increased ris ks for workers and residents in the areas adjacent to transport routes and landfills. A lthough this concern was raised repeatedly to the National Academy of Sciences by c oncerned citizens who could provide concrete evidence of airborne transport (e. g., thin layers of ash covering their cars, homes, etc.), the committee did not eva luate 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 (es pecially surface impoundments) are active. Because these sites can b e active for decades and this period may represent the greatest exposure risk to wildlife (especially in surface impoundments), the current distributions grossly un derestimate 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 landf ill closes. In reality, the greatestResponse 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 ser ious 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 land fill model used in the CCR risk assessment does not hand le variable infiltration rates required to model leaching during landfill operation. With respect to fugitive dust, EPA acknowledges tha t the draft risk assessment did not fully evaluate the inhalation pathway. To correct this de ficiency, 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 impoun dments 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 scr eening 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 scre ening analysis in which it determined the subset of exposure pathways and CCR constituents that would undergo full-scale evaluation in the risk assessmen t. Figure ES-1 summarizes results of the exposure pathway screening, and Tabl e 2-3 summarizes results of the CCR constituent screening. No discussion is provide d 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 d ermal contact with drinking water, e.g., during showering? EPA provides guidanc e 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 be en made available in the docket at www.regulations.gov (Document #: EPA-HQ-RCRA-2006-0796-0470). Furtherm ore, to increaseResponse to Peer Review Comments Source Modeling

4-8 transparency, the revised risk assessment now inclu des a detailed presentation of the screening assessment in Section 3, which describes the methodology used to eliminate exposur e media and pathways from the full-scale risk assessment modeli ng.Response to Peer Review Comments

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# 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 mu ltiple 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 interactio n of people consuming both contaminated fish and drinking water from the same waterbody source w as considered and where this was documented. Dr. Vorhees questioned why a cumulative risk evalua tion was not attempted for simultaneous exposure to CCR constituents. Specifically, she sug gests that potential cumulative exposures of concern could be identified by a review of EPA’s ex isting data related to relative proportion of CCR constituents at WMU locations combined with pre dictions of CCR constituent concentrations in drinking and surface water near WMU locations. A dditionally, she noted that cumulative risk needs to be reported from the perspective of the re ceptor and that cumulative exposure should be considered for all 21 constituents with risks excee ding chosen benchmark values. Dr. Hopkins noted that it is not appropriate to tre at each constituent separately because they exist in a mixture in the waste stream and some constitue nts are known to interact. He suggests that this at least be addressed by modeling additivity, altho ugh this would underestimate synergistic interactions. Additionally, he notes that multiple exposure routes should be considered, with the most likely combinations used for the risk assessme nt.Response to Peer Review Comments Human Exposure and Toxicity

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### Dr. Kerry Rowe, Queens University The study considered people consuming fish from the water body and drinking water from ground water (without considering intera ction). It is not clear why the potential for people both consuming fish and drinki ng water from the water body was not considered. This would seem entirely possib le especially if people had a residence/cottage adjacent to the water body. Was t his possibility examined and if so where is the documentation? 

### Dr. Donna Vorhees, The Science Collaborative

Cumulative risk refers to the combined risk from ex posure 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 2 007), so it is puzzling that EPA provides no reason for why it did not attempt a cum ulative risk evaluation except to say that such an evaluation is difficult. In Superfund risk assessments, cumulative risk is o ften addressed by summing HQs [hazard quotients] across constituents and if the s um is greater than 1, examining the underlying assumption of additivity more closel y. 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 r eflect 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 th e 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 consti tuents at individual WMU locations and predictions of CCR constituent concen trations 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 i ts evaluation of cumulative risk, it is important that EPA report findings from the p erspective of the receptor: what combination of CCR constituents will he or she be e xposed to within a timeframe where they might collectively cause harm? This appr oach is particularly important given the 10,000 year modeling timeframe – for both the assessment of individual chemical risk and cumulative risk. Also, in reachin g a decision about cumulative risk, EPA should consider cumulative exposure to al l 21 constituents associated with risks that exceed selected benchmarks, not jus t the 12 that underwent full-scale analysis. 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd 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 eachResponse to Peer Review Comments Human Exposure and Toxicity

5-3 constituent separately from one another. Some of th e elements in coal combustion wastes are known to interact with one another, whic h could lead to a very different outcome in the risk models. The risk assessment doc ument acknowledges this shortfall, but it should be corrected in the next d raft. At the very least, additivity (which is an underestimate because it does not cons ider synergistic interactions) should be modeled. Consideration of multiple exposure routes. Human an d 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 assessmen t. 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 ex ample, the risk assessment only considers single exposure pathways. Yet in reality, multiple exposure pathways are important for both humans and wildlife. In many cas es the analytical results are in place for individual scenarios, but the outcomes ma y 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 consider ed potential risks to human health from individual constituents and individual pathways. Al though it is possible that an individual could be exposed to risks from drinking contaminated grou nd water, as well as eating contaminated fish from a local surface water body, EPA does not belie ve that this overlap is likely to occur in significant numbers in the real world due to, for e xample, the average distance anglers travel to fish. A full list of the reasons EPA did not evalua te 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 t o be exposed to multiple constituents through a single pathway. This is a more likely scenario beca use, as demonstrated by the available data, CCRs may leach multiple inorganic constituents. Whe re exposure to multiple constituents is likely to occur, EPA policy is to assume that the risks re sulting from these exposures are additive (U.S. EPA, 2000a). However, the current risk assessment d id 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 cumul ative risk is a source of uncertainty that may result in an underestimation of risks for certain i ndividuals. However, because the risks forResponse to Peer Review Comments Human Exposure and Toxicity

5-4 individual constituents were found to be above leve ls of concern, the magnitude of the uncertainty introduced into the final conclusions of the risk a ssessment is likely to be small. 

## 5.2. Toxicity Values Comment Summary Dr. Vorhees corrected several toxicity values and s uggested the use of the Integrated Exposure Uptake Biokinetic (IEUBK) model for calculating ris ks to human health from lead. Additionally, she noted that EPA should include a discussion of t he 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 Va lue] RfD [reference dose] for aluminum is 1 mg/kg-d, not 2 mg/kg-d (PPRTV). 2. The IRIS [Integrated Risk Information System] Rf D 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 f or cobalt: a. Unit Risk of 2.8E-3 ( μ g/m 3 ) -1 b. Data insufficient to derive an oral Cancer Slop e Factor c. Reference Dose of 0.02 mg/kg-d (EPA reports thi s value in the risk assessment) d. Reference Concentration of 2E-5 mg/m 3 For some reason, EPA does not provide PPRTV documen tation 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 assess ment 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 su ch 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 l east discuss uncertainty associated with chemical toxicity values in the ris k assessment to facilitate interpretation of risk results.Response to Peer Review Comments Human Exposure and Toxicity

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### EPA Response

Human health benchmarks were chosen based on the Of fice 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 c ontaminant level (MCL) to estimate risks from drinking water exposure in the draft risk asse ssment. In the revised risk assessment, EPA continued to rely on the MCL, but also used the IEU BK model for comparison in a sensitivity analysis described in Section 5 of the revised risk assessment. With respect to PPRTVs, documentation is now availa ble online at hhpprtv.ornl.gov/

. 

## 5.3. Target Cancer Risk Comment Summary Dr. Vorhees questioned why EPA chose a target cance r 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 war rants 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 wit h 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 a nd 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 r easonable maximum exposure (RME) scenario. Specifically, she noted that this does not represen t the entire exposure distribution. She suggests that EPA clearly define the exposed population of i nterest in the evaluation based upon the requirements of applicable laws and regulations. Ad ditionally, she notes that the use of exposure data and distributions relevant to the population o f interest needs to be demonstrated. 

### Dr. Donna Vorhees, The Science Collaborative EPA reports that:

“the recreational fisher scenario was used to estim ate risks to recreational fishers (and their children) who live near the CCR landfill s and surface impoundments and catch and consume fish from a waterbody located adj acent to the [WMU] buffer” (page 2-12).

EPA selected the recreational fisher because: “they represent the reasonable maximum exposed indi viduals 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 evaluat e 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 p opulation that should be the subject of an exposure evaluation presumably is dic tated by requirements of the applicable laws and regulations, so I do not attemp t to define this population. However, EPA must clearly do so. Is this population everyone who lives near WMUs or just recreational fishers and their familie s 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 popula tion of interest and demonstrate that it is using exposure data and dist ributions relevant to that exposed population (see related commentary under EPA Condit ion #5 and Charge Question #4). 

### EPA Response EPA acknowledges that the recreational fisher scena rio 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 polic y statesResponse to Peer Review Comments Human Exposure and Toxicity

5-7 that decision-makers should be given a range of ris k 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 regulati ons under RCRA, EPA traditionally assesses potential risks resulting from an RME scenario in o rder 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 recreationa l fishers living near CCR WMUs and whether or not they are consuming fish from CCR-contaminate d waterbodies. EPA believes that the RME assumption is a reasonable and protective alternati ve given this data gap. 

## 5.5. Exposure Factor Assumptions Comment Summary Dr. Vorhees questioned the use of data from the 199 7 Exposure Factors Handbook in the development of intake rate distributions for variou s exposures, because more current data are available. Additionally, she questioned why the var iability of fish consumption rates was not considered and suggests that EPA determine rates fr om the bodies of water affected by WMUs. Minimally, she suggests that more current fish cons umption 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 d ata from its three-volume Exposure Factors Handbook (1997a-c) to develop many exposure input distributions. EPA asserts that this handbook “prov ides 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 i ncorporate new data available since 1997” ( cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=12464 ). Fish Consumption Rate. To truly describe the variab ility 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 abo ve, studies have been conducted and published in the scientific literatur e since publication of the Exposure Factors Handbook. Moya (2004) reviews thes e 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 tha t 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 cour se, the fish consumption rate distribution first must be included in EPA’s sensit ivity analyses).Response to Peer Review Comments Human Exposure and Toxicity

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### EPA Response EPA agrees that newer exposure factor data are avai lable in the 2008 Child-Specific Exposure Factors Handbook

(U.S. EPA, 2008a). The 2008 data, in addition to t he 1997 EFH data used in the draft risk assessment, were used to as the prim ary 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 n ot available for use in this analysis. Instead, fish consumption rates were drawn from a study of M aine anglers that fished from streams, rivers, and ponds. Additionally, data were available only f or 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 iss ues do introduce uncertainty into the analysis, which is discussed i n 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 exposu re assessment does not address infant exposure to tap water. She noted that tap water con sumption rates are available for infants. Also, because infants are less likely to consume recreati onally caught fish, they should be excluded from the evaluation of this exposure pathway. Dr. Vorhee s suggests that data are available for tap water consumption rates among children that are more rece nt than the 1997 Exposure Factors Handbook

, and because the newer data set contains more data f or 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 suggest s that the child fish consumption rates are unnecessarily conservative and other rates should b e considered. Additionally she thought it would be useful to include a summary of the more recent l iterature since the 1997 Exposure Factors Handbook . Dr. Vorhees questions why the maximum value for c hild exposure duration is 50 years and suggested that an explanation of how the age di stributions 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 hig her intake to body weight ratios. The exposure assessment includes four age groups fo r 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 r egarding the evaluation of exposure during childhood (e.g., EPA 2006a, EPA 200 5a), and infant exposure toResponse to Peer Review Comments Human Exposure and Toxicity

5-9 tap water is not examined. Tap water consumption ra tes for infants are summarized by EPA (2006a) and discussed under EPA Condition #5 . Infants are less likely to consume recreationally caught fish; therefore, it i s reasonable to exclude this age range from the evaluation of the fish consumption p athway. EPA’s external review draft of its Child-Specific E xposure Factors Handbook (EPA 2006a) includes some more recent data that are relevant to the evaluation of the drinking water pathway. It summarizes data on t ap water intake among children ([U.S.] EPA 2004[a]) that were collected more recen tly 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 Foo d Intakes by Individuals, conducted by the United States Department of Agricu lture. In addition to being more recent than the data set in the exposure facto r 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. Includin g an infant will likely have minimal effect on risk calculations, but exposure d uring this life stage should be acknowledged in the risk assessment. EPA assumed that the child fish consumption rate wa s the same as the adult fish consumption rate. This assumption is unnecessarily conservative for many but not necessarily all U.S. subpopulations. EPA should con sider reducing the fish consumption rate for a child, using the ratio of ad ult 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. P repared by the University of Michigan, School of Natural Resources for the Michi gan Department of Natural Resources, Ann Arbor, MI. Technical Report No. 6; M ay 1993. It would also be useful to include a summary of rec ent 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 the se 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 appr opriate at some sites, depending on the size and productivity of water bodies near W MUs. 

### 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 in clude evaluation of infants drinking formulaResponse to Peer Review Comments Human Exposure and Toxicity

5-10 made with contaminated water. Since Dr. Vorhees is correct that exposure factors such as body weight are correlated to the receptor’s age, EPA us ed separate exposure factor distributions for each age cohort. A discussion of the exposure facto rs is available in Section 2 and Appendix D of the revised risk assessment, and the uncertainti es associated with their use is discussed in Section 5

. With respect to the aging of receptors, EPA has add ed 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 d iscussed 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 fo r correlations among inputs to the EPACMTP model. There is no discussion of cor relations among other input distributions, such as fish consumption rate and bo dy weight or among age-specific distributions for multiple child age groups that ar e analyzed in a single Monte Carlo simulation. Only one constituent was modeled at a t ime; therefore, EPA does not need to consider correlations among CCR constituent concentrations in drinking water or fish. Also, with the exclusion of the derm al exposure pathway, EPA does not need to consider the correlation between body s urface area and body weight. 

### EPA Response Although exposure factors were selected for specifi c 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 selecte d from its age group–based distribution independently. This introduces some uncertainty int o the evaluation because some combinations of exposure factors, such as a high fish consumptio n 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 uncertaint y 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 exp osure 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 cons tituents and/or pathways. For example, amphibians may be subject to both dermal and ingest ion exposure. 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd State University Ecological scenarios can be even more complex and c onsideration needs to be given to the full lifecycle of receptors in the ana lysis. Take for example amphibians that use surface impoundments for reproductive purp oses. Adults can be exposed transdermally because most of the water they acquir e crosses the skin (they don’t typically drink). Concomitantly, they can be expose d trophically because the invertebrates they ingest accumulate trace elements from the site. Their eggs are deposited in the water, where developing embryos ar e directly exposed to dissolved concentrations in the impoundment. Larvae that succ essfully hatch from these eggs are then exposed to not only the water, but also th e contaminated plant material and coal combustion wastes that they ingest directly. 

### EPA Response EPA acknowledges that cumulative effects can be imp ortant for ecological receptors. However, just as EPA did not consider cumulative human healt h risks from exposures to ground water (discussed in Section 6.1 of this document), they were not modeled for ecolo gical receptors. In Section 4 of the revised risk assessment, risks for all cons tituents 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 acknowl edges that ecological risk could be underestimated to some degree for surface water exp osures. However, these uncertainties are unlikely to affect the principal findings of the ri sk assessment. In addition, EPA also notes that allResponse to Peer Review Comments Ecological Exposure and Toxicity

6-2 surface water risks are orders of magnitude lower t han the risks resulting from direct discharges modeled in U.S. EPA (2013). In contrast to the surface water and sediment expos ures, ecological risks for individual constituents were appreciably above risk criteria for direct exp osure to impoundment wastewater. As a result, it is clear that CCR disposal in surface impoundmen ts 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 deal t with on a site-specific basis. Dr. Hopkins requested additional discussion of this issue, incl uding “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 a nd State University The only other major comment I have relates to the exclusion of sensitive habitats and sensitive species from the analysis. This is li sted as an uncertainty that will need to be dealt with on site-specific basis. I agr ee 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-specif ic basis? What specific steps should be taken to determine what habitats and spec ies deserve special consideration (besides the obvious threatened and e ndangered species)? 

### EPA Response

EPA did not evaluate sensitive habitats and sensiti ve/endangered ecological receptors because the presence of such habitats and receptors is inherent ly a site-specific issue, and data on potential impacts are often not available and can be difficul t to ascertain, even on a site-specific basis. Although these classes of receptors and potential e cological hazards are not explicitly considered in the analysis, conditions represented by simulati ons 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 s ituations with such sensitive species or habitats. EPA acknowledges that the inability to qu antitatively 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 indir ect effects from the risk assessment underestimates risk. He requested at a minimum disc ussion of indirect effects as a major uncertainty. Dr. Harvey requested additional discus sion of “how ecosystems can be adversely affected by discharges of solutes in unexpected way s” and how this issue is uncertain due to insufficient scientific understanding. 

### Dr. William Hopkins, Virginia Polytechnic Institute a nd State University

Consideration of indirect effects of toxic constitu ents 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., direc t 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 resourc es, alteration of predator-prey interactions, and modified host-pathogen interactio ns. It is well known that the indirect effects of contaminants can be just as imp ortant, and in some cases more important, than direct effects. This has been demon strated 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 c ombustion wastes that could have broad, indirect effects on other community con stituents (e.g., Reviewed in National Academy of Sciences [National Resources Co uncil] 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 Techno logy I recognize that the hazard quotient approach may b e 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 way s. The state of the science is simply not sufficient to predict how different spec ies, let alone ecosystems, will respond to an input of a mixture of solutes. Many e xamples exist of how aquatic environments are impacted in surprising ways by shi fts 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 benchma rks used in the risk assessment may have been overly conservative and that many are at or be low background soil concentrations, mentioning lead in particular (specifically, that t he 95th percentile of the natural background of lead in soils in the United States is 38.8 mg/kg [S mith et al., 2005], higher than the value of 28 mg/kg used in the risk assessment). He suggested EP A Ecological Soil Screening levels (EcoSSLs) as an alternative. In the example of lead, th e 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 so il concentrations. Ecotoxicological data were identified from summary documents prepared at the Oak Ridge National Laboratory (Efroymson et al., 19 97a,b). Many of the Soil Criteria Ecological Benchmarks in the Draft are well below natural background levels in soil. Natural backgrou nd soil levels of the constituents considered in Table H-3 of the Draft Ecological ris k assessment are not phytotoxic. Contaminant soil concentrations must be much greate r than natural background concentrations to observe ecotoxicity at Draft Benc hmark effects levels. For example, the Soil Criteria of 28 mg/kg Pb [lead] wa s used in the risk assessment (Table H-3) for soil invertebrates as the terrestri al 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 backgroun d soil Pb levels. We do not observe phytotoxicity to soil invertebrates at 28 m g/kg Pb in natural soils.

USEPA has established Eco-SSLs of contaminants in s oil that are protective of ecological receptors that commonly come into contac t with and/or consume biota that live in or on the soil. The derivation procedu res for the Eco-SSLs represent the collaborative effort of a multi-stakeholder team co nsisting of federal, state, consulting, industry, and academic participants led by the USEPA, Office of Solid Waste and Emergency Response. The Eco-SSL values we re derived separately for four groups of ecological receptors: plants, soil i nvertebrates, birds, and mammals. These values are presumed to provide adequate prote ction of terrestrial ecosystems. Eco-SSLs are derived to be protective of the conser vative 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 procedu res 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

6-5 The USEPA Pb Eco-SSL for soil invertebrates is 1,70 0 mg/kg Pb (U.S. EPA, 2005[c]). Thus, the Eco-SSL of 1,700 mg/kg is consi dered to be protective of the conservative end of the exposure and effects specie s distribution. The Eco-SSL is 60 times higher than the Soil Criteria Ecological B enchmark of 28 mg/kg used in the Draft. Why the difference? The Eco-SSL values a re based on an exhaustive review of previously published peer-reviewed litera ture from soil invertebrate studies that included natural soils and soil invert ebrate 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 establ ish Ecological Benchmarks in the Draft. The Ecological Benchmarks in Table H-3 should be co mpared with (a) the 95th percentile concentration of natural soils for each constituent, and (b) the USEPA Eco-SSL values. The Soil Criteria should be reevalu ated and justified if the Benchmark is below natural soil concentrations (Smi th, 2005) where we know toxicity does not occur. At a minimum, a table comp aring 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 ecologica l benchmarks used in the draft CCR risk assessment were developed, EPA used a very differen t 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 inten tionally 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 bee n a considerable effort by EPA and others to improve the data and methods used in benchmark deri vation. 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 benchma rks is available in Appendix E of the revised risk assessment, while uncertainty surrounding thes e 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 b iota. Thus, no further response to this comment was necessary. However, Dr. Basta’s broader implica tion that ecological screening levels are below background is slightly misleading. The expres sion of toxicity with regards to soil biota (as well as plants and other flora and fauna) for any c onstituent 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 constituent s 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 comm unity that could adversely affect the ecosystem.Response to Peer Review Comments Ecological Exposure and Toxicity

6-6 These are valid considerations for site-specific an alyses, 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 Carl o analysis approach are grouped into four subcategories: 1. Use of conservative parameter estimates 2. Variability versus uncertainty 3. The calculation of percentile probabilities as o pposed to an overall probability 4. Comments related to the numerical stability of M onte 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 conse rvative estimates for some parameters. He emphasized that the ideal approach would be to esti mate 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 b est estimate. Then attitudes towards risk (i.e., be ing “protective”) can be considered when using this dis tribution to make a decision.” 

### Dr. Charles Harvey, Massachusetts Institute of Techno logy The logic of this assessment also skates on thin ic e 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 probabi lity distribution. While there is a clear motivation to use protective values of a para meter when assessing environmental contaminants, choosing a value that g ives an upper bound on risk, rather than the best estimate of risk, may be an ea sy way out of the difficult job of assessing probabilities and this approach may muddl e the overall assessment. It is often easier to say, “I know that this parameter ca n’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 i t moves risk aversion into the characterization of the distribution of outcomes. F rom a decision making point of view, it is much cleaner if the distribution of ris ks represents a best estimate. Then attitudes towards risk (i.e. being “protective”) ca n be considered when using this distribution to make a decision. (Note: for the can cer risk from arsenic the distribution may be best collapsed into a single pr obability, 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 pr obabilistic 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, cons tituent 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 th e 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 do es 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. Di stinguishing between them quantitatively is important for determining opportu nities to reduce uncertainty in risk estimates. EPA’s input distributions are inten ded to represent national variability. In addition EPA reports that “Uncertai nty also was considered in the analysis by using reasonable ranges and distributio ns 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 blen ded them in some input distributions. To the extent possible, EPA guidance recommends separating them to help in identifying opportunities to reduce unce rtainty. Simulation inputs were not defined in a manner that would allow for a clear quantitative distinction between the contribution o f 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 variabilit y from uncertainty when possible in a probabilistic risk assessment. EPA was able to redu ce a substantial number of the uncertainties in the revised risk assessment through the acquisition of additional data on facilities, environmental parameters, and constituent concentrations. Variabi lity and uncertainty are still comingled in aResponse to Peer Review Comments Monte Carlo Analysis Approach

7-3 large number of cases due to remaining data gaps; h owever, EPA conducted multiple sensitivity analyses to determine the potential for different i nputs to affect risk results. Additional discussion of the differences between parameter variability, d ata uncertainty, and model error, as well as discussions of the sensitivity and uncertainty anal yses, 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 resul t can provide particular insight into the results. 

### Dr. Charles Harvey, Massachusetts Institute of Techno logy For the cancer risks from arsenic, the Monte Carlo model generates probability distributions of cancer probabilities. A probabilit y distribution of binary probabilities can be reduced to a single probabilit y. For example, consider the case where you are adverse to tails in a coin toss. If t here is a 0.6 probability that the coin is fair and 0.4 probability that the coin is w eighted so that it lands tails with 0.75 probability, then the probability of getting t ails is: 0.6*0.5 + 0.4*0.75 = 0.6. What you really care about is the 0.6 chance of tai ls, and the distribution of probabilities used to calculate this risk is of lit tle value to you. Likewise, for the cancer risks one could simply calculate the final c ancer risk (the probability of cancer) over the Monte Carlo generated distribution of risks. This calculated probability may be the most important estimate, mor e useful than the 0.5 and 0.9 quantiles of probability provided in this report. T he assessment should certainly report this probability, and it would also be usefu l 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 w ould help the reader understand the conditions for which distributions are useful, and the conditions under which they may be converted to a single probability witho ut 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 est imates 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 us eful information to the decision-makers than what would effectively be an unweighted average. Th erefore, no changes were made in response to this comment.Response to Peer Review Comments Monte Carlo Analysis Approach

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## 7.4. The Numerical Stability of Monte Carlo Results Comment Summary Dr. Vorhees requested an evaluation of the stabilit y of the Monte Carlo results. In other words, is the number of simulations sufficient, so that the r esults do not change significantly with more simulations? 

### Dr. Donna Vorhees, The Science Collaborative EPA performed Monte Carlo simulations of 10,000 ite rations 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 rep ort. In addition, when EPA reports results by liner type, e.g., Table 4-1, it is repor ting 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 Mont e Carlo simulation. 

### EPA Response Figure 1 shows average risk versus the number of simulation s for arsenic under selected CCR disposal scenarios in the draft risk assessment. Th e lower two lines depict landfill risks for the 10,000 model iterations of ash and ash mixed with c oal mill rejects, respectively. Similarly, the upper two lines depict surface impoundment risks fo r 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 a re 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 mor e than sufficient for all modeled cases.Response to Peer Review Comments Monte Carlo Analysis Approach

7-5 Figure 1. Example showing convergence of Monte Carl o 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 f uture. Similarly, Dr. Rowe questioned whether ground water use patterns would change in the futur e, 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 r esults to the well placement assumptions. 

### Dr. Charles Harvey, Massachusetts Institute of Techno logy 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 advers e health impacts, there is an important adverse effect of contaminating ground wa ter. The ground water downgradient of a WMU may be lost as a useable sour ce 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 10,000Average Risk

Number of realizations

Landfill, ash Landfill, ash and coal Surface impoundment, ash Surface impoundment, ash and coalResponse to Peer Review Comments Monte Carlo Analysis Approach

7-6 substantially larger than the volume of ground wate r that is actually contaminated because the pattern of ground water contamination d ownstream of a source is nearly impossible to completely characterize, so the groun d water over a large area will not be used. Completely ignoring health effects because of the b elief that no one will drink contaminated water, and shifting the analysis to pu rely protection of water resources, would be an extreme approach, and I woul d not support such a limited analysis. However, I think that the report would be nefit 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 contaminat ed well water and the detrimental effects of loosing valuable water suppl ies. 

### Dr. Kerry Rowe, Queens University In the absence of an actual survey of water well us age around existing CCR facilities, I am not aware of a better source of da ta than that available for MSW landfills. EPA recognized this as “one of the large r uncertainties in this analysis” (RA, pg. 4-37) however the statement that “EPA beli eves that the MSW well distance distribution used is protective for CCR la ndfills 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 yea rs but no consideration appears to have been given to likelihood of increased deman d 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 g ood to have examined the implications of wells being closer than that indica ted 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 gr ound water resources. However, this issue is beyond the scope of the risk assessment, as stat ed in Section 1 of the revised risk assessment, and therefore the risk assessment did not explicitl y consider potential impacts on the availability of ground water in the future. Nevertheless EPA not es that the results do clearly indicate that there can be a reduction in resource availability if grou nd water contaminated by CCRs becomes unsuitable for consumption. Dr. Rowe’s comments on the changing location of wel ls 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 anal ysis independently 2. Graphical input/output distributions, truncation values 3. Documentation of sensitivity analysis 4. Discussion of general risk-susceptibility patter ns (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 th e documentation is incomplete and that an independent reviewer could not reproduce the analys is. For example, K d 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 bu t 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 input s and outputs for each step of the risk assessment should be provided. For example , K d values generated by using MINTEQA2 (used as input data for EPACMTP) are criti cal but are not reported. The K d value selected can greatly influence the outcome o f the risk assessment. Review of K d values, and other intermediate modeled outputs, is critical. The reviewer cannot determine whether K d values used were “reasonable.” Similarly, modeled ground water concentration used as input da ta for the risk assessment should be provided for review. In short, the modeli ng methodology should be more transparent.Response to Peer Review Comments Documentation and Miscellaneous Comments

8-2 The parameterization of the risk models is clear, b ut 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 v ariable 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 quest ions, appears reasonable at the level provided. However the level of detail is insu fficient for a reviewer to comment in detail on the distributions that were input to t he Monte Carlo simulations and hence it is also not possible to reproduce the RA b ased on the documentation provided for review. Thus, except at a very high le vel, it is not possible to comment on the completeness or reasonableness of the distri butions that were input to the Monte Carlo simulations. This is a significant shor t-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 reco gnized, that full documentation will likely be quite voluminous and would take much long er 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 sim ulation 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 si mulation of 10,000 iterations per waste type/WMU type/constituent combination. EP A also should provide the name of any software program and/or annotated compu ter code that it used to perform these simulations. 

### EPA Response EPA acknowledges that the documentation of the inpu ts and intermediate outputs could have been more transparent. In the revised risk assessment, E PA 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 K d values, these comments are addressed in Section 2.1 of this response to comments document. Finally, EPA acknowledges that the additions and di scussions of inputs in the document are not sufficient for duplication of the results. Thus, th e input and output files for the draft risk assessm entResponse to Peer Review Comments Documentation and Miscellaneous Comments

8-3 were made available in the docket of the proposed r ule 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 inp ut and output distributions. She also requested further explanation of the minimum and maximum trun cating 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 noncance r hazard quotients and cancer risks. EPA discusses many of the most important ass umptions inherent in their choices of input distributions. However, EPA does n ot 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 t o construct the distributions as a supplement to goodness-of-fit statistical test resu lts. 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 c onsistently higher than HQs for the adult resident; therefore, only child HQs are p resented. 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 tab les accordingly. 

### EPA Response Although EPA did not provide a graphical presentati on 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 t runcates input distributions for the human exposure factors. Instead, exposure factor distribu tions in the revised risk assessment were generated with the @Risk software (Palisade Co., Ne wfield, 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 cohort s 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 o f 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 tha t it describes in another report (EPA 2005[b]). I was unable to find this report onl ine. The sensitivity analyses are an integral part of the PRA, vital to proper interp retation and use of results, and should not be reported in a separate document. EPA’s summary is not sufficient to understand the f ull 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 sensit ivity analysis, describing them as sources of variability that could not be ch anged or managed in anyway. Nevertheless, if one of these inputs strongly influ enced risk results, this might indicate that EPA needs to take additional steps to determine how well its input distributions accurately reflect variability on a n ational level. The fish consumption rate distribution is based on data from only one re gion, so it will be particularly important to determine its relative influence on ri sk estimates. 

### EPA Response EPA acknowledges the omission of the original sensi tivity analysis from the docket. EPA updated the sensitivity analysis (U.S. EPA, 2009a) and plac ed it in the docket for the proposed rule. A summary of the methodology and results is also pres ented 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 ri sk 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 Techno logy This report misses the opportunity to describe whic h 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 exi st. 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 charac teristics 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 ins ight 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, i t needs to be recognized that (a) climate and (b) composite-liner design and construc tion 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 discuss ed below. The potential risk of a disposal facility in an ari d 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 v ary 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 develo ping management options for CCR (Objective 2), more cost effective management s trategies may be developed by considering what is required for different clima tic 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 sen sitivity analysis is provided. EPA finds that across constit uents and pathways, the most sensitive drivers of risk appear to be leachate concentration and inf iltration rate. To the extent that infiltration rat e is affected by the precipitation rate, the sensitiv ity analysis suggests that the risk results may be sensitive to the particular climate variable that t he commenter suggests. Other parameters that appear to be sensitive for sp ecific constituents and pathways include aquifer hydraulic conductivity and gradient, adsorption iso therm coefficient, depth to ground water, receptor well distance, and waterbody flow rate. Al though EPA did not analyze the top 20 percent of model runs as the commenter suggests, the sensit ivity analysis results confirm that higher input values for these variables are likely to lead to hi gher 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 e xceed the risks modeled in the risk

assessment. 

### Dr. Kerry Rowe, Queens University The discussion of receptor populations is considere d reasonable given the broad scope of the study. However it should be acknowledg ed that there may be special cases where the assessment may underestimate risk. Under these circumstances, site specific studies would be warranted. These sit uations are unlikely to occur often but the possibility should be recognized in the dev elopment of any regulations based on the RA. For example, the consumption of fi sh 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 subs tantially 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 curren t disposal practices in Section 5 that may be closer to the “worst-case” scenarios discussed by D r. 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 chl oride were excluded from the analysis. He requested more justification. 

### Dr. Kerry Rowe, Queens University Although it is acknowledged that some of the contam inants not considered (e.g. sulfate, phosphate and chloride; RA pg. 2-3) could “pose an ecological hazard if concentrations are high enough”, there is inadequat e discussion of the justification of this exclusion and its rationalization. 

### EPA Response The revised risk assessment no longer excludes cons tituents from the analysis if they pass through the hazard identification in Section 2

. The hazard identification results present the avail ability 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, i s 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 conc entrations 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 co ncentrations of CCR constituents would be helpful to a risk manager, especially if a CCR faci lity 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 m anagement. Although background concentrations certainly may contribute to risk whe n present, or can be higher than some of the media concentrations calculated in the CCR risk ass essment, EPA generally considers only the incremental increase in risk associated with consti tuents in wastes when conducting risk assessments under RCRA.Response to Peer Review Comments Documentation and Miscellaneous Comments

8-8 [This page intentionally left blank.]Response to Peer Review Comments

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# 9. References

Bhaduri, B., E. Bright, P. Coleman, and M. Urban. 2 007. LandScan USA: A high resolution geospatial and temporal modeling approach for popul ation distribution and dynamics. GeoJournal 69 :103–117. Dzombak, D.A and F.M.M. Morel. 1990. Surface Complexation Modeling: Hydrous Ferric Oxide

. Wiley-Interscience, New York, 393 pp. Efroymson, R. A., M. E. Will, G. W. Suter II and A. C. Wooten. 1997b. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on Terrestrial Plants: 1997 Revision . ES/ER/TM-85/R3. Oak Ridge National Laboratory, Oa k Ridge, Tennessee. Efroymson, R.A., M. E. Will, and G. W. Suter II. 19 97a. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on So il and Litter Invertebrates and Heterotrophic Process: 1997 Revision . ES/ER/TM-126/R2. Oak Ridge National Laboratory, Oak Ridge, Tennessee. EPRI (Electric Power Research Institute). 1997. Coal Combustion By-Products and Low-Volume Wastes Comanagement Survey . Palo Alto, CA. June. Washington, DC. March 5. Fleeger, J.W., K.R. Carman, and R.M. Nisbet. 2003. Indirect effects of contaminants in aquatic ecosystems. Science of the Total Environment 317 (1–3):207–233. Kosson, D.S., H.A. van der Sloot, F. Sanchez and A. C. Garrabrants. 2002. An integrated framework for evaluating leaching in waste manageme nt and utilization of secondary materials. Environmental Engineering Science 19 (3):159–204. Available online at: www.niehs.nih.gov/news/assets/docs_a_e/an_integrate d_framework_for_evaluating_leac hing_in_waste_management_and_utilization_of_seconda ry_materials_508.pdf Lang, D.J., and J.R. Schlictmann. 2004. Leaching of arsenic from a fly ash dump in Beverly, Massachusetts. In Proceedings of State Regulation of Coal Combustion By-Product Placement at Mine Sites. May 4–6, 2004, Harrisburg, Pennsylvania. U.S. Depar tment of the Interior, Office of Surface Mining, Alton, IL. Loeffler Peltier, G., J.L. Meyer, C.H. Jagoe, and W .A. Hopkins. 2008. Using trace element concentrations in Coricula fluminea to identify potential sources of contamination in an urban river. Environmental Pollution 154(2):283–290

. Mathur, Samir S. 1995. Development of a Database for Ion Sorption on Goeth ite using Surface Complexation Modeling. Carnegie Mellon University, M.S. Thesis, Departmen t of Civil and Environmental Engineering. Meeussen, J.C.L. 2003. ORCHESTRA: An Object-Oriente d Framework for Implementing Chemical Equilibrium Models. Environmental Science & Technology 37(6):1175–1182. Available online at www.meeussen.nl/orchestra/Response to Peer Review Comments References

9-2 Moya, J. 2004. Overview of fish consumption rates i n the United States. Human and Ecological Risk Assessment 10 (6):1195–1211. Sample, B. E. and G. W. Suter II. 2002. Screening E valuation of the Ecological Risks to Terrestrial Wildlife Associated with a Coal Ash Disposal Site. Human and Ecological Risk Assessment 8 :637–656. Smith, D.B., W.F. Cannon, L.G. Woodruff, R.B. Garre tt, R. Klassen, J.E. Kilburn, J.D. Horton, H.D. King, M.B. Goldhaber, and J.M. Morrison. 2005. Major- and Trace-Element Concentrations in Soils from Two Continental-Scale Transects of the United States and Canada . Open-File Report 2005–1253, U.S. Geological Surve y, Reston, VA. Available online at pubs.usgs.gov/of/2005/1253/pdf/OFR1253.pdf

. Stepanauskas, R., T.C. Glenn, C.H. Jagoe, R.C. Tuck field, A.H. Lindell, and J.V. McArthur. 2005. Elevated microbial tolerance to metals and anticiot ics in metal-contaminated industrial environments. E nvironmental Science & Technology 39 :3671–3678.

TetraTech. 2001. Characterization of Infiltration Rate Data to Suppo rt Ground water Modeling Efforts (Draft) . Prepared for the Office of Solid Waste, U.S. Envi ronmental Protection Agency, Washington, DC. Contract No. 68-W6-0061. Ma y. U.S. DOE (U.S. Department of Energy). 2006. Coal Combustion Waste Management at Landfills and Surface Impoundments, 1994–2004 . DOE/PI-0004, ANL-EVS/06-4. Office of Scientific and Technical Information, Oak Ridge, TN . August. Available online at: www.ipd.anl.gov/anlpubs/2006/09/57081.pdf

. U.S. EPA (Environmental Protection Agency). 1992. Guidance on Risk Characterization for Risk Managers and Risk Assessors. Memorandum from F. Henry Habicht II, Deputy Administrator, to EPA Assistant Administrators and Regional Administrators. Office of the Administrator. Washington, DC. February 26. Ava ilable online at www.epa.gov/ swerrims/riskassessment/habicht.htm

. U.S. EPA (Environmental Protection Agency). 1997a. Exposure Factors Handbook, Volume I, General Factors . EPA/600/P-95/002Fa. Office of Research and Develo pment, Washington, DC. August. U.S. EPA (Environmental Protection Agency). 1997b. Exposure Factors Handbook, Volume II, Food Ingestion Factors. EPA/600/P-95/002Fa. Office of Research and Develop ment, Washington, DC. August. U.S. EPA (Environmental Protection Agency). 1997c. Exposure Factors Handbook, Volume III, Activity Factors. EPA/600/P-95/002Fa. Office of Research and Develop ment, Washington, DC. August.Response to Peer Review Comments References

9-3 U.S. EPA (Environmental Protection Agency). 1999. Understanding Variation In Partition Coefficient, Kd, Values Volume I: The Kd Model, Met hods of Measurement, and Application of Chemical Reaction Codes . EPA 402-R-99-004A. OAR. Washington, DC. August. Available online at: www.epa.gov/rpdweb00/cleanup/402-r-99-004.html U.S. EPA (Environmental Protection Agency). 2000a. Supplementary Guidance for Conducting Health Risk Assessment of Chemical Mixtures . Risk Assessment Forum, Washington, DC. August. U.S. EPA (Environmental Protection Agency). 2000b. Review of Causative Factors for Coal Combustion Waste Damage Cases . Prepared by SAIC for U.S. EPA Office of Solid Was te under EPA contract 68-W-99-001, WA No. 121. Washing ton, DC. November 29. U.S. EPA (Environmental Protection Agency). 2001. Risk Assessment Guidance for Superfund, Volume III (Part A, Process for Conducting Probabil istic Risk Assessment) . EPA/540/R02/002. Office of Emergency and Remedial Response. December. U.S. EPA (Environmental Protection Agency). 2002a. Constituent Screening for Coal Combustion Wastes. Draft Report prepared by RTI International for Off ice of Solid Waste, Washington, DC. September. U.S. EPA (Environmental Protection Agency). 2002b. Industrial Waste Management Evaluation Model (IWEM) Technical Background Document. EPA530-R-02-012. Office of Solid Waste, Washington, DC. August. U.S. EPA (Environmental Protection Agency). 2002c. Estimated Per Capita Fish Consumption in the United States. August. Available online at: water.epa.gov/scitech/swguidance/fishshellfish/outr each/upload/2002_08_28_fish_consu mption_report.pdf U.S. EPA (Environmental Protection Agency). 2003a. EPA’s Composite Model for Leachate Migration with Transformation Products (EPACMTP): P arameters/Data Background Document. EPA 530-R-03-003. Office of Solid Waste, Washingto n, DC. April. U.S. EPA (Environmental Protection Agency). 2003b. EPACMTP Technical Background Document. Office of Solid Waste, Washington, DC. U.S. EPA (Environmental Protection Agency). 2003c. Framework for Cumulative Risk Assessment . EPA/630/P-02/001F. Office of Research and Develop ment, Washington, DC. U.S. EPA (Environmental Protection Agency). 2003d. Guidance for Developing Ecological Soil Screening Levels . OSWER Directive 9285.7-55. Office of Solid Waste and Emergency Response. November. The 2005 revision is available online at www.epa.gov/ ecotox/ecossl/SOPs.htm

.Response to Peer Review Comments References

9-4 U.S. EPA (Environmental Protection Agency). 2003e. Final Revised Report on Resolution of 18 Previously Indeterminate Candidate Damage Cases . Prepared by SAIC for U.S. EPA Office of Solid Waste under EPA contract 68-W-02-03 6, WA No. 1-12. Washington, DC. March 5. U.S. EPA (Environmental Protection Agency). 2004a. Estimated Per Capita Water Ingestion and Body Weight in the United States— an Update: Based on Data Collected by the United States Department of Agriculture’s 1994–96 and 1998 Continuing Survey of Food Intakes by Individuals . EPA-822-R-00-001. Office of Water. October. U.S. EPA (Environmental Protection Agency). 2004b. Risk Assessment Guidance for Superfund, Volume I: Human Health Evaluation Manual (Part E, S upplemental Guidance for Dermal Risk Assessment) . EPA/540/R-99/005. Office of Emergency and Remedia l Response. July. U.S. EPA (Environmental Protection Agency). 2005a. Guidelines for Carcinogen Risk Assessment. EPA/630/P-03/001B. Risk Assessment Forum, U.S. Env ironmental Protection Agency, Washington, DC. March. Available online at: nepis.epa.gov/ EPA/html/Pubs/pubtitleORD.htm

. U.S. EPA (Environmental Protection Agency). 2005b. Sensitivity Analysis for the Coal Combustion Waste Risk Assessment. Technical Report prepared by RTI International for U.S. EPA Office of Solid Waste under EPA contract 68-W-03-04 2, WA No. 1-16. Washington, DC. March 5.

U.S. EPA (Environmental Protection Agency). 2005c. Ecological Soil Screening Levels for Lead

. Office of Solid Waste and Emergency Response. Washi ngton DC. March. Available online

at www.epa.gov/ecotox/ecossl/

. U.S. EPA (Environmental Protection Agency). 2006a. Child-Specific Exposure Factors Handbook (External Review Draft) . EPA/600/R-06/096A. September 2006. U.S. EPA (Environmental Protection Agency). 2006b. Characterization of Mercury-Enriched Coal Combustion Residues from Electric Utilities Us ing Enhanced Sorbents for Mercury Control . EPA-600/R-06/008. Prepared by F. Sanchez, R. Keen ey, D. Kosson, and R. DeLapp for the U.S. Environmental Protection Agency , Air Pollution Prevention and Control Division. February. U.S. EPA (Environmental Protection Agency). 2007. Framework for Metals Risk Assessment

. Office of the Science Advisor. Risk Assessment Foru m. EPA 120/R-07/001. Available online at www.epa.gov/raf/metalsframework/pdfs/metals-risk-as sessment-final.pdf U.S. EPA (Environmental Protection Agency). 2008a. Child-Specific Exposure Factors Handbook. EPA/600/R-06-096F. National Center for Environment al Assessment, Cincinnati, OH.Response to Peer Review Comments References

9-5 U.S. EPA (Environmental Protection Agency). 2008b. Characterization of Coal Combustion Residues from Electric Utilities Using Wet Scrubber s for Multi-Pollutant Control . EPA/600/R-08/077. Prepared by F. Sanchez, D. Koss on, R. Keeney, R. DeLapp, L.Turner, and P.Kariher for the U.S. Environmental Protection Agency, Air Pollution Prevention and Control Division. July. U.S. EPA (Environmental Protection Agency). 2009a. Sensitivity Analysis for the Coal Combustion Waste Risk Assessment . Prepared by RTI International for U.S. EPA, Offic e of Solid Waste, Washington, DC. U.S. EPA (Environmental Protection Agency). 2009b. Characterization of Coal Combustion Residues from Electric Utilities – Leaching and Cha racterization Data . EPA-600/R09/151. Office of Research and Development, Nationa l Risk Management Research Laboratory, Research Triangle Park, NC. December. U.S. EPA (Environmental Protection Agency. 2010. 2010 Questionnaire for the Steam Electric Power Generating Effluent Guidelines. Available online at water.epa.gov/scitech/ wastetech/guide/steam-electric/questionnaire.cfm

. U.S. EPA (Environmental Protection Agency). 2012a. Interlaboratory Validation of the Leaching Environmental Assessment Framework (LEAF) Method 13 14 and Method 1315 . EPA/600/R-12/624. Prepared by A.C. Garrabrants, D .S. Kosson, R. DeLapp, P. Kariher, P.F.A.B. Seignette, H.A. van der Sloot, L. Stefanski, and M. Baldwin for the U.S. EPA Office of Research and Development, Air Polluti on Control Division. September. U.S. EPA (Environmental Protection Agency). 2012b. Interlaboratory Validation of the Leaching Environmental Assessment Framework (LEAF) Method 13 13 and Method 1316. EPA/600/R-12/623. Prepared by A.C. Garrabrants, D. S. Kosson, L. Sefanski, R. DeLapp, P.F.A.B. Seignette, H.A. van der Sloot, P. Kariher, and M. Baldwin for the U.S. EPA Office of Research and Development, Air Polluti on Control Division. September. U.S. EPA (Environmental Protection Agency). 2013a. Environmental Assessment for the Proposed Effluent Limitation Guidelines and Standar ds for the Steam Electric Power Generating Point Source Category. EPA-821-R-13-003. Office of Water. Washington, DC. 20460. April. U.S. EPA (Environmental Protection Agency). 2013b. Methodology for Evaluating Encapsulated Beneficial Uses of Coal Combustion Residuals . EPA530-R-13-005. OSWER. September. Available online at www.epa.gov/epawaste/conserve/imr/ccps/pdfs/ccr_bu_ method.pdf

. U.S. EPA (Environmental Protection Agency). 2014a. Leaching Test Relationships, Laboratoryto-Field Comparisons and Recommendations for Leachi ng Evaluation using the Leaching Environmental Assessment Framework . EPA-600/R-14/061. EPA Office of Research and Development, National Risk Management Research Labo ratory, Research Triangle Park, NC, 27711. September.Response to Peer Review Comments References

9-6 U.S. EPA (Environmental Protection Agency). 2014b. Coal Combustion Residual Beneficial Use Evaluation: Fly Ash Concrete and FGD Gypsum Wallboa rd

. 

### EPA530-R-14-001. OSWER. February. Available online at: www.epa.gov/epawaste/conserve/imr/ccps/ pdfs/ccr_bu_eval.pdf Zilmer, M., and P. Fauble. 2004. Groundwater impact s from coal combustion ash disposal sites in Wisconsin. In: Proceedings of State Regulation of Coal Combustion By-Product Placement at Mine Sites. May 4–6, 2004, Harrisburg, Pennsylvania. U.S. Depar tment of Interior, Office of Surface Mining, Alton, IL.



### EPA530-R-15-002