June 5, 1998

Draft Final Report 

Non-groundwater Pathways, Human Health 

and Ecological Risk Analysis for Fossil Fuel

Combustion Phase 2 (FFC2)

Prepared for

Office of Solid Waste

401M St., SW (5307W)

Washington, DC 20460

EPA Contract Number: 68-W6-0053

RTI Project Number: 92U-6720-017
Draft Final Report

Non-groundwater Pathways, Human Health and

Ecological Risk Analysis for Fossil Fuel Combustion

Phase 2 (FFC2)

June 5, 1998

Draft Final Report

Prepared for

Office of Solid Waste, Environmental Protection Agency

401 M St., SW (5307W)

Washington, DC 20460

Prepared by

Center for Environmental Analysis

Research Triangle Institute

Research Triangle Park, NC
Draft Version: Do Not Cite or Quote June 5, 1998

Disclaimer

This document was prepared by Research Triangle for the

Environmental Protection Agency under Contract 68-W6-0053,

Work Assignment B-17. Any mention of company or product

names is not to be considered an endorsement by the U.S.

Government or by the Environmental Protection Agency. 

This is a draft document that has not undergone a thorough internal

or external review. It does not represent Agency policy. 
Draft Version: Do Not Cite or Quote June 5, 1998

TABLE OF CONTENTS

EXECUTIVE SUMMARY ................................................. ES-1

1.0 BACKGROUND, PURPOSE, AND SCOPE ............................ Page 1

1.1 Background ............................................... Page 1

1.2 Purpose of Study ........................................... Page 1

1.3 Scope of Report ............................................ Page 2

2.0 ANALYTICAL FRAMEWORK AND METHODOLOGY ................. Page 3

2.1 Analytical Framework ........................................ Page 3

2.2 Risk Assessment Methodology ................................. Page 7

2.2.1 Bounding Analysis .................................... Page 7

2.2.2 High-end/Central Tendency Analysis ....................... Page 8

3.0 WASTE STREAM AND WASTE MANAGEMENT UNIT CHARACTERIZATION

.............................................................. Page 9

3.1 Waste Streams and Waste Management Units Modeled .............. Page 9

3.1.1 Utility Coal Co-managed Wastes .......................... Page 9

3.1.2 Utility Oil Combustion Wastes ........................... Page 9

3.1.3 FBC Wastes ........................................ Page 10

3.1.4 Non-utility FFC Wastes ................................ Page 10

3.2 Waste Management Unit Dimensions ........................... Page 10

3.2.1 Utility Coal-fired Co-managed Waste Dewatered Surface Impoundment

.................................................. Page 10

3.2.2 Utility Coal-fired Co-managed Waste Onsite Landfill ......... Page 11

3.2.2.1 Central Tendency .............................. Page 11

3.2.2.2 High-end ..................................... Page 11

3.2.3 Utility Oil-fired Waste Onsite Landfill ..................... Page 11

3.2.4 FBC Onsite Landfill .................................. Page 12

3.2.4.1 Central Tendency .............................. Page 12

3.2.4.2 High-end ..................................... Page 12

3.2.5 FBC Agricultural Soil Amendment Field ................... Page 13

3.2.6 Non-utility Coal-fired Waste Onsite Landfill ................ Page 13

3.2.6.1 Central Tendency .............................. Page 13

3.2.6.2 High-end ..................................... Page 13

3.2.7 Non-utility Coal-fired Waste Offsite Commercial Landfill ...... Page 14

4.0 FATE AND TRANSPORT IN THE ENVIRONMENT ................... Page 15

4.1 Waste Management Unit Releases ............................. Page 15

4.2 Soil Erosion and Runoff ..................................... Page 18

4.3 Particulate Air Emissions and Dispersion ........................ Page 18

4.3.1 Particulate Air Emissions and Dispersion from Landfills ....... Page 19
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4.3.2 Particulate Air Emissions and Dispersion from the Dewatered Surface

Impoundment ....................................... Page 21

4.4 Fate and Transport from the Agricultural Field .................... Page 21

5.0 HUMAN HEALTH RISK ANALYSIS ............................... Page 23

5.1 Constituents of Concern ..................................... Page 23

5.2 Potential Routes of Exposure ................................. Page 23

5.3 Identification of Receptors ................................... Page 25

5.3.1 Child Receptor ...................................... Page 29

5.3.1.1 Dietary Intakes for Children ....................... Page 29

5.3.1.1.1 Dairy Intake for Children ................. Page 31

5.4 Exposure Durations ........................................ Page 31

5.5 Results and Discussion ...................................... Page 32

5.4.1 Bounding Human Health Analysis Results .................. Page 32

5.4.2 High-end Human Health Analysis Results .................. Page 32

5.5 Discussion of Results ................................. Page 41

5.5.1 Coal-fired Utility Co-managed Wastes .................... Page 41

5.5.1.1 Onsite Landfill Scenario .......................... Page 41

5.5.1.1.1 Ingestion Risks ......................... Page 41

5.5.1.1.2 Inhalation Risks ........................ Page 41

5.5.1.2 Dewatered Surface Impoundment Scenario ........... Page 42

5.5.1.2.1 Ingestion Risks ......................... Page 42

5.5.1.2.2 Inhalation Risks ........................ Page 42

5.5.2 Oil-fired Utility Wastes ................................ Page 43

5.5.2.1 Onsite Landfill Scenario .......................... Page 43

5.5.2.1.1 Ingestion Risks ......................... Page 43

5.5.2.1.2 Inhalation Risks ........................ Page 43

5.5.3 FBC Wastes ........................................ Page 43

5.5.3.1 Onsite Landfill Scenario .......................... Page 43

5.5.3.1.1 Ingestion Risks ......................... Page 43

5.5.3.1.2 Inhalation Risks ........................ Page 43

5.5.3.2 Agricultural Soil Amendment Scenario .............. Page 44

5.5.4 Coal-fired Non-utility Wastes ........................... Page 44

5.5.4.1 Onsite Landfill Scenario .......................... Page 44

5.5.4.1.1 Ingestion Risks ......................... Page 44

5.5.4.1.2 Inhalation Risks ........................ Page 44

5.5.4.2 Offsite Commercial Landfill Scenario ................ Page 44

5.5.4.2.1 Ingestion Risks ......................... Page 44

5.5.4.2.2 Inhalation Risks ........................ Page 44

5.6 Risks from Mercury ........................................ Page 45

5.7 Risks from Lead ........................................... Page 45

5.8 Risks from Beryllium ....................................... Page 46
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6.0 ECOLOGICAL RISK ASSESSMENT OF COMANAGED FOSSIL FUEL

COMBUSTION RESIDUALS ...................................... Page 47

6.1 Technical Approach for ERA of Comanaged FFC Residuals .......... Page 47

6.2. Problem Formulation ....................................... Page 50

6.2.1 Selection of Assessment Endpoints ....................... Page 50

6.2.1.1 Characterization of Constituent Behavior and Toxicity . . Page 54

6.2.1.2 Source Characterization for CPEC Releases from Comanaged FFC

Residuals ..................................... Page 55

6.2.1.3 Identification of Ecosystems/Ecological Receptors Potentially at

Risk ......................................... Page 57

6.2.2.4 Identification of Exposure Pathways of Concern ....... Page 58

6.3 ANALYSIS PHASE ....................................... Page 65

6.3.1 Exposure Profiles .................................... Page 65

6.3.2 Stressor-Response Profiles ............................. Page 65

6.3.2.1 Benchmark and CSCL Development for Wildlife Populations

............................................ Page 66

6.3.2.2 CSCL Development for Communities ............... Page 69

6.4 Risk Characterization ....................................... Page 72

6.4.1 Risk Estimation ...................................... Page 72

6.4.2 Risk Description ..................................... Page 75

6.4.2.1 Exposure Issues. .............................. Page 75

6.4.2.2 CSCL Development ............................ Page 76

6.4.2.3 Receptors/Ecosystems at Risk .................... Page 76

7.0 UNCERTAINTY ................................................ Page 79

8.0 CONCLUSIONS ................................................ Page 82

8.1 Coal-fired Utility Co-managed Wastes .......................... Page 83

8.1.1 Coal-fired Utility Co-managed Wastes Managed in Onsite Landfill

.................................................. Page 83

8.1.2 Coal-fired Utility Co-managed Wastes Managed in Dewatered Surface

Impoundment ....................................... Page 84

8.2 Oil-fired Utility Wastes ................................ Page 84

8.3 FBC Wastes ........................................ Page 84

8.4 Coal-fired Non-utility Wastes ........................... Page 85

8.5 General Conclusions from Human Health Risk Assessment ..... Page 85

8.6 General Conclusions from Ecological Risk Assessment ........ Page 86

9.0 References Cited ................................................ Page 87

APPENDIX A Physical and Chemical Properties for Constituents of Concern

APPENDIX B Waste Characterization
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APPENDIX C Overland Transport Model

APPENDIX D ISCST3 Air Dispersion Model

APPENDIX E Landfill and Dewatered Surface Impoundment Equations

APPENDIX F Soil Amendment Equations

APPENDIX G Waste Partitioning Model Used for Agricultural Soil Amendment Scenario

APPENDIX H Results

APPENDIX I Ecotoxicological Profiles for Constituents of Concern

APPENDIX J Review and Comparison of Available Criteria for Chemical Stressor

Concentration Limit (CSCL) Development
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LIST OF TABLES

Table 2-1. Meteorological Data Used in Analysis ........................... Page 5

Table 4-1. Input Values for Agricultural Liming Practice Parameters ............ Page 22

Table 5-1. Constituents Included in the Human Health Risk Analysis by Wastestream Page 23

Table 5-2. Waterbody Data Used in Analysis .............................. Page 26

Table 5-3. Dietary Consumption Items for Receptor Scenarios ................ Page 27

Table 5-4. Intake Rates Used in Analysis ................................. Page 28

Table 5-5. Exposure Durations Used in Analysis ........................... Page 28

Table 5-6. Fraction of Dietary Item Contaminated .......................... Page 29

Table 5-7. Average Body Weights for Children by Age ...................... Page 30

Table 5-8. Average Body Weights for Age Ranges ......................... Page 30

Table 5-9. Descriptive Statistics for Population Mobility for Children by Current Age Page 31

Table 5-10. Parameters Varied in High-end Analysis and Accompanying Codes Used in Results

Tables .................................................. Page 33

Table 5-11. Draft Human Health Summary Results for Utility Coal Co-managed Wastes

Managed in an Onsite Landfill ................................ Page 34

Table 5-12. Draft Human Health Summary Results for Utility Coal Co-managed Wastes

Managed in a Dewatered Surface Impoundment ................... Page 35

Table 5-13. Draft Human Health Summary Results for Utility Oil Wastes Managed in an Onsite

Landfill .................................................. Page 36

Table 5-14. Draft Human Health Summary Results for FBC Wastes Managed in an Onsite

Landfill .................................................. Page 37

Table 5-15. Draft Human Health Summary Results for FBC Wastes Used as Agricultural Soil

Amendment .............................................. Page 38

Table 5-16. Draft Human Health Summary Results for Non-utility Coal Co-managed Wastes

Managed in an Onsite Landfill ................................ Page 39

Table 5-17. Draft Human Health Summary Results for Non-utility Coal Co-managed Wastes

Managed in an Offsite Commercial Landfill ....................... Page 40

Table 5-18. Maximum Estimated Lead Concentrations in Soil Per Scenario ........ Page 46

Table 6-1. Suite of Assessment Endpoints Considered for the FFC ERA ......... Page 53

Table 6-2. Matrix Summarizing Waste Residuals Evaluated for Each Source ...... Page 55

Table 6-3. Development of Exposure Scenario for the ERA of FFC Residuals Comanaged in

Landfills ................................................. Page 58

Table 6-4. Development of Exposure Scenario for the ERA of FFC Residuals Comanaged in

Surface Impoundments ...................................... Page 60

Table 6-5. Development of Exposure Scenario for the ERA of FFC Residuals Applied as a

Soil Supplement in Land Application ........................... Page 62

Table 6-6. CPECs Included in the ERA of High-end and Central-tendency Management and

Use Practices (by sector and waste management unit) ............... Page 73

Table 6-7. Screening Ecological Risk Assessment Results for Surface Impoundments

....................................................... Page 74
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LIST OF FIGURES

Figure 2-1. Location of Utility Coal-fired Power Plants ....................... Page 5

Figure 2-2. Location of Oil-fired Power Plants .............................. Page 6

Figure 2-3. Location of FBC Facilities .................................... Page 6

Figure 2-4. Location of Non-utility Facilities ................................ Page 7

Figure 4-1. Depiction of Environmental Release and Transport for the Landfill Scenario

....................................................... Page 16

Figure 4-2. Depiction of Environmental Release and Transport for the Dewatered Surface

Impoundment Scenario ...................................... Page 17

Figure 4-3. Depiction of Environmental Release and Transport from the Agricultural Soil

Amendment Scenario ....................................... Page 18

Figure 4-4. Depiction of Landfill Scenario Air Emissions and Dispersion ......... Page 20

Figure 6-1. Technical Approach Developed for ERA of Management & Use of Comanaged

FFC Residuals ............................................ Page 49
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ES-1

EXECUTIVE SUMMARY

Wastes from the combustion of fossil fuels are exempt from regulation as hazardous

wastes under the Resource Conservation and Recovery Act (RCRA) pending completion of a

Report to Congress by the Environmental Protection Agency (EPA) that details the need for more

stringent regulation of these wastes. In 1988 EPA issued a Report to Congress addressing the

risks associated with the disposal of wastes generated by the combustion of coal in the electric

utility industry. This was followed, in 1993, by a Regulatory Determination that in essence stated

that such wastes, as then managed, posed no risks that would justify special regulation. However,

this work was limited in its scope. Not only was it limited to the electric power industry, it was

also limited to but one fuel (coal), and to but four high-volume wastes when these wastes are

managed alone. Certain categories of fossil fuel combustion (FFC) wastes were not permanently

excluded from regulation by the 1993 Regulatory Determination pending additional investigation

by EPA. 

The purpose of this study is to characterize the potential human health and ecological risks

associated with the management and use of the remaining wastes in support of a Report to

Congress for these wastes. To do this, EPA performed a multi-pathway human health and

ecological risk analysis. Both direct and indirect exposure pathways were assessed for both

human and ecological receptors. A deterministic approach was used to estimate point values for

individual risks to human health and, by inference, population- and community-level risks to

wildlife in generalized aquatic and terrestrial ecosystems.

The universe of wastes considered in this analysis was divided into four sectors: (1) coalfired utility co-managed wastes, (2) oil-fired utility wastes, (3) fluidized bed combustion wastes,

and (4) non-utility FFC wastes. EPA found that each sector represented a distinct generator

population with distinct byproduct characteristics and, therefore, elected to study the risks from

each sector separately. Only waste management or disposal practices that are currently used were

assessed and included management in surface impoundments, management in landfills, beneficial

use as an agricultural soil amendment, and beneficial use as minefill.

Given the number of facilities within each industry sector and the geographic distribution

of facilities, site specific analyses were not possible for any of the industry sectors. Therefore,

hypothetical wastes and waste management units (WMU’s) were developed for each industry

sector based on available data. Individual facilities for all industry sectors are distributed

nationally with the exception of oil-fired utilities and, therefore, data on waste matrices and onsite

waste management practices were taken from sector-specific reports (e.g., comanaged coal ash)

and national data compilations (e.g., industrial boilers). National data were also used to

characterize the environmental setting for each exposure scenario for human and ecological

receptors. For example, meteorological data and soil characteristics were identified from national
Draft Version: Do Not Cite or Quote June 5, 1998

ES-2

data distributions. Previous analyses conducted by OSW were used to determine appropriate

human health and ecological exposure factors (e.g., EPA's Exposure Factors 

Handbooks) as well as receptor distances from waste management units. Because the analysis was

not site-specific, ecological receptors were presumed to co-occur with waste management units. 

The types of contaminant release and transport that were assessed included: leaching to

groundwater; soil erosion and runoff; and particulate air emissions and dispersion. For both the

human health and ecological risk assessment, exposures were assessed for direct contact with

contaminated media as well as ingestion of contaminated food items or prey. Direct pathway

exposures stem from ingestion of contaminated groundwater and soil as well as direct inhalation

of contaminated air. Indirect pathway exposures stem from ingestion of food items (e.g., plants,

beef, or dairy products) that have been grown in, or raised on, areas that have been contaminated

from offsite migration of constituents from the waste or direct application of the waste material as

agricultural soil amendment.

Several different types of receptors were considered in this analysis in order to represent

the full spectrum of behaviors associated with “typical” exposures (e.g., adult residents) and high

exposures indicative of certain subpopulations (e.g., farmers). Including the highly exposed

subpopulations ensures that significant subpopulations of potentially exposed humans and wildlife

are protected. For example, potentially more exposed human populations are identified based on

behaviors and activities (e.g., consumption of self-caught fish or growing foods for home

consumption), or based on their proximity to a contaminant source. Selected receptors include:

(1) adult resident, (2) home gardener, (3) farmer, (4) child of farmer, and (5) fisher. This array of

receptors covers all plausible exposure pathways. The child receptor was included to represent a

sensitive subpopulation potentially exposed to all of the most plausible direct and indirect

exposure pathways. With respect to ecological risks, receptors are chosen to represent the full

trophic continuum of wildlife species populations and communities that are essential to the

structure and function of ecosystems.

In the initial stages of this analysis, a bounding assessment was performed. For the human

health risk assessment, the bounding analysis estimated risk for the most exposed individual living

in the proximity of the waste management unit (i.e., off-site exposure). For the ecological risk

assessment, the bounding analysis estimated risks to wildlife living in the vicinity of units that

were characterized by conservative management and use practices (e.g., maximum waste

constituent concentrations; maximum unit sizes). For this deterministic assessment, all parameters

were set at high-end values (5th or 95th percentile depending on the parameter’s correlation with

risk) and risks were estimated. In evaluating potential health and ecological risks, the bounding

analysis was designed with very conservative assumptions intended capture the tail of the risk

distribution (i.e., > 95th percentile). Constituents, waste streams, or waste management

units/disposal practices that showed no excess risk in the bounding analysis were excluded from
Draft Version: Do Not Cite or Quote June 5, 1998

1

Throughout this assessment, excess risk was defined for humans as risk values greater than or equal

to 1E-6 for carcinogens or hazard quotients greater than or equal to 1.0 for non-carcinogens. For

ecological receptors, excess risk was defined as hazard quotients greater than 1.0. 

ES-3

further analysis.1 The results of the bounding analysis indicated the need for further refinements in

the form of high-end analyses. 

For the high-end analysis, both high-end and central tendency risk estimations are

presented. High-end analyses are intended to represent risk above the 90th percentile of the

distribution of individual risk in a population but not higher than the individual with the highest

risk. Central tendency estimates are intended to represent risks near the 50th percentile of the

distribution of individual risk or, in other words, the risk to someone with a more typical

exposure. 

For the central tendency risk estimation, all parameters are set to their central tendency

value (usually the median value of the distribution) and the risk or hazard quotient for each

constituent is calculated. The high-end risk estimation utilizes a two parameter high-end

assessment methodology. With this approach, two driving risk parameters at a time are set to

their high-end value while the remainder of the parameters are set at central tendency and risk

values are calculated accordingly. This continues until risk values are calculated for all possible

high-end parameter combinations. As suggested under the description of the bounding analysis,

high-end and central tendency estimates of ecological risk refer only to the management and use

parameters; the ecotoxicological data and exposure assumptions remained constant throughout all

tiers of the ecological risk assessment.

In analyses such as this, uncertainty is introduced in a number of ways. In general, the

major sources of uncertainty are parameter uncertainty and model uncertainty. Model uncertainty

is associated with all models used in all phases of a risk assessment. Computer models are

simplifications of reality, requiring exclusion of some variables that influence predictions but

cannot be included in models due either to increased complexity or to a lack of data on that

variable. Other than these inherent model uncertainties, there were two major sources of

uncertainty in this analysis. These included waste characterization uncertainty and waste

management practice uncertainty. Many of the sources used for the waste characterization and

waste management unit parameter development had limited data or were based on small sample

sizes. This causes problems when trying to infer from a limited data set to the population of

wastes or waste management units and practices. In addition, the variability in many of the input

parameters introduces significant uncertainty in the risk results, particularly since data were

frequently selected from national (versus regional or site-based) data distributions.

All of these uncertainties need to be taken into account when attempting to characterize

the risks from the management and use of fossil fuel wastes. The human health risk results
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ES-4

indicate that arsenic risks from ingestion are of concern for some of the waste management

unit/receptor combinations and that chromium VI risks from inhalation are of potential concern. 

Barium and thallium also had hazard quotients that indicated that these constituents were of

potential concern. The driving risk parameter was starting waste concentration. Other important

parameters include area of the waste management unit, exposure duration, and distance to

receptor. The ecological risk results indicate that amphibians and wildlife that utilize surface

impoundments as part of their natural habitat may be at risk from several metals, particularly

selenium and aluminum. Although elevated risks were also shown for mercury, the paucity of

sampling data makes the risks results difficult to interpret.

Consequently, there are several uncertainty issues that should be considered when

evaluating the results for this analysis. Many of the assumptions required in this analysis are, as a

matter of policy or past practice, conservative and intended to be protective. For some

environmental settings and waste management units, these assumptions likely lead to an

overstatement of risks. However, EPA has identified the major uncertainty issue in this

assessment: the waste characterization. Modeling constituent concentrations that reflect current

comanaged FFC residuals is especially important since the waste concentration tends to be the

driving risk parameter. The representativeness and statistical rigor in the sampling data used in

the waste characterization have important implications for the risk results and subsequent

decisions supported with this analysis. 

For the draft analysis, uncertainty has been addressed qualitatively. Given the high degree

of variability for many of the driving risk parameters, and the number of data deficiencies inherent

in a national-scale (versus site-based) analysis, a quantitative uncertainty analysis will be

performed to ascertain how these uncertainties influence risk results.
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Page 1

1.0 BACKGROUND, PURPOSE, AND SCOPE

1.1 Background

Wastes from the combustion of fossil fuels are exempt from regulation as hazardous

wastes under the Resource Conservation and Recovery Act (RCRA) pending completion of a

Report to Congress by the Environmental Protection Agency (EPA) that details the need for more

stringent regulation of these wastes. In 1988 EPA issued a Report to Congress addressing the

risks associated with the disposal of wastes generated by the combustion of coal in the electric

utility industry. This was followed, in 1993, by a Regulatory Determination that in essence stated

that such wastes, as then managed, posed no risks that would justify special regulation. However,

this work was limited in its scope. Not only was it limited to the electric power industry, it was

also limited to but one fuel (coal), and to but four wastes (fly ash, bottom ash, boiler slag, and flue

gas desulphurization [FGD] sludge) when these wastes are managed alone. Certain categories of

fossil fuel combustion (FFC) wastes were not permanently excluded from regulation by the 1993

Regulatory Determination pending additional investigation by EPA. These “remaining wastes”

include coal-fired electric utility wastes that are co-managed with other low volume wastes;

wastes from coal-fired non-utility industries; fluidized bed combustion wastes and; wastes from

the combustion of other fossil fuels.

1.2 Purpose of Study

The purpose of this study is to characterize the potential human health and ecological risks

associated with the management and use of the remaining wastes in support of the Report to

Congress for these wastes. The risk assessment for the remaining FFC wastes includes: human

health risks from groundwater contamination; human health risks from multiple above-ground

exposure routes; and ecological risks. This report presents the technical approach to, and results

of, the above-ground multipathway human health risk assessment and the ecological risk

assessment. The groundwater pathway human health risk assessment, conducted in close

coordination with the above-ground multipathway human health risk assessment, is presented in

the Technical Background Document for the Supplemental Report to Congress on Remaining

Fossil Fuel Combustion Wastes; Ground-Water Pathway Human Health Risk Assessment; Draft

Final (SAIC, 1998a), henceforth referred to as the SAIC Background Document.

The Report to Congress, for which this analysis is being performed, has a legislatively

mandated delivery date of September 30, 1998. Following review of the Report to Congress, a

regulatory determination for these remaining FFC wastes is scheduled for April 1, 1999. This

analysis will be used in concert with other information (i.e., the groundwater risk assessment,

damage cases, uncertainty analyses, assessment of coverage by other regulatory programs) to

make the Regulatory Determination of whether or not these wastes warrant listing as a hazardous

waste under RCRA.
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Page 2

1.3 Scope of Report

The remainder of the report begins by developing the analytical framework for the

analysis. Following this, a general overview of the risk assessment methodology that was

employed for this assessment is reviewed. Section 3.0 presents the waste stream and waste

management unit (WMU) characterizations that were developed to represent the remaining FFC

waste universe. Section 4.0 discusses the fate and transport modeling that was performed. A

discussion of the human health risk assessment, including a discussion of risk results, follows in

Section 5.0 and the ecological risk assessment is discussed in Section 6.0. Uncertainty issues for

this analysis are discussed in Section 7.0. These uncertainty issues are combined with the risk

results to draw some general conclusions in Section 8.0. 
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Page 3

2.0 ANALYTICAL FRAMEWORK AND METHODOLOGY

EPA sought to assess risks from the remaining universe of FFC wastes by utilizing a multipathway human health and ecological risk analysis. Both direct and indirect human exposure

pathways were assessed as well as ecological exposures. Direct pathway exposures stem from

ingestion of contaminated groundwater and soil as well as direct inhalation of contaminated air. 

Indirect pathway exposures stem from ingestion of plants, beef, or dairy products that have been

grown in, or raised on, soil that has been contaminated from offsite migration of constituents from

the waste. For this analysis, all constituents are modeled for all pathways for a number of

receptors.

2.1 Analytical Framework

The remaining waste universe was segregated into four sectors: coal-fired utility comanaged wastes, oil-fired utility wastes, fluidized bed combustion wastes, and non-utility FFC

wastes. EPA found that each sector represented a distinct generator population with distinct

byproduct characteristics and therefore, EPA elected to study the risks from each remaining

category separately.

All waste stream and waste management unit characterizations for each of the four

industry sectors were supplied by to RTI by EPA. For an in depth analysis of these industries,

including waste stream and WMU characterization, see the SAIC Background Document. 

Physical and chemical properties for the constituents of concern are presented in Appendix A.

Waste stream concentration characterization and surface impoundment characterization (used in

the ecological risk assessment) are discussed in Appendix B.

Given the number of facilities within each industry sector and the geographic distribution

of facilities, site specific analyses were not possible for any of the industry sectors. Figures 2-1

through 2-4 show the locations, by state, of facilities for each industry sector. The numbers for

the respective states represents the number of facilities within that state. Review of Figures 2-1

through 2-4 gives insight into the geographic distribution of facilities for each industry sector. 

Individual facilities for all industry sectors are well distributed nationally with the exception of oilfired utilities. For this reason, national data are assumed protective in all cases and were used to

characterize parameters other than waste characterization and onsite WMU’s - namely

meteorological data, soil parameters, distance to receptor and nearest waterbody, national

exposure factors, and offsite WMU’s. While it is noted that the geographic distribution of oilfired utilities is predominately in the northeast and southeast, it is assumed that high-end

parameters based on national data would maintain conservatism in the analysis.

Central tendency and high-end meteorological locations were selected based on a

sensitivity analysis. Central tendency and high-end values generally will be a median or mean

value and a 90th percentile value; however, it is difficult to identify true central tendency and high-
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Page 4

end meteorological locations because of the numerous variables associated with each location. 

Different high-end meteorological parameters will necessarily drive exposures from different

pathways. For the non-groundwater pathways analysis, it was decided that the high-end

meteorological location would be selected to maximize air transport of contaminants versus other

transport mechanisms. 

Three sources of contamination from air transport were assessed -- particulate air

concentration, wet particle deposition, and dry particle deposition. Wet deposition of particles

occurs during precipitation and therefore is maximized in areas with high rainfall. However,

rainfall also reduces emissions and therefore air concentrations and dry deposition. Because dry

particle deposition predominates over wet particle deposition with respect to mass transport, as

seen in sensitivity analyses, it was theorized that by assessing areas with moderate rainfall and

assessing meteorological stations by wind conditions, representative high-end and central

tendency sites could be determined. In general, light winds will yield high concentrations and

high dry deposition values. Dry deposition of particles is the product of deposition velocity and

concentration. Based on the equation for concentration from area source emissions, wind speed

is inversely proportional to concentration values (U.S.EPA, 1995a). Predominant winds will also

lead to higher long term average concentrations. 

Using this selection process, distribution data for concentration, windroses, and

climatological data from 29 meteorological stations were examined. These 29 meteorological

stations were used to represent the conditions throughout the continental United States in a

previous analysis (EQM, 1993) and were selected to represent a range of meteorological and

physiographic conditions. The high-end meteorological location was selected based on its high

particulate concentration values, light predominant winds, and moderate precipitation. The

central-tendency meteorological location was selected based on its moderate concentration

values, moderate predominant winds, and moderate precipitation. The meteorologic data that

were used in this analysis are presented in Table 2-1. 

These data sources and conditions supplied the guidelines for selection of input parameters

that were used in the deterministic risk analysis that was performed. A description of this

deterministic analysis is presented below.
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Table 2-1. Meteorological Data Used in Analysis

Parameter Units High-end Central

Tendency

Average Annual Precipitation inches/yr 41.4 15.4

Average Annual Precipitation cm/yr 105.2 39

Average Annual Evapotranspiration cm/yr 48 25

Average Annual Runoff in/yr 8.8 0.5

Average Annual Runoff cm/yr 22 1

Average Annual Temperature F 55 44.4

Average Annual Temperature K 286 280

Mean Annual Wind Speed m/s 4.6 6.2

USLE Rainfall/ Erosivity Factor 1/yr 189 58

Source: SAIC 1998.

8

7

2

10

22 24

20

21

15

20

7

10

3

20

17

20

12 13

3

14

4

29

1 (DC)

2

9

3

1 (DE)

7

1 (MA)

5 (MD)

2

1 (NH)

1 (NJ)

4

3

1

9

3

8

5

5

1

16

7

Figure 2-1 - Location of Utility Coal-fired Power Plants
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1

1 (DC)

2 (DE)

20

2

8

4 3

1

1

7 (MA)

5 (MD)

2

4

2

2

2 (NH)

11

1

5

1

3

1

Source: SAIC, 1998

U.S. territories: GU-2, PR-4, VI-2

Shaded areas represent 61% of total utility

fuel oil usage.

10 (NJ)

6 (CT)

1(RI)

Figure 2-2 - Location of Oil-fired Power Plants

Source: SAIC, 1998

1

1

2

12

1

2

1

7 2

5

4

2

1

1

2

1

17

2

1

2

3

1 4

2 2

1

1

1

1

1

1 (DC)

Figure 2-3 - Location of FBC Facilities
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Figure 2-4 - Location of Non-utility Facilities

2.2 Risk Assessment Methodology

The risk assessment was conducted in accordance with the EPA human health and

ecological risk assessment guidance and is consistent with the methodology employed in recent

OSW listing projects including the Risk Assessment Support for Cement Kiln Dust Regulatory

Activities (RTI, 1997) (henceforth referred to as the CKD Analysis) and the Nongroundwater

Pathway Risk Assessment; Petroleum Process Waste Listing Determination (RTI, 1997). These

risks were developed using a deterministic method, which produces point estimates of risk based

upon single values for input parameters.

2.2.1 Bounding Analysis

The risk assessment began with a bounding analysis. Bounding analyses estimate risk for

the most exposed individual and exposures for the most exposed ecological receptors. For a

deterministic analysis, all parameters are set at high-end values (5th or 95th percentile depending on

the parameter’s correlation with risk) and human health risks or hazard quotients are calculated. 

From these same model runs, maximum media concentrations are obtained and used in the

ecological risk assessment. Constituents, waste streams, or waste management units/disposal

practices that show no excess risk (defined as carcinogenic risk values greater than or equal to

1E-6, human health hazard quotients greater than or equal to 1.0 for non-carcinogens, or

ecological hazard quotients greater than or equal to 1.0) in the bounding analysis can be excluded

from further analysis. For constituents that do not bound out, input parameters are refined. 
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2.2.2 High-end/Central Tendency Analysis

High-end estimates of individual risk are intended to represent risk above the 90th

percentile of the distribution of individual risk in a population but not higher than the individual

with the highest risk. Exposure estimates for the ecological high-end scenario are presumed to

represent above the 90th percentile exposure in the ecosystem. Central tendency estimates are

intended to represent risks near the 50th percentile of the distribution of individual risk or, in other

words, the risk to someone with a more typical exposure. Similarly, central tendency exposure

estimates for ecological receptors are presumed to represent more typical exposures in the

ecosystem.

For the central tendency risk estimation, all parameters are set to their central tendency

value and the risk or hazard quotient for each constituent is calculated. The resultant media

concentrations are then used in the ecological risk assessment. The high-end risk estimation

utilizes a double-high-end assessment methodology. With this approach, two parameters at a time

are set to their high-end value while the remainder of the parameters are set at central tendency

and risk values are calculated. Then another combination of parameters are set at their high-end

value while the remainder are set at central tendency and this set of results is calculated. This

continues until risk values are calculated for all possible high-end parameter combinations. For

completeness, and to gain insight on the importance of each parameter individually, each

parameter is independently set to high-end while all other parameters are set at central tendency

and risks are calculated. The maximum media concentrations from these model runs are then

used in the ecological risk assessment.

In depth discussions of the human health and ecological risk assessments are presented in

Sections 5 and 6 respectively.
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3.0 WASTE STREAM AND WASTE MANAGEMENT UNIT CHARACTERIZATION

3.1 Waste Streams and Waste Management Units Modeled

Waste stream and waste management unit characteristics are the basis for all potential

contaminant releases. All waste characterization data and waste management data were supplied

by EPA. 

The following sections discuss the types of waste and waste management units that were

determined to exist for each of the industry sectors assessed in this analysis. 

It should be noted that many of these waste streams are managed in surface

impoundments. The only non-groundwater pathway for active surface impoundments is

volatilization. Because the constituents of concern consist only of non-volatile metals, it was

determined that an active surface impoundment would not result in emissions and human health

exposures for non-groundwater pathways.

3.1.1 Utility Coal Co-managed Wastes

As discussed above, the analysis for the 1993 Regulatory Determination focused on the

four large volume wastes that are produced from coal combustion - fly ash, bottom ash, boiler

slag, and FGD sludge. The analysis also only considered the electric utility industry. This analysis

assesses the human health and ecological risks from the co-management of these large volume

wastes with smaller volume wastes such as pyrites, demineralizer regenerate, coal mill rejects, and

boiler chemical cleaning wastes. 

It was determined from the Coal Combustion By-products and Low Volume Wastes Comanagement Survey data base (EPRI, 1997) that the majority of these wastes are managed in

onsite solid waste landfills, surface impoundments, or are used in ways defined as "beneficial

uses." Examples of beneficial uses for utility coal co-managed wastes include: minefill and mine

reclamation; aggregate in concrete; asphalt and grout; waste stabilization; road materials; roofing

shingles; and as an ingredient in many other products.

3.1.2 Utility Oil Combustion Wastes

The total volume of utility oil combustion waste is small compared with the quantity

generated by the coal-fired utilities. This difference is due to a smaller number of oil-fired utilities

and a lower ash content of fuel oil as opposed to coal. Typically, 70 percent of oil combustion

waste is fly ash and 30 percent is bottom ash. 

Utility oil combustion wastes are managed in landfills and surface impoundments

(commonly called solids settling basins in the industry). Surface impoundments, however, are

rarely the final disposal unit. Instead, these wastes typically remain in surface impoundments only

temporarily. Then, the solids are dredged and transported to an off-site landfill or utilized for
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vanadium recovery. Thus, a given oil combustion waste stream may be managed in both a surface

impoundment and a landfill in the course of waste management.

3.1.3 FBC Wastes

Two types of waste are generated in FBC units - fly ash and bed ash. Thus, there are

three potential wastes to be managed at FBC facilities - fly ash, bed ash, and combined ash. This

analysis models combined ash wastes because it more accurately represents the waste as it is

managed.

FBC wastes are either disposed of or employed in beneficial uses. Disposal is limited

almost exclusively to onsite, permitted solid waste landfills. Beneficial uses of FBC waste include

mine reclamation, agricultural applications (such as liming agent), cement uses (raw feed or

cement substitute), other geotechnical uses, and stabilization applications.

3.1.4 Non-utility FFC Wastes

The non-utility FFC universe includes both coal- and oil-fired boilers. Steam generated by

non-utility combustors is used to generate electricity, to provide heat, or as a production process

input. Because they use similar combustion technologies, the types of combustion wastes (e.g.,

fly ash, bottom ash) generated by non-utilities are the same as those generated by utilities. Based

on a survey by the Council of Industrial Boiler Owners (CIBO), it also appears that comanagement of high-volume wastes with low volume wastes is as common with non-utility coal

combustion as with the utility coal combustion. However, EPA did not receive waste

characterization data for non-utility FFC combustion facilities. Therefore, the waste

characterization data used to assess risks from utility coal-fired co-managed wastes are used to

characterize waste for the non-utility coal combustion sector.

Disposal in landfills is the primary disposal practice for non-utility coal combustion

residuals. Non-utility combustion waste are disposed of in both onsite landfill and offsite

commercial landfills.

3.2 Waste Management Unit Dimensions

Waste management unit sizes were derived by Sciences Applications International

Corporation (SAIC). This section summarizes the derivation of these dimensions and is excerpted

from SAIC 1998b. Where practicable, a reality check was conducted by comparing parameters

that are calculated based on the hypothetical WMU to those parameter values from other data

sources. This assured that internal consistency was maintained and that the hypothetical WMU’s

were realistic. FFC wastes are managed in a variety of settings and therefore this report uses

different assumptions for each management practice (e.g., landfill) in each of the generating

sectors (e.g., oil combustion, FBC). Specifically, two different active lives are used in this report,

30 years and 40 years, which refer to the time that the management unit is open and accepting

waste. These two active lives are based on two separate data sources. The 40 year active life is
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an assumption based on discussions with EPRI concerning typical active lives of management

units at utilities. Therefore, all management units similar to these types of units were assigned

values of 40 years: onsite landfills and impoundments at coal-fired comanagement utilities and at

FBC utilities. Commercial offsite landfills, however, are not similar to these types of units and

therefore different data were used. Specifically, EPA 

estimates the lifetime of an offsite commercial landfill to be approximately 30 years (Additional

Listing Support Analyses for the Petroleum Refining Listing Determination, EPA, 1998). 

WMU’s for which specific data on lifetime were not available were assumed to have a lifetime of

30 years.

3.2.1 Utility Coal-fired Co-managed Waste Dewatered Surface Impoundment 

For the non-groundwater pathways the only WMU parameter that is of concern is area. 

The following areas were used for contaminant fate and transport modeling:

• a surface area of 364,000 square meters, or 90 acres, corresponding to the 50th

percentile value reported in the EPRI comanagement survey;

• a surface area of 1,670,000 square meters, or 412 acres, corresponding to the 95th

percentile value reported in the EPRI co-management survey.

3.2.2 Utility Coal-fired Co-managed Waste Onsite Landfill

3.2.2.1 Central Tendency. The following data were used for this scenario:

• a surface area of 267,000 square meters, or 66 acres, corresponding to the 50th

percentile value reported in the EPRI co-management survey; and

• a height of 9.45 meters, or 31 feet, corresponding to the 50th percentile value

derived from capacity and area reported in the EPRI co-management survey.

These modeled dimensions correspond to the following assumptions about the hypothetical

landfill:

• a total capacity of 3,300,880 cubic yards; and

• an annual waste disposal rate of 82,522 cubic yards, assuming a 40 year lifetime.

For comparison purposes, the annual waste disposal rate and total capacity are just smaller

than the median values (40th and 47th percentiles, respectively) calculated for the landfills in the

EPRI co-management survey. Thus, the hypothetical landfill is well within the range of

dimensions reported in the EPRI population.

3.2.2.2 High-end. The following data were used for this scenario:

• a surface area of 1,330,000 square meters, or 328 acres, corresponding to the 95th

percentile value reported in the EPRI comanagement survey; and

• a height of 9.45 meters, or 31 feet, corresponding to the 50th percentile value

derived from capacity and area reported in the EPRI comanagement survey.
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These modeled dimensions correspond to the following assumptions about the

hypothetical landfill:

• a total capacity of 16,404,373 cubic yards; and

• an annual waste disposal rate of 410,109 cubic yards, assuming a 40 year lifetime.

For comparison purposes, the annual waste disposal rate and total capacity are near the upper end

but within the distribution of values reported in the EPRI survey (80th and 86th percentile,

respectively).. Thus, the hypothetical landfill is well within the range of dimensions reported in

the EPRI population.

3.2.3 Utility Oil-fired Waste Onsite Landfill

Because no directly reported data on the dimensions of oil combustion waste landfills

were available, the dimensions of the hypothetical landfills were derived differently from those for

other FFC waste management units. One facility in the EPRI oil ash report disposes of 3,000 tons

per year of oil ash in an on-site landfill. This annual waste disposal rate is at the upper bound of

the distribution of generation rates in the EPRI report. It was decided that there were not

sufficient data to characterize a high-end and central tendency landfill and thus only one size was

modeled. A density of 1 ton/cubic yard and constant disposal rates over a 30 year life for the unit

to arrive at the following statistics for a hypothetical landfill:

• an annual waste disposal rate of 3,000 cubic yards;

• a total capacity of 90,000 cubic yards, assuming a 30 year lifetime;

• a surface area of 10,500 square meters, or 2.6 acres; and

• a height of 6.5 meters, or 21 feet.

3.2.4 FBC Onsite Landfill

3.2.4.1 Central Tendency. The following data were used for this scenario:

• a surface area of 155,000 square meters, or 38 acres, corresponding to the

50th percentile value reported in a combined data set from the CIBO

survey and the EPRI co-management survey; and

• a height of 15.8 meters, or 52 feet, corresponding to the 50th percentile

value derived from capacity and area reported in the combined data set.

These modeled dimensions correspond to the following assumptions about the

hypothetical landfill:

• a total capacity of 2,792,747 cubic yards; and

• an annual waste disposal rate of 69,819 cubic yards, assuming a 40 year lifetime.
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For comparison purposes, the annual waste disposal rate and total capacity are near the

upper end but within the distribution of values reported in the combined data set (66th and 78th

percentile, respectively). Thus, the hypothetical landfill is within the range of dimensions reported

in the population.

3.2.4.2 High-end. The following data were used for this scenario:

• a surface area of 317,000 square meters, or 77 acres, corresponding to the 95th

percentile value reported in a combined data set from the CIBO survey and the

EPRI comanagement survey; and

• a height of 15.8 meters, or 52 feet, corresponding to the 50th percentile value

derived from capacity and area reported in the combined data set.

These modeled dimensions correspond to the following assumptions about the hypothetical

landfill:

• a total capacity of 6,459,787 cubic yards; and

• an annual waste disposal rate of 161,485 cubic yards, assuming a 40 year lifetime.

The annual waste disposal rate is larger than the median, but within the distribution of values

reported in the CIBO survey (80th percentile). However, the total capacity is slightly larger than

the largest landfill reported in the combined data set (6,100,000 cubic yards). Thus, while this

hypothetical landfill falls slightly outside the range of values observed in the population for this

one dimension, it is well within the range for the other dimensions. While unusually large in

capacity, it probably is sufficiently realistic for purposes of a conservative bounding scenario.

3.2.5 FBC Agricultural Soil Amendment Field

The agricultural field size used in this analysis is consistent with the agricultural field size

used in the CKD Analysis. Because the FBC waste material is directly applied to the agricultural

field at prescribed rates and frequencies, the size of the field has no impact on the constituent

waste concentration in the soil and subsequent impacted media. It was found that the variation in

the size of the field had little impact on stream concentrations and fish ingestion risks. Therefore,

size of the agricultural field was not varied. The area of the source was determined from the

census of agriculture. The field size is the average agricultural field size in states that have acid

soils and active cement kiln plants. It is noted that this selection protocol may preclude some

states that may apply FBC wastes from being represented, however, it is believed that this would

not significantly bias the results of the analysis. The field size that was used in this analysis was

902,450 m2.

3.2.6 Non-utility Coal-fired Waste Onsite Landfill
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3.2.6.1 Central Tendency. Because no directly reported data on the dimensions of nonutility FFC waste landfills were available, the dimensions of the hypothetical landfills were derived

differently from those for other FFC waste management units. The central tendency scenario used

the 50th percentile annual coal consumption rate from the US90 database to derive an annual ash

generation rate, assuming a density of 1 ton/cubic yard. A constant disposal rates over a 30 year

life for the unit was used to arrive at the following statistics for a hypothetical central tendency

landfill:

• an annual waste generation rate of 1,795 cubic yards;

• a total capacity of 53,844 cubic yards, assuming a 30 year lifetime;

• a surface area of 7,700 square meters, or 1.9 acres; and

• a height of 5.3 meters, or 17.4 feet.

3.2.6.2 High-end. The high-end scenario used the same procedure described above with

the 95th percentile annual coal consumption rate to arrive at the following dimensions:

• an annual waste disposal rate of 20,026 cubic yards; and

• a total capacity of 600,782 cubic yards, assuming a 30 year lifetime.

• a surface area of 34,500 square meters, or 8.5 acres; and

• a height of 5.3 meters, or 17.4 feet.

3.2.7 Non-utility Coal-fired Waste Offsite Commercial Landfill

The offsite commercial landfill dimensions were calculated from a subset of the Industrial

D database. The Industrial D data were collected in the 1980s to characterize on-site landfills. 

To make these data more appropriate for FFC waste management, only the landfills from

industries most likely to generate FFC wastes are included. The seven industries considered

correspond to SIC codes 20, 22, 26, 28, 33, 37, and 49 (an eighth industry, SIC code 82, was

initially considered but no Industrial D landfill data existed for this sector). These seven industries

use the largest quantities of coal for non-utility fuel and were therefore assumed to represent onsite FFC waste disposal practices. The 50th percentile median area associated with these facilities

is 34,400 square meters, while the 95th percentile high-end area is 404,700 square meters.

The landfill capacity was calculated based on a regression equation presented in EPA’s Air

Characteristics Study (U.S. EPA, 1998). The landfill areas were estimated to be 96,600 yd3 and

1,100,000 yd3 for the central tendency and high-end landfills respectively. Using the annual waste

generation rate that was calculated for the onsite landfill and an assumed 30 year landfill lifetime,

a waste fraction (percentage of landfill that is FFC waste) was calculated. Waste fractions were

0.56 for the central tendency landfill and 0.55 for the high-end landfill. The starting waste

concentration is then multiplied by the waste fraction to derive an effective starting concentration

for the fate and transport modeling.

4.0 FATE AND TRANSPORT IN THE ENVIRONMENT
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This section describes the types of releases that can occur from each WMU assessed in the

non-groundwater analysis and the models that were used to estimate constituent fate and

transport in the environment. Detailed discussions of the models used for estimating fate and

transport are provided in the Appendices. Appendix C details the overland transport models used

to calculate soil erosion and run-off. Appendix D gives an overview of the air dispersion

modeling that was performed. Appendices E and F provide all equations used for the Indirect

Exposure Methodology (IEM) modeling. Appendix E equations are used to model fate and

transport, exposure, and risk from landfills and the dewatered surface impoundment while

Appendix F provides the equations used to model fate and transport, exposure, and risk from the

agricultural soil amendment scenario. Appendix G provides the model used to calculate

contaminant losses in the agricultural field to arrive at the starting concentration for the soil

amendment scenario.

4.1 Waste Management Unit Releases

This section explains the types of environmental releases that can be expected from each

of the waste management options described above. Also, for each of the waste management

options, the major assumptions that were used for the fate and transport modeling are presented.

Landfill

Potential contaminant releases from landfills include: leaching to groundwater; overland

transport from erosion and runoff; and air emissions. A complete description of the groundwater

pathway can be found in the SAIC Background Document. The overland transport mechanisms

assessed in this analysis are depicted in Figure 4-1. Both erosion and runoff transport

contaminants from the source and deposit them onto the intervening area, the agricultural field,

and the stream as depicted in Figure 4-1. 

Air emissions can originate from waste unloading operations, spreading and compacting

operations, resuspension of particulates from vehicular traffic, and from wind erosion. 

All onsite landfills are assumed to contain only the FFC waste being assessed. The landfill

sizes were provided by EPA and are discussed in Section 3.2.

Surface Impoundment

The primary release mechanisms for active surface impoundments are leaching to

groundwater and air emissions of volatile constituents. Since no volatile emissions are assumed

and a separate groundwater analysis is being performed, an active surface impoundment was not 
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2

 No volatile emissions are assumed due to the fact that only non-mercury metals are assessed.

3

 An active surface impoundment was however modeled for ecological risks. A discussion of this analysis

is presented in Section 6.0, and the characterization of the surface impoundment is discussed in Appendix B.

Page 16

Figure 4-1. Depiction of Environmental Release and Transport for the Landfill Scenario 

modeled for human health risks.2, 3 Rather, a closed, dewatered surface impoundment was

modeled for aboveground risk. A dewatered surface impoundment is assumed to be below grade

due to design characteristics. Therefore, it is assumed that there would be no overland transport

of contaminants through erosion and runoff. And since there are no waste loading operations, it

follows that the only source of emissions will be from wind erosion. Emissions were estimated

and dispersion was modeled as a flat, even-grade unit. These assumptions will tend to

overestimate risks from this type of unit. A dewatered surface impoundment is depicted in Figure

4-2.

Beneficial Uses

There are a large number of beneficial uses identified for these wastes. Most of these

beneficial uses employ the wastes as ingredients in a final product (e.g., concrete, asphalt, roofing

shingles) and thus the wastes are considered encapsulated and the mobility of its constituents in

the environment is greatly reduced. EPA also limited its review to those beneficial uses where the

waste is applied directly to the ground. These uses include minefill/mine reclamation and use of

the waste as agricultural soil amendment. Application of the waste to agricultural lands as a soil
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4

 FBC wastes are used as liming agents due to their naturally high alkilinity.

Page 17

amendment may provide risks from a variety of pathways.4 Use of the waste as minefill/mine

reclamation also may have significant human health and ecological impacts. However, the data

provided by EPA indicate that minefills are less numerous and generally smaller than conventional

landfills. Since the mine would be modeled like the landfill, a separate analysis was not performed

to assess risks from FFC wastes used as minefill.

Once applied to the agricultural lands, contaminants are taken up by the plants grown on

the amended soil. Wind erosion and runoff/erosion from the agricultural field to a nearby stream

will also occur. This source is depicted in Figure 4-3.

Figure 4.2 Depiction of Environmental Release and Transport for the Dewatered Surface

Impoundment Scenario
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Figure 4-3. Depiction of Environmental Release and Transport from the Agricultural Soil

Amendment Scenario

4.2 Soil Erosion and Runoff

Soil erosion and runoff were assumed to occur from all landfill scenarios and from the soil

amendment scenario. A modified Universal Soil Loss Equation (USLE) was utilized to estimate

overland erosion and runoff. The USLE is an empirical erosion model originally designed to

estimate long-term average soil erosion losses to a nearby waterbody from an agricultural field. 

The USLE was modified to estimate soil erosion and runoff from WMU’s, across intervening

areas, to nearby waterbodies, by evaluating this process in an integrated setting. A complete

write-up of the overland transport models is provided as Appendix C.

4.3 Particulate Air Emissions and Dispersion

Particulate emissions differ between each of the WMU/sources that were assessed in this

analysis. Therefore, emissions from each of the WMU/sources will be discussed separately below. 

Dispersion for all WMU/sources was modeled using the EPA’s Industrial Source Complex

Short Term (ISCST3) Model. ISCST3 can be used for continuous releases from one or more

point, area, volume, or line sources. For all sources, wet particle deposition, dry particle

deposition, and particulate air concentration were modeled for receptors located 300 meters from
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the source for central tendency and 75 meters from the source for high-end. Thirty-two, equal

spaced, receptor points were modeled for each distance. (See Figure 4-4 for depiction of distance

to receptor and spacing of modeled receptors.) Additional detail on ISCST3 is presented in

Appendix D.

4.3.1 Particulate Air Emissions and Dispersion from Landfills

Several different types of particulate air emissions contribute to aggregate particulate

emissions from landfills. These include emissions from wind erosion of the active landfill, from

vehicle resuspension of contaminants while delivering waste to the landfill, from waste material

blowing from trucks hauling the waste to the landfill (assume less than 100% cover control

efficiency), from unloading the waste at the landfill, and from spreading and compacting

operations. Figure 4-4 presents a pictorial representation of the landfill.

Emissions from wind erosion are estimated only for the active cell of the landfill. It is assumed

that only part of the entire landfill will be active at any particular time and that the rest of the

landfill will have a cover of uncontaminated, native soil. The area of the active cell is assumed to

be one years worth of waste capacity. Therefore, the active landfill area is equal to the total

landfill area divided by the active life of the landfill. Wind erosion emissions are calculated using

the same methodology employed in Methodology for Assessing Health Risks Associated with

Indirect Exposure to Combustor Emissions (U.S. EPA, 1990). For dispersion modeling, the

active cell is assumed to be located in the center of the landfill (see Figure 4-4) Using the center

cell will yield results that simulate an average concentration over the entire lifetime of the landfill

for any given receptor.

Both emissions from vehicle resuspension and from waste being blown from the trucks are

estimated using AP-42 emissions equations (U.S. EPA, 1995b). AP-42 equations are empirically

derived and are used to estimate fugitive dust emissions from a variety of activities for both point

and area sources. For dispersion modeling, the source of these emissions was assumed to be the

area of the road depicted in Figure 4-4. The length of the road is dependent on the size of the

landfill being modeled while the width of the road is set at three meters for all landfills. Three

meters was determined to be wide enough to allow one way traffic under the assumption of a

single entrance and exit for the landfill. A sensitivity analysis showed that maximum air

concentration results are slightly sensitive to the orientation of the landfill. Higher air

concentrations were calculated when the landfill was oriented with the predominant wind

directions as depicted in Figure 4-4.
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Figure 4-4. Depiction of Landfill Scenario Air Emissions and Dispersion
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4.3.2 Particulate Air Emissions and Dispersion from the Dewatered Surface

Impoundment

Only emissions from wind erosion were estimated for the dewatered surface

impoundment. These emissions were estimated using the same methodology as was employed in

the landfill scenarios. Dispersion was modeled for the entire surface area of the waste unit. 

Receptors were modeled as they were for the landfill scenarios.

4.4 Fate and Transport from the Agricultural Field

Because FBC residues contain alkaline oxides and plant nutrients that are useful in

agriculture, they are often applied to agricultural lands to increase pH and supply these necessary

nutrients (USDA, 1988). Cement kiln dust (CKD) is also used for this purpose and this practice

is the focus of a recent risk analysis to assess the risks that result from applying CKD to

agricultural lands as a liming agent. Due to these inherent similarities, the development of this

scenario and the subsequent modeling was based on the methodology employed in the CKD

Analysis. For this scenario it is assumed that the FBC combined ash is applied directly to an

agricultural field as a liming agent. Therefore, the same input parameters were used for this

analysis that were used in the CKD Analysis. These values are presented in Table 4-1. It is also

assumed that FBC wastes will be used, as CKD wastes are used, on acidic soils. Therefore, the

same soil parameters and meteorological locations that were used in the CKD Analysis are used

to estimate risks from FBC wastes used as agricultural soil amendment. 

The same routes of exposure that were assumed in the CKD Analysis and the other

scenarios for this analysis are assumed for this scenario. These exposure routes include soil

ingestion, ingestion of plants, beef, and dairy products grown on the soil amended agricultural

field, and ingestion of fish caught in a stream nearby the soil amended agricultural field. 

Inhalation risks to the farmer from tilling and wind erosion were assessed in the CKD Analysis. 

These risks bounded out and were considered inconsequential relative to risks from other

pathways. A comparison of constituents and starting concentrations between CKD and FBC

revealed that the FBC risks from inhalation would likely be insignificant. Therefore, it was

assumed that risks would be driven by other pathways and thus inhalation risks were not

evaluated for this analysis.

Partitioning of metals in the agricultural field was estimated using a set of equations that

calculate contaminant losses due to leaching and rainwater runoff. The model tracks the average

annual soil concentration for a period of 100 years of active use (corresponding to the period over

which waste application occurs) followed by 40 years of inactive use. The maximum rolling

average starting soil concentration which is based on the exposure duration is then used as the soil

concentration for all pathways. A complete write-up of the partitioning equations used for this

analysis is presented in Appendix G.
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Page 22

Crops on the agricultural field receive dry deposition of particles from the agricultural field

as well as uptake of contaminant through the roots.

The stream also receives runoff/erosion, and air deposition from the agricultural field. The

equations used for overland transport from the agricultural field to the stream are provided in

Appendix F. The air deposition to the stream is set equal to the onsite deposition of dry particles

to the agricultural field. It is assumed that the stream is 75 meters from the agricultural field. 

Table 4-1. Input Values for Agricultural Liming Practice Parameters

Parameter Central

Tendency

High-end

Application Rate

(tons/acre/application)

3 5

Application Frequency

(years)

1/3 1/2

Tilling Depth (cm) 15 10
Draft Version: Do Not Cite or Quote June 5, 1998

Page 23

5.0 HUMAN HEALTH RISK ANALYSIS

5.1 Constituents of Concern

The constituents that were modeled were based on analytical data provided by EPA. The

constituents with human health toxicity values (i.e., RfC, RfD, or CSF values) that were assessed

for the human health risk analysis are provided in Table 5-1. A complete description of the waste

characterization for each waste stream is provided in Appendix B.

Table 5-1. Constituents Included in the Human Health Risk Analysis by Wastestream

Wastestream Constituents Modeled for Human Health

Coal-fired utility and non-utility co-managed

wastes

Nickel, silver, thallium, arsenic, barium,

beryllium, boron, cadmium, chromium VI,

cobalt, selenium

Oil-fired utility wastes Nickel, silver, thallium, arsenic, barium,

boron, cadmium, chromium VI, cobalt,

copper, vanadium, zinc

FBC wastes Nickel, silver, thallium, arsenic, barium,

beryllium, boron, cadmium, chromium VI,

cobalt, selenium

5.2 Potential Routes of Exposure

Individuals can be exposed to the previously described contaminant releases through a

number of exposure routes. The relative contribution of any one of these exposure pathways for

a particular chemical is dependent on the physical and chemical characteristics of the chemical, the

properties of the wastestream, and the environmental setting that is being modeled. The following

exposure pathways were assessed for this analysis.

Groundwater Ingestion

For any of the waste management units described above, contaminants can leach from the

waste into the groundwater and subsequently be ingested by individuals who rely on well water. 

A detailed discussion of the modeling of and risks from this pathway can be found in the SAIC

Background Document. Untreated surface water is not considered a source of residential

drinking water. Further, it is assumed that exposure from inadvertent ingestion of surface water

would be in small volume and infrequent.
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Page 24

Air Emissions, Inhalation

Another source of exposure is from inhalation. Since this analysis only considers nonmercury metals, only emissions of particulates are considered. For the inhalation pathway only

emissions and air concentrations of respirable PM10 are considered.

Ingestion of Contaminated Soil

Exposure from this pathway stems from inadvertent ingestion of contaminated soil. The

consumed soil has been contaminated by air deposition and deposition from overland transport of

contaminants through erosion and runoff. For the soil amendment scenario, exposure stems from

inadvertent ingestion of soil directly contaminated from application of the waste product.

Ingestion of Fruits and Vegetables

Individuals may ingest fruits and vegetables that have been contaminated by migration of

waste constituents to offsite agricultural fields or from direct application of the waste as

agricultural soil amendment. For above-ground fruits and vegetables, this pathway includes two

concurrent mechanisms of plant uptake: air deposition directly to the plant, and deposition to soil

(including air particulate deposition and erosion and runoff deposition) followed by uptake by the

plant. For root vegetables, this pathway includes only one mechanism of plant uptake: deposition

to soil followed by root uptake by the plant. Uptake via direct deposition to the root plant is not

considered, since the edible (root) portion is protected from contact with contaminants in air, and

it is unclear whether contaminants deposited on plant surfaces are internalized by plants. 

Beef and Dairy Products Ingestion

Individuals may also ingest beef and dairy products from cows raised on contaminated

agricultural fields. The estimated constituent concentrations in beef and dairy products are

estimated based on the dietary intake assumptions for cattle. The cattle’s diet is assumed to

consist of forage (i.e., pasture grass and hay), silage, and grain. In addition, the cattle are

assumed to directly ingest the contaminated soil. 

Fish Ingestion

Exposure for this pathway stems from human ingestion of fish that are caught in a stream

located nearby a waste management unit or soil amended agricultural field. The stream has been

contaminated from runoff and erosion from the waste management unit and direct deposition of

particles into the stream. Once the constituents are in the surface water, fish may “ingest” the

dissolved constituents during normal respiration across the gills. In addition, contaminants that

concentrate in the sediments may be introduced into fish through the food chain, beginning with

benthic organisms (i.e., bottom dwellers). Contaminants can accumulate in fish from either or

both of these exposure vehicles depending on the chemical’s potential for bioconcentration and

bioaccumulation. 
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Page 25

There is the potential for contaminated groundwater recharge to surface water bodies (i.e.,

streams) resulting in contamination of surface waters and fish, and risk from subsequent fish

ingestion. This pathway was not considered in this analysis for several reasons. The primary

reasons are that this scenario is a very site specific phenomena and would require site specific data

to model. This type of analysis is not consistent with the more general bounding analysis

performed here. Also, it is assumed that the load to the surface waterbody from groundwater

recharge would be far surpassed by the load from the overland routes (i.e., erosion and runoff) or

from outfall permits under the National Pollutant Discharge Elimination System (NPDES).

5.3 Identification of Receptors

Receptors evaluated in multiple pathway analyses are selected to represent a typical

individual and highly exposed individuals. Highly exposed subpopulations (i.e., high-end

receptors) are examined to ensure that significant subpopulations of potentially highly exposed

individuals are protected. For human receptors, potentially more exposed populations are

identified based on the behavior of potential receptors such as dietary habits and activities (e.g.,

consumption of self-caught fish or growing foods for home consumption) or based on their

proximity to a contaminant source. Selected receptors include: (1) adult resident, (2) home

gardener, (3) farmer, (4) child of farmer, and (5) fisher. This array of receptors covers all

plausible exposure pathways.

An adult resident living near the waste management unit could inhale airborne constituents

transported off-site as particulates or ingest constituents via incidental soil ingestion.

Indirect exposure pathways include uptake of constituents from home-grown fruits and

vegetables, ingestion of home-grown meat and dairy products, and ingestion of fish caught from

local impacted streams. A home gardener, farmer, and fisher were selected to evaluate these

indirect exposure pathways. 

The home gardener is an adult resident that, in addition to the exposure pathways

identified for the adult resident, is also exposed by ingesting contaminated homegrown fruits and

vegetables. The farmer and child exposure includes all of the exposure pathways listed above plus

ingestion of meat and dairy produced on their farm. The child receptor was included to represent

a sensitive subpopulation potentially exposed to all of the most plausible direct and indirect

exposure pathways. In modeling the child receptor, the input parameters that differ from the adult

farmer receptor include: body weight; ingestion and inhalation rates; and exposure duration. 

Finally, an adult fisher was selected to assess potential risk associated with fish ingestion

from an impacted stream. Parameters used to estimate impacts to a nearby fishable stream are

provided in Table 5-2. The dietary consumption items assessed for each receptor are presented in

Table 5-3.
Draft Version: Do Not Cite or Quote June 5, 1998

5

 Pica behavior is defined as an abnormal desire to eat substances not normally eaten. Often young

children will exhibit pica behavior with soil.

Page 26

Exposure factors were selected to represent both central tendency (50th percentile) and

high-end (95th percentile) values for the selected receptors and exposure pathways. These values

were obtained from U.S. EPA’s Exposure Factors Handbook (EFH) (U.S. EPA, 1998). 

Table 5-4 presents ingestion rates and inhalation rates for all receptors. Note that beef and dairy

ingestion rates are presented in both whole weight (WW) and dry weight (DW). This is due to

the fact that the beef and dairy biotransfer factors for cadmium and selenium are based on dry

weight concentrations while all other contaminants' biotransfer factors are based on wet weight

concentrations. 

Table 5-5 presents the various exposure duration values used. It should be noted that the

time in which the child exhibits pica behavior was set at 6 years.5 After age six, the child ingests

soil at the same rate as the adult for a period of years that were in accord with the exposure

duration distribution presented in Table 5-5. 

The fraction of each dietary item ingested that is contaminated is presented in Table 5-6. 

Fraction contaminated values are based on data presented in Table 12-71 of the 1998 EFH. This

data was used to represent the fraction of the total intake that is assumed to be home grown in the

contaminated area. These fractions are mean values and are used as a single quantity in the

absence of additional data. 

Table 5-2. Waterbody Data Used in Analysis

Parameter Units National Average Reference

Flow m3/yr 3.00E+08 HWIR

Total Waterbody Depth m 0.67 HWIR

Depth of Upper Benthic Layer m 0.03 US EPA, 1993

Velocity m/s 0.7 HWIR

Waterbody Area m2

1.00E+06 HWIR
Draft Version: Don Not Cite or Quote June 5, 1998

Page 27

Table 5-3. Dietary Consumption Items for Receptor Scenarios

Dietary Item

Receptor Scenario

Adult

Resident

Home

Gardener

Farmer Child of

Farmer

Fisher

Soil T T T T

Exposed Fruits T T T

Exposed Vegetables T T T

Root Vegetables T T T

Beef T T

Dairy Products T T

Fish T
Draft Version: Do Not Cite or Quote June 5, 1998

Page 28

Table 5-4. Intake Rates Used in Analysis

Adult Resident Home Gardener Farmer Child of Farmer Fisher

Unit/Percentile 50 95 50 95 50 95 50 95 50 95

Soil kg/day 0.00005 0.0001 0.00005 0.0001 0.00005 0.0001 0.0002 0.001 NA NA

Aboveground Vegetables kg/DW/d`ay NA NA 0.004 0.025 0.006 0.03 0.003 0.017 NA NA

Fruits kg/DW/day NA NA 0.01 0.072 0.019 0.089 0.0085 0.067 NA NA

Root Vegetables kg/DW/day NA NA 0.005 0.028 0.0067 0.035 0.0042 0.025 NA NA

Beef kg/DW/day NA NA NA NA 0.031 0.13 0.025 0.059 NA NA

kg/WW/day NA NA NA NA 0.11 0.45 0.088 0.21 NA NA

Dairy kg/DW/day NA NA NA NA 0.17 0.63 0.088 0.21 NA NA

kg/WW/day NA NA NA NA 0.73 2.64 0.365 0.88 NA NA

Air m3/hr 0.83 NA 0.83 NA 0.83 NA 0.2 NA NA NA

Fish g/day NA NA NA NA NA NA NA NA 61.8 393.6

Table 5-5. Exposure Durations Used in Analysis

Adult Resident Home

Gardener

Farmer Child of

Farmer

Fisher

Exposure Duration Unit/Percentile 50 95 50 95 50 95 50 95 50 95

Exposure Duration (soil

ingestion) a

year 3.3 32.3 3.3 32.3 10 58.4b

6

18 3.3 32.3

Exposure Duration (all

other exposures)a

year 3.3 32.3 3.3 32.3 10 58.4b

7.3 18 3.3 32.3
Draft Version: Do Not Cite or Quote June 5, 1998

Page 29

Table 5-6. Fraction of Dietary Item Contaminated

Dietary Item Adult

Resident

Home

Gardener

Farmer Child of

Farmer

Soil a

1

1 1 1

Aboveground Vegetables b

NA 0.233 0.42 0.42

Fruits b

NA 0.116 0.328 0.328

Root Vegetables b

NA 0.106 0.173 0.173

Beef b

NA NA 0.485 0.485

Dairy b

NA NA 0.254 0.254

Fishb

NA NA 0.133 NA

a - Parameters Guidance, March 1997 

b - Exposure Factors Handbook, 1998. Table 12-17 Fraction of Food Intake that is Home Produced

5.3.1 Child Receptor

This section focuses on the child receptor because they are expected to be a more sensitive

subpopulation and EPA recognizes the need to consider health risks to children. EPA has yet to

establish policy guidelines that detail the methodology to be used to assess risks to children. The

methodology employed in this analysis differentiates risks between adults and humans based solely

on different exposure profiles. Toxicity values (i.e., RfD, RfC, and CSF) were not adjusted as

these values are developed to be protective of more sensitive subpopulations.

5.3.1.1 Dietary Intakes for Children. This risk analysis provides a preliminary

conservative approach for addressing exposure to children. The consumption rates for children of

various ages must be keyed to the body weight for that age group. In the EFH, ingestion rates for

all dietary items are presented by the following age groups: 1 to 2, 3 to 5, 6 to 11, and 12 to 9

years. The EFH also presents body weight distribution charts for males and females ages 6 to 11

months and in 1-year increments thereafter to age 19. In order to obtain average body weights

for use with the dietary intake tables, body weights for both sexes for each year of age are needed. 

The average body weights provided in EFH are presented in Table 5-7. 
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Page 30

Table 5-7. Average Body Weights for Children by Age

Average Wt. for Age (Kg)

Age

group

1 to 2 3 to 5 6 to 11 12 to 19

Age/

Sex

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

male 11.8 13.6 15.7 17.8 19.8 23 25 28.2 31.1 36.4 40.3 44.2 49.9 57.1 61 67.1 66.7 71.1 71.7

female 10.8 13 14.9 17 19.6 22.1 25 27.9 31.9 36.1 41.8 46.4 50.9 54.8 55.1 58.1 59.6 59 60.2

The body weights for both males and females in each year of the age range are averaged to

obtain the average body weight for each age group. These average weight values are presented in

Table 5-8. 

Table 5-8. Average Body Weights for Age Ranges

Age Range (Yrs) Weights (kg)

1 to 2 12.3

3 to 5 17.5

6 to 11 30.7

12 to 19 58.3

This average body weight (kg) for the age groups is used to estimate the daily

consumption rate distributions (kg/d) for the age groups from the intake rate distributions (kg

diet/kg body weight -day) presented in the EFH. This approach will yield a distribution of

consumption rates for children in each age range. However, children may be any age range during

the period of exposure and may not remain in a single age range throughout the selected exposure

duration. For example, the child’s high-end exposure duration is 18 years. Obviously the child

will span all of the aforementioned age ranges during this period of exposure. For long exposure

durations, some type of weighted average ingestion rate may be used; however, this may not be

appropriate for shorter exposure durations. For this analysis the age range with the highest

consumption rate is selected for use. This consumption rate is used for all children for all

exposure durations. This is a conservative assumption for exposure durations larger than the age

ranges used. For all dietary items except dairy products, the age range with the highest intake is

12 to 19 years. For dairy products, the age range with the highest consumption rate is 6 to 11

years. Options for combining consumption rates and exposure durations for growing children are

important for all dietary items. This issue is under continuing development. The child’s

consumption rates that were used in this analysis are presented in Table 5-4.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 31

5.3.1.1.1 Dairy Intake for Children. Dairy intake rates for children uses a different

source than all other intake parameters. All data for the other intake parameters are from the

tables of intakes of home-produced food items. The data for dairy intake for children are from the

EFH’s Appendix 3A, “Sample Calculation of Mean Daily Fat Intake Based on CDC (1994)

Data.” Table 3-2 in that appendix presents intake of total dairy products by age groups. These

data represent per capita intake rates and are not limited to home-produced products. In the

absence of other data sources on home produced dairy products, it is recommended that these

data be used. The home-produced products section does give a fraction of home-produced dairy

items consumed that can be used to develop a distribution to be used in the analysis. The

fractions of dietary intakes that are home produced, and thus considered contaminated, are

presented in above in Table 5-6.

5.4 Exposure Durations

Data for exposure duration are obtained from the distributions presented for population

mobility (Chapter 14.3 of the EFH). There are data for numerous categories of residents. For

children, the exposure duration will change from using only the traditional 6 years’ exposure

duration to using the distribution of values presented in Table 14-159 of the EFH, “Descriptive

Statistics for Both Genders by Current Age.” These data are relatively constant over childhood

and can be adapted for use as a general distribution of values for children up to age 18. 

Table 5-9 presents estimated mobility data for children based upon current age. 

Table 5-9. Descriptive Statistics for Population Mobility for Children by Current Age

Residential Occupancy Period (yrs)

Percentile

Current Age

(yr)

25 50 75 90 95 99

3 3 5 8 13 17 22

6 4 7 10 15 18 22

9 5 8 12 16 18 22

12 5 9 13 16 18 23

15 5 8 12 16 18 23

18 4 7 11 16 19 23

Average 4.3 7.3 11 15.3 18 22.5
Draft Version: Do Not Cite or Quote June 5, 1998

6

 The term“bound out” refers to the a situation when there is no excess risk or hazard quotients. When

this occurs, the constituent or waste stream can be omitted from further analysis.

Page 32

5.5 Results and Discussion

5.5.1 Bounding Human Health Analysis Results

As discussed in Section 2.2.1 the bounding analysis was designed to be extremely

conservative. No scenarios bounded out completely; however, most constituents showed no

cancer risks greater than 1E-6 or hazard quotients greater than 1.0 for non-carcinogens for most

scenarios.6 The results of this analysis indicated the need for more realistic analyses for some

constituents. Since many additional constituents needed to be modeled for the ecological risk

analysis, all constituents that were assessed in the bounding analysis were again assessed in the

high-end analysis.

5.5.2 High-end Human Health Analysis Results

Result summaries are presented in tables 5-11 through 5-17. These summaries present

only WMU/chemical/receptor combinations that had a cancer risk of greater than 1E-6 or a

hazard quotient, for non-carcinogens, of greater than 1.0 (carcinogen risk values are presented in

scientific notation while non-carcinogen hazard quotients are presented in standard notation). If a

WMU/chemical/receptor combination met this criterion, then the highest risk value is reported

and the high-end parameter combination that led to this result is presented by code letters below

the risk or hazard quotient value in the summary table. Table 5-10 lists the letter codes for the

parameters used in the exposure modeling. 

A full set of the human health risk analysis results are presented in Appendix H. Similarly,

cancer risk numbers are presented in scientific notation and non-cancer hazard quotients are

presented in standard notation. All cancer risk or hazard quotient exceedences have a bold border

and the number is italicized. The maximum value for that WMU/chemical/receptor combination is

in bold font in addition to having a bold border and being italicized.

Note that the results tables present values for beryllium as a carcinogen. The oral CSF for

beryllium was withdrawn from IRIS on April 3, 1998. Risk values had already been generated

and presented in this document for beryllium using the oral CSF before the CSF was withdrawn. 

Therefore, ingestion risk values for beryllium are no longer valid. Section 5.8 below addresses the

potential for adverse human health effects from beryllium based on its RfD. 
Draft Version: Do Not Cite or Quote June 5, 1998

Page 33

Table 5-10. Parameters Varied in High-end Analysis and Accompanying Codes Used in

Results Tables

High-End Code High-end Parameter1 Soil Amendment High-end

Parameter

Z Beef Intake Rate Beef Intake Rate

A Dairy Intake Rate Dairy Intake Rate

B Above-ground, Exposed Vegetable

Intake Rate

Above-ground, Exposed

Vegetable Intake Rate

C Root Vegetable Intake Rate Root Vegetable Intake Rate

D Fish Intake Rate Fish Intake Rate

E Fruit Intake Rate Fruit Intake Rate

F NA Waste Application Rate

G NA Waste Application Frequency

H Starting Waste Concentration Starting Waste Concentration

I NA Tilling Depth

J Adult Soil Intake Rate Adult Soil Intake Rate

K Child Soil Intake Rate Child Soil Intake Rate

L Meteorological Data NA

M Distance to Receptor NA

N Waste Management Unit Area NA

Y Long Exposure Duration Long Exposure Duration

U Single Variable Place Holder Single Variable Place Holder

1 High-end parameters for all scenarios except agricultural soil amendment scenario.
Table 5-11. Draft Human Health Summary Results for Utility Coal Co-managed Wastes Managed in an

Onsite Landfill

Page 34

Ingestion Inhalation

Nickel

Silver

Thallium

Arsenic

Barium

Beryllium

Boron

Cadmium

Chromium VI

Cobalt

Selenium

Adult

Resident ! ! ! ! ! ! ! ! ! ! !

Home

Gardener ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! !2.5E-6

HN ! ! ! ! ! ! !

Child of

Farmer ! !

1.1

HN

1.7E-5

HK

1.0

HN,HK

1.3E-5

KN ! ! ! ! !

 Fisher ! ! ! ! ! ! ! ! ! ! !

Adult Res./

Home Gard. ! ! ! ! ! ! ! !

2.3E-6

HY,NY ! !

 Farmer ! ! ! ! ! ! ! !3.5E-6

HN ! !

Child of

Farmer ! ! ! ! ! ! ! !

2.5E-6

HN ! !
Table 5-12. Draft Human Health Summary Results for Utility Coal Co-managed Wastes Managed in a

Dewatered Surface Impoundment

Page 35

Ingestion Inhalation

Nickel

Silver

Thallium

Arsenic

Barium

Beryllium

Boron

Cadmium

Chromium VI

Cobalt

Selenium

Adult

Resident ! ! ! ! ! ! ! ! ! ! !

Home

Gardener ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! !2.1E-6

HL ! ! ! ! ! ! !

Child of

Farmer ! ! !

2.0E-6

HL ! ! ! ! ! ! !

 Fisher ! ! ! ! ! ! ! ! ! ! !

Adult Res./

Home Gard. ! ! ! ! ! ! ! !

1.5E-6

HY,LY ! !

 Farmer ! ! ! ! ! ! ! !2.2E-6

HL ! !

Child of

Farmer ! ! ! ! ! ! ! !

1.6E-6

HL ! !
Table 5-13. Draft Human Health Summary Results for Utility Oil Wastes Managed in Onsite Landfill

Page 36

Ingestion Inhalation

Nickel

Silver

Thallium

Arsenic

Barium

Boron

Cadmium

Chromium VI

Cobalt

Vanadium

Zinc

Adult

Resident ! ! ! ! ! ! ! ! ! ! !

Home

Gardener ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! ! ! ! ! ! ! ! ! !

Child of

Farmer ! ! !

5.3E-6

HK ! ! ! ! ! ! !

 Fisher ! ! ! ! ! ! ! ! ! ! !

Adult Res./

Home Gard. ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! ! ! ! ! ! ! ! ! !

Child of

Farmer ! ! ! ! ! ! ! ! ! ! !
Table 5-14. Draft Human Health Summary Results for FBC Wastes Managed in Onsite Landfill

Page 37

Ingestion Inhalation

Nickel

Silver

Thallium

Arsenic

Barium

Beryllium

Boron

Cadmium

Chromium VI

Cobalt

Vanadium

Adult

Resident ! ! ! ! ! ! ! ! ! ! !

Home

Gardener ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! !1.0E-6

HY ! ! ! ! ! ! !

Child of

Farmer ! ! !

8.2E-6

HK !

4.7E-6

HK ! ! ! ! !

 Fisher ! ! ! ! ! ! ! ! ! ! !

Adult Res./

Home Gard. ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! ! ! ! ! ! !1.0E-6

MY ! !

Child of

Farmer ! ! ! ! ! ! ! ! ! ! !
Table 5-15. Draft Human Health Summary Results for FBC Wastes Used as Agricultural Soil Amendment

Page 38

Ingestion Inhalation

Nickel

Silver

Thallium

Arsenic

Barium

Beryllium

Boron

Cadmium

Chromium VI

Cobalt

Vanadium

Adult

Resident ! ! ! ! ! ! ! ! ! ! !

Home

Gardener ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! ! ! ! ! ! ! ! ! !

Child of

Farmer ! ! ! ! ! ! ! ! ! ! !

 Fisher ! ! ! ! ! ! ! ! ! ! !

Adult Res./

Home Gard. ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! ! ! ! ! ! ! ! ! !

Child of

Farmer ! ! ! ! ! ! ! ! ! ! !
Table 5-16. Draft Human Health Summary Results for Non-utility Coal Co-managed Wastes Managed in an

Onsite Landfill

Page 39

Ingestion Inhalation

Nickel

Silver

Thallium

Arsenic

Barium

Beryllium

Boron

Cadmium

Chromium VI

Cobalt

Selenium

Adult

Resident ! ! ! ! ! ! ! ! ! ! !

Home

Gardener ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! ! ! ! ! ! ! ! ! !

Child of

Farmer ! ! !

1.2E-6

HN ! ! ! ! ! ! !

 Fisher ! ! ! ! ! ! ! ! ! ! !

Adult Res./

Home Gard. ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! ! ! ! ! ! ! ! ! !

Child of

Farmer ! ! ! ! ! ! ! ! ! ! !
Table 5-17. Draft Human Health Summary Results for Non-utility Co-disposed Wastes Managed in an

Offsite Commercial Landfill

Page 40

Ingestion Inhalation

Nickel

Silver

Thallium

Arsenic

Barium

Beryllium

Boron

Cadmium

Chromium VI

Cobalt

Vanadium

Adult

Resident ! ! ! ! ! ! ! ! ! ! !

Home

Gardener ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! ! ! ! ! ! ! ! ! !

Child of

Farmer ! ! !

4.9E-6

HN !

4.2E-6

KN ! ! ! ! !

 Fisher ! ! ! ! ! ! ! ! ! ! !

Adult Res./

Home Gard. ! ! ! ! ! ! ! ! ! ! !

 Farmer ! ! ! ! ! ! ! ! ! ! !

Child of

Farmer ! ! ! ! ! ! ! ! ! ! !
Draft Version: Do Not Cite or Quote June 5, 1998

Page 41

5.6 Discussion of Results

The following subsections discuss the results of the high-end analysis presented above. 

Each subsection will present the maximum calculated risk or hazard quotient and will also discuss

the number of exceedences that were observed. Exceedence is defined as a cancer risk of 1E-6 or

greater or a non-cancer hazard quotient (HQ) of 1.0 or greater. Also, the number of risks or

hazard quotients that are of potential concern are addressed. Risks or hazard quotients of

potential concern are defined as values within one order of magnitude of the risk or HQ level of

concern (i.e., risks greater than or equal to 1E-7 or HQ’s greater than or equal to 0.1.) Finally,

the driving risk parameters for the scenario and pathway under consideration are discussed.

5.6.1 Coal-fired Utility Co-managed Wastes

5.6.1.1 Onsite Landfill Scenario.

5.6.1.1.1 Ingestion Risks. For the ingestion pathways for both the farmer and child

receptors arsenic had risk exceedences. The maximum risk value for the child was 1.7E-5 and the

maximum risk value for the farmer was 2.5E-6. In addition, both barium and thallium had a

hazard quotient (HQ) that exceeded the threshold HQ (greater than or equal to 1.0) for the child

receptor. The maximum HQ for barium was 1.0 and the maximum HQ for thallium was 1.1.

Including the central tendency run, all single-variable high-end runs, and all doublevariable high-end runs, a total of 67 model runs were performed for the farmer receptor. From

these 67 model runs the farmer had 5 exceedences for arsenic. All other model runs (model runs

that did not result in an exceedence) resulted in arsenic risks are greater than 1E-8 and a

significant portion (greater than 1/2) of these risks are greater than 1E-7. The child receptor had

a total of 79 model runs and these runs resulted in 52 exceedences for arsenic, 4 exceedences for

thallium, and 2 exceedences for barium. All other model runs resulted in arsenic risks greater than

1E-7 and thallium HQ’s greater than 0.1 . For barium, 23 of the other model runs resulted in

HQ’s greater than 0.1.

The starting waste concentration was the driving risk parameter for both the farmer and

child receptors -- being one of the high-end parameters in all maximum exceedences. Other

parameters that contributed to exceedences for the farmer include: exposure duration, WMU area,

dairy intake rate, and distance to receptor. For the child receptor the most important parameters,

other than starting waste concentration include: child soil intake rate, distance to receptor, and

WMU area.

5.6.1.1.2 Inhalation Risks. Chromium VI is the only constituent that showed excess risks

for the inhalation pathway. It did so for all receptors. The highest risk value was 3.5E-6 for the
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7

 All adult receptors have the same inhalation rate, exposure time, exposure frequency, body weight, and

are exposed to the same air concentration. Therefore, the only difference between receptors is exposure duration. 

Because the home gardener and adult resident have the same exposure durations, they are combined for the

inhalation pathway.

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farmer. The other maximum risks were 2.5E-6 for the child and 2.3E-6 for the adult

resident/home gardener.7

Including the central tendency model run, the single-variable high-end runs, and the

double-variable high-end runs there were 16 model runs performed. The farmer showed six

exceedences for chromium VI while the child showed five exceedences for chromium VI and the

adult resident/home gardener showed four exceedences for chromium VI. All results, except for

two results for the adult resident/home gardener, showed risk levels greater than 1E-7. There

also were several arsenic risk levels that exceeded 1E-7 and a small number of barium HQ’s that

exceeded 0.1.

Similar to the ingestion pathway, the starting waste concentration is the driving risk

parameter -- being one of the high-end parameters in all maximum exceedences. Other important

parameters include exposure duration, distance to receptor, and WMU area.

5.6.1.2 Dewatered Surface Impoundment Scenario.

5.6.1.2.1 Ingestion Risks. Only arsenic showed exceedences for this exposure pathway. 

Both the farmer and child receptors showed excess risks with maximum values of 2.1E-6 and

2.0E-6 respectively. 

The farmer showed five exceedences in 67 model runs (as discussed in Section 5.6.1.1.1,

there were a total of 67 model runs including central tendency, single-variable high-end, and

double variable high-end runs) while the child showed three exceedences in 79 model runs. All

other arsenic results (results other than the exceedences) for both the farmer and child yielded

risks greater than 1E-8 with the majority of the risk values greater than 1E-7. No other

constituent showed risks or HQ’s within an order of magnitude of the target level.

Starting waste concentration was the driving risk parameter for both the child and farmer

receptors. Other important high-end parameters include meteorological location, exposure

duration, WMU size, distance to receptor, and dairy products intake rate. 

5.6.1.2.2 Inhalation Risks. Chromium VI is the only constituent that showed excess

risks for the inhalation pathway. It did so for all receptors. The highest risk value was 2.2E-6 for

the farmer receptor. The other maximum risks were 1.6E-6 for the child and 1.5E-6 for the adult

resident/home gardener. 
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The farmer scenario showed six exceedences out of 16 model runs for Chromium VI while

the child showed only one exceedences and the adult resident/home gardener showed two

exceedences. All results, except for two results for the adult resident/home gardener receptor and

the central tendency results for all receptors, showed risk levels greater than 1E-7. There also are

several arsenic risk levels that exceed 1E-7 for all receptors but there are no exceedences for

arsenic.

Starting waste concentration was the driving risk parameter -- being one of the high-end

parameters in all maximum exceedences. Other driving high-end parameters include exposure

duration, meteorological location, and distance to receptor.

5.6.2 Oil-fired Utility Wastes

5.6.2.1 Onsite Landfill Scenario.

5.6.2.1.1 Ingestion Risks. Only arsenic for the child receptor resulted in excess risks with

a maximum risk of 5.3E-6. Eleven of 67 model runs showed excess risks for the child receptor. 

(Note that there were only 67 model runs for the child receptor for this scenario because there is

no high-end WMU size.) Four other child model runs resulted in risks greater than 1E-7. For the

farmer, there were no risks greater than 1E-6; however, 10 runs resulted in arsenic risks greater

than 1E-7. For both the home gardener and the adult resident, one run resulted in arsenic risks

greater than 1E-7. In addition, all vanadium HQ’s were greater than 0.1 for the child receptor.

Starting waste concentration was the driving risk parameter showing an excess risk when

modeled as the single high-end parameter and therefore showing risks when combined with all

other high-end parameters. No other high-end parameter was significant in itself.

5.6.2.1.2 Inhalation Risks. There were no exceedences for the inhalation exposure

pathway. There were however several chromium VI risk results that were greater than 1E-7 for

all receptors (seven exceedences for both the child and farmer and three exceedences for the adult

resident/home gardener). In addition, there were a few nickel risk values that were greater than

1E-7 for all receptors (one for the adult resident/home gardener, three for the farmer, and two for

the child) and one arsenic value greater than 1E-7 for both the farmer and child receptor.

5.6.3 FBC Wastes

5.6.3.1 Onsite Landfill Scenario.

5.6.3.1.1 Ingestion Risks. Only arsenic showed exceedences for this pathway. Both the

farmer and child showed excess risks with maximum risk values of 1.0E-6 and 8.2E-6

respectively. 
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The farmer showed only one exceedence in 67 model runs while the child showed 22

exceedences in 79 model runs. All other arsenic results for both the farmer and child yielded risks

greater than 1E-8 with the majority of the risks greater than 1E-7. In addition, the adult resident

and home gardener each yielded two results with risks greater than 1E-7 for arsenic. There also

were 11 instances where vanadium yielded HQ’s greater than 0.1 for the child receptor.

Waste concentration was the driving risk parameter for both the farmer and child

receptors. Child soil intake was also an important risk parameter for the child receptor. 

5.6.3.1.2 Inhalation Risks. There was only one exceedence for this exposure pathway —

one model run for the farmer yielded a risk of 1.0E-6. All but two runs yielded risks greater than

1E-7 for the farmer receptor and a significant portion of the runs for the adult resident/home

gardener and child receptors yielded risks greater than 1E-7 ( seven for the adult resident/home

gardener and 10 for the child).

Distance to receptor and exposure duration were the driving risk parameters.

5.6.3.2 Agricultural Soil Amendment Scenario. There were no exceedences for this

scenario. Further, there were no risks in excess of 1E-7 nor any HQ’s greater than 0.1.

5.6.4 Coal-fired Non-utility Wastes

5.6.4.1 Onsite Landfill Scenario.

5.6.4.1.1 Ingestion Risks. There was only one exceedence for this pathway. Arsenic for

the child receptor yielded a risk value of 1.2E-6 when both the waste concentration and WMU

area were set at high-end. Twenty-two of the other runs for the child yielded results greater than

1E-7. Only one run for the farmer scenario yielded a risk value greater than 1E-7. There was

only one occurrence of an HQ greater than or equal to 0.1. This was for thallium for the child

receptor with a value of 0.1.

5.6.4.1.2 Inhalation Risks. There were no inhalation risk exceedences for this pathway. 

Further, there were only three occurrences (two for the farmer and one for the child) of risk

values greater than 1E-7 -- the greatest of these values being 1.4E-7.

5.6.4.2 Offsite Commercial Landfill Scenario.

5.6.4.2.1 Ingestion Risks. Only arsenic ingestion for the child receptor showed excess

risks for this scenario. The maximum child risk was 4.9E-6.

The child showed four exceedences in 79 model runs. Slightly more than 1⁄2 of the

remaining child risks were greater than 1E-7. The child receptor also had 11 HQ’s for thallium
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greater than 0.1 and two HQ’s for barium greater than 0.1. Also, the farmer receptor showed six

risk results for arsenic greater than 1E-7.

Waste concentration was the driving risk parameter. Other important parameters included

WMU area, child soil ingestion rate, and distance to receptor.

5.6.4.2.2 Inhalation Risks. There were no inhalation risk exceedences for this scenario. 

For chromium VI there were occurrences of risk greater than 1E-7. These included one

occurrence for the adult resident, four occurrences for the farmer, and two occurrences for the

child with the highest risk being 2.2E-7 for the farmer.

5.7 Risks from Mercury

Modeling mercury in the environment is a complex issue. Mercury was not modeled in

this analysis. Mercury levels are low in the wastes in which it was detected. There was no

mercury reported in the coal co-managed waste analytical data. For FBC waste the maximum

concentration was 2.78 ppm while the maximum concentration in oil combustion wastes was 0.38

ppm. Due to the volatility of mercury and the environment of the fossil fuel combustion process,

most mercury is emitted from the stack. 

The major reason for non-inclusion in this analysis is that the risk assessment methodology

for mercury is much more complex than for other metal constituents and the methodology is

under review by EPA’s Office of Research and Development. Fate and transport modeling for

mercury requires a complex analytical framework that accounts for both the species-specific

mobility of mercury between media compartments as well as the interconversion between different

species as mercury equilibrates within individual compartments. A draft Report to Congress

(RTC) for Science Advisory Board (SAB) review was released in June 1996. This RTC proposed

a methodology for modeling mercury. Based on SAB review, a final RTC was issued in January,

1998 that included significant changes to the methodology presented in the review draft RTC. 

The timeframe for this analysis did not allow for the new methodology to be developed into a

modeling tool and utilized in this project.

Finally, even if the modeling methodology and capabilities were developed, speciation data

at the source are needed to employ the methodology in the RTC. Only total mercury

concentrations were supplied in the analytical data provided to RTI.

5.8 Risks from Lead

Because lead does not have human health toxicity benchmarks (i.e.,RfC, RfD, CSF) risks

or hazard quotients cannot be calculated. However, lead does have the potential for adverse

health and developmental effects especially for children. To estimate the potential for adverse

effects from lead, maximum lead soil concentrations for each scenario were compared to the lead
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screening level of 400 mg/kg from Revised Interim Soil Lead Guidance for CERCLA Sites and

RCRA Corrective Action Facilities (U.S. EPA, 1994). The Risk Assessment Guidance for

Superfund (RAGS) (U.S. EPA, 1989) has established this is the maximum safe lead concentration

for child soil ingestion based on a risk analysis. Table 5-18 presents the maximum lead soil

concentrations that were calculated for each scenario that was modeled. All lead soil

concentrations fall well below 400 mg/kg. It is therefore concluded that lead soil levels resulting

from the management and use of FFC wastes are unlikely to cause a significant threat to human

health.

5.9 Risks from Beryllium

The ingestion CSF for beryllium was removed from the Integrated Risk Information

System (IRIS) on April 3, 1998. All modeling for this project had already been completed using

the ingestion CSF of 4.3 (mg/kg/day)-1. The RfD for beryllium has also recently been revised to

2E-3 mg/kg/day. To ascertain the potential for adverse health effects from beryllium utilizing the

new RfD from IRIS the same scenario that resulted in the highest cancer risk value for beryllium

was duplicated except the RfD was utilized instead of the CSF. This would result in the

maximum HQ that would be expected to occur for all scenario/pathway/receptor combinations. 

Therefore, the child ingestion pathway for the utility coal-fired co-managed waste managed in an

onsite landfill scenario with child soil ingestion and WMU area set to high-end values was

recalculated using the RfD instead of the CSF. The resulting HQ was 0.02. Therefore, it is

assumed that beryllium in FFC wastes, as modeled, does not pose significant threat to human

health.

Table 5-18. Maximum Estimated Lead Concentrations in Soil Per Scenario

Scenario Lead Soil Concentration

(mg/kg)

Utility Coal-fired Co-managed Waste Onsite Landfill 7.63

Utility Coal-fired Co-managed Waste Dewatered

Surface Impoundment

1.30

Utility Oil-fired Waste Onsite Landfill 0.98

FBC Onsite Landfill 0.81

FBC Used as Soil Amendment 0.009

Non-utility Coal-fired Waste Onsite Landfill 0.21

Non-utility Coal-fired Waste Offsite Landfill 1.33

6.0 ECOLOGICAL RISK ASSESSMENT OF COMANAGED FOSSIL FUEL

COMBUSTION RESIDUALS
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This section describes the ecological risk assessment (ERA) developed to evaluate the

potential ecological risks associated with the management and use of comanaged fossil fuel

combustion (FFC) residuals. This section is intended to complement the human health risk

analysis and the SAIC Background Document and, therefore, detailed information on

management practices and fate and transport modeling of FFC constituents has not been included. 

This section is organized as follows. Section 6.1 describes the overall technical approach for the

ERA process of comanaged FFC residuals. Sections 6.2 through 6.4 describe the three basic

phases of the ERA process: problem formulation; analysis; and risk characterization; and provide

sufficient detail to repeat all calculations used in the analysis. Two critical products from this

ERA are included in Appendices I and J, respectively: (1) the stressor-response profiles for

constituents of potential ecological concern (CPECs) found in FFC residuals and (2) the

calculation spreadsheet used to estimate the ecological risks associated with the management and

use of FFC residuals. The calculation spreadsheet includes all of the inputs required to calculate

chemical stressor concentration limits (CSCLs) for the CPECs considered in this analysis,

background soil concentrations of CPECs, and comparisons of CSCLs developed for the FFC

ERA with criteria used in other programs and agencies. Conclusions are summarized in Section

6.5

6.1 Technical Approach for ERA of Comanaged FFC Residuals

The technical approach developed to evaluate the potential for adverse ecological effects

associated with the management and use of comanaged FFC residuals follows EPA’s Guidelines

for Ecological Risk Assessment (U.S. EPA, 1996a). The Guidelines describe the three basic

phases that frame the ecological risk assessment process, namely; problem formulation, analysis,

and risk characterization. The framework advocated in the Guidelines has been adopted by OSW

for all ecological risk assessment work conducted in support of regulatory determinations (e.g.,

HWIR, silver delisting, hazardous waste combustion). Briefly, these phases may be summarized

as follows:

Problem formulation phase - Defines the problem by answering these questions: (1)

What are the constituents of concern? (2) Once released, what is the environmental behavior of

the constituents (e.g., persistence, bioaccumulation, speciation)? (3) Given the source

characterization (e.g., size, geographical location), what ecosystems and ecological receptors are

potentially at risk? (4) What adverse ecological effects are possible following exposure? The

three key activities in this phase are: (1) the selection of assessment endpoints, (2) development of

a conceptual model, and (3) preparation of an analysis plan.

Analysis phase - Provides estimates of the constituent concentrations in the environment

to which ecological receptors are exposed (i.e., exposure profile) and develops chemical stressor

concentration limits, or CSCLs, from data on adverse ecological effects on various receptors (i.e.,

acceptable concentrations in environmental media).
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Risk characterization phase - Compares the modeled exposure concentrations to the

chemical stressor concentration limits (CSCLs) developed in the analysis phase to estimate the

potential for adverse ecological effects (i.e., the hazard quotient, or HQ, approach). Includes a

risk description of the assessment (e.g., limitations) and discusses the ecological significance of

HQ exceedances.

The technical approach shown in Figure 6-1 was developed to provide a tiered strategy for

the assessment of ecological risks. The tiers progressed from a highly conservative on-site

screening assessment to an off-site modeling exercise of CPEC release and transport for central

tendency management and use practices. The tiers consisted of four different assessments for

management and use practices of comanaged FFC residuals:

1. on-site screening (problem formulation);

2. bounding assessment (analysis phase);

3. high-end assessment (analysis phase); and

4. central tendency assessment (analysis phase).

Although the progression of the bounding assessment through the central tendency

assessment is shown in the analysis phase, the process was iterative in that CPECs could be

removed from further consideration at any point in the progression. Hence, the decision in Item

#7 (Do the modeled exposure concentrations exceed the CSCLs?) could have resulted in removal

of the CPEC for the bounding, high-end, or central tendency assessments. Each tier is described

briefly below.

On-site screening - As part of the problem formulation, CSCLs were compared directly

with maximum concentrations of CPECs found in comanaged FFC residuals (both total

concentrations and pore water concentrations). Although direct comparison of ecological effects

levels with waste concentrations is highly conservative, the results provided important insights

into the potential ecological risks and were instructive in identifying CPECs . For example,

concentrations of a number of CPECs were below the CSCLs or were within a factor of 10. 

Given the level of conservatism in the comparison, the CPEC/CSCL ratios below 10 were

considered to be strongly suggestive of de minimis potential ecological impacts.
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Figure 6-1. Technical Approach Developed for Era of Management & Use of Comanaged Ffc

Residuals
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Bounding assessment - During the analysis phase, all parameters for the fate and

transport model (including source area sizes and concentrations) were set at high-end values that

approximated the 95th percentile. The off-site concentrations in soils and surface waters represent

the extreme tail of the exposure distribution and, therefore, comparison with the CSCLs provided

a conservative tool to evaluate off-site exposures. It is important to recognize that the intent of

the bounding assessment is to indicate whether additional ecological analyses are required, not to

support a regulatory decision. As with the on-site screening, CPEC/CSCL ratios below 10 were

considered to be strongly suggestive of de minimis potential for ecological impacts.

High-end assessment - During the analysis phase, CPECs that were not ruled out for the

bounding analysis were evaluated for high-end management and use practices. The high-end

exposure assessment is defined by setting the two most sensitive model parameters to high-end

values (i.e., approximating 95th percentile) and setting all other model parameters to central

tendency values. In virtually all cases, the two parameters set to high-end values were source

concentration and source area.

Central tendency assessment - During the analysis phase, CPECs that were not ruled out

for the high-end assessment were evaluated for central tendency management and use practices.

The central tendency assessment is defined by setting all model inputs to central tendency values.

Note that the CSCLs and underlying assumptions (e.g., 100% of the diet originates on

contaminated area) remain constant throughout the analysis. Consequently, the comparison of

CSCLs with off-site CPEC concentrations is, for most ecological receptors, inherently

conservative. 

6.2. Problem Formulation

As described in EPA’s Proposed Guidelines for Ecological Risk Assessment (U.S. EPA,

1996), a successful problem formulation “depends upon the quality of three products: (1)

assessment endpoints that adequately reflect management goals and the ecosystem they represent,

(2) conceptual models that describe key relationships between a stressor and assessment endpoint

or among several stressors and assessment endpoints, and (3) an analysis plan.” Although these

products are presented sequentially below, it is important to note that the problem formulation

phase (like the ERA process) is iterative in nature.

6.2.1 Selection of Assessment Endpoints

Perhaps the most important step in the problem formulation phase is the selection of

assessment endpoints, defined as “explicit expressions of the actual environmental value that is to

be protected” (EPA, 1996). The assessment endpoints serve as a critical link between the

ecological risk assessment (ERA) and the management goal which, for the FFC ERA, may be

stated as follows: “to evaluate the potential for adverse ecological effects associated with the 
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management, and/or use of comanaged FFC residuals.” The assessment endpoints must be

ecologically relevant to the ecosystem(s) they represent and susceptible to the stressors of

concern, in this case the CPECs found in FFC residuals. Candidates for assessment endpoints

often include threatened/endangered species, critical habitats and ecosystems, commercially or

recreationally important species, functional attributes that support food sources or flood control,

or aesthetic values, such as the existence of charismatic species like eagles (U.S. EPA 1996a).

Regardless of the assessment endpoint(s) chosen for this analysis, it should be emphasized that

each assessment endpoint is defined by two key elements: (1) a valued ecological entity (e.g., a

species) and (2) an attribute of that entity is important to protect (e.g., reproductive fitness).

For the FFC ERA, the assessment endpoints were chosen to be consistent with the

assessment endpoints selected for the proposed Hazardous Waste Identification Rule (HWIR). As

with the HWIR, ecological exposures are presumed to occur anywhere in the contiguous United

States. Consequently, a suite of assessment endpoints was chosen based on: (1) their significance

to the ecosystem, (2) their position along a continuum of trophic levels, and (3) their susceptibility

to metals based on exposure and/or toxicological sensitivity. In Table 6-1, the assessment

endpoints (i.e., values to be protected) are defined in terms of: (1) the significance of an

ecological entity, (2) the ecological receptor representing that entity, (3) the characteristic about

the entity that is important to protect, and (4) the measures of effect used to predict risk. The

intent of including multiple receptors is that, by protecting producers (i.e., plants) and consumers

(i.e., predators) at different trophic levels, as well as certain structural components (e.g., benthic

community), a degree of protection from CPECs may be inferred to the ecosystem as a whole.

 

In addition to evaluating representative species populations and communities, it is also

important to consider the potential effects on, managed lands (e.g., National Wildlife Refuges),

critical habitats (e.g., wetlands), and threatened and endangered species. Although metrics to

evaluate the impacts on the ecological “health” of these entities are not available for use in this

type of analysis, the presence of valued habitats and species may require a different approach in

assessing ecological impacts associated with CPEC releases. However, these assessment

endpoints were not evaluated since the FFC ERA was a national rather than a site-based analysis.

Subsequent to assessment endpoint selection, the conceptual model for this bounding

analysis was developed through a synthesis of information generated under the activities indicated

in Item #3 in Figure 6-1. By integrating the data developed under each activity, a conceptual

model was developed that included three source scenarios: (1) landfilling of FFC residuals, (2)

management in surface impoundments (i.e., settling basins), and (3) application to agricultural

soils. For each scenario, potential ecological receptors were identified along with exposure

pathways of concern. This conceptual model frames the entire screening analysis of 
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ecological risks and, therefore, each of these activities is described below in Sections 6.2.1.1

through 6.2.1.4. Some sections are intentionally brief to avoid duplication with the SAIC

Background Document.

6.2.1.1 Characterization of Constituent Behavior and Toxicity

Constituent behavior - The CPECs in comanaged FFC residuals include essential and

non-essential metals at concentrations both above and below background soil concentrations in

the United States (see Table 2.2 in Appendix J for a list of soil background concentrations). 

Nevertheless, the behavior of metals in the environment depends on the specific geochemistry of

the ecosystem as defined by a number of characteristics such as: pH, concentration of competing

constituents (e.g., other metals), availability of inorganic moieties to react with metal (e.g., sulfide

and chloride ions), concentration of dissolved organic matter (DOC), and concentration of total

suspended solids (TSS). For example, studies on fish have shown that organic acids (e.g., humic,

fulvic) bind tightly to metals reducing their bioavailability and, ultimately, their toxicity

(Hutchinson and Sprague, 1987). Thus, water quality characteristics directly influence the

partitioning of metals between particles and soluble species and determine the fraction of free

ionic metal to which biota are exposed. This last point is particularly important for aquatic biota

since a preponderance of studies have demonstrated that organism response is correlated with free

metal ion (Allen and Hansen, 1996). Section II of the stressor-response profile in Appendix I of

this report contains a concise discussion of the geochemistry of each CPEC in soils, surface

waters, and sediments, respectively. The profiles pay particular attention to the predominant

metal species in each medium as well as the relationship between bioavailability and environmental

characteristics in terrestrial and aquatic ecosystems (e.g., pH, DOC).

Constituent toxicity - The majority of the ecotoxicological data identified for CPECs was

based on acute and chronic laboratory results for mammals, birds, terrestrial plants, aquatic

species, (e.g., fish, invertebrates, algae, amphibians, and the benthic community), and the soil

community (e.g., earthworms). Ranges of effects are presented in Section III of the stressorresponse profiles (see Appendix I). In addition, the profiles address the following issues: 

C concentrations for acute and chronic endpoints; 

C potential for bioaccumulation;

C conditions that influence bioavailability;

C relative sensitivities of various receptors; and

C ecotoxicity data gaps. 

A figure is provided in each profile illustrating the range of acute and chronic effects data in

general taxa groups. Information regarding the observed responses of exposed receptors (e.g.,

toxicity endpoints such as organ damage, teratogenecity, neurotoxicity) are outlined briefly. 
Page 53

Table 6-1. Suite of Assessment Endpoints Considered for the FFC ERA

Ecological Significance Assessment Endpoint Receptors Characteristic(s) Measure of Effect 

C Upper trophic level consumers

C Socially valued (e.g., endangered species)

C Top recipients of bioaccumulative chemicals

C Represent species with large foraging ranges 

C Represent species with longer life spans

viable mammalian wildlife

populations

e.g., deer mouse,

meadow vole, red fox

reproductive and

developmental success

chronic or subchronic NOAEL(s) or

LOAEL(s) for developmental and

reproductive effects

viable avian wildlife populations e.g., red-tailed hawk,

northern bobwhite

reproductive and

developmental success

chronic or subchronic NOAEL(s) or

LOAEL(s) for developmental and

reproductive effects

C Species represent unique habitat niches (e.g., partially aquatic

and terrestrial)

C Some species are sensitive to contaminant exposure

viable amphibian and reptile

wildlife populations (“herps”)

e.g., frog, newt, snake,

turtle

reproductive and

developmental success

chronic or subchronic NOAEL(s) or

LOAEL(s) for developmental and

reproductive effects

C Represents base food web in terrestrial systems

C Habitat vital to decomposers and soil aerators 

C Proper soil community function related to nutrient cycling 

sustainable soil community

structure and function

e.g., nematodes, soils

mites, springtails,

annelids, arthropods

growth, survival, and

reproductive success

95% of species below no effects

concentration at 50th percentile

confidence interval

C Primary producers of energy in ecosystems

C Act as food base for herbivores

C Able to sequester some contaminants

C Can act as vectors to bioaccumulation

C Constitute a large fraction of the earth’s biomass

maintain primary terrestrial

producers (plant community)

e.g., soy beans, alfalfa,

rye grass

growth, yield,

germination

10th percentile from LOEC data

distribution

C Highly exposed receptors from constant contact with

contaminated media

C Act as vectors to transfer contaminants to terrestrial species

sustainable aquatic community

structure and function

e.g., fish (salmonids),

aquatic invertebrates

(daphnids)

growth, survival,

reproductive success

ambient water quality criteria

(NAWQC) for aquatic life (95%

species protection)

C Provide habitat for reproductive lifestages (e.g., eggs, larval

forms)

C Habitat for key invertebrate species

C Act to process nutrients and decompose organic matter

sustainable benthic community

structure and function

e.g., protozoa, flat

worms, ostracods

growth, survival,

reproductive success

10th percentile from LOEC data

distribution

C Primary producers of energy in the aquatic system.

C Base food source in the aquatic system

C Can act to sequester contaminants from the water column

C Act as substrate for other organisms in the water column (e.g.,

periphyton)

maintain primary aquatic

producers (algal & plant

community)

e.g., algae and

vascular aquatic plants

growth, mortality,

biomass, root length

EC20 for algae; lowest LOEC for

aquatic plants
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In addition to laboratory toxicity data, literature describing field studies of the environmental

effects of FFC residuals and CPECs was examined. A number of articles were identified linking

adverse effects in amphibians (and other biota) with exposure to sluiced ash that is pumped into a

series of settling basins and, ultimately, into a two hectare drainage swamp. The drainage swamp

at the Savannah River Site historically received effluent from other coal ash settling basins that are

no longer in use (Rowe et al., 1996). Various studies related to this site (e.g., Cherry et al., 1984;

Guthrie and Cherry, 1979; Hopkins et al., 1997) have demonstrated that effects ranging from

mortality to sublethal endpoints such developmental anomalies are causally linked to the presence

of elevated concentrations of trace elements found in coal ash residuals. In particular, selenium

has been shown to be toxic to amphibians at relatively low levels of exposure (e.g., Browne and

Dumont, 1979). In addition, accumulation of selenium (a common trace metal in FFC residuals)

has been demonstrated in both terrestrial (e.g., Carlson and Adriano, 1993) and aquatic

ecosystems (e.g., Lemly, 1985; Ohlendorf et al., 1990; Saiki et al., 1993). Many studies

suggested that effects were caused by the properties of FFC ash (e.g., low pH; siltation; high

soluble salts concentration; pozzolanic action) as well as the trace metals in combustion ash.

6.2.1.2 Source Characterization for CPEC Releases from Comanaged FFC Residuals

The source characterization for the management, disposal, and beneficial use of

comanaged FFC residuals is described in detail in the SAIC Background Document. In brief, three

major types of wastes were evaluated: (1) utility and non-utility comanaged residuals, (2) utility

oil combustion residuals, and (3) fluidized bed combustion residuals. As depicted in Table 6-2,

the FFC ERA considered potential release and exposure for landfill disposal, surface

impoundment management, and application to agricultural areas as a soil amendment (FBC ash

only).

Table 6-2. Matrix Summarizing Waste Residuals Evaluated for Each Source

management

unit

coal

comanaged

residuals

FBC

combined

ash

oil fly ash oil bottom

ash

oil settling

basin solids

landfill yes yes yes yes yes

surface

impoundment yes yes

soil amendment yes
Draft Version: Do Not Cite or Quote June 5, 1998

Page 55

Aluminum

Antimony

Arsenic

Barium

Beryllium

Boron

Cadmium

Chromium

Cobalt

Copper

Lead

Mercury

Molybdenum

Nickel

Selenium

Silver

Thallium

Vanadium

Zinc

CPECs Selected for FFC ERA

Combustion of coal and other fossil fuels produces

a variety of residuals including, for example, fly ash,

bottom ash, flue gas desulfurization (FGD sludge),

fluidized bed combustion (FBC) ash, coal gasification ash,

oil fly ash, oil bottom ash, and oil settling basin solids. The

physical, chemical, and mineralogical characteristics of

these comanaged residuals depend on a variety of factors

such as the composition of the parent fuel (e.g., sulfur

content in coal), the efficiency and type of emission control

devices, the character of comanaged wastes, and the

management methods used. As a result, it is difficult to

generalize about the composition and properties of FFC

residuals or their behavior in the environment (Carlson and

Adriano, 1993). For example, ash pH can vary from 4.5 to

12 depending on the S content of the parent coal, with

high-S, eastern coals typically producing acidic ashes and

low-S, western coals frequently producing alkaline ashes

(Adriano et al., 1980). The pH of the ash is particularly

important with regard to ecological effects since many

metals are more mobile and toxic at lower pHs (e.g., Jung

and Jagoe, 1995). Although additional detail on

comanaged FFC residuals is available in the SAIC

Background Document, it is useful to point out several

common characteristics in FFC residuals that are relevant to environmental behavior and potential

effects associated with their release:

C many residuals exhibit pozzolanic properties, i.e., they react with water in the

presence of lime to form cement (e.g., Adriano et al., 1980);

C most residuals are enriched in trace elements including both essential (e.g, Se, Ca,

Zn) and non-essential metals (e.g., As, Hg, Sb);

C trace elements tend to be concentrated on smaller ash particles (Adriano et al.,

1980); and

C particle sizes range from 0.01 μm for fly ash to >2 mm for bottom ash comanaged

with boiler slag (Carlson and Adriano, 1991).

The constituents of potential ecological concern were selected based on: (1) availability of

ecotoxicological data and criteria on metals, particularly those evaluated under the HWIR, (2)

evidence of adverse effects and uptake of metals in the scientific literature, especially from case

studies involving FFC residuals, and (3) presence of constituents in sampled residuals. Where
Draft Version: Do Not Cite or Quote June 5, 1998

Page 56

possible, metal species were considered along with total metal concentrations (e.g., Cr3+ and Cr6+;

As3+ and As5+). However, quantitative criteria were available only for aquatic exposures.

6.2.1.3 Identification of Ecosystems/Ecological Receptors Potentially at Risk

Essentially three types of information were used to identify ecosystems and receptors

potentially at risk from exposure to CPECs released from comanaged FFC residuals: source

location, CPEC behavior, and ecological effects.

Location of Sources—Because FFC landfills and surface impoundments may be located

virtually anywhere within the conterminous United States, ecosystems potentially at risk include

the full array of ecoregions as defined by Bailey (1996). Consequently, ecosystems potentially at

risk include the same subset as those evaluated for the HWIR proposed rule. In addition, the

literature reviewed regarding field assessments of FFC residual management and use practices

indicated that impacts were possible on a variety of terrestrial and aquatic habitats (see, for

example, Carlson and Adriano, 1993; Cherry et al., 1984; Golden, 1983). As with the HWIR, a

generic scheme of freshwater aquatic and terrestrial ecosystems was chosen to provide the

screening-level context for selection of ecological receptors. Freshwater ecosystems include a

variety of waterbodies such as lakes and streams, and terrestrial ecosystems are soil-based ecosystems such as forests and grasslands. This coarse level of resolution was deemed appropriate for a

bounding analysis, particularly since site-specific risk assessment work was not envisioned for this

study.

Environmental Behavior of CPECs—Although the geochemistry of the ecosystem will

determine what fraction of metal is bioavailable to various biota, the range of partition coefficients

indicates that many of the CPECs will be particle-bound and tend to move with the soil particles

and deposit to adjacent soils or to nearby surface waters. Indeed, soils and sediments serve as

environmental sinks for metal contamination; high sediment levels of trace metals have been

shown in an ash drainage system (Guthrie and Cherry, 1979). Consequently, ecological receptors

that live in close contact with the contaminated media (soil, sediment) and receptors in the lower

trophic levels that are exposed through direct contact and ingestion of contaminated media and

prey (e.g., worms) were considered to be potentially at risk. In addition, data on the

bioaccumulation potential strongly suggested that food web exposure to upper trophic level

predators is unlikely for most of the constituents evaluated in this screen; notable exceptions

include: arsenic - uptake by plants may result in elevated exposures to herbivores; mercury -

uptake by aquatic organisms may lead to significant exposures in animals that eat fish and/or

aquatic invertebrates; and selenium - accumulation from coal ash residuals has been demonstrated

in both terrestrial and aquatic systems (e.g., Cherry and Guthrie, 1977; Lemly, 1985; Mandisoza

et al., 1980).

Ecological Effects Data on CPECs—As noted above, effects data on trace metals found

in comanaged FFC residuals were identified on virtually all types of receptors that are typical of
Draft Version: Do Not Cite or Quote June 5, 1998

Page 57

terrestrial and aquatic habitats. Of particular concern are the recent data on trace metal impacts

on amphibians (e.g., two articles by Rowe et al., in press in Physiological Zoology and Copiea,

respectively). In addition, research conducted by Freda (1991) on amphibians strongly suggested

that temporary breeding ponds may be particularly at risk from wastes that are acidic and contain

trace metals. As an example, the author noted that a by-product of coal mining is the mobilization

of iron pyrite (FeS). This compound is oxidized in the presence of bacteria to form sulfuric acid

and, as a result, may enhance the toxicity of trace metals. Importantly, Freda pointed out that an

estimated 30% to 50% of all species of caudates (salamanders) and anurans (frogs), respectively,

use temporary ponds for breeding and many of these species reproduce in them exclusively. 

Given the total area likely to be impacted by comanaged FFC residuals, it appears likely that some

fraction of these temporary ponds may be affected. It should be noted that the effects of concern

from these exposures are often sublethal endpoints that influence the growth, metamorphosis, and

subsequent reproduction. Rowe et al. (1996) observed a considerable abundance of bullfrog

tadpoles in the settling basins and receiving swamp at the Savannah River Site despite the

presence of elevated trace metals, suggesting that conditions were not severe enough to cause

widespread mortality in developing larvae of this species. Although visual inspection of the site

would not have suggested that any adverse effects were occurring, the study data indicate that

oral deformities were occurring in tadpoles in the drainage system and that these deformities

result in a reduction in survival ability. 

6.2.2.4 Identification of Exposure Pathways of Concern

The identification of exposure pathways of concern is a function of all of the activities

conducted during the conceptual model development. These activities share a common goal in

that they are intended to characterize the exposure scenario that is evaluated for the on-site

screening and the bounding, high-end, and central tendency assessments. Tables 6-3 through 6-5

present the exposure scenarios developed and summarize information on the industrial sector,

overall strategy, exposure pathways, routes and receptors, and key assumptions, issues, and

inputs. Ecological exposure pathways considered in the FFC ERA include:

C overland transport and ingestion of contaminated medium and food;

C overland transport and direct contact with contaminated medium;

C aerial dispersion, deposition, and direct contact with contaminated medium;

C aerial dispersion, deposition, and ingestion of contaminated medium and food;

C ingestion of contaminated aquatic organisms from the surface impoundment;

C ingestion of contaminated surface water in the impoundment (i.e., surface

impoundment used as drinking water source);

C direct contact with surface impoundment waters for amphibians (acute effects

only); and

C leaching to groundwater and subsequent discharge to surface waters and wetlands

has not yet been evaluated.
Table 6-3. Development of Exposure Scenario for the ERA of FFC Residuals Comanaged in Landfills

Page 58

Sectors:

Waste Concentrations:

Waste Management:

comanaged wastes from Utility Coal, Utility Oil, FBC (CIBO)

coal ash residuals (fly ash, bottom ash, FGD sludge), FBC ash, oil fly ash, oil bottom ash, oil settling basin solids

landfill

Strategy: As with the exposure scenario constructed to evaluate health risks, the combination of assumptions (e.g., area, concentrations) tends to overstate

the constituent releases to surface pathways and, to a lesser degree, subsurface pathways. Because ecological receptors may be exposed to constituents

through the same media via similar pathways as are human receptors, this scenario is also presumed to rule out the following scenarios for ecological risks:

(1) coal ash comanagement landfills, (2) dewatered coal ash comanagement impoundments, (3) coal ash minefills, (4) FBC ash landfills, (5) dewatered FBC

ash impoundments, (6) FBC ash minefills, and (7) oil ash landfills. 

 Pathway Route Receptors Key assumptions, issues, and inputs

leaching,

recharge to

aquatic

ecosystem,

wetlands

direct

contact

ingestion

aquatic &

sediment

biota,

amphibians

mammals,

birds, herps

The issue of surface water recharge for metals presents a number of complicated, albeit solvable, modeling

issues (e.g., speciation in the subsurface; sediment sorption). Although many metals are relatively immobile in

the subsurface due to strong binding attractions to organics and charged ions (e.g., clay), metal mobility is

strongly influenced by site-specific soil and aquifer conditions, including pH and binding capacity (e.g., as a

function of anion concentrations such as FeOx). Because subsurface movement of these constituents tends to

be somewhat limited, exposures to animals that feed on aquatic biota (e.g., piscivores) are presumed to be

below exposures for pathways involving overland transport or aerial emissions from a landfill to an aquatic

ecosystem (see below). Consequently, food chain exposures may not need to be considered in this pathway. 

Nevertheless, this scenario may pose ecological risks to receptors in direct contact with contaminated sediments

and surface waters and should be evaluated in the future. 

overland

transport to

terrestrial

ecosystem

direct

contact

ingestion 

soil biota,

plants

mammals,

birds, herps

Overland transport of metal constituents from a landfill to an adjacent terrestrial ecosystem, through the

watershed, and into surface water requires essentially the same assumptions as applied to the health risk

scenario. In addition, it is important to note that contamination of an adjacent ecosystem would generally not

occur through sheet flow, but rather through rill and channel flow (because the terrestrial ecosystem is not tilled

or mixed). As a result, this scenario tends to present a conservative exposure profile for ecological receptors in

a terrestrial ecosystem; the pattern of contamination that may actually be observed would likely be a ribboned

surface drainage pattern. Any effects on soils would likely be highly localized (i.e., hot spots of metal

contamination) and, consequently, the ecological significance to the ecosystem may be low. Moreover, many

metal constituents are required for proper growth and maintenance of plants and animals, so it is critical to

evaluate the relationship between background concentrations modeled concentrations of metals. 
Table 6-3. Development of Exposure Scenario for the ERA of FFC Residuals Comanaged in Landfills

 Pathway Route Receptors Key assumptions, issues, and inputs

Page 59

overland

transport in

watershed to

aquatic

ecosystem

direct

contact

ingestion

aquatic &

sediment

biota,

amphibians

mammals,

birds, herps

Overland transport of metal constituents from a landfill through the watershed and into surface waters and/or

wetlands may result in adverse ecological effects in the affected stream reach, pond, or wetland area. For

wetlands, in particular, these effects may result in significant ecological impacts to species that rely on the

wetland as a nursery or as migratory stopover (e.g., cranes). Metals deposition to sediments may, over time,

compromise the structure and function of the sediment community and ultimately impact the overall aquatic

community. For example, release data associated with a nine acre fly ash pile environmental restoration site on

the Oak Ridge K-25 site indicated that runoff and leachate resulted in low pH in surrounding surface water and a

storm drain characterization showed high levels of aluminum, arsenic, and iron sulfate (http://www.ornl.gov/er/ker-47/c-50.htm).

emissions,

dispersion,

deposition

to terrestrial

ecosystem

direct

contact 

ingestion

soil biota,

plants

mammals,

birds, herps

The pattern of contamination associated with aerial emissions of metal constituents from the landfill is much

more likely to resemble the homogenous mixing represented in the bounding screen. Metal constituents that

accumulate over time in the surficial soil may adversely effect species in the soil community, potentially

disrupting critical functions that the community performs (e.g., nutrient cycling). In addition, metals are

phytototoxic at levels not far above those required for normal growth and have been shown to be toxic to sessile

animals exposed via incidental ingestion of soil or, for bioaccumulative metals, through the food chain. These

considerations notwithstanding, the spatial extent of contamination (and resulting effect) is likely to be relatively

small and probably of limited ecological significance.

emissions,

dispersion,

deposition

to aquatic

ecosystem,

wetlands 

direct

contact

ingestion

aquatic &

sediment

biota,

amphibians

mammals,

birds, herps

The contribution to surface water loads via this pathway will be significant only for certain conditions, as

described in the development of exposure scenarios for human health. Sediments serve as a sink for metal

contaminants and, as with the overland transport pathway, the benthos and aquatic biota are potentially at risk.
Table 6-4. Development of Exposure Scenario for ERA of FFC Residuals Comanaged in Surface Impoundments

Page 60

Sectors:

Waste Concentrations:

 Waste Management:

comanaged wastes from Utility Coal, FBC

coal ash residuals (fly ash, bottom ash, FGD sludge), FBC ash

Surface Impoundment (settling basin)

Strategy: The surface impoundment scenario is constructed similar to the human health risk (e.g., surface area for comanaged coal ash impoundments

bounds all surface impoundments). Given the number of studies that were identified on this scenario and the current interest in metals toxicity on

amphibians, this scenario may contain the most relevant exposure pathways to evaluate the potential for adverse ecological effects. However, since effluent

discharges into swamps may already be covered under other permits, and drainage systems may include the surface impoundment as well as nearby

swamps and wetlands, this exposure scenario presents some interesting issues to resolve (particularly with respect to modeled releases). Few studies were

identified that provided a thorough characterization of constituent releases from the surface impoundment.

 Pathway Route Receptors Key assumptions, issues, and inputs

direct

exposure

direct

contact

ingestion

all receptors

mammals,

birds, herps

This exposure pathway is unique to the ecological risk assessment component of this analysis. Surface

impoundments are used by a variety of waterfowl and settling basin systems and associated receiving waters

may contain a variety of flora and fauna (generally species that are tolerant of metals). Consequently, direct

exposures to surface impoundment waters and food chain impacts on wildlife that rely on impoundment species

as a food source should be considered.

leaching,

recharge to

aquatic

ecosystem,

wetlands

direct

contact

ingestion 

aquatic &

sediment

biota,

amphibians

mammals,

birds

The issue of surface water recharge for metals presents a number of complicated, albeit tractable, modeling

issues (e.g., speciation in the subsurface; sediment sorption). Although many metals are relatively immobile in

the subsurface due to strong binding attractions to organics and charged ions (e.g., clay), metal mobility is

strongly influenced by soil and aquifer conditions, including pH and binding capacity (e.g., as a function of anion

concentrations such as FeOx). Nevertheless, metal constituents have been shown to seep into wetlands and

groundwater from fly ash surface impoundments (Golden, 1983; Guthrie et al., 1982) and amphibians have been

shown to be sensitive to the presence of heavy metals associated with coal ash in the ppm to ppb range (e.g.,

Rowe et al., 1997). Moreover, recent studies have confirmed that the gills are the primary target of metal toxicity

(particularly acute toxicity) and, therefore, these effects may be additive. While the ecological significance of

such exposures is a difficult question to answer (e.g., is the spatial extent of contamination sufficient to

significantly impact wildlife populations and communities), this pathway should be considered in future analyses.
Table 6-4. Development of Exposure Scenario for ERA of FFC Residuals Comanaged in Surface Impoundments

 Pathway Route Receptors Key assumptions, issues, and inputs

Page 61

overland

transport to

terrestrial

ecosystem

direct

contact

ingestion

soil biota,

plants

mammals,

birds, herps

The same limitations apply to this pathway as with the human health scenario. For example, the overland

pathways are believed to be highly unlikely since: (1) surface impoundments are generally not above grade and

(2) existing regulatory authority is considered sufficient to mitigate the risks from overflow due to storm events. 

Although fish kills have been observed following collapse of settling basins (e.g., Carlson and Adriano, 1993;

Cherry et al., 1984), catastrophic failures of surface impoundments were not included in this bounding scenario

since fault analysis would be required to estimate the probability of failure. Interestingly, a follow up study two

years after the spill indicated that while recovery was occurring, ecological impacts were still observed (e.g.,

reduction in diversity of bottom fauna). 

overland

transport in

watershed to

aquatic

ecosystem

direct

contact

ingestion

aquatic &

sediment

biota,

amphibians

mammals,

birds, herps

This pathway has generated considerable interest by researchers, with studies initiated in the 1970's and

continuing to the present day. Carlson and Adriano (1993) identified a number of potential impacts of fly ash

disposal in settling ponds on adjacent aquatic ecosystems, including water salinization, decreased

photosynthesis, reduced animal reproduction, decreased species densities, and bioaccumulation of metals and

metalloids, particularly in aquatic plants. Other authors (e.g., Cherry et al., 1984) noted that contamination of

aquatic ecosystems by fly ash probably represent a chronic stress to organisms in a swamp drainage system. In

contrast, the man-made wetland associated with an old oil ash/scrubber sludge impoundment in Arizona has

provided an enormously important wintering habitat for sandhill cranes suggesting, in the least, that site-specific

conditions (e.g., soil type, hydrology) may mitigate the potential for toxicity.
 Table 6-5. Development of Exposure Scenario for ERA of Comanaged FFC Residuals Applied as a Soil Supplement in

Land Application

Page 62

Sector:

Waste Concentrations:

Waste Unit:

FBC wastes

FBC ash

land application

Strategy: The land application of FBC ash scenario, as constructed for the ecological analysis, is very similar to the landfill scenario. Because it is primarily

applied to agricultural lands as a soil amendment, it is expected that the land use patterns for the areas receiving FBC ash contained fragmented terrestrial

habitats. Consequently, a limited variety of ecological receptors is likely to be exposed to FBC ash. In addition, Carlson and Adriano (1993) point out that the

results of studies conducted up to 1993 indicate that FBC ash can be used as a lime substitute, and as a source of CA and S on problem soils. Relatively few

problems have been associated with its use (e.g., high alkalinity and salinity), and metals toxicity has been absent in plant studies. Accumulation of metals of

metals at levels of concern in animals has not been shown when animals are fed plants grown on FBC-amended soils (Cochran et al., 1991). In fact, a

number of studies demonstrated improved crop yields and overall improvement of soil characteristics. Transport of metal constituents from land-applied FBC

ash applications to wetlands and aquatic ecosystems is possible and should be considered.

 Pathway Route Receptors Key assumptions, issues, and inputs

overland

transport to

terrestrial

ecosystem

direct

contact

ingestion

soil biota,

plants

mammals,

birds, herps

Study data suggest that food chain impacts are absent from FBC application for plants and, therefore,

exposures to herbivores need not be evaluated (Carlson and Adriano, 1993). Potential exposures to birds and

mammals that feed primarily on earthworms and insects should be considered, however, the nature of FBC ash

application suggests that this pathway is likely to be of little concern. 

overland

transport in

watershed to

aquatic

ecosystem

direct

contact

ingestion 

aquatic &

sediment

biota,

amphibians

mammals,

birds

Proximity of agricultural field to aquatic ecosystem will be a key determinant of whether the potential for adverse

effects to aquatic biota and associated wildlife exists. Since the toxicity of many metals to aquatic biota and

amphibians tends to increase with decreasing pH (e.g., Freda, 1991), metal contamination from FBC ash may

be bounded out by the landfill scenario. For example, FBC ash is alkaline and coal fly ash is highly variable and

includes fairly acidic wastes, particularly those that contain pyrites. Nevertheless, impacts on sediment

communities may be of potential concern.
 Table 6-5. Development of Exposure Scenario for ERA of Comanaged FFC Residuals Applied as a Soil Supplement

in Land Application

 Pathway Route Receptors Key assumptions, issues, and inputs

Page 63

emissions,

dispersion,

deposition

to terrestrial

ecosystem

direct

contact

ingestion

soil biota,

plants

mammals,

birds, herps

As with the human health scenario, environmental settings favorable to windblown emissions (e.g., high wind

speeds) should be used to screen this pathway. Considering the results of studies on phytotoxicity (of food

crops) and on animal toxicity, it would seem unlikely that windblown emissions would approach constituent

concentrations observed on the actual application site. Hence, exposures from windblown emissions and

deposition may be substantially less than on-site exposures for which there are data. As with the landfill

scenario, total metal concentrations are used to approximate the mass available for transport and air emission

factors may be estimated from AP-42.

emissions,

dispersion,

deposition

to aquatic

ecosystem,

wetlands 

direct

contact

ingestion 

aquatic &

sediment

biota,

amphibians

mammals,

birds

Depending upon the topography of the modeled site, this exposure pathway may contain the most significant

release and transport mechanism of FBC ash to aquatic ecosystems. It seems somewhat unlikely that

appreciable mass of FBC would be blown to a nearby surface water body for certain applications of FBC ash

(e.g., orchards) and, therefore, the application use should be considered in evaluating potential transport. 
Draft Version: Do Not Cite or Quote June 5, 1998

Page 64

6.3 ANALYSIS PHASE

This section covers the methodology used to develop the exposure profiles specific to the

scenario/residual combinations in Table 6-2 as well as the methodology used to estimate

ecotoxicological benchmarks and chemical stressor concentration limits (CSCLs), as appropriate,

for receptors evaluated in this screening analysis. The fate and transport model used to estimate

CPEC concentrations in plants, soil, sediment, and surface water (i.e., exposure profile) is

discussed in previous sections in this report and the derivation of CPEC concentrations for

comanaged FFC residuals is described in detail in the SAIC Background Document. 

Consequently, the discussion relative to the exposure profiles is intentionally brief. The

methodology used to support the development of CSCLs for the FFC ERA (e.g., stressorresponse profiles) is explained in some detail in Sections 6.3.2 and 6.3.3.

6.3.1 Exposure Profiles

As described in Section 4 of this report, the exposure profiles were generated using the

fate and transport model under development for the HWIR and currently in use by a number of

other projects at the Office of Solid Waste (OSW). Depending on the assessment tier, the model

provided medium-specific concentrations of CPECs for bounding, high-end, and central tendency

management and use practices.

6.3.2 Stressor-Response Profiles

For each CPEC, a stressor-response profile (i.e., the quantitative relationship between

exposure and effect) was created to serve as the basis for ecotoxicological benchmarks and

CSCLs. For the purposes of the FFC ERA, benchmarks are defined as effects levels in units of

dose (mg/kg-day) that are relevant to population sustainability. Chemical stressor concentration

limits (CSCLs) are defined as effects levels in units of concentration (ppm) that are relevant to:

(1) population sustainability (i.e., CSCL is based on the benchmark), or (2) community structure

and function (i.e., CSCL is based on data on individual species assigned to the community).

Ecotoxicological data are collected on acute endpoints (e.g., lethality), chronic endpoints (e.g.,

growth, reproduction), and on bioaccumulation potential to develop CSCLs that reflect the nature

of exposure (i.e., direct or food web).

It is useful to think about the CSCLs developed from stressor-response profiles in terms of

either population-type concentration limits or community-type concentration limits. The

population-type concentration limits generally reflect exposures via ingestion of contaminated

media and food items (e.g., plants, prey). One exception to this tenet is for amphibian

populations; the CSCLs were based on direct aqueous exposures over subchronic durations for

endpoints generally limited to measures of lethality. The community-type concentration limits
Draft Version: Do Not Cite or Quote June 5, 1998

8 Several Ambient Water Quality Criteria (e.g., for DDT) are based on Final Residue

Values that reflect the bioaccumulation of contaminants in aquatic organisms. 

However, most AWQC are based on direct effects to aquatic organisms.

Page 65

generally reflect direct exposures to contaminated media.8 It should be noted that the CSCLs for

receptor communities are not truly community-level concentration limits in the sense that they do

not consider predator-prey interactions. Rather, they are based on the theory that protection of

95% of the species in the community will provide a sufficient level of protection for the

community (see, for example, Stephan et al., 1985, for additional detail).

The CSCLs developed for constituents found in FFC residuals are consistent with the

proposed guidelines for ecological risk assessment. For example, point estimates of CSCLs were

derived for no observed adverse effects levels (NOAELs may be applied for T&E species or in

conservative analyses), lowest observed adverse effects levels (LOAELs), or other de minimis

effects levels for selected endpoints (e.g., protection of 95% of the species). The overall

methodology used to derive benchmarks and CSCLs for the FFC ERA is described briefly below.

6.3.2.1 Benchmark and CSCL Development for Wildlife Populations

For amphibian populations, the development of CSCLs was severely limited by data

availability. After a review of several compendia presenting amphibian ecotoxicity data (e.g.,

EPA, 1996b; Power et al., 1989) as well as primary literature sources, it was determined that the

lack of standard methods on endpoints, species, and test durations made deriving a chronic CSCL

for amphibians inappropriate. Consequently, an acute CSCL was derived for aqueous exposures

in amphibians by taking a geometric mean of LC50 data identified in studies with exposure

durations less than eight days. Although the use of acute effects levels is not consistent with other

benchmarks and CSCLs, the sensitivity of these receptors warrants their inclusion even though

chronic concentration limits have not yet been developed. Other methods to address chronic

exposures to amphibians are currently being evaluated. One alternative under consideration is the

addition of amphibian toxicity data to the data set used to the Ambient Water Quality Criteria (see

Stephan et al, 1985) since the AWQC methodology allows for amphibians to be included among

the representative taxa.

For populations of mammals and birds, the overall approach used to establish

ecotoxicological benchmarks was similar to the methods used to establish RfDs for humans as

described in the Integrated Risk Information System (IRIS). Each method uses a hierarchy for

the selection of toxicity data and extrapolates from a test species to the species of interest. 

However, there are fundamental differences in the goals of noncancer risk assessments for humans

and ecological receptors. Risk assessments of humans seek to protect the individual while risk

assessments of ecological receptors typically seek to protect populations or communities of

important species. The procedures used to develop benchmarks (i.e., RfDs) for the protection of

human health are very sensitive by design, and go beyond the need to sustain the reproductive
Draft Version: Do Not Cite or Quote June 5, 1998

Page 66

Benchmarkw' LOAELtx

bwt

bww

1/4

(Eqn 1)

fitness in a local population (U.S. EPA, 1992b). Consequently, benchmarks for mammals and

birds were established using three key guidelines. 

C First, because population viability was selected as an assessment endpoint, the

benchmarks were developed from measures of reproductive/developmental success or,

if unavailable, other effects that could conceivably impair population dynamics.

C Second, the population-level benchmark is preferred over population-inference

benchmarks (i.e., LOAELs for individual organisms on reproductive endpoints). 

Although relatively few population-level benchmarks have been developed to date,

these benchmarks are considered to be more rigorous than the point estimates gleaned

from toxicity studies. 

C Third, uncertainty factors (UFs) are generally not applied to address interindividual

variability. For example, a UF of 10 was not applied to subchronic studies since

reproductive and developmental toxicity studies are frequently short-term.

Once the benchmark study was identified, the CSCL was calculated for each medium of

interest using a three step process. The remainder of this section outlines the basic technical

approach used to convert avian or mammalian benchmarks (in daily doses) to the CSCL (in units

of concentration) for surface water and soil. The methods reflect exposure through the ingestion

of contaminated plants, prey, and various media and include parameters on accumulation (e.g.,

bioconcentration factors), uptake (e.g., consumption rates), and dietary preferences.

STEP 1 

Scale benchmark: The benchmarks derived for various taxa (e.g., mammals) can be

extrapolated to other species within a taxa by the cross-species scaling equation (Sample et al.,

1996). For population-level benchmarks, this extrapolation integrated into the population model

framework. For population-inference benchmarks, the extrapolation is performed using Equation.

where LOAELt is the LOAEL for the test species, bww is the body weight of the wildlife species,

and bwt is the body weight of the test species. This is the default methodology EPA proposed for

carcinogenicity assessments and reportable quantity documents for adjusting animal data to an

equivalent human dose (57 FR 24152). It should be noted that at least one recent paper

demonstrated that cross-species scaling may be problematic for avian species (Mineau et al.,

1996).
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Benchmark (mg/kg&day) '

[I

fish × (BAF × C

t

w

)] % (Iw× C

t

w

)

bw

(Eqn 2)

Benchmark (mg/kg&day) '

I

fish × (BAF × C

t

w

)

bw

(Eqn 3)

STEP 2

Identify BCF/ BAFs: For metal constituents, whole-body bioconcentration (BCFs) and

bioaccumulation factors (BAFs) were identified or estimated, as appropriate, for aquatic and

terrestrial organisms that may be used as food sources (e.g., fish, plants, earthworms). The Oak

Ridge National Laboratory has recently proposed methods and data that are useful in predicting

bioaccumulation in earthworms and small mammals (Sample et al, 1998a, 1998b). In short, these

values are typically identified in the open literature and EPA references, or calculated based on the

relationship between log Kow and accumulation in lipid tissue. Currently, distributions of BAFs

are under development for HWIR98 that reflect variability across hydrological regions as well as

various fish species and aquatic food webs.

STEP 3 

Calculate CSCLs: The following equation provides the basis for calculating the CSCL

for surface water using a population-inference benchmark (e.g., endpoint on fecundity).

where: 

 Ifish = intake of contaminated fish (kg/d)

 BAF = whole-body bioaccumulation factor (L/kg)

 bw = weight of the representative species (kg)

 Iw = intake of contaminated water (L/d)

 Cw

t

 = total concentration in the water (mg/L)

and the whole-body concentration in fish (Cfish) is given by BAF x Cw

t

.

For chemicals that bioaccumulate significantly in fish tissue, the ingestion of contaminated food

will tend to dominate the exposure (i.e., [Ifish x Cfish] >> [Iw x Cw

t

]), and the water term (i.e., [Iw x

Cw

t

]) can be dropped from Eqn 2 resulting in Eqn 3.

At the benchmark dose (mg/kg-day), the concentration in water is equivalent to the chemical

stressor concentration limit for that receptor as a function of body weight, ingestion rate, and the

bioaccumulation potential for the CPEC. Hence, Equation 3 can be rewritten to solve for the

CSCL in surface water (CSCLsw) as follows:
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CSCLsw'

benchmark × bw

Iw% (I

fish × BAF)

(Eqn 4)

CSCLsoil '

benchmark x bw

(I

food 3 BCFj

x Fjx ABj) % (I

soil)

(Eqn 5)

For wildlife populations of mammals and birds in terrestrial systems, the CSCLsoil for a given

receptor is given by Equation 5:

where

bw = body weight (kg)

Ifood = total daily food intake of species (kg/d)

Isoil = total daily soil intake of species (kg/d)

BCFj = bioaccumulation factor in food item j (assumed unitless)

Fj = fraction of consisting of food item j (unitless)

ABj = absorption of chemical in the gut from food item j

6.3.2.2 CSCL Development for Communities

For the aquatic community, the Final Chronic Value (FCV) developed for: (1) the Great

Lakes Water Quality Initiative, or (2) the National Ambient Water Quality Criteria (NAWQC)

was the preferred sources for the CSCLsw. If an FCV was unavailable and could not be calculated

from available data, a Secondary Chronic Value (SCV) was estimated using methods developed

for wildlife criteria estimated for the Great Lakes Initiative (e.g., 58 FR 20802). The SCV

methodology is based on the original species data set established for the NAWQC, however, it

requires fewer data points and includes the statistically derived adjustment factors. For CSCL

derivation, the minimum data set required at least one data point for daphnids.

For the sediment community, the approach used to establish CSCLs for metals is based

on a complete assessment of several sources proposing sediment benchmark values. For nonionic

organic chemicals, the methods used were adapted from the EPA guidance: Technical Basis for

Deriving Sediment Quality Criteria for Nonionic Organic Contaminants for the Protection of

Benthic Organisms by Using Equilibrium Partitioning (U.S. EPA, 1993).

For algae and aquatic plants, adverse effects concentrations are identified in the open

literature or from a data compilation presented in Toxicological Benchmarks for Screening

Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision (Suter and Tsao,

1996). For most contaminants, studies were not available for aquatic vascular plants and lowest

effects concentrations were identified for algae. The CSCL for algae and aquatic plants was

based on (1) a lowest observed effects concentration (LOEC) for vascular aquatic plants or (2) an
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Sources Evaluated for Developing Sediment

Community CSCLs

Approach to the Assessment of Sediment Quality in

Florida Coastal Waters Volume 1- Development and

Evaluation of Sediment Quality Assessment Guidelines. 

Florida Department of Environmental Protection. (FDEP,

1994)

National Oceanic and Atmospheric Administration

(NOAA), (Long and Morgan, 1991)

Screening Level Ecological Risk Assessment at Hazardous

Waste Combustion Facilities. Office of Solid Waste (U.S.

EPA, 1997)

Eco Update. Office of Emergency and Remedial

Response. (U.S., EPA, 1996)

Oak Ridge National Laboratory. Screening Level

Benchmarks for Ecological Risk Assessment. U.S.

Department of Energy. (ORNL, 1996)

Technical Support Document for the Hazardous Waste

Identification Rule: Risk Assessment for Human and

Ecological Receptors. 1995 (U.S. EPA, 1995)

effective concentration (ECxx) for a species

of freshwater algae, frequently a species of

green algae (e.g., Selenastrum

capricornutum). Because of the lack of data

for this receptor group and the differences

between vascular aquatic plants and algae

sensitivity, the lowest value of those

identified was usually chosen.

For the terrestrial plant

community, ecotoxicological data were

identified from a summary document

prepared at the Oak Ridge National

Laboratory: Toxicological Benchmarks for

Screening Potential Contaminants of

Concern for Effects on Terrestrial Plants:

1997 Revision (Efroymson et al., 1997a). 

The measurement endpoints are generally

limited to growth and yield parameters

because: (1) they are the most common class

of response reported in phytotoxicity studies

and, therefore, will allow for criterion

calculations for a large number of

constituents, and (2) they are ecologically

significant responses both in terms of plant populations and, by extension, the ability of producers

to support higher trophic levels. As presented in Efroymson et al. (1997a), CSCLsoil for

phytotoxicity are selected by rank ordering the LOEC values and then approximating the 10th

percentile. If there are 10 or fewer values for a chemical, the lowest LOEC is used. If there are

more than 10 values, the 10th percentile LOEC was used. 

For the soil community, CSCLs are developed using methods analogous to those used in

deriving the NAWQC. In brief, the CSCLsoil values for soil fauna were estimated to protect 95%

of the species found in a typical soil community, including earthworms, insects, and other various

soil fauna. Microflora have not been included in the soil community primarily because of the

difficulty in assigning ecological significance to effects levels for soil microorganisms. However,

appropriate methods to add microflora are currently under evaluation since: (1) microflora make

up approximately 80-90% of the biomass in soil and (2) microflora are responsible for the

majority of the biological activity in soil (e.g., N mineralization).

In developing CSCLs, eight taxa of soil fauna were identified to capture the key structural

(e.g., trophic elements) and functional (e.g., decomposers) components of the soil ecosystem. 

The methodology presumes that protecting 95% of the soil species with a 50th percentile level of

confidence will ensure long-term sustainability of a functioning soil community. The toxicity data
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HC5%' [xm& klsm] Eqn 6

on soil fauna are gleaned from several major compendia and supplemented with additional studies

identified in the open literature. Generally, the studies are not evaluated in terms of quality

because there is currently no consensus on standard methods and species for soil testing (although

earthworms are frequently used as indicator species). However, acceptable toxicity data are

limited to soil studies (vs aqueous studies) on measurement endpoints believed to be relevant to

population survival (e.g., growth, reproduction).

The approach to calculating benchmarks for the soil community is based on efforts by

Dutch scientists (i.e., the RIVM methodology) to develop hazardous concentrations (HC) at

specified levels of protection (primarily 95%) at both a 95th percentile and a 50th percentile level

of confidence (Sloof, 1992). For the soil fauna benchmarks, the 50th percentile level of

confidence was selected because the 95th percentile appeared to be overly conservative for a “no

effects” approach. The RIVM methodology follows two steps: (1) fitting a distribution to the

log of the selected endpoints, and (2) extrapolating to a benchmark concentration based on the

mean and standard deviation of a set of endpoints. The key assumptions in the Dutch

methodology are that: (1) LOEC data are distributed logistically, and (2) the 95% level of

protection is ecologically significant. The following formula was used to calculate soil fauna

benchmarks:

where

HC5% =soil concentration protecting 95% of the soil species

xm =sample mean of the log LOEC data

kl =extrapolation constant for calculating the one-side leftmost confidence

limit for a 95% protection level

sm =sample standard deviation of the log LOEC data

It is important to note that only one value for kl is calculated for the 50th and 95th

percentile confidence limits, respectively, for each sample size (m). Consequently, it is assumed

that: (1) there is just one extrapolation constant with the required confidence property for each

species sample size, and (2) extrapolation factors may be determined through Monte Carlo

simulation by generating random sample averages and deviations for the standard logistic

distribution and adjusting for a specified confidence level (i.e., 50th or 95th). When data are

insufficient for CSCL development, benchmark studies identifying effects to earthworms and

other soil biota proposed by Oak Ridge National Laboratory (Efroymson et al., 1997b) or criteria

developed by the Canadian Council of Ministers of the Environment (CCME, 1997) were used to

estimate protective soil concentrations.
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9

In the jargon of ecological risk assessment, the HQ approach is often referred to as a screening

approach.

10 In almost all cases, the high-end parameters were concentration and surface area of the WMU.

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6.4 Risk Characterization

EPA defines the risk characterization in terms of: (1) the risk estimation which integrates

the exposure and stressor-response profile to estimate the likelihood of adverse ecological effects

and (2) the risk description which synthesizes the overall conclusion of the assessment and

addresses uncertainty, assumptions, and limitations. For assessments that are based upon hazard

quotient (HQ) approach,9 the comparison of modeled exposure concentrations to CSCLs in the

risk estimation has a binary outcome: either the constituent concentration is above the screening

criteria (HQ>1) or the concentration is below the criteria (HQ<1). Since the CSCLs are based on

de minimis ecological effects, it is presumed that a hazard quotient below 1 indicates a low

potential for adverse ecological effects for those receptors included in the analysis for which data

are available. However, it is important to recognize that the HQ methodology is designed to

delineate the potential for adverse ecological effects as a function of HQ exceedances. Although

this method provides important insight into the potential for adverse ecological effects, the results

are relevant only to those receptors that were included in the assessment and for which data were

available. The results have limited utility in interpreting the ecological significance of predicted

effects and caution should be exercised in extrapolating to ecosystems (e.g., wetlands) and

receptors (e.g., threatened and endangered species) not explicitly modeled in this framework.

6.4.1 Risk Estimation

This section presents the risk results (i.e., hazard quotient exceedances) from the ERA for

bounding, high-end, and central-tendency management and use practices for comanaged FFC

residuals. The risk results from the bounding assessment were used to define the list of CPECs

evaluated for each sector and management/use practice for the high-end and central tendency

analyses.10 Table 6-6 presents the constituents considered for each of the eight sector and

management/use combinations considered in the ERA. 

The hazard quotient results for the high-end and central tendency surface impoundments

are presented in Table 6-7. Although no HQ exceedances were observed for any off-site

exposures (i.e., receptors not located on the WMU), exceedances were identified for direct use of

the surface impoundment by receptors associated with aquatic systems for bounding, high-end,

and central tendency management and use practices. For the assessment of surface impoundment

use by ecological receptors, the “management and use practices” are defined simply as the

maximum, high-end (i.e., 95th %ile), and central tendency (i.e., median value) CPEC

concentrations in the comanaged, coal ash surface impoundment waters. For the high-end

assessment, HQ exceedances indicated the potential for acute effects in amphibians (direct

exposure) and chronic effects in mammals and birds associated with aquatic ecosystems (direct &
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Page 72

food chain exposure). For the central-tendency assessment, HQ exceedances were only observed

for mammals and birds exposed to lead, mercury, and selenium. All HQ results are presented in

Appendix J.

Table 6-6. CPECs Included in the ERA of High-end and Central-tendency Management

and Use Practices (by sector and waste management unit)

Management and Use Scenarios Constituents

Utility Coal Co-managed Coal Waste

Landfill Barium, Lead, Cadmium, Selenium, Silver, Aluminum, Boron,

Cobalt, Thallium

On-site Surface Impoundment* Aluminum, Antimony, Arsenic, Barium, Boron, Cadmium,

Chromium, Cobalt, Copper, Lead, Mercury, Molybdenum,

Nickel, Selenium, Silver, Thallium, Vanadium, Zinc

Dewatered Surface Impoundment Barium, Lead, Cadmium, Selenium, Silver, Aluminum, Boron,

Cobalt, Thallium

Fluidized Bed Combustion (FBC) Combined Ash Wastes

Landfill Cadmium, Lead, Nickel, Vanadium, Silver, Aluminum, Boron,

Cobalt, Thallium

Agricultural Soil Amendment Nickel, Vanadium, Aluminum, Boron, Cobalt, Thallium

Utility Oil-Fired Wastes (Solids Settling Basin Ash)

Landfill Onsite Arsenic , Cadmium, Copper, Lead, Nickel, Vanadium, Zinc, 

Chromium, Silver, Aluminum, Boron, Cobalt, Thallium

Non-Utility Coal Co-Managed Wastes

Landfill Onsite Barium, Lead, Cadmium, Selenium, Silver, Aluminum, Boron,

Cobalt, Thallium

Landfill Offsite Barium, Lead, Cadmium, Selenium, Silver, Aluminum, Boron,

Cobalt, Thallium

* Measured concentrations identified from EPRI site investigations.

6.4.2 Risk Description

The risk description attempts to integrate all of the qualitative and quantitative information

developed during the screening ERA and to interpret the results for use in the decision-making

process. The lines of evidence are examined based on the relevance of the assessment endpoints,

the sufficiency of the data presented in the exposure and stressor-response profiles, the

appropriateness of the methods used to predict ecological effects. Interpreting the impact of an

HQ exceedances requires an understanding of both the derivation (data and methods) of CSCLs

as well as insight into the CPEC concentrations predicted by fate and transport models.
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Ecological risk characterizations, especially predictive ones such as the FFC ERA, often

require the development of assumptions to characterize emissions, sites, receptors, exposure, and

spatial and temporal factors; the risk results must be interpreted within the context of the

limitations inherent in a generalized approach (versus a site-based analysis). Although tools to

evaluate HQ exceedances within the context of ecosystem function and structure are not

available for HQ-based approaches, key assumptions and uncertainties should be examined in

delineating ecological significance. The major limitations and uncertainties in the FFC ERA can

Table 6-7. Ecological Risk Assessment Results for Surface Impoundments

High-end

Assessment

Central-tendency

Assessment

Receptor Group

Aluminum 10 2 amphibians

Antimony -- -- no exceedances

Arsenic 19 -- birds

Barium -- -- no exceedances

Beryllium -- -- no exceedances

Boron 16 -- amphibians

Cadmium 23 -- mammals

Chromium -- -- no exceedances

Cobalt -- -- no exceedances

Copper -- -- no exceedances

Lead 830 45 mammals

Mercury 4,500 3,100 birds

Molybdenum -- -- no exceedances

Nickel -- -- no exceedances

Selenium 30,000 & 5 150 mammals & amphibians

Silver -- -- no exceedances

Thallium -- -- no exceedances

Vanadium -- -- no exceedances

Zinc -- -- no exceedances
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be grouped under: (1) exposure issues, (2) CSCL development, and (3) receptors/ecosystems at

risk. While certain limitations are intrinsic to any ecological risk assessment (e.g., extrapolation of

laboratory data to field exposures; application of bioaccumulation factor ratios), this section is

focused on the uncertainty, limitations, and the confidence specific to the ERA of comanaged FFC

residuals.

6.4.2.1 Exposure Issues. 

Co-occurrence of Receptor and CPEC - As a simplification for national-scale analyses

(i.e., no site-based data), co-occurrence is typically assumed. However, the prior probability that a

receptor will be found in a contaminated sector is not known nor is it known whether a receptor

will forage for food in contaminated areas or if those areas do, in fact, support the type of habitat

needed by the receptor. Although the assumption of co-occurrence was necessary for the FFC

ERA, the increase in resolution offered by GIS tools and other data sources greatly improves the

strength of that assumption (e.g., topo maps; local FWS agencies). Nevertheless, the cooccurrence of the stressor and the assessment endpoint must be demonstrated to the extent

supported by the data.

Assumptions on Dietary Exposure - National-scale assessments often assume maximum

intake of contaminated prey in the diets of primary and secondary consumers (i.e., 100 percent of

the diet originates from the contaminated area). Obviously, under field conditions many receptors

are opportunistic feeders with substantial variability in both the type of food items consumed as

well as the seasonal patterns of feeding and foraging. Consequently, the exclusive diet of

contaminated food items tends to provide a very conservative estimate of potential risks. With

the introduction of site-based data on wildlife use of surface impoundments, it is possible to adjust

dietary exposure estimates to reflect the food web structure of nearby habitats.

Bioavailability of Constituents of Concern - For the purposes of this analysis, all forms

of a constituent are assumed to be equally bioavailable and, therefore, the actual exposures that

may occur in the field tend to be overestimated. This assumption is appropriate for a conservative

analysis; however, both the chemical form and the environmental conditions influence

bioavailability and, ultimately, the expression of adverse effects. For example, the form of arsenic

has been shown to profoundly influence mobility and toxicity. The stressor-response profiles

developed for metal CPECs should include at least a qualitative discussion of the speciation

behavior of metals in various environmental media.

Multiple Constituent Exposures - The risk of each CPEC was considered separately in

this analysis. However, the waste concentration data on FFC residuals comanaged in surface

impoundments suggest that exposure to multiple constituents is highly likely. The synergism or

antagonism between different constituent combinations may elicit unexpected adverse impacts to

ecosystems. Hence, a single-CPEC analysis may underestimate risks associated with multiple

chemical stressors.
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CPEC Concentrations in FFC Residuals - One of the most significant sources of

uncertainty in the ecological risk analysis is the CPEC concentrations selected for the surface

impoundment scenario. As described in Appendix B (Concentration Data Used for FFC Risk

Assessment - Table B-5), the sample population for CPECs is relatively small. In the case of

mercury, for example, only two samples were available and one of the samples was below the

detection limit. As a result, it is difficult to determine the potential significance of HQ

exceedances shown in this study with respect to entire universe of comanaged FFC residuals. 

6.4.2.2 CSCL Development

Data Gaps - CSCLs were developed for constituents when sufficient data are available. 

In many cases, sufficient data were unavailable for a receptor/constituent combination and,

therefore, the potential risk to a receptor can not be assessed. In particular, insufficient data were

available to derive chronic effects CSCLs for amphibians. Because the risk results can only be

interpreted within the context of available data, the absence of data can not be construed to mean

that adverse ecological effects will not occur.

Conservatism of CSCL Development - Because the overall approach is based on “no

effects” or “lowest effects” study data, these criteria tend to be fairly conservative. In site-specific

assessments, a de minimis effects approach is often replaced with an effects level similar to natural

population variability (e.g., sometimes as high as a 20% effects level). As a result, the CSCLs

may be overly conservative for representative species and communities assigned to the habitats of

interest. Since the difference between a LOAEL and a NOAEL is often about a factor of 10, an

HQ exceedances around 10 may not be ecologically significant (e.g., high-end arsenic exposure in

birds). In contrast, CSCLs based on no effects data that are developed for the protection of T&E

species are presumed to be appropriately conservative.

6.4.2.3 Receptors/Ecosystems at Risk

One of the most intractable problems in conducting a predictive ERA intended to reflect

risks at a national scale is evaluating all of the receptors and ecosystems at risk. In the Wastes

from the Combustion of Coal by Electric Utility Power Plants - Report to Congress (EPA, 1988),

the authors pointed out that plants or animals of concern were located within a 5 km radius of the

FFC waste management units at between 12% and 32% of the sites. Although these figures are

based on the Biological and Conservation Data (BCD) System and are, therefore, of limited

spatial resolution, they suggest the possibility that threatened and endangered species and/or

critical habitats may be at risk from comanaged FFC residuals. In particular, the impacts of

comanaged FFC residual releases on estuarine systems and associated receptors (e.g., manatees)

has been raised internally by OSW staff. Examples of other critical assessment endpoints not

evaluated in the FFC ERA include the following.

Managed lands - Because ecosystem degradation is proceeding at an unprecedented rate,

and because protected lands play a critical role in preserving plant and animal species, managed
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areas in the United States represent well-recognized ecological values. Managed lands refer to a

variety of lands designated by the federal government as worthy of protection, including National

Wildlife Refuges, National Forests, Wilderness areas, and National Recreation areas.

Critical habitats - Although critical habitats may be defined in a number of ways (e.g.,

presence of threatened species; decreasing habitat area), wetlands are widely recognized as

serving critical ecological functions (e.g., maintenance of water quality). The U.S. Fish and

Wildlife Service estimates that approximately 45% of the Nation’s threatened and endangered

species directly depend on aquatic and wetland habitats. Consequently, impacts of chemical

stressors on wetland habitats may have high ecological (and societal) significance. The presence

of critical habitats such as wetlands is also used to inform the selection of ecological receptors

(e.g., amphibians; waterfowl) and the construction of appropriate food webs.

Threatened and endangered species - For most ecological risk assessments of chemical

stressors, available data on toxicity and biological uptake are sufficient to support the evaluation

of effects on representative species populations or generalized communities (e.g., aquatic

community). However, despite their obvious value, threatened and endangered (T&E) species,

species of special concern, or species in need of conservation are frequently excluded from the

analytical framework for national rulemakings. The assessment of T&E species requires a sitebased approach in which locations, habitats, and species of concern are identified and

characterized with respect to the spatial scale of CPEC releases. A number of sources of

information on T&E species are available, ranging from a county-level database developed by the

EPA Office of Pesticide Programs that lists T&E species, to a network of state and local contacts

responsible for the maintenance and administration of the National Biological Database. In

addition, there are other federal agencies such as the Department of Defense that are in the

process of developing wildlife species profiles for T&E species.
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7.0 UNCERTAINTY

Previous sections of this report have presented the principal data, assumptions, and

models used to develop risk results for FFC wastes. This section qualitatively addresses the

primary sources of uncertainty within the risk assessment and the effects that this uncertainty has

on interpreting the results. The discussion is intended to provide a basis for developing

conclusions regarding the risk results. It is important to note that the uncertainties discussed

below are relevant to both the human health and ecological risk assessment. For both receptor

types, the major uncertainties are associated with the characterization of FFC wastes and waste

management practices. Key uncertainties that are exclusive to the ecological risk analysis are

described in Section 6.4 - Risk Characterization. 

Uncertainty in an analysis such as this can be introduced in a number of places. In general,

the major sources of uncertainty are parameter uncertainty and model uncertainty. Parameter

uncertainty occurs when parameters appearing in equations cannot be measured precisely and/or

accurately. Model uncertainty is associated with all models used in all phases of a risk

assessment. Computer models are simplifications of reality, requiring exclusion of some variables

that influence predictions but cannot be included in models due either to increased complexity or

to a lack of data on that variable. 

Most of the issues addressed in this section are specific to this project. These issues

include uncertainties regarding waste characterization, waste management practices, and

uncertainties introduced with the models that were used. The exception to the analysis specific

uncertainty discussion will be a brief discussion on chemical specific uncertainty issues;

specifically, metal speciation in the environment. Each of these issues will be discussed below. 

The discussion on uncertainty will discuss the possibilities for a follow on, quantitative uncertainty

analysis.

Waste Characterization

Waste characterization is the main uncertainty issue for this study. Review of Section 5.6

strongly suggests that waste concentration is the single most important parameter in determining

human health risk. The sensitivity of the model to this parameter, the small sample size for the

waste characteristics data, and the high demonstrated variability of waste characteristics across

facilities presents significant uncertainty issues for EPA. 

Sample size is an important issue for all waste streams. However, sample size is

particularly small relative to the size of the industry for the coal-fired co-managed wastes. The

waste characterization is based on 14 Electric Power Research Institute (EPRI) Site

Investigations plus two additional EPRI reports. How well this limited sample characterizes the

population of coal-fired co-managed wastes is questionable. 
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For all wastes there were little to no data provided on the physical characteristics, such as

particle size distribution. Particle size can have significant impacts on the waste’s mobility in the

environment. Many of these wastes also have self cementing properties which would greatly

retard constituent mobility in the environment. These properties were not characterized in any

quantitative assessment that could be incorporated into the analysis. (Even if data had been

supplied on these properties, there would be significant model uncertainty in measuring transport

from the source.)

Waste characterization uncertainty may be especially important in the dewatered surface

impoundment and the oil ash landfill scenarios. In each case, the scenario assumes that exposure

occurs after the wastes have been subjected to leaching in an impoundment. Since many

constituents of concern may be readily leached from particle surfaces in impoundments, the total

concentration of these constituents at the end of the active life of the impoundment (or at the time

of transfer to a landfill) may be expected to be lower than at the time of generation. The data

provided for these wastes, however, reflect an uncertain extent of chemical and physical alteration

resulting from management. Therefore, concentrations used for these scenarios may overstate the

true concentration of the waste after such leaching has taken place.

Non-utility combustion processes and the types of fuels used are many and varied. Much

uncertainty is introduced into the assessment by assuming that the waste is identical to the utility

coal-fired co-managed wastes.

Finally, for all waste sectors, different types of wastes were analyzed (e.g., fly ash, bottom

ash, solids settling basin sludge). Decisions were made on how to aggregate or dis-aggregate

wastes based on various criteria. These decisions can have significant impact on risk results as

this determination will necessarily dictate the waste concentrations, constituents of concern, and

other physical characteristics of the waste.

These are some of the primary uncertainty issues for the human health, non-groundwater

pathway risk assessment. Other waste characterization uncertainty issues are addressed in Section

7 of SAIC’s Background Document.

Waste Management Practices

Many waste management practices have significant impacts on risk results and also have a

great amount of uncertainty. Some of the major issues include: landfill cover practices; the use of

erosion and runoff controls; waste hauling practices; the actual unit sizes; and actual landfill active

lifetime.

There are many options for applying a cover to a landfill. Some options may include:

applying no cover; applying a daily cover; disposing of waste in cells and when a cell is filled

applying a permanent cap. These choices have significant impacts on the types of emissions that

can be expected from a unit.
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Many landfills may be required to have runoff and erosion controls installed either due to

other environmental regulations or due to permit requirements. There were no information on the

prevalence of runoff and erosion controls for the landfills assessed for this analysis. 

Waste hauling and disposal practices have significant impacts on particulate air emissions. 

If dump trucks are used, input parameters that are important in the determining particulate

emissions include: capacity of the dump truck; number of tires on the dump truck; and waste

cover efficiency, length of road. It is assumed in this analysis that dump trucks were used to haul

the waste to the landfill. If other delivery mechanisms are used this could have major impacts on

amount of air emissions. 

Waste management unit size and active lifetime are also important risk drivers. As with

waste characterization, it is questionable whether the small sample size of units accurately

represents the universe of disposal units in the nation. This is especially true for the utility oilfired wastes and the non-utility coal-fired wastes. Because there were not sufficient data to

characterize WMU sizes, dimensions were developed based on fuel use. There are many

assumptions that are made when going from fuel use to WMU size. Each of these assumptions

introduces uncertainty into the analysis.

Model Uncertainties

Assessing model uncertainties is a complex issue and beyond the scope of this report;

however, there are a few issues that warrant mentioning. These issues will be mentioned in the

conclusion section below when they have the potential to have a significant impact on the risk

results that have been calculated. 

Metal Speciation

Analytical data provided to RTI were in the form of total metal concentrations, which do

not account for metal speciation. As a consequence, the risk analysis did not account for metal

speciation in the various environmental compartments. Metal speciation is an important factor in

assessing the fate, mobility, and toxicity of metals in the environment. Without a clear

understanding of metal speciation, behavior is uncertain. For purposes of the risk assessment, the

most toxic metal species were assumed to equal to total metal concentration (e.g., chromium VI

was assumed to be equal to total chromium concentration). Although this is considered a

conservative assumption, it is important to recognize the uncertainty that this assumption

introduces into the analysis. 

Quantitative Uncertainty Analysis

Given the level of uncertainty for many of the data for this analysis a quantitative

uncertainty analysis should be performed. EPA guidance for performing a probabilistic risk

analysis as a quantitative uncertainty/variability analysis states that it is necessary to conduct a

sensitivity analysis to identify the risk driving parameters as an initial step. A sensitivity analysis

will be will be performed for each constituent, waste, waste management unit, and receptor
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combination. Once the risk driving parameters are identified a probabilistic (Monte Carlo)

analysis may be performed for these wastes.
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11 Because of the recent removal of the ingestion CSF for beryllium, any beryllium exceedences will not be

discussed in this section.

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8.0 CONCLUSIONS

In this study to assess human health and ecological risks from the management and use of

the remaining FFC wastes, EPA found that the remaining waste universe is represented by a large

and diverse population of wastes and WMU’s located throughout the nation. To determine the

risks from this large and diverse population, EPA segregated the wastes into four categories:

coal-fired utility co-managed wastes, oil-fired utility wastes, FBC wastes, and non-utility coalfired wastes. Attention was focused on the WMU that EPA believed to present the greatest

potential for release of contaminants to the environment. For the non-groundwater pathways,

these WMU’s included landfills, a dewatered surface impoundment, use of the waste as

agricultural soil amendment, and an active surface impoundment (for ecological risks only). 

Initially, risks were estimated using a bounding approach where all input parameters are

set to their high-end values. The bounding analysis is designed to be conservative; however, this

bounding analysis was made even more conservative because the largest waste management unit

size that was found for any waste stream/WMU combination was used for all WMU/waste stream

analyses (excluding the agricultural soil amendment scenario). The largest WMU size was the

dewatered surface impoundment for the utility coal-fired co-managed waste scenario. The size of

this unit was 412 acres. This unit size was then used for all landfill scenarios for all waste streams

even though no landfill was actually estimated to be that large. Note that for all landfill scenarios

except the non-utility offsite commercial landfill, all waste in the landfill is assumed to be the

particular FFC waste under consideration. Therefore, larger landfills will necessarily be more

conservative as there will be no dilution of the FFC wastes by mixing with other wastes. No waste

streams bounded out completely and therefore a more realistic, high-end assessment was

undertaken using a deterministic modeling approach. 

The following subsections present the major issues to consider in reaching a conclusion

for each of the waste categories, a preliminary conclusion for each waste category, and finally

presentation of a brief overall conclusion. For each subsection, any exceedences will be discussed

with particular attention to the maximum exceedence11. Driving input parameters that lead to

these exceedences will then be discussed. In addition, results that are close to an exceedence

(defined as one order of magnitude) will be discussed.
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8.1 Coal-fired Utility Co-managed Wastes

8.1.1 Coal-fired Utility Co-managed Wastes Managed in Onsite Landfill

Ingestion

Arsenic, barium, and thallium, showed exceedences for ingestion from the landfill

scenario. All risks and HQ’s are fairly low with the exception of child ingestion risks from arsenic. 

For modeling purposes the entire landfill was made up of the coal co-managed wastes and

thus starting concentrations were those totals data as presented in Appendix B. The

representativeness of this data for the universe of coal-fired co-managed wastes is questionable. 

It is possible that true waste population concentrations differ from the data used. This could

substantially increase or decrease risks depending on the direction degree of the bias. 

Conservative assumptions were made regarding the physical characteristics of the waste. 

For fate and transport modeling, the waste was characterized as an ash. It is likely that the comanaged waste would not retain the properties of the ash and therefore its mobility would be less

than that of an ash. Further, coal ash demonstrates self cementing properties. These properties

would also retard mobility in the environment; however, the effects of this behavior was not able

to be modeled.

It is uncertain whether there are erosion and runoff controls from these landfills. The

landfills were modeled under the assumption that there are no controls. If, in fact, there are

erosion and runoff controls, exposure and risk estimates will be overstated.

Many of the conservative assumptions that were made for this analysis (e.g., physical

properties of the waste, no runoff/erosion controls) would lead to overestimates of risk. Some

modeling assumptions would also overestimate risk (e.g., inability to take into account self

cementing properties) while other modeling assumptions may slightly underestimate risks

(assuming a flat, even-grade source for dispersion modeling). In general, it is believed that the

conservative assumptions used in the fate and transport modeling would overestimate risks. 

However, the driving risk parameter is waste concentration. The waste characterization data also

has a great deal of uncertainty. Any bias in the waste characterization data could have significant

impacts on the level of risk. A fairly small bias could dictate whether arsenic, thallium, and/or

barium exceed risk levels of concern.

Inhalation

Exceedences were only seen for chromium VI at fairly low levels for this pathway. Many

of the conservative assumptions regarding the physical characteristics of the waste and the waste

management practices would tend to overestimate emissions. Also, total chromium

concentrations were modeled as chromium VI. It is highly unlikely that all of the chromium in the
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waste would be present solely as chromium VI. If the various species of chromium were

accounted for individually, the risks from chromium would probably drop.

8.1.2 Coal-fired Utility Co-managed Wastes Managed in Dewatered Surface

Impoundment

Ingestion and Inhalation

Arsenic showed exceedences at relatively low risk levels for ingestion and chromium VI

showed exceedences at relatively low levels for chromium. The only release mechanism modeled

for this scenario were air emissions. As mentioned above, the waste is characterized as an ash. 

Also, emissions are calculated, and dispersion is modeled, as if the WMU were a flat, even grade

unit. In reality, if a surface impoundment were left without official closure, the design

characteristics would dictate that the waste would actually be below-grade. This would

significantly reduce windblown emissions and dispersion. Also, if the unit were left without

official closing, the waste would not retain ash-like properties. It is more likely that the waste

would cake over thereby reducing emissions potential. Further, it is documented that often these

types of units exhibit opportunistic re-vegetation given sufficient time. This too would retard

both emissions and dispersion of particles. Based on these arguments, the risks from this scenario

are probably overstated.

8.2 Oil-fired Utility Wastes

The only exceedence observed for this waste stream was for ingestion of arsenic for the

onsite landfill scenario. (Note that this is the only waste management unit assessed.)

As with the coal-fired utility co-managed waste, this waste was modeled using fly ash

characteristics and assuming year round disposal and emissions. In reality, it is more likely that

the surface impoundments, from which this waste is derived, are dredged infrequently (once or

twice per year) and these wastes then sent to the landfill. The waste material would be wet,

thereby reducing air emissions. It is also likely that the wastes would be covered when disposed

of due to the infrequency of the landfill disposal. If not covered, the waste would probably crust

over as it dried thereby reducing the potential for emissions. Due to the conservative assumptions

of the waste management practices, and fate and transport modeling, the risks from this waste

may be overestimated. 

8.3 FBC Wastes

Exceedences were observed for ingestion of arsenic and inhalation of chromium VI for the

onsite landfill scenario. No exceedences were observed for the agricultural soil amendment

scenario.
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Ingestion

All of the uncertainty issues discussed in the coal-fired co-managed waste landfill are

relevant to this scenario also. Of particular importance to this waste, however, is the issue of the

wastes self cementing properties. FBC waste’s self cementing properties are more pronounced

than those of coal ash. This property would retard migration of waste contaminants and, thus,

risks may be over stated.

Inhalation

It is believed that risks from inhalation of chromium are overstated due to the speciation

issue mentioned above and due to the fact that the waste’s self cementing properties were not able

to be incorporated in fate and transport modeling.

8.4 Coal-fired Non-utility Wastes

The only exceedences observed for this waste stream are from ingestion of arsenic. This

was observed in both the onsite and offsite landfill. Because the same waste characterization data

that were used for the coal-fired utility wastes were used for this waste, all of the issues discussed

for ingestion in Section 7.1.1 are relevant here. 

8.5 General Conclusions from Human Health Risk Assessment

All risk exceedences for all waste streams were below 1E-5 with the exception of the

utility coal-fired co-managed waste/child receptor scenario which had a maximum risk of 1.7E-5. 

For ingestion pathways, arsenic is the only carcinogen that had exceedences and for the inhalation

pathway chromium VI is the only carcinogen that had exceedences. The only non-carcinogens

that had an exceedence were barium and thallium with maxium HQ’s of 1.0 and 1.1 for the utility

coal-fired co-managed waste/child receptor scenario via the ingestion pathway. There were no

non-carcinogen HQ exceedences for the inhalation pathway. The general conclusion is that the

constituents of most concern are arsenic for ingestion and chromium VI for inhalation.

The driving risk parameter is starting waste concentration. Other important parameters

include: area of the WMU, exposure duration, and distance to receptor. 

There are several uncertainty issues for this analysis. Most of the assumptions made are

conservative and would err to be protective. These assumptions thus may overstate risks. 

However, the major uncertainty issue for this study is the waste characterization. This is

especially important since the driving risk parameter is waste concentration. Any bias in the

sampling data that were used to develop the waste characterization would have important effects

on the risk results and decisions drawn from this analysis.

8.6 General Conclusions from Ecological Risk Assessment
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The risk estimates (i.e., HQ results) for landfills and land application units suggest that

ecological risks associated with the release and surface transport of CPECs are not likely to be

significant for these management/use practices. Because these results are generally based on no

effects levels for mammals and birds, it is expected that even threatened and endangered

mammalian and avian species are unlikely to receive exposures that would warrant concern. 

However, it is difficult to provide unequivocal support to that assertion without the benefit of a

more site-based analytical framework. In addition, the subsurface pathway was not evaluated in

the FFC ERA, and there is some concern that this pathway may be significant in areas with high

water tables that intersect critical wetlands and estuarine systems.

The risk estimates for on-site use of comanaged coal ash surface impoundments indicate

that this scenario is of special concern. The potential for adverse effects associated with exposure

to CPECs in surface impoundments is support by SAB comments on the HWIR analysis as well as

a review of case studies on surface impoundments used to manage FFC residuals. Wildlife (i.e.,

mammals and birds) and amphibians frequently utilize surface impoundments and nearby wetlands

as part of their habitat. Amphibian sensitivity to these trace metals has been confirmed by review

of case studies indicating adverse effects to amphibians exposed to FFC coal residuals. The

exceedances noted for amphibians indicate the potential for acute effects (i.e., lethality) to

amphibian populations inhabiting surface water impoundments. In contrast, the exceedances noted

for wildlife indicate the potential for adverse effects to the reproductive capacity of wildlife

species. The probability of wildlife being directly exposed to surface impoundment water will vary

depending on the surrounding habitat. The most likely receptor to be exposed would be avian

receptors that are able to circumvent barriers to forage or nest in pond areas. The lack of prey for

avian species (i.e., absence of fish and aquatic invertebrates) may limit the capacity of the pond to

support large populations of birds. Although this exposure pathway is only likely to affect a small

portion of receptors species, it may have acute impacts to receptors inhabiting these areas.
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9.0 References Cited

ABC (American Biogenics Corp.). 1986. Ninety-day gavage study in albino rats using nickel. 

Draft Final Report submitted to Research Triangle Institute, P.O. Box 12194, Research Triangle

Park, NC 27709. As cited in U.S. EPA (Environmental Protection Agency). IRIS (Integrated

Risk Information System). 1994.

Adriano, D. C., Page, A. L., Elseewi, A. A., Chang, A. C., and Straughan, I. 1980. Utilization and

disposal of fly ash and other coal residues in terrestrial ecosystems: A review. Journal of

Environmental Quality 9, 333-344. 

Alberts, James J., Newman, Michael C., and Evans, David W. 1985. Seasonal variations of trace

elements in dissolved and suspended loads for coal ash ponds and pond effluents. Water, Air, and

Soil Pollution 26, 111-128.

Allen, Herbert E. and David J. Hansen. 1996. The importance of trace metal speciation to water

quality criteria. Water Environment Research. 68: 42-54.

Allen, Herbert E., (Ed.). Metal Contaminated Aquatic Sediments. 1995. Ann Arbor Press, Inc.,

Chelsea, Michigan.

Allen, Herbert E., Garrison, A. Wayne, and Luther, George W. III., (Eds.). 1998. Metals in

Surface Waters. Sleeping Bear Press, Chelsea, Michigan.

Alloway, B. J. 1995. Heavy Metals in Soils. Blackie Academic and Professional, London, UK.

Ambrose, A. M., P. S. Larson, J. F. Borzelleca, and G. R. Hennigar, Jr. 1976. Long term

toxicologic assessment of nickel in rats and dogs. J. Food Sc. & Tech. 13:181-187.

Andreae, M. O. (1986). Organoarsenic compounds in the environment. In: Craig, P. J. (Ed.),

Organometallic compounds in the environment. Harlow, Longman, pp. 198-228.

Andreae, M. O., Byrd, J. T., and Froelich, P. N., Jr. (1983). Environ. Sci. Technol. 17:731.

Andreae, M. O., and Froelich, P. N., Jr. (1984). Tellus 36B:101.

Andreae, M. O., and Andreae, T. W. (1989). Dissolved arsenic species in the Schelde Estuary

and watershed, Belgium, Estuarine Coastal Shelf Sci. 29:421-433. 

Anderson, L. C. D., and Bruland, K. W. (1991). Biogeochemistry of arsenic in natural waters:

The importance of methylated species. Environ. Sci. Technol. 25:420-427.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 88

Anderson, M. A., Ferguson, J. F., and Gavis, J. (1976). Arsenate adsorption on amorphous

aluminum hydroxides. J. Colloid Interface Sci. 54:391-399. 

Andren, A.W., B. Wingert-Runge, and D.Sedlak. 1995. The occurrence and behavior of silver in

natural waters. In: A.W. Andren and T.W. Bober (eds.). Argentum International Conference

Proceedings (3rd): Transport, Fate and Effects of Silver in the Environment, pp. 7-10. Held in

Washington DC, August 6-9, 1995.

Ansari, M.S., W.J. Miller, M.W. Neathery, J.W. Lassiter, R.P. Gentry, and R.L. Kincaid. 1976. 

Zinc metabolism and homeostasis in rats fed a wide range of high dietary zinc levels. Proc. Soc.

Exp. Biol. Med. 152:192-194.

AQUIRE (AQUatic toxicity Information REtrieval Database). 1994. Environmental Research

Laboratory, Office of Research and Development, U.S. Environmental Protection Agency,

Duluth, MN

AQUIRE (AQUatic toxicity Information REtrieval Database). 1995. Environmental Research

Laboratory, Office of Research and Development, U.S. Environmental Protection Agency,

Duluth, MN

Arrington, L.R., and G.K. Davis. 1953. Molybdenum toxicity in the rabbit. Journal of Nutrition

51:295-304.

Arrington, L.R., C.B. Ammerman, and J.E. Moore. 1965. Molybdenum toxicity in rats and

rabbits. Quart. J. of the Flor. Acad. of Sci. 28:129-136.

ATSDR, (Agency for Toxic Substances and Disease Registry). 1989a. Toxicological Profile for

Arsenic. ATSDR/TP-88/02. Agency for Toxic Substances and Disease Registry (ATSDR). 

Public Health Service. 

ATSDR, (Agency for Toxic Substances and Disease Registry). 1989. Toxicological Profile for

Cadmium. U.S. Department of Health and Human Services, Public Health Service, Agency for

Toxic Substances and Disease Registry. 

ATSDR, (Agency for Toxic Substances and Disease Registry). 1989. Toxicological Profile for

Copper. US Department of Health and Human Services, Public Health Service, Agency for Toxic

Substances and Disease Registry. 

References cited therein:

Davies-Colley, R. J., Nelson, P. O., and Williamson, K. J., 1984. Copper and cadmium

uptake by estuarine sedimentary phase. Environ. Sci. Technol., 18:491-499.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 89

Elliot, H. A., Leberati, M. R., and Huang, C. P., 1986. Competitive adsorption of heavy

metals by soil. J. Environ. Qual., 15:214-219.

Fuhrer, G. J., 1986. Extractable cadmium, mercury, copper, lead, and zinc in the Lower

Columbia River Estuary, Oregon and Washington. In: U.S. Geological Survey waterresources investigations report. Portland, OR: U.S. Department of the Interior, U.S.

Geological Survey 86:4088.

Long, D. T., and Angino, E. F., 1977. Chemical speciation of Cd, Cu, Pb, Zn in mixed

freshwater, seawater, and brine solutions. Geochim. Cosmochim. Acta, 41:1183-1191.

McIlroy, L. M., DePinto, J. V., Young, T. C., et al., 1986. Partitioning of heavy metals to

suspended solids of the Flint River, Michigan. Environ. Toxicol. Chem., 5:609-623.

Stiff, M. J., 1971. The chemical states of copper in polluted fresh water and a scheme of

analysis to differentiate them. Water Res., 5:585-599.

Tan W. T., Tan, G. S., and Khan, I. S. A. N., 1988. Solubilities of trace copper and lead

species and the complexing capacity of river water in the Linggi River Basin. Environ.

Pollut., 52:221-235.

Truitt, R. E., and Weber, J. H., 1981. Copper (II) - and cadmium (II) - binding abilities of

some New Hampshire freshwaters determined by dialysis titration. Environ. Sci.

Technol., 15:1204-1212.

Tyler, L. D., and McBride, M. B., 1982. Mobility and extractability of cadmium, copper,

nickel, and zinc in organic and mineral soil columns. Soil Sci., 134:198-205. 

ATSDR, (Agency for Toxic Substances and Disease Registry). 1990. Toxicological Profile for

Silver. U.S. Department of Health and Human Services, Public Health Service, Agency for Toxic

Substances and Disease Registry.

ATSDR, (Agency for Toxic Substances and Disease Registry). 1992. Toxicological Profile for

Antimony: Draft. U.S. Department of Health and Human Services, Public Health Service,

Agency for Toxic Substances and Disease Registry.

ASTDR, (Agency for Toxic Substances and Disease Registry), 1993. Toxicological Profile for

Cadmium (Update). U.S. Department of Health and Human Services, Public Health Service,

Agency for Toxic Substances and Disease Registry. 

References cited therein:
Draft Version: Do Not Cite or Quote June 5, 1998

Page 90

Callahan, M. A., Slimak, M. W., Gable, N. W., et al., 1979. Water-related fate of 129

priority pollutants. Washington D.C.: U.S. Environmental Protection Agency, Office of

Water Planning and Standards. EPA-440/4-79-029a.

ATSDR (Agency for Toxic Substances and Disease Registry). 1993a. Toxicological Profile for

Beryllium. U.S. Department of Health and Human Services, Public Health Service, Agency for

Toxic Substances and Disease Registry, Atlanta, GA.

References cited therein:

Bowen, H. J. M., 1979. Environmental chemistry of the elements. New York, NY,

Academic Press.

Callahan, M. A., Slimak, M .W., Gabel, N. W., et al., 1979. Water-related environmental

fate of 129 priority pollutants. Washington, D.C., U.S. Environmental Protection Agency,

Vol. 1, Washington D.C., EPA-440/4-79-029a.

Eckel, W. P., and Jacob, T. A., 1989. Ambient concentrations of 25 “dissolved” and

“total” metals in U.S. surface waters. Environ. Sci. Technol., (cited as accepted in

ASTDR).

Eckel, W. P., and Langley, W. D., 1988. A background-based ranking technique for

assessment of elemental enrichment in soils at hazardous waste sites. In: Proceedings of

the 9th National Conference: Superfund ’88, Washington D.C. November 28-30, 1988.

Fishbein, L., 1981. Sources, transport and alterations of metal compounds: an overview. 

I. Arsenic, beryllium, cadmium, chromium, and nickel. Environmental Health

Perspective, 40:43-64.

Reeves, A. L., 1986. Beryllium. In: Handbook on the toxicology of metals, Vol. II. 2nd

Edition. New York, Elsevier Science Publishing Co., Inc., pp. 95-116.

Rossman, M. D., and Barres, J., 1988. Trace element concentrations in near-surface

waters of the great lakes and methods of collection storage and analysis. J. Great Lakes

Res., 14:188-204.

ATSDR (Agency for Toxic Substances and Disease Registry). 1993e. Toxicological Profile for

Lead. U.S. Department of Health and Human Services, Public Health Service, Atlanta, Georgia.

References cited therein:

EPA, 1979d. Water-related environmental fate of 129 priority pollutants. Volume I:

Introduction and technical background, metals and inorganic pesticides and PCBs. 
Draft Version: Do Not Cite or Quote June 5, 1998

Page 91

Washington D.C.: U.S. Environmental Protection Agency. EPA-440/4-79-029a, 13-1-43-

19.

EPA, 1986a. Air quality criteria for lead. Research Triangle Park, NC: U.S.

Environmental Protection Agency, Office of Research and Development, Office of Health

and Environmental Assessment, Environmental Criteria and Assessment Office. EPA

600/8-83-028F.

NSF, 1977. Lead in the environment. In: W. R., Boggess (Ed.), Washington D.C.:

National Science Foundation, NSF/RA-770214.

Olson, K. W., and Skogerboe, R. K., 1975. Identification of soil lead compounds from

automotive sources. Environ. Sci. Technol., 9:327-333.

ATSDR (Agency for Toxic Substances and Disease Registry). 1993f. Toxicological Profile for

Nickel. U.S. Department of Health and Human Services, Public Health Service. Atlanta,

Georgia.

ATSDR (Agency for Toxic Substances and Disease Registry). 1993h. Toxicological Profile for

Chromium. Public Health Service, U.S. Department of Health and Human Services, Atlanta, GA.

References cited therein:

Borg, H., 1987. Trace metals and water chemistry in forest lakes in northern Sweden. 

Water Res., 21:65-72.

Cary, E. E., 1982. Chromium in air, soil, and natural. In: S. Langard (Ed.), Topics in

Environmental Health 5: Biological and Environmental Aspects of Chromium. Elsevier

Science Publishers, New York, pp. 49-64.

EPA, 1984a. Health assessment document for chromium. Research Triangle Park, NC:

Environmental Assessment and Criteria Office, U.S. Environmental Protection Agency. 

EPA 600/8-83-014F

ATSDR, (Agency for Toxic Substances and Disease Registry). 1994c. Toxicological Profile for

Zinc (Update). Public Health Service, U.S. Department of Health and Human Services, Atlanta,

GA.

References cited therein:

Houba, C., Remacle, J., Dubois, D., et al., 1983. Factors affecting the concentrations of

cadmium, zinc, copper, and lead in the sediments of the Vesdre River. Water Res.,

17:1281-1286.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 92

Pita, F. W., and Hyne, N. J., 1975. The depositional environment of zinc, lead and

cadmium in reservoir sediments. Water Res., 9:701-706.

Saeed, M., and Fox, R. L., 1977. Relations between suspension pH and zinc solubility in

acid and calcareous soils. Soil Sci., 124:199-204.

Sprenger, M., McIntosh, A. W., and Hoenig, S., 1987. Variability in concentrations of

selected trace elements in water and sediment of six acidic lakes. Arch. Environ. Contam.

Toxicol., 16:383-390.

White, J. R., and Discoll, C. T., 1987. Zinc cycling in an acidic Adirondack Lake. 

Environ. Sci. Technol., 21:211-216.

ATSDR (Agency for Toxic Substances and Disease Registry). 1996. Toxicological Profile for

Selenium, (Update). 

Aulerich, R.J., R.K. Ringer, and S. Iwamoto. 1974. Effects of dietary mercury on mink. 

Archives of Environmental Contamination and Toxicology, 2:43-51.

Aulerich, R.J., R.K. Ringer, M.R. Bleavins, and A. Napolitano. 1982. Effects of supplemental

dietary copper on growth, reproductive performance and kit survival of standard dark mink and

the acute toxicity of copper to mink. Journal of Animal Science 5(2):337-343

Aulerich, R.J., S.J. Bursian, R.H. Poppenga, W.E. Braselton, and T.P Mullaney. 1991. 

Toleration of high concentrations of dietary zinc by mink. J. Vet Diagn Invest 3:232-237.

Baes, C.F., and R.D. Sharp. 1983. A proposal for estimation of soil leaching and leaching

constants for use in assessment models. J. Environ. Qual. 12(1):17-28. 

Baes, C.F., III, R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. Review and Analysis of

Parameters for Assessing Transport of Environmentally Released Radionuclides Through

Agriculture. Oak Ridge National Laboratory, Oak Ridge, TN.

Bailey, Robert G. 1996. Ecosystem Geography. Springer-Verlag, New York, Inc. pp 83-104.

Barrows, M. E., S. R. Petrocelli, and K. J. Macek. 1980. Bioconcentration and elimination of

selected water pollutants by bluegill sunfish (Lepomis macrochirus). Ch. 24 in: Dynamics,

Exposure and Hazard Assessment of Toxic Chemicals. R. Haque, Ed. Ann Arbor Science Pub.

Inc., Ann Arbor, MI. pp. 379-392. 
Draft Version: Do Not Cite or Quote June 5, 1998

Page 93

Bartlett, R. J., and James, B. R., 1989. Mobility and bioavailability of chromium in soils. In: J. O.

Nriagu and E. Nieboer (Eds.), Chromium in the Natural and Human Environments. John Wiley

& Sons, Inc. pp. 267-304

Baxley, M. N., R. D. Hood, G. C. Vedel, W. P. Harrison, and G. M. Szczech. 1981. Prenatal

toxicity of orally administered sodium arsenite in mice. Bull. Environm. Contam. Toxicol.

26:749-756.

Benoit, D.A. 1975. Chronic effects of copper on survival, growth, and reproduction of the

bluegill (Lepomis macrochirus). Transactions of the Am. Fish. Soc. 104:353-358.

Benoit, G., 1995. Evidence of the particle concentration effect for lead and other metals in fresh

waters based on ultra clean technique analyses. Geochim. Cosmochim. Acta, 59(13):2677-2687.

Bergman, Harold and Dorward-King, Elaine J., (Eds.). 1997. Reassessment of Metals Criteria for

Aquatic Life Protection. SETAC Press, Pensacola, Florida. 

Besser, J. M., T. J. Canfield, and T. W. LaPoint. 1993. Bioaccumulation of organic and

inorganic selenium in a laboratory food chain. Environmental Toxicology and Chemistry 12:57-

72.

Bhumbla, D. K., and Keefer, R. F. 1994. Arsenic mobilization and bioavailability in soils. In: J.

O. Nriagu (Ed.), Arsenic in the Environment. Part I: Cycling and Characterization. John Wiley

& Sons, Inc. pp. 51-82.

Biesinger, K.E., and G.M. Christensen. 1972. Effects of various metals on survival, growth,

reproduction, and metabolism of Daphnia magna. J. Fish. Res. Bd. of Canada 29:1691-1700.

Birdsall, Charles W., Grue, Christian E., and Anderson, Allen. 1986 Lead concentrations in

bullfrog Rana catesbeiana and green frog R. clamitans tadpoles inhabiting highway drainages.

Environmental Pollution 40, 233-247.

Bleavins, M.R., R.J. Aulerich, J.R. Hochstein, T.C. Hornshaw, and A.C. Napolitano. 1983. 

Effects of excessive dietary zinc on the intrauterine and postnatal development of mink. J.

Nutrition 113:2360-7

Borg, K., K. Ernie, E. Hanko, and H. Wanntorp. 1970. Experimental secondary methyl mercury

poisoning in the goshawk (Accipiter g. gentilis L.).
Draft Version: Do Not Cite or Quote June 5, 1998

Page 94

Bosque, M.A, J.L. Domingo, J.M. Llobet, and J. Corbella. 1993. Variability in the

embryotoxicity and fetotoxicity of vanadate with the day of exposure. Vet. Hum. Toxicol.

35(1):1-3.

Brannon, J. M., and Patrick, W. H., Jr. 1987. Fixation, transformation, and mobilization of

arsenic in sediments. Environ. Sci. Technol. 21:450-459.

Browning, E. 1969. Toxicity of Industrial Metals. Ch. 25. Molybdenum pp. 243-248. 

Appleton-Century-Crofts, New York

Brieger, Gottfried, Wells, James R., and Hunter, R. Douglas. 1992. Plant and animal species

composition and heavy metal content in fly ash ecosystems. Water, Air, and Soil Pollution 63, 87-

103.

Browne, Carole and Dumont, James N. 1980. Cytotoxic effects of sodium selenite on tadpoles.

Archives of Environmental Contamination and Toxicology 9, 181-191.

Buhler, D. R., R.M. Stokes, and R.S. Caldwell. 1977. Tissue accumulation and enzymatic effects

of hexavalent chromium in rainbow trout (Salmo gairdneri). Journal of the Fisheries Research

Board of Canada 34:9.

Byron, W. R., G. W. Bierbower, J. B. Brouwer, and W. H. Hansen. 1967. Pathologic changes in

rats and dogs from two-year feeding of sodium arsenite or sodium arsenate. Toxicology and

Applied Pharmacology 10:132-147.

Cairns, Jr., J., and A. Scheier. 1968. A comparison of the toxicity of some common industrial

waste components tested individually and combined. Prog. Fish-Cult. 30(1):3-8. As cited in

AQUIRE (AQUatic Toxicity Information REtrieval Database). Environmental Research

Laboratory, Office of Research and Development, U.S. Environmental Protection Agency,

Duluth, MN.

Calamari, D., G.F. Gaggino, and G. Pacchetti. 1982. Toxicokinetics of low levels of Cd, Cr, Ni

and their mixture in long-term treatment on Salmo gairdneri rich. Chemosphere 11:59.

Camardese, M. B., D. J. Hoffman, L. J. LeCaptain, and G. W. Pendleton. 1990. Effects of

arsenate on growth and physiology in mallard ducklings. Environmental Toxicology and

Chemistry 9:785-795.

Canton, J.H., and W. Sloof. 1982. Toxicity and accumulation studies of cadmium (Cd2+) with

freshwater organisms of different trophic levels. Ecotoxicology and Environmental Safety, 6:113-

128.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 95

Carlson, Claire L. and Adriano, Domy C. 1991. Growth and elemental content of two tree species

growing on abandoned coal fly ash basins. Journal of Environmental Quality 20, 581-587.

Carlson, Claire L. and Adriano, Domy C. 1993. Environmental impacts of coal combustion

residues. Journal of Environmental Quality 22, 227-247.

Carlton, B.D., M.B. Beneke, and G.L Fisher. 1982. Assessment of the teratogenicity of

ammonium vanadate using Syrian golden hamsters. Env. Research 29:256-262.

Carson, T.L., G.A. Van Gelder, G.C. Karas, and W.B. Buck. 1974. Slowed learning in lambs

prenatally exposed to lead. Archives of Environmental Health 29:154-156.

CCME (Canadian Council of Ministers of the Environment), 1997. Recommended Canadian Soil

Quality Guidelines. 

Cember, H., E.H. Curtis, and B.G. Blaylock. 1978. Mercury bioconcentration in fish:

Temperature and concentration effects. Environmental Pollution, 17:311-319.

Chapman, Peter M., Allen, Herbert E., Godtfredsen, Kathy, and Z'Graggen, Michael N. 1996.

Evaluation of bioaccumulation factors in regulating metals. Environmental Science and

Technology 30, 448A-452A.

Chapman, G.A., S. Ota, and F. Recht. 1980. Effects of water hardness on the toxicity of metals

to Daphnia magna. U.S. EPA, Corvallis, OR. As cited in AQUIRE (AQUatic Toxicity

Information REtrieval Database), 1995. Environmental Research Laboratory, Office of Research

and Development, U.S. Environmental Protection Agency, Duluth, MN.

Cherry, D. S. and Guthrie, R. K. 1977. Toxic metals in surface water from coal ash. Water

Resources Bulletin 13, 1227-1236

Cherry, Donald S. and Guthrie, Rufus K. 1978. Mode of elemental dissipation from ash basin

effluent. Water, Air, and Soil Pollution 9, 403-412. 

Cherry, Donald S., Guthrie, Rufus K., Davis, Ernst M., and Harvey, Raymond S. 1984. Coal ash

basin effects (particulates, metals, acidic pH) upon aquatic biota: An eight-year evaluation. Water

Resources Bulletin 20, 535-544.

Chowdhury, A. R., and H. Venkatakrishna-Bhatt. 1983. Effect of selenium dioxide on the testes

of rat. Indian J Physiol Pharmacol. 27:237-240. 

Chunguo, C., and Zihui, L. (1988). Chemical speciation and distribution of arsenic in water,

suspended solids and sediments of Xiangjiang River, China. Sci. Tot. Environ. 77:69-82. 
Draft Version: Do Not Cite or Quote June 5, 1998

Page 96

Clement Associates, Inc. 1990a. Toxicological Profile for Barium: Draft. Prepared for U.S.

Department of Health and Human Services, Public Health Service, Agency for Toxic Substances

and Disease Registry (ATSDR).

Clement Associates, Inc. 1990b. Toxicological Profile for Vanadium: Draft. U.S. Department

of Health and Human Services, Public Health Service, Agency for Toxic Substances and Disease

Registry (ATSDR).

Clement International Corporation. 1994a. Draft: Toxicological Profile for Silver. Prepared for

U.S. Department of Health and Human Services, Agency for Toxic Substances and Disease

Registry, Contract No. 205-88-0608.

Cockell, K. A., and J. W. Hilton. Abstract: Chronic Toxicity of Dietary Inorganic and Organic

Arsenicals to Rainbow Trout (Salmo gairdneri R.). Sponsor: S. J. Slinger. Nutrition

Department, University of Guelph, Guelph, Ontario, N1G 2W1. Nutritional Pharmacology and

Toxicology. 

Connell, D.B., J.G. Sanders, G.F. Riedel, and G.R. Abbe. 1991. Pathways of silver uptake and

trophic transfer in estuarine organisms. Environ. Sci. Technol. 25:921-924.

Coughlan, D.J., S.P. Gloss, and J. Kubota. 1986. Acute and sub-chronic toxicity of lead to the

early life stages of smallmouth bass (Micropterus dolomieui). Water, Air, and Soil Pollution

28:265-275. 

Coyle, J. J., D. R. Buckler, C. G. Fairchild, and T. W. May. 1993. Effect of dietary selenium on

the reproductive success of bluegills (Lepomis macrochirus). Environmental Toxicology and

Chemistry 12:551-565.

Craig, P. J. (Ed.). 1985. Organometallic compounds in the environment: principles and reactions. 

Longman, New York, pp. 1-58.

Crecelius, E. A., Bloom, N. S., Cowan, C. E., and Jenne, E. A. (1986). Speciation of selenium

and arsenic in natural waters and sediments: arsenic speciation. Electric Power Research

Institute, vol. 2, EA-4641. Project 2020-2.

Crecelius, E., and J. Leather. 1996. Release of silver and other metals from resuspended harbor

sediment. In: Argentum International Conference Proceedings (4th): Transport, Fate, and

Effects of Silver in the Environment. Held at University of Wisconsin-Madison, August 25-28.

Cullen, W. R., and Reimer, K. J. (1989). Arsenic speciation in the environment. Chem. Rev.

89:713-764.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 97

Custer, T.W., J.C. Franson, and J.F. Moore. 1986. Reproductive success and heavy metal

contamination in Rhode Island common terns. Environmental Pollution A41:33-52.

Cutter, G.A. 1986. Speciation of Selenium and Arsenic in Natural Waters and Sediments, Vol. 1,

EA-4641. Electric Power Research Institute, Palo Alto, California. 

Cutter, G.A. 1989. The estuarine behavior of selenium in San Francisco Bay. Estuarine, Coastal

Shelf Science, 28(1):13-34

Dallinger, Reinhard and Rainbow, Philip S. , (Eds.). 1993. Ecotoxicology of Metals in

Invertebrates. Lewis Publishers, Boca Raton, Florida,. 

Dave, G. 1984. Effects of copper on growth, reproduction, survival, and haemoglobin in

Daphnia magna. Comp. Biochem. Physiol. 78C:425-431. As cited in Suter II, G.W. and J.B.

Mabrey. 1994. Toxicological Benchmarks for Screening of Potential Contaminants of Concern

for Effects on Aquatic Biota: 1994 Revision. DE-AC05-84OR21400. Office of Environmental

Restoration and Waste Management, U.S. Department of Energy, Washington, DC.

Davies, B.E., 1983. Heavy Metal Contamination from Base Metal Mining and Smelting: 

Implications for Man and His Environment. Chapter 14 in: Applied Environmental

Geochemistry. Academic Press, London. ISBN 0-12-690640-8.

Davies, P.H., J.G. Goettl, J.R. Sinley, Jr., and N.F. Smith. 1976. Acute and chronic toxicity of

lead to rainbow trout, Salmo gairdneri, in hard and soft water. Water Res. 10:199-206

Davies, P.H., J.P. Goettl, Jr. and J.R. Sinley. 1978. Toxicity of silver to rainbow trout (Salmo

gairdneri) Water Res. 12:113-117. As cited in LeBlanc, G.A. 1984. Interspecies relationships in

acute toxicity of chemicals to aquatic organisms. Environmental Toxicology and Chemistry,

Vol.3, p47-60.

Day, W.A., J.S. Hunt and A.R. McGiven. 1976. Silver deposition in mouse glomeruli. 

Pathology. 8:201-204. As cited in U.S EPA (Environmental Protection Agency). 1985. Drinking

Water Criteria Document for Silver. Prepared by the Environmental Criteria and Assessment

Office, Cincinnati, OH for the Office of Drinking Water.

De Boeck, Gudrun, De Smet, Hans, and Blust, Ronny. 1995. The effects of sublethal levels of

copper on oxygen consumption and ammonia excretion in the common carp, Cyprinus carpio.

Aquatic Toxicology 32, 127-141.

Deknudt, Gh., A. Leonard, J. Arany, G. Jenar-Du Buisson, and E. Delavignette. 1986. In vivo

studies in male mice on the mutagenic effects of inorganic arsenic. Mutagenesis 1(1):33-34.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 98

Delos et al., 1984. Technical guidance manual for performing waste load allocations. Book II:

Streams and rivers. Chapter 3: Toxic substances. US EPA. Washington, DC. EPA-440/4/84-022.

Demayo, A., M.C. Taylor, K.W. Taylor, and P.V. Hodson. 1982. Toxic effects of lead and lead

compounds on human health, aquatic life, wildlife plants, and livestock. CRC Critical Reviews in

Environmental Controls 12:257-305.

Desquidt, J., P. Vasseur and J. Gromez-Potentier. 1974. Etude toxicologique experimentale de

quelques derive argentiques. 1. Localisation et elimination. (Experimental toxicological study of

some silver derivatives. 1. Localization and elimination.) Bull. Soc. Pharm. Lille.1:23-35. As

cited in U.S EPA (Environmental Protection Agency). 1985. Drinking Water Criteria Document

for Silver. Prepared by the Environmental Criteria and Assessment Office, Cincinnati, OH for the

Office of Drinking Water. 

Deutch, B., B. Borg, L. Kloster, H. Meyer, and M.M. Moller. 1980. The accumulation of 65Zn

by various marine organisms. Ophelia (Suppl.) 1:235-240. 

Dewar, W.A., P.A.L. Wright, R.A. Pearson, and M.J. Gentle. 1983. Toxic effects of high

concentrations of zinc oxide in the diet of the chick and laying hen. Poultry Science 24:397-404.

Dixon, R.L., I.P. Lee, and R.J. Sherins. 1976. Methods to assess reproductive effects of

environmental chemical studies of cadmium and boron administered orally. Environmental Health

Perspectives, 13:59-67.

Domsch, K.H. 1984. Effects of pesticides and heavy metals on biological processes in soil. 

Plant and Soil 76:367-378.

Dougherty, W.J., F. Coulston, and L. Goldberg. 1974. Toxicity of methylmercury in pregnant

rhesus monkeys. Toxicology and Applied Pharmacology, 39:138.

Doyle, Georgia A., W.Berry Lyons, Glenn C. Miller, Susan G, Donaldson. 1995. Oxyanion

concetrations in eastern Sierra Nevada rivers - 1. Selenium. Applied Geochemistry, 10:553-564.

Diaz-Mayans, J., R. Laborda, and A. Nunez. 1986. Hexavalent chromium effects on motor

activity and some metabolic aspects of Wistar albino rats. Comparative Biochemistry and

Physiology 83C:191-195.

Domingo, J.L, J.L Paternain, J.M Llobet, and J. Corbella. 1986. Effects of vanadium on

reproduction, gestation, parturition, and lactation in rats upon oral administration. Life Sciences

39:819-824.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 99

Dragun, James. 1988. The Soil Chemistry of Hazardous Materials. Hazardous Materials

Control Research Institute, Silver Spring, Maryland.

Dragun, J., and A. Chiasson. 1991. Elements in North American Soils. Hazardous Material

Control Resources Institute, Greenbelt, Maryland.

Edens, F.W., and J.D. Garlich. 1983. Lead-induced egg production decrease in Leghorn and

Japanese quail hens. Poultry Science 62:1757-1763.

Eisler, R. 1985a. Cadmium Hazards to Fish, Wildlife and Invertebrates: a Synoptic Review. 

U.S. Fish and Wildlife Service. Biological Report 85(1.2).

Eisler, R. 1985b. Selenium Hazards to Fish, Wildlife and Invertebrates: a Synoptic Review. 

U.S. Fish and Wildlife Service. Biological Report 85(1.5).

Eisler, R. 1986a. Chromium hazards to fish, wildlife, and invertebrates: a synoptic review. U.S.

Fish and Wildl. Serv. Biol. Rep. 85(1.6). 60pp

Eisler, R. 1987a. Mercury hazards to fish, wildlife, and invertebrates: a synoptic review. U.S.

Fish Wildl. Serv. Biol. Rep. 85(1.10).

Eisler, R. 1988a. Arsenic Hazards to Fish, Wildlife, and Invertebrates: A Synoptic Review. U.S

Fish and Wildlife Service. Biological Report 85(1.12)

Eisler, R. 1988b. Lead Hazards to Fish, Wildlife, and Invertebrates: A Synoptic Review. U.S.

Department of the Interior, Fish and Wildlife Service Biological Report 85(1.14).

Eisler, R. 1989b. Molybdenum Hazards to Fish, Wildlife, and Invertebrates: A Synoptic Review.

U.S. Fish and Wildlife Service Biol Rep. 85 (1.19).

Eisler, R. 1993. Zinc Hazards to Fish, Wildlife, and Invertebrates: A Synoptic Review. U.S.

Fish and Wildlife Service, Biological Report 10, Contaminant Hazards Reviews Report 25.

Elkhatib, E. A., Bennet, O. L., and Wright, R. J. (1984). Arsenite sorption and desorption in

soils. Soil Sci. Soc. Am. Proc. 48:1025-1030.

Elseroad, H.J, Rue Jr. WJ, Hinckley , DA, Woodis H.L. 1994. Chemical translator guidance

manual. Palo Alto CA: Electric Power Research Institute. EPRI Report #TR-104047. 

EPRI (Electric Power Research Institute). 1997. Coal Combustion By-products and Low

Volume Wastes Co-management Survey (electronic database). June.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 100

EPRI, (Electric Power Research Institute). 1984. Chemical Attenuation Rates, Coefficients, and

Constants in Leachate Migration, Volume 1: A Critical Review. EPRI EA-3356, Final Report. 

Prepared by Battelle, Pacific Northwest Laboratories, Richland, Washington.

EPRI, Electric Power Research Institute. 1994. Chemical Translator Guidance Manual. EPRI TR104047. EA Engineering,Science,and Technology, Inc., Hunt Valley, Maryland. 

EQM (Environmental Quality Management, Inc.) and E.H. Pechan and Associates. 1993. 

Evaluation of the Dispersion Equations in the Risk Assessment Guidance for Superfund: 

Volume I- Human Health Evaluation Manual; Draft. Prepared for U.S. Environmental

Protection Agency. Office of Remedial Response Toxics Integration Branch. Washington, D.C. 

57 FR 24152. June 5, 1992. U.S. Environmental Protection Agency (FRL-4139-7). Draft Report:

A Cross-Species Scaling Factor for Carcinogen Risk Assessment Based on Equivalence of

mg/kg3/4/day. 

57 FR 60848. December 22, 1992. U.S. Environmental Protection Agency. 40 CFR Part 131. 

Water Quality Standards; Establishment of Numeric Criteria for Priority Toxic Pollutants; States’

Compliance; Final Rule.

60 FR 15366. March 23, 1995. Final Water Quality Guidance for the Great Lakes System; Final

Rule.

60 FR 22229-22237. May 4, 1995. U.S. Environmental Protection Agency. 40 CFR Part 131.

Water quality standards; Establishment of numeric criteria for Priority Toxic Pollutants; States'

compliance - Revison of metals criteria, Interim Final Rule. 

Ferard, J.F., J.M. Jouany, R. Truhaut, and P. Vasseur. 1983. Accumulation of cadmium iuna

freshwater food chain experimental model. Ecotoxicology and Environmental Safety, 7:43-52. 

Ferm, V. H., and S. J. Carpenter. 1968. Malformations induced by sodium arsenate. J. Reprod.

Fert. 17:199-201.

Ferm, V. H., A. Saxon, and B. M. Smith. 1971. The teratogenic profile of sodium arsenate in the

golden hamster. Arch Environ Health 22:557-560.

Fimreite, N. 1970. Effects of methyl mercury treated feed on the mortality and growth of

leghorn cockerels. Canadian Journal of Animal Science, 50:387-389.

Finley, M.T., W.H. Stickel, and R.E. Christensen. 1979. Mercury residues in tissues of dead and

surviving birds fed methylmercury. Bulletin of Environmental Contamination and Toxicology. 

21(1/2):105-110.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 101

Ford, C. J., Byrd, J. T., Grebmeier, J. M., Harris, R. A., Moore, R. C., Madix, S. E., Newman, K.

A., and Rash, C. D. 1995. Final project report on arsenic biogeochemistry in the Clinch River

and Watts Bar Reservoir; Volume 1: Main Text. ESD Publication 4185. Environmental Sciences

Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee.

Forsythe, B.L., II, T.W. La Point, G.P. Cobb, and S.J. Klaine. Clemson University, Pendleton,

South Carolina. In: A.W. Andren and T.W. Bober (eds.). Argentum International Conference

Proceedings (3rd): Transport, Fate and Effects of Silver in the Environment, pp. 7-10. Held at the

University of Wisconsin - Madison on August 25-28, 1996.

Franson, J.C., and T.W. Custer. 1982. Toxicity of dietary lead in young cockerels. Veterinary

and Human Toxicology 24:421-423.

Franson, J.C., L. Sileo, O.H. Pattee, and J.F. Moore. 1983. Effects of chronic dietary lead in

American kestrels (Falco sparverius). J. Wildl. Dis. 19(2):110-113.

Freda, Joseph. 1991. The effects of aluminum and other metals on amphibians. Environmental

Pollution 71, 305-328.

Frost, R. R., and Griffin, R. A. (1977). Effect of pH on adsorption of arsenic and selenium from

landfill leachate by clay minerals. Soil Sci. Soc. Am. J. 41:53-57.

Fungwe, T.V., F. Buddingh, D.S. Dimmock, C.D. Lox, M.T. Yang, and S.P. Yang. 1990. The

role of dietary molybdenum on estrous activity, fertility, reproduction and molybdenum and

copper enzyme activities of female rats. Nutrition Research 10:515-524.

Geering, H.R., E.E. Cary, L.H.P. Jones, et al. 1968. Solubility and redox criteria for the possible

forms of selenium in soils. Soil Science Society of America Proceedings, 32:35-40.

Ghosh, T.K., J.P. Kotangle, and K.P. Krishnamoorthi. 1990. Toxicity of selective metals to

freshwater algae, ciliated protozoa, and planktonic crustaceans. Environ. Ecol., 8(1B):356-360.

Giesy, J.P., Jr., G.J. Leversee, and D.R. Williams. 1977. Effects of naturally occurring aquatic

organic fractions on cadmium toxicity to Simocephalus serrulatus (Daphidae) and Gambusia

affinis (Poeciliidae. Water Res., 11:1013-1020.

Gill, G.A., P.H. Santschi, R. Lehman, and L.S. Wen. 1994. Silver measurements in Texas

watersheds. In: Argentum International Conference Proceedings (2nd): Transport, Fate, and

Effects of Silver in the Environment, pp. 95-97. September 11-14.

Goettl, J.P., Jr., J.R. Sinley, and P.H. Davies. 1972. Laboratory Studies: Water Pollution

Studies. In: L.E. Yeager and D.T. Weber (Eds.), Colorado Fish. Res. Rev. No. 7, Div. Game
Draft Version: Do Not Cite or Quote June 5, 1998

Page 102

Fish Parks, Ft.Collins, CO:36-49. As cited in AQUIRE (AQUatic Toxicity Information REtrieval

Database). 1995. Environmental Research Laboratory, Office of Research and Development,

U.S. Environmental Protection Agency, Duluth, MN.

Golden, D. M. 1983. Water pollution arising from solid waste (coal, fly ash, slag) disposal, and

measures to prevent water pollution. Water Sci.Technol. 15, 1-10. 

Guthrie, Rufus K. and Cherry, Donald S. 1979. Trophic level accumulation of heavy metals in a

coal ash basin drainage system. Water Resources Bulletin 15, 244-248.

Guthrie, R. K., Davis, E. M., Cherry, D. S., and Walton, J. R. 1982. Impact of coal ash from

electric power production on changes in water quality. Water Resources Bulletin 18, 135-138.

Gutenmann, Walter H., Bache, Carl A., Youngs, William D., and Lisk, Donald J. 1976. 

Selenium in fly ash. Science 191, 966-967.

Hale, J.G. 1977. Toxicity of metal mining wastes. Bulletin of Environmental Contamination

and Toxicology 17:66-73.

Halter, M.T., W.J. Adams, and H.E. Johnson. 1980. Selenium toxicity to Daphnia magna,

Hyallela azteca, and the fathead minnow in hard water. Bull. Envionm. Contam. Toxicol.

24:102-107.

Hamilton, S.J., and K.J. Buhl. 1990. Safety assessment of selected inorganic elements to fry of

chinook salmon (Oncorhynchus tshawytscha). Ecotox. and Env. Safety 20:307-324

Hamilton, S.J., and K.J. Buhl. 1990. Acute toxicity of boron, molybdenum, and selenium to fry

of chinook salmon and coho salmon. Arch. Environ. Toxicol. 19:366-373.

Hamilton, Steven J., Buhl, Kevin J., Faerber, Neil L., Wiedmeyer, Raymond H., and Bullard, Fern

A. 1990. Toxicity of organic selenium in the diet of chinhook salmon. Environmental Toxicology

and Chemistry 9, 347-358. 

Hamilton, A., and H. Hardy. 1974. Industrial Toxicology. Publishing Sciences Group, Inc.,

Acton, MA.

Harr, J. R., and O. H. Muth. 1972. Selenium poisoning in domestic animals and its relationship

to man. Clin Toxicol 5:175-186.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 103

Harrison, S.E. and J. F. Klaverkamp. 1989. Uptake, elimination and tissue distribution of dietary

and aqueous cadmium by rainbow trout (Salmo gairdneri Richardson) and lake whitefish

(Coregonus clupeaformis Mitchill). Environmental Toxicology and Chemistry, 8:87-97.

Hart, B. T., and Hines, T., 1995. Trace elements in rivers. In: B. Salbu and E. Steinnes (Eds.),

Trace Elements in Natural Waters. CRC Press, Inc. pp. 203-221.

Hartenstein, R., E.F. Neuhauser, and J. Collier. 1980. Accumulation of heavy metals in the

earthworm Eisenia foetida. Journal of Environmental Quality 9:23-26.

Heinz, G. H. 1974. Effects of low dietary of methyl mercury on mallard reproduction. Bulletin

of Environmental Contamination and Toxicology. 11:386-392.

Heinz, G.H. 1975. Effects of methylmercury on approach and avoidance behavior of mallard

ducklings. Bulletin of Environmental Contamination and Toxicology, 13:554-564

Heinz, G. H. 1976a. Methylmercury: second-year feeding effects on mallard reproduction and

duckling behavior. Journal of Wildlife Management. 40(1):82-90.

Heinz, G. H. 1976b. Methylmercury: second-generation reproductive and behavioral effects of

mallard ducks. Journal of Wildlife Management. 40(4):710-715.

Heinz, G. H. 1979. Methylmercury: reproductive and behavioral effects on three generations of

mallard ducks. Journal of Wildlife Management. 43(2):394-401.

Heinz, G. H., and S. D. Haseltine. 1981. Avoidance behavior of young black ducks treated with

chromium. Toxicology Letters. 8:307-310.

Heinz, G. H., S. D. Haseltine, and L. Sileo. 1983. Altered avoidance behavior of young black

ducks fed cadmium. Environmental Toxicology and Chemistry. 2:419-421.

Heinz, G. H., D. J. Hoffman, A. J. Krynitsky, and M. G. Weller. 1987. Reproduction in mallards

fed selenium. Environmental Toxicology and Chemistry. 6:423-433.

Helmke, P. A., W. P. Robarge, R. L. Korotev, and P. J. Schomberg. 1979. Effects of soil-applied

sewage sludge on concnetrations of elements in earthworm. J. Environ. Qual. 8: 322-327.

Hermanutz, Roger O., Allen, Kathleen N., Roush, Thomas H., and Hedtke, Steven F. 1992. 

Effects of elevated selenium concentrations on bluegills (Lepomis macrochirus) inoutdoor

experimental streams. Environmental Toxicology and Chemistry 11, 217-224. 
Draft Version: Do Not Cite or Quote June 5, 1998

Page 104

Hernmayer, K.L., P.E. Stake, R.L. Shippe. 1977. Evaluation of dietary zinc, cadmium, tin, lead,

bismuth, and arsenic toxicity in hens. Poultry Science, 56:1721-1722.

Hilderbrand, D.C., R. Der, W.T. Griffin, and M.S. Fahim. 1973. Effect of lead acetate on

reproduction. Am J. Obstet Gynecol 115:1058-1065.

Hirsch, M. 1996. The effect of stabilized silver-laden waste activated sludge on the growth of

terrestrial plants. In: A.W. Andren and T.W. Bober (eds.). Argentum International Conference

Proceedings (4th): Transport, Fate, and Effects of Silver in the Environment. Held at University

of Wisconsin-Madison, August 25-28.

Hirsch, M., M. Ritter, K. Roser, P. Garrisi, and S. Forsythe. 1993. The effect of silver on plants

grown in sludge-amended soil. In: A.W. Andren and T.W. Bober (eds.). Argentum International

Conference Proceedings (1st): Transport, Fate, and Effects of Silver in the Environment, pp. 69-

73. Held at University of Wisconsin-Madison, August 10, 1993.

Hodson, P.V., D.J. Spry, and B.R. Blunt. 1980. Effects on rainbow trout (Salmo gairdneri) of a

chronic exposure to waterborne selenium. Can. J. Fish. Aquat. Sci. 37:233-240.

Hoffman, D.J., J.C. Franson, O.H. Pattee, C.M. Bunck, and A. Anderson. 1985. Survival,

growth and accumulation of ingested lead in nesting American kestrels (Falco sparverius). 

Archives of Environmental Contamination and Toxicology 14:89-94.

Hoffman, D.J., B.A. Rattner, G.A. Burton, Jr., and J. Cairns, Jr. 1995. Handbook of

Ecotoxicology. Lewis Publishers, Boca Raton. pp. 356-391.

Hogstrand, C., F. Galvez, and C.M. Wood. 1996. Toxicity, silver accumulation and

metallothionein induction in freshwater Rainbow Trout during exposure to different silver salts.

Environ. Toxicol. and Chemistry 15(7):1102-1108.

Holcombe, G.W., D.A. Benoit, E.N. Leonard, and J.M. McKim. 1976. Long-term effects of lead

exposure on three generations of brook trout (Salvelinus fontinalis). J. Fish Res. Board Can.

33:1731-41.

Holdway, D.A., J.B. Sprague, and J.G. Dick. 1983. Bioconcentration of vanadium in American

flagfish over one reproductive cycle. Water Res. 17(8):937-941.

Hood, R. D. 1972. Effects of sodium arsenite on fetal development. 1972. Bulletin of

Environmental Contamination & Toxicology 7(4):216-222.

Hood, R. D., and S. L. Bishop. 1972. Teratogenic effects of sodium arsenate in mice. Arch

Environ Health 24:62-65.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 105

Hopkins, William A., Congdon, Justin D., and Mendonça, Mary T. 1997. Increased circulating

levels of testosterone and corticosterone in southern toads, Bufo terrestris, exposed to coal

combustion waste. General and Comparative Endocrinology 108, 237-246.

Hothem, Roger L. and Ohlendorf, Harry M. 1989. Contaminants in foods of aquatic birds at

Kesterson Reservoir, California, 1985. Archives of Environmental Contamination and Toxicology

18, 773-786. 

Hulse, Michael, Mahoney, John S., Schroder, Gene D., Hacker, Carl S., and Pier, Stanley M. 

1980. Environmentally acquired lead, cadmium, and manganese in the cattle egret, Bubulcus ibis,

and the laughing gull, Larus atricilla. Archives of Environmental Contamination and Toxicology

9, 65-78.

Hutchinson, N.J. and J.B. Sprague. 1987. Reduced lethality of Al, Zn, and Cu mixtures to

American Flagfish by complexation with humic substances in acidified soft waters. 

Environmental Toxicology and Chemistry. 6:1-11.

Ihnat, M. (ed.) 1989. Occurrence and Distribution of Selenium. CRC Press. Boca Raton. 

Florida. 

Ingersoll, Christopher G., Dillon, Tom, and Biddinger, Gregory R., (Eds.). 1997. Ecological Risk

Assessment of Contaminated Sediments. SETAC Press, Pensacola, Florida.

Isensee, A. R., P. C. Kearney, E. A. Woolson, G. E. Jones, and V. P. Williams. 1973. 

Distribution of alkyl arsenicals in model ecosystems. Environmental Science and Technology .

7(9):841-845

Ivankovic, S., and R. Preussmann. 1975. Absence of toxic and carcinogenic effects after

administrations of high doses of chronic oxide pigment in subacute and long term feeding

experiments in rats. Food and Cosmetics Toxicology 13:347-351.

Jauge, P., and L. M. Del-Razo. 1985. Uric acid levels in plasma and urine in rats chronically

exposed to inorganic As (III) and As (V). 1985. Toxicology Letters 26:31-35.

Jensen, A. and F. Bro-Rasmussen. 1992. Environmental Cadmium in Europe. Reviews of

Environmental Contamination and Toxicology. Vol. 125., Springer-Verlag New York, Inc.

Jeter, M.A., and G.K. Davis. 1954. The effect of dietary molybdenum upon growth, hemoglobin,

reproduction and lactation of rats. Journal of Nutrition 54:215-220.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 106

Johnson, D., A.L. Mehring, H.W. Titus. 1960. Tolerance of chickens for barium. Proc. Soc.

Exp. Biol. Med. 104:436-438

Jones, K.C., B.E. Davies, and P.J. Peterson. 1986. Silver in Welsh soils: Physical and chemical

distribution studies. Geoderma 37:157-174.

Jones, K.C., and P.J. Peterson. 1986. The influence of humic and fulvic acids on silver uptake by

perennial ryegrass and its relevance to the cycling of silver in soils. Plant and Soil 95:3-8.

Jung, Robin E. and Jagoe, Charles H. 1995. Effects of low pH and aluminum on body size,

swimming performance, and susceptibility to predation of green tree frog (Hyla cinerea) tadpoles.

Canadian Journal of Zoology 73, 2171-2183. 

K-25, East of Powerhouse Area. K-720 Fly Ash Pile. Http://www.ornl.gov/er/k-er-47/c-50.htm .

1997.

Kapusta, Lawrence A., Lipton, Joshua, Galbraith, Hector, Cacela, Dave, and LeJeune, Katherine.

1995. Metal and arsenic impacts to soils, vegetation communities and wildlife habitat in southwest

Montana uplands contaminated by smelter emissions: II. Laboratory phytotoxicity studies.

Environmental Toxicology and Chemistry 14, 1905-1912.

Katz, S. A., and Salem, H., 1994. The Biological and Environmental Chemistry of Chromium. 

VCH Publishers, Inc., 214 pp.

References cited therein:

Bart, G., and von Gunten, H. R., 1979. Determination of trace elements in the river Aare

by neutron activation analysis. Inst. J. Environ. Anal. Chem., 6:25-42.

Bartlett, R. J., and James, B. R., 1979. Oxidation of chromium in soils. J. Environ.

Qual., 8:31-35.

Kaczynski, S. E., and Kieber, R. J., 1993. Aqueous trivalent chromium production in

natural waters. Environ. Sci. Technol., 27:1572-1576.

Kieber, R. J., and Heiz, G. R., 1992. Indirect photoreduction of aqueous chromium(VI). 

Environ. Sci. Technol., 26:3-07-312.

Pettine, M., Camusso, M., and Martinotti, W., 1992. Dissolved and particulate transport

of arsenic and chromium in the River Po. Sci. Tot. Environ., 119:253-280.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 107

Rai, D., Eary, L. E., and Zachara, J. M., 1989. Environmental chemistry of chromium. 

Sci. Tot. Environ., 86:15-23.

Smith, S., Peterson, P. J., and Kwan, K. H. M., 1989. Chromium accumulation, transport,

and toxicity in plants. Toxicol. Environ. Chem., 24:241-251.

Khera, K. S. 1979. Teratogenic and genetic effects of mercury toxicity. pp. 501-518. In J. O.

Nriagu (ed.). The Biogeochemistry of Mercury in the Environment. Elsevier/North-Holland

Biomedical Press, New York.

Kimmel, C.A., L.D. Grant, C.S. Sloan, and B.C. Gladen. 1980. Chronic low-level lead toxicity

in the rat. I. Maternal toxicity and perinatal effects. Toxicology and Applied Pharmacology

56:28-41.

Klein-MacPhee, G., J.A. Cardin, and W.J. Berry. 1984. Effects of silver on eggs and larvae of the

winter flounder. Transactions of the American Fisheries Society 113(2):247-251

Kline, K. D., V. W. Hays, and G. L. Cromwell. 1971. Effects of copper, molybdenum and

sulfate on performance, hematology and copper stores of pigs and lambs. J Animal Sci 33:771-

779. As cited in Agency for Toxic Substances and Disease Registry (ATSDR). 1990.

Toxicological Profile for Copper. Public Health Service, U.S. Department of Health and Human

Services, Atlanta, GA.

Koljonen, T. 1975. The behavior of selenium in Finnish soils. Ann. Agric. Fenn. Vol. 14. Page

240

Kramer, J.R. 1995. Aqueous geochemistry of silver: Conceptual. In: A.W. Andren and T.W.

Bober (eds.). Argentum International Conference Proceedings (3rd): Transport, Fate, and

Effects of Silver in the Environment, pp. 19-30. Held in Washington, DC, August 6-9.

Kramer, J.R., R.A. Bell, P.V. Collins, S. Malcolmson, and C. Rogers. 1994. Nature and fate of

silver, Part I. In: A.W. Andren and T.W. Bober (eds.). Argentum International Conference

Proceedings (2nd): Transport, Fate, and Effects of Silver in the Environment, pp. 51-56. Held at

University of Wisconsin-Madison, September 11-14.

Krasovskii, G.N., L.Y. Vasukovish, and O.G. Chariev. 1979. Experimental study of biological

effects of lead and aluminum following oral administration. Environ Health Perspect 30:47-51.

Kucera, E. 1983. Mink and otter as indicators of mercury in Manitoba waters. Canadian Journal

of Zoology. 61:2250-2256.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 108

Kumada, H., S. Kimura, M. Yokote, and Y. Matida. 1973. Acute and chronic toxicity, uptake and

retention of cadmium in freshwater organisms. Bull. Freshwater Fish. Res. Lab. (Tokyo) 

22(2):157-165.

Kumada, H., S. Kimura, and M. Yokote. 1980. Accumulation and biological effects of cadmium

in rainbow trout. Bull. Jpn. Soc. Sci. Fish. 46:97-103.

Lazareva, L.P. 1985. Changes in biological characteristics of Daphnia magna from chronic

action of copper and nickel at low concentrations. Hydrobiol. J. 21(5):59-62.

Leblanc, G.A. 1980. Acute toxicity of priority pollutants to water flea (Daphnia magna). Bull.

Environ. Contam. Toxicol. 24:684-691.

LeBlanc, G.A. 1984. Interspecies relationships in acute toxicity of chemicals to aquatic

organisms. Environmental Toxicology and Chemistry 3:47-60.

LeBlanc, G.A, J.D. Madstone, A.P. Paradice and B.F. Wilson. 1984. The influence of speciation

on the toxicity of silver to fathead minnow (Pimephales promelas). Environmental Tox and

Chem. 3:37-46.

Lecyk, M. 1980. Toxicity of CuSO4 in mice embryonic development. Zoologica Poloniae

28:101-105.

Lee, S-Z., Allen, H. E., Huang, C. P., Sparks, D. L., Sanders, P. F., and Peijnenburg, W. J. G.

M., 1996. Predicting soil-water partition coefficients for cadmium. Environ. Sci. Technol.,

30:3418-3424.

Lemly, A.D. 1985. Toxicology of selenium in a freshwater reservoir: Implications for

environmental hazard evaluation and safety. Ecotoxicology and Environmental Safety 10:314-

338.

Lemly, A.D. 1993. Teratogenic effects of selenium in natural populations of freshwater fish. 

Ecotoxicology and Environmental Safety 26:181-204

Leonard, A., and R. Lauwerys. 1987. Mutagenicity, carcinogenicity and teratogenicity of

beryllium. Mutation Res. 186:35-42.

Levesque, M. 1974. Selenium distribution in Canadian soil profiles. Can. J. Soil Sci. Vol. 54. 

Page. 63.

Lind, D., K. Alto, and S. Chatterton. 1978. Regional Copper-Nickel Study. Draft Report. 

Minnesota Environmental Quality Board, St. Paul, NN. 54 pp. As cited in AQUIRE (AQUatic
Draft Version: Do Not Cite or Quote June 5, 1998

Page 109

Toxicity Information REtrieval Database). Environmental Research Laboratory, Office of

Research and Development, U.S. Environmental Protection Agency, Duluth, MN.

Llewellyn, G.C., E.A. Floyd, G.D. Hoke, L.B. Weekley, and T.D. Kimbrough. 1985. Influence

on dietary aflatoxin, zinc, and copper on bone size, organ weight, and body weight in hamsters

and rats. Bull Environ Contam Toxicol 35:149-156. 

Loeser, E. and D.Lorke. 1977. Semichronic oral toxicity of cadmium, 2. Studies on dogs. 

Toxicology, 7:225-232.

Lokemoen, J.T., D. H. Johnson, D.E. Sharp. 1990. Weights of wild mallard Anas platyrhyncos,

Gadwall A. strepera, and blue-winged teal A. discors during the breeding season. Wildfowl

40:122-130.

Long, E.R., D.D. MacDonald, S.L. Smith, and F.D. Calder. 1995. Incidence of adverse

biological effects with ranges of chemical concentrations in marine and estuarine sediments. 

Environmental Management, 19(1):81-97. 

Ma, L. Q., and Rao, G. N., 1997. Heavy metals in the environment. J. Environ. Qual., 26:259-

264.

MacDonald, D.D. 1994. Approach to the assessment of sediment quality in Florida coastal

waters, Volume 1 - Development and evaluation of sediment quality assessment guidelines. 

MacDonald Environmental Sciences Ltd., British Columbia, Canada.

Macleod, J. C. and E. Pessah. 1973. Temperature effects on mercury accumulation, toxicity, and

metabolism rate in rainbow trout (Salmo gairdneri). Journal of the Fisheries Research Board of

Canada. 30:485-492.

Marmo, E., M.H. Matera, R. Acampora, C. Vacca, D. DeSantis, S. Maione, V. Susanna, S.

Chieppa, V. Guarino, R. Servodio, B. Cuparencu, and F. Rossi. 1987. Prenatal and postnatal

metal exposure: Effect on vasomotor reactivity development of pups. Curr. Ther. Res.

42(5):823-838. 

Masscheleyn, P. H., Delaune, R. D., and Patrick, W. H., Jr. (1991). Effect of redox potential and

pH on arsenic speciation and solubility in a contaminated soil. Environ. Sci. Technol. 25:1414-

1419.

Massie, H. R. and V. R. Aiello. 1984. Excessive intake of copper: influence on longevity and

cadmium acculumation in mice. Mech. Ageing Dev. 26:195-203.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 110

Mathew, R., and N.R. Menon. 1983. Effects of heavy metals on byssogenesis in Perna viridis

(Linn.) Indian J. Mar. Sci. 12(2):125-127.

Mathur, R., S. Sharma, S. Mathur, and A.O. Prakash. 1987. Effect of beryllium nitrate on early

and late pregnancy in rats. Bull. Environ. Contam. Toxicol. 38:73-77

Mayer, L. M., 1988. Geochemistry of chromium in the oceans. In: J. O. Nriagu and E. Nieboer

(Eds.), Chromium in the Natural and Human Environments. John Wiley & Sons, Inc. pp. 173-

187.

References cited therein:

Douglas, G. S., Mills, G. L., and Quinn, J. G., 1986. Organic copper and chromium

complexes in the interstitial waters of Naragansett Bay sediments. Mar. Chem., 19:161-

174.

Kahn, D., Heggie, D., and Bender, M., 1984. Trace metals (Mn, Cu, Ni, Cd, V, Cr) in

surficial pore waters (from MANOP site M of the eastern Pacific). EOS, 64:243.

Kato, T., Endo, M., and Kato, M., 1983. Vertical distribution of various elements in

sediment cores from the Japan Sea. Mar. Geol., 53:277-290.

Loring, D. H., 1979. Geochemistry of cobalt, nickel, chromium, and vanadium in the

sediments of associated pelagic sediments. Geochim. Cosmochim. Acta, 46:1053-1060.

Mayer, L. M., and Fink, L. K., Jr., 1980. Granulometric dependence of chromium

accumulation in estuarine sediments in Maine. Est. Coastal Shelf Sci., 11:491-503.

Mazbich, B.I. 1960. Some aspects of the pathogenesis of edema of the lungs due to silver

nitrate. Communication III. The mechanism of death of experimental animals. (Translated from

Byull. Eksp. Biol. Med., 50(9):70-75. As cited in U.S EPA (Environmental Protection Agency).

1985. Drinking Water Criteria Document for Silver. Prepared by the Environmental Criteria and

Assessment Office, Cincinnati, OH for the Office of Drinking Water.

McConnell, R. P. 1977. Toxicity of molybdenum to rainbow trout under laboratory conditions. 

Ch. 14 in W.R. Chappell and K.K. Peterson (eds.). Molybdenum in the environment. Vol. 2. 

The geochemistry, cycling, and industrial uses of molybdenum. Marcel Dekker, New York.

McLean, J. E., and Bledsoe, B. E., 1992. Behavior of metals in soils. U.S. Environmental

Protection Agency, Office of Research and Development. EPA/540/S-92/018, 25 pp.

Merlini, M. and G. Pozzi. 1977. Lead and freshwater fishes: part I - Lead accumulation and

water pH. Environmental Pollution 12:167-172.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 111

Miller, J.C. and R. Landesman. 1978. Reduction of heavy metal toxicity to Xenopus embryos by

magnesium ions. Bull. Environ. Contam. Toxicol. 20:93-95.

Mok, W. M., and Wai, C. M. (1989). Distribution and mobilization of arsenic species in the

Blackbird Mining Area, Idaho. Water Res. 23:7-13.

Mok, W. M., and Wai, C. M. (1990). Distribution and mobilization of arsenic and antimony

species in the Coeur D’Alene River System, Idaho. Environ. Sci. Technol. 22:432-437.

Mok, W. M., and Wai, C. M. (1994). Mobilization of arsenic in contaminated river waters. In: J.

O. Nriagu (Ed.), Arsenic in the Environment. Part I: Cycling and Characterization. John Wiley

& Sons, Inc. pp. 99-117.

Moore, J. N., Kicklin, W. H., and Johns, C. (1988). Partitioning of arsenic and metals in reducing

sulfidic sediments. Environ. Sci. Technol. 22:432-437.

Mount, D.I and T.J. Norberg. 1984. A seven-day life cycle Cladoceran toxicity test. Environ. 

Toxicol. Chem. 3(3):425-434. As cited in AQUIRE (AQUatic Toxicity Information REtrieval

Database), 1995. Environmental Research Laboratory, Office of Research and Development,

U.S. Environmental Protection Agency, Duluth, MN.

Muramoto, S. 1980. Effect of complexans (EDTA, NTA and DTPA) on the exposure of high

concentrations of cadmium, copper, zinc and lead. Bulletin of Environmental Contamination and

Toxicology 25:941-946.

Murphy, B. R., G. J. Atchison, and A. W. McIntosh. 1978. Cadmium and zinc in muscle of

bluegill (Lepomis macrochirus) and Largemouth bass (Micropterus salmoides) from an

industrially contaminated lake. Environ. Pollut. 17: 253-257.

Nagy, K.A. 1987. Field metabolic rate and food requirement scaling in mammals and birds. Ecol.

Mono. 57:111-128.

Naqvi, S. M., R.D. Howell, and M. Sholas. 1993. Cadmium and lead residues in field-collected

red swamp crayfish (Procambarus Clarkii) and uptake by alligator weed, Alternanthera

philoxiroides. Journal of Environmental Science and Health B28(4):473-485.

National Oceanic and Atmospheric Administration (NOAA). 1991. The Potential for Biological

Effects of Sediment-Sorbed Contaminants Tested in the National Status and Trends Program. 

NOAA Technical Memorandum, NOS OMA 52.

Nebeker, A.V., C. Savonen, and D.G. Stevens. 1985. Sensitivity of rainbow trout early life

stages to nickel chloride. Environmental Toxicology and Chemistry 4:233-239.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 112

Newman, Michael C. and Jagoe, Charles H., (Eds.). 1996. Ecotoxicology; A Hierarchical

Treatment. Lewis Publishers, Boca Raton, Florida.

NIOSH (National Institute for Occupational Safety and Health). 1994. RTECS (Registry of

Toxic Effects of Chemical Substances) March Database.

Nobunaga, T., H. Satoh, and T. Suzuki. 1979. Effects of sodium selenite on methylmercury

embryotoxicity and teratogenicity in mice. Toxicol Appl Pharmacol 47:79-88. 

Norberg, T.J., and D.I Mount. 1985. A new fathead minnow (Pimephales promelas) subchronic

toxicity test. Environmental Toxicology and Chemistry 4:711-718.

Norberg-King, T.J. 1989. An evaluation of the fathead minnow seven-day subchronic test for

estimating chronic toxicity. Environmental Tox and Chem 8:1075-1089

NRCC. 1973. Lead in the Canadian Environment. National Research Council, NRC Associate

Committee on Scientific Criteria for Environmental Quality, Ottawa, Canada. Publication No.

BY73-7 (ES). 116 pp.

Ogle, Richard S. and Knight, Allen W. 1989. Effects of elevated foodborne selenium on growth

and reproduction of the fathead minnow (Pimephales promelas). Archives of Environmental

Contamination and Toxicology 18, 795-803.

Ohlendorf, Harry M., Hoffman, David J., Saiki, Michael K., and Aldrich, Thomas W. 1986.

Embryonic mortality and abnormalities of aquatic birds: Apparent impacts of selenium from

irrigation drainwater. The Science of the Total Environment 52, 49-63. 

Ohlendorf, Harry M., Hothem, Roger L., and Aldrich, Thomas W. 1988. Bioaccumulation of

selenium by snakes and frogs in the San Joaquin Valley, California. Copeia 3, 704-710. 

Ohlendorf, Harry M., Hothem, Roger L., and Welsh, Daniel. 1989. Nest success, cause-specific

nest failure, and hatchability of aquatic birds at selenium-contaminated Kesterson Reservoir and a

reference site. The Condor 91, 787-796.

Ohlendorf, H.M., R.L. Hothem, C.M. Bunck, and K.C. Marois. 1990. Bioaccumulation of

selenium in birds at Kesterson Reservoir, California. Arch. Environ. Contam. Toxicol.

19:495-507.

Opresko, D.M., B.E. Sample, G.W. Suter II. 1994. Toxicological Benchmarks for Wildlife:

1994 Revision. ES/ER/TM-86/R1. U.S Department of Energy, Oak Ridge National Laboratory,

Oak Ridge, Tennessee.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 113

Outridge, P.M. and A.M. Scheuhammer. 1993. Bioaccumulation and toxicology of chromium: 

Implications for Wildlife. Reviews of Environmental Contamination and Toxicology, 130:31-77.

Pal, N., and B. Pal. 1987. Zinc feeding and conception in the rats. Int J. Vit. Nutr. Res. 57:437-

440.

Palmer, I. S., and O. E. Olson. 1974. Relative toxicities of selenite and selenate in the drinking

water of rats. J Nutr 104:306-314.

Parkhurst, C.R. 1995. Personal communication. Professor, Department of Poultry Science,

North Carolina State University.

Passino, D. R. M., and A. J. Novak. 1984. Toxicity of arsenate and DDT to the cladoceran

Bosmina longirostris. Bull. Environ. Contam. Toxicol. 33:325-329.

Paternain, J.L., J.L. Domingo, M. Gomez, A. Ortega, and J. Corbella. 1990. Developmental

toxicity of vanadium in mice after oral administration. J. Appl. Tox. 10(3):181-186.

Pattee, O.H. 1984. Eggshell thickness and reproduction in American kestrels exposed to chronic

dietary lead. Archives of Environmental Contamination and Toxicology 13:29-34.

Peterson, M. L., and Carpenter, R. (1983). Biogeochemical processes affecting total arsenic and

arsenic species distributions in an intermittently anoxic fjord. Mar. Chem. 12:295-321.

Peterson, R. H., J. L. Metcalfe, and S. Ray. 1983. Effects of cadmium on yolk utilization,

growth, and survival of Atlantic salmon alevins and newly feeding fry. Arch. Environ. Contam.

Toxicol. 12:37-44

Pickering, Q. H. 1974. Chronic toxicity of nickel to the fathead minnow. Journal WPCF

46:760-765.

Pickering, Q. H. 1980. Chronic toxicity of hexavalent chromium to the fathead minnow. 

Archives of Environmental Contamination and Toxicology 9:405-413.

Pierce, M. L., and Moore, C. B. (1980). Adsorption of arsenite on amorphous iron hydroxide

from dilute aqueous solution. Environ. Sci. Technol. 14:214-216.

Pierce, M. L., and Moore, C. B. (1982). Water Res. 16:1247-1253.

Pitt, M., J. Fraser, and D.C. Thurley. 1980. Molybdenum toxicity in sheep, epiphysiolysis,

exotoses and biochemical changes. J. Comp. Path. 90:567-576.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 114

Power, T., K.L. Clark, A. Harfenist, and D.B. Peakall. 1989. A Review and Evaluation of the

Amphibian Toxicological Literature. Technical Report Series No. 61, Canadian Wildlife Service.

Prothro, M.G. 1993. Office of Water. Policy and technical guidance on interpretation and

implementation of aquatic metals criteria. Memorandum from Acting Assistant Administrator for

Water. Washington DC: US EPA Office of Water. 7 p. Attachments 41 p.

Raimondo, Sandra M., Rowe, Christopher L., and Congdon, Justin D. 1998 Exposure to coal

ash impacts swimming performance and predator avoidance in larval bullfrogs (Rana

catesbeiana). Journal of Herpetology , in press.

Reiser, M.H., and S.A. Temple. 1981. Effects of chronic lead ingestion on birds of prey. In:

Recent Advances in the Study of Raptor Diseases. Proceedings of the International Symposium

on Diseases of Birds of Prey. July 1-3, 1980. 21-25. Chiron Publications.

Reiter, L.W., G.E. Anderson, J.W. Laskey, and D.F. Cahill. 1975. Development and behavioral

changes in the rat during chronic exposure to lead. Environ. Health Perspect 12:119-123.

Renner, Rebecca. 1997. Rethinking water quality standards for metals toxicity. Environmental

Science and Technology 31, 466A-468A.

Richardson , M.E., M.R. Spivey Fox, and B.E. Fry. 1974. Pathological changes produced in

Japanese quail by ingestion of cadmium. J. Nutr. 104:323-338.

Ridgway, L.P, and D.A. Karnofsky. 1952. The effects of metals on the chick embryo: toxicity

and production of abnormalities in development. Ann. N.Y. Acad. Sci. 55:203-215.

Romoser, G. L., W. A. Dudley, L. J. Machlin, and L. Loveless. 1961. Toxicity of vanadium and

chromium for the growing chick. Poultry Science 40:1171-1173. 

Rosenfeld, I. and O.A. Beath. 1954. Effect of selenium on reproduction in rats. Proc. Soc. Exp.

Biol. Med. 87:295-297.

Rossi, F, R., R. Acampora, C. Vacca, S. Maione, M.G. Matera, R. Servodio, and E. Marmo. 

1987. Prenatal and postnatal antimony exposure in rats: Effect on vasomotor reactivity

development of pups. Teratogenesis, Carcinogenesis, and Mutagenesis 7:491-496.

Rowe, Christopher L., Kinney, Owen M., Fiori, Alison P., and Congdon, Justin D. 1996. Oral

deformities in tadpoles (Rana catesbeiana) associated with coal ash deposition: Effects on

grazing ability and growth. Freshwater Biology 36, 723-730.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 115

Rowe, Christopher L., Kinney, Owen M., and Congdon, Justin D. 1998. Oral deformities in

tadpoles of the bullfrog (Rana catesbeiana) caused by conditions in a polluted habitat. Copeia 1, in

press.

Rowe, Christopher L., Kinney, Owen M., Nagle, Roy D., and Congdon, Justin D. 1998. Elevated

maintenance costs in an Anuran (Rana catesbeiana) exposed to a mixture of trace elements

during the embryonic and early larval periods. Phys.Zool. In press.

RTI (Research Triangle Institute). 1997. Risk Assessment Support For Cement Kiln Dust

Regulatory Activities: Draft Report. Prepared for U.S. EPA’s Office of Solid Waste under

Contract No. 68W-6-0053. Research Triangle Park, NC. September.

RTI (Research Triangle Institute). 1997. Background Document; NonGroundwater Pathway

Risk Assessment; Petroleum Process Waste Listing Determination. Prepared for U.S. EPA’s

Office of Solid Waste under Contract No. 68W-6-0053. Research Triangle Park, NC. March 20.

RTI (Research Triangle Institute). 1987. Two generation reproduction and fertility study of

nickel chloride administered to Cd rats in drinking water: Fertility and reproductive performance

of the Po generation (Part II of III) and F1 generation (Part III of III). Final study report. Report

submitted to Office of Solid Waste Management, U.S. EPA, Washington, DC. As cited in As

cited in U.S. EPA (Environmental Protection Agency). IRIS (Integrated Risk Information

System). 1994.

Research Triangle Institute (RTI). 1995a. Technical Support Document for the Hazardous

Waste Identification Rule: Risk Assessment for Human and Ecological Receptors- Volumes I and

II. Prepared for the Office of Solid Waste, U.S. Environmental Protection Agency (EPA) under

subcontract 801-01.

Research Triangle Institute (RTI). 1995b. Supplemental Technical Support Document for the

Hazardous Waste Identification Rule: Risk Assessment for Human and Ecological ReceptorsVolumes I. Prepared for the Office of Solid Waste, U.S. Environmental Protection Agency (EPA)

under contract number 68-W3-0028.

Rungby, J., and G. Danscher. 1984. Hypoactivity in silver exposed mice. Acta Pharmacol et

Toxicol 55:398-401. As cited in Clement Associates, Inc.. 1989. Draft: Toxicological Profile for

Silver. Prepared for Agency for Toxic Substances and Disease Registry (ATSDR), U.S. Public

Health Service. 

Sadinski, Walter J. and Dunson, William A. 1992. A multilevel study of effects of low pH on

amphibians of temporary ponds. Journal of Herpetology 26, 413-422.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 116

SAIC (Science Applications International Corporation). 1998a. Technical Background

Document for the Supplemental Report to Congress on Remaining Fossil Fuel Combustion

Wastes: Draft Final Report. Prepared for U.S. EPA’s Office of Solid Waste. Reston, VA. 

April.

SAIC (Science Applications International Corporation). 1998b. Memorandum from Pat Ransom

(SAIC), to Greg Carter (Research Triangle Institute), Chris Long (SAIC) and John Vierow

(SAIC). Subject: FFC Waste Management Unit Dimensions used in Risk Assessment. March 10.

Saiki, Michael K., Jennings, Mark R., and Brumbaugh, William G. 1993. Boron, molybdenum,

and selenium in aquatic food chains from the lower San Joaquin River and its tributaries,

California. Archives of Environmental Contamination and Toxicology 24, 307-319. 

Saiki, Michael K. and Lowe, T. Peter. 1987. Selenium in aquatic organisms from subsurface

agricultural drainage water, San Joaquin Valley, California. Archives of Environmental

Contamination and Toxicology 16, 657-670.

Sakata, M. (1987). Relationship between adsorption of As(III) and boron by soil and soil

properties. Environ. Sci. Technol. 21:1126-1130.

Samanta, K., and B. Pal. 1986. Zinc feeding and fertility of male rats. International Journal of

Vitamin and Nutrition Research 56:105-108.

Sample, B. E., D. M. Opresko, and G. W. Suter II. Toxicological Benchmarks for Wildlife: 1996

Revision. ES/ER/TM-86/R3. Oak Ridge National Laboratory, Oak Ridge, TN.

Sanders, J. G. (1985). Arsenic geochemistry in Chesapeake Bay: Dependence upon

anthropogenic inputs and phytoplankton species composition. Mar. Chem. 17:320-340.

Santschi, P. H., 1988. Factors controlling the biogeochemical cycles of trace elements in fresh

and coastal marine waters as revealed by artificial radioisotopes. Limnol. Oceanogr., 33(4, part

2):848-866.

Sauter, S., K.S. Buxton, K.J. Macek, and S.R. Petrocelli. 1976. Effects exposure to heavy

metals on selected freshwater fish, EPA-600/3-76-105. U.S. Environmental Protection Agency,

Duluth, Minn. As cited in Suter II, G.W. and J.B. Mabrey. 1994. Toxicological Benchmarks for

Screening of Potential Contaminants of Concern for Effects on Aquatic Biota: 1994 Revision.

DE-AC05-84OR21400. Office of Environmental Restoration and Waste Management, U.S.

Department of Energy, Washington, DC.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 117

Schlicker, S.A., and D.H. Cox. 1968. Maternal dietary zinc, and development and zinc, iron,

copper content of the rat fetus. J. Nutrition 95:287-294.

Schroeder, H. A., and J. J. Balassa. 1967. Arsenic, germanium, tin and vanadium in mice: 

effects on growth, survival and tissue levels. J. Nutrition 92:245-252.

Schroeder, H.A., M. Mitchener, J.J. Balassa, M. Kanisawa, and A.P. Nason. 1968a. Zirconium,

niobium, antimony and fluorine in mice: Effects on growth, survival and tissue levels. J. Nutrition

95:95-101.

Schroeder, H. A., M. Kanisawa, D. V. Frost, and M. Mitchener. 1968b. Germanium, tin and

arsenic in rats: Effects on growth, survival, pathological lesions and life span. J. Nutrition

96:37-45.

Schroeder, H.A., M. Mitchener, and A.P. Nason. 1970. Zirconium, niobium, antimony,

vanadium, and lead in rats: Life term studies. J. Nutrition, 100:59-68. 

Schroeder, H. A., and M. Mitchener. 1971a. Selenium and tellurium in rats: effects on growth,

survival, and tumors. J. Nutr 101:1531-1540. 

Schroeder, H. A., and M. Mitchener. 1971b. Toxic effects of trace elements on reproduction of

mice and rats. Arch Environmental Health 23:102-106. 

Schroeder, H.A., and M. Mitchener. 1975a. Life-term studies in rats: Effects of aluminum,

barium, beryllium, and tungsten. J. of Nutrition 105:421-427.

Schroeder, H.A., and M. Mitchener. 1975b. Life-term effects of mercury, methyl mercury, and

nine other trace metals on mice. J. of Nutrition 105:452-458.

Sciences International, Inc. 1994. Draft: Toxicological Profile for Selenium. Prepared for U.S.

Department of Health and Human Services, Public Health Service, Agency for Toxic Substances

and Disease Registry (ATSDR). Atlanta, GA. 

Shafer, M.M., Overdier, J. T., Hurley, J. P., Armstrong, D., and Webb, D., 1997. The influence

of dissolved organic carbon, suspended particulates, and hydrology on the concentration,

partitioning and variability of trace metals in two contrasting Wisconsin watersheds (USA). 

Chem. Geol., 136:71-97.

Shamberger, R.J. (Ed.). 1983. Chemistry of Selenium. Pgs. 167-183,

Sheffy, T. B., and J. R. St. Amant. 1982. Mercury burdens in furbearers in Wisconsin. Journal

of Wildlife Management. 46:1117-1120.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 118

Shore, Richard F., and Peter E.T. Douben. 1994. The ecotoxicological significance of cadmium

intake and residues in terrestrial small mammals. Ecotoxicology and Environmental Safety,

29:101-112.

Sittig, M, ed. 1980. Priority Toxic Pollutants: Health Impacts and Allowable Limits. Noyes

Data Corporation, Park Ridge, NJ.

Smith, B.L., and P.P. Embling. 1984. The influence of chemical form of zinc on the effects of

toxic intraruminal dose of zinc to sheep. J. Appl. Toxicol. 4(2):92-96. 

Smith, M. K., J. A. George, H. F. Stober, and G. L. Kimmel. 1990. Perinatal toxicity associated

with nickel chloride exposure. Fund. Appl. Toxicol. Preliminary unpublished draft. As cited in

U.S. EPA (Environmental Protection Agency). IRIS (Integrated Risk Information System). 

1994.

Smith, M.K., E.L. George, J.A. Stober, H.A. Feng, and G.L. Kimmel. 1993. Perinatal toxicity

associated with nickel chloride exposure. Environmental Research 61:200-211.

Smith, Sherri L., Donald D. MacDonald, Karen A. Keenleyside, Christopher G. Ingersoll, and L.

Jay Field. 1996. A preliminary evaluation of sediment quality assessment values for freshwater

ecosystems. J. Great Lakes Res., 22(3):624-638.

Sorell, T. L., and J. H. Graziano. 1990. Effect of oral cadmium during pregnancy on maternal

and fetal zinc metabolism in the rat. Toxicology and Applied Pharmacology. 102:537-545.

Sorensen, Elsie M. B., Cumbie, Peter M., Bauer, Thomas L., Bell, James S., and Harlan, Charles

W. 1984. Histopathological, hematological, condition-factor, and organ weight changes

associated with selenium accumulation in fish from Belews Lake, North Carolina. Archives of

Environmental Contamination and Toxicology 13, 153-162. 

Spehar, R. L., J. T. Fiandt, R. L. Anderson, and D. L. DeFoe. 1980. Comparative toxicity of

arsenic compounds and their accumulation in invertebrates and fish. Arch. Environm. Contam.

Toxicol. 9:53-63. 

Sreedevi, P., A. Suresh, B. Sivaramakrishna, B. Prabhavathi, and K. Radhakrishnaiah. 1992. 

Bioaccumulation of nickel in the organs of the freshwater fish, Cyprinus carpio, and the

freshwater mussel, Lamellidens marginalis, under lethal and sublethal nickel stress. 

Chemosphere 24:29-36

Stanley, Jr., T. R., J. W. Spann, G. J. Smith, and R. Rosscoe. 1994. Main and interactive effects

of arsenic and selenium on mallard reproduction and duckling growth and survival. Arch.

Environ. Contam. Toxicol. 26:444-451.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 119

Stauffer, R. E., and Thompson, J. M. (1984). Geochim. Cosmochim. Acta 84:2547.

Stephan, C. E., D. I. Mount, D. J. Hansen, J. H. Gentile, G. A. Chapman, and W. A. Brungs.

1985. Guidelines for deriving numerical national water quality criteria for the protection of

aquatic organisms and their uses. PB85-227049. National Technical Information Service,

Springfield, VA

Stephan, C.E. 1993. Derivation of Proposed Human Health and Wildlife Bioaccumulation

Factors for the Great Lakes Initiative. Office of Research and Development, U.S. Environmental 

Research Laboratory. PB93-154672. Springfield, VA. 

Stevens, D. G., and G. A. Chapman. 1984. Toxicity of trivalent chromium to early life stages of

steelhead trout. Environmental Toxicology and Chemistry 3:125-133

Storeng, R., and J. Jonsen. 1981. Nickel toxicity in early embryogenesis in mice. Toxicology

20:45-51

Sunderman, Jr., F. W., S. K. Shen, J. M. Mitchell, P. R. Allpass, and I. Damjanov. 1978. 

Embryotoxicity and fetal toxicity of nickel in rats. Toxicology and Applied Pharmacology

43:381-390.

Suter II, G. W., M. A. Futrell, and G. A. Kerchner. 1992. Toxicological Benchmarks for

Screening of Potential Contaminants of Concern for Effects of Aquatic Biota on the Oak Ridge

Reservation, Oak Ridge, Tennessee. DE93-000719. Office of Environmental Restoration and

Waste Management, U.S. Department of Energy, Washington, DC.

Suter II, G.W., and J.B. Mabrey. 1994. Toxicological Benchmarks for Screening Potential

Contaminants of Concern for Effects on Aquatic Biota: 1994 Revision. ES/ER/TM-96/R1. 

Prepared for the U.S. Department of Energy, Washington, DC.

Suter II, G. W., and C. L. Tsao. 1996. Toxicological Benchmarks for Screening Potential

Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/R2.

Prepared for the U.S. Department of Energy, Washington, DC.

Sutou, S., K. Yamamoto, H. Sendota, and M. Sugiyama. 1980. Toxicity, fertility, teratogenicity,

and dominant lethal tests in rats administered cadmium subchronically: I and II. Toxicology and

Environmental Safety. 4:39-56.

Suzuki, T. 1979. Dose-effect and dose-response relationships of mercury and its derivatives. pp.

399-431. In J. O. Nriagu (ed.). The Biogeochemistry of Mercury in the Environment. 

Elsevier/North-Holland Biomedical Press, New York.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 120

Syracuse Research Corporation. 1989. Draft: Toxicological Profile for Copper. U.S.

Department of Health and Human Services, Public Health Service, Agency for Toxic Substances

and Disease Registry, Atlanta, GA.

Szabo, G., J. Guczi, J. Valyon, and R. Bulman. 1995. Investigations of the sorption characteristics

of radiosilver on some natural and artificial soil particles. Sci. of the Tot. Environ. 72:65-78.

Tachon, P., A. Laschi, J.P. Briffaux, and G. Brian. 1983. Lead poisoning in monkeys during

pregnancy and lactation. The Science of the Total Environment 30:221-229.

Tarasenko, N. Y., O.A Pronin, and A.A. Silayev. 1977. Barium compounds as industrial poisons

(an experimental study). J. Hygiene, Epidemiology, Microbiology and Immunology 21(4):361-

373.

Tardiff, R.G, M. Robinson, N.S. Ulmer. 1980. Subchronic oral toxicity of BaCl2 in rats. J.

Environmental Path and Tox. 4:267-275.

Taylor, D. 1983. The significance of the accumulation of cadmium by aquatic organisms. 

Ecotoxicology and Environmental Safety. 7:33-42.

Taylor, D.H., C.W. Steele, and S. Strickler-Shaw. 1990. Responses of green frog (Rana

clamitans) tadpoles to lead-polluted water. Environmental Toxicology and Chemistry 9:87-93.

Tokunaga, Tetsu K., Gordon E. Brown, Jr., Ingrid J. Pickering, Stephen R. Sutton, Sasa Bajt. 

1997. Selenium redox reactions and transport between ponded waters and sediments. 

Environmental Science and Technology, 31:1419-1425.

Trivedi, B., D. K. Saxema, and R. C. Murthy. 1989. Embryo toxicity and fetotoxicity of orally

administered hexavalent chromium in mice. Reproductive Toxicology 3:275-278.

Tyler, G., M Balsbery Pahlsson, G. Bengtsson, F. Raath, and L. Tranvik. 1989. Heavy-metal

ecology of terrestrial plants, microorganisms and invertebrates: a review. Water, Air, and Soil

Pollution 47:189-215.

Uriu-Hare, J.Y., J.S. Stern, and C.L. Keen. 1989. Influence of maternal dietary Zn intake on

expression of diabetes-induced teratogenicity in rats. Diabetes 38:1282-1290. 

U.S. EPA (Environmental Protection Agency). 1980c. Ambient Water Quality Criteria for

Antimony. Criteria and Standards Division. Washington, D.C. 
Draft Version: Do Not Cite or Quote June 5, 1998

Page 121

U.S. EPA (Environmental Protection Agency). 1980d. Ambient Water Quality Criteria for

Arsenic. U.S. Environmental Protection Agency, Washington, DC. Publication No. EPA-440/5-

80-021.

U.S. EPA (Environmental Protection Agency). 1980k. Ambient Water Quality Criteria for

Silver. EPA-440/5-80-071. Office of Water Regulations and Standards, Criteria and Standards 

Division, Washington, DC; Office of Research and Development, Environmental Criteria and

Assessment Office, Cincinnati, Ohio; Carcinogen Assessment Group, Washington, DC, 

Environmental Research Laboratories, Corvallis, Oregon, Duluth Minnesota, Gulf Breeze,

Florida, Narrangasett, Rhode Island.

U.S. EPA (Environmental Protection Agency). 1984. Ambient Water Quality Criteria for

Copper-1984. Environmental Protection Agency. Washington, DC. Criteria and Standards

Division. PB85-227023

U.S. EPA (Environmental Protection Agency). 1985b. Ambient Water Quality Criteria for

Lead — 1984. U.S. Environmental Protection Agency Rep. 440/5-84-027. 81 pp.

U.S EPA (Environmental Protection Agency). 1985d. Drinking Water Criteria Document for 

Silver. Prepared by the Environmental Criteria and Assessment Office, Cincinnati, OH for the

Office of Drinking Water.

U.S. EPA (Environmental Protection Agency). 1986c. Quality Criteria for Water. EPA 440/5-

86-001. Washington, DC.

U.S. EPA (Environmental Protection Agency). 1986d. Ambient Water Quality Criteria for

Nickel. EPA/440/5-86-004. Office of Water Regulations and Standards, Criteria and Standards

Division, Washington, DC.

U.S. EPA (Environmental Protection Agency). 1986g. Health Assessment Document for

Beryllium: Review Draft. EPA 600/8-84-026B. Office of Health and Environmental Assessment,

Washington, DC.

U.S. EPA (Environmental Protection Agency). 1987b. Ambient Water Quality Criteria for

Selenium. U.S. Environmental Protection Agency, Washington, DC. Publication No. EPA440/5-87-006.

U.S. Environmental Protection Agency. 1987c. Final Draft for the Drinking Water Criteria

Document on Barium. Office of Drinking Water, Criteria and Standards Division, Washington,

DC.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 122

U.S. EPA (Environmental Protection Agency). 1988a. Recommendations for and

Documentation of Biological Values for Use in Risk Assessment. PB88-179874. Environmental

Criteria and Assessment Office, Office of Research Development, Cincinnati, OH. 

U.S. EPA (Environmental Protection Agency). 1988. Ambient Water Quality Criteria

Document: Addendum for Antimony (Draft Report (Final)). Cincinnati, OH.

U.S. EPA (Environmental Protection Agency). 1989. Risk Assessment Guidance for Superfund,

Volume I, Human Health Evaluation Manual (Part A). EPA/540/1-89/002. Office of

Emergency and Remedial Responses. Washington, D.C. December.

U.S. EPA (Environmental Protection Agency). 1990. Methodology for Assessing Health Risks

Associated with Indirect Exposure to Combustor Emissions - Interim Final. EPA/600/6-90/003. 

January.

U.S. EPA (Environmental Protection Agency). 1990a. Methodology for Assessing Health Risks

Associated with Indirect Exposure to Combustor Emissions. Interim Final. Office of Health and

Environmental Assessment, Washington, DC. January.

U.S. EPA (Environmental Protection Agency). 1990d. Molybdenum: Drinking Water Health

Advisory Draft. Office of Water. September.

U.S. EPA (Environmental Protection Agency). 1992a. Framework for Ecological Risk

Assessment. Risk Assessment Forum, Washington, DC. EPA/630/R-92/001.

U.S. EPA (Environmental Protection Agency). 1992b. Technical Support Document for Land

Application of Sewage Sludge, Volume I and II. EPA 822/R-93-001a. Office of Water,

Washington, DC. 

U.S. EPA (Environmental Protection Agency). 1992c. 304(a) Criteria and Related Information

for Toxic Pollutants. Water Management Division, Region IV.

U.S. Environmental Protection Agency (EPA). 1993. Derivations of proposed human health and

wildlife bioaccumulation factors for the great lakes initiative. PB93-154672. Environmental

Research Laboratory, Office of Research and Development, Duluth, MN.

U.S. Environmental Protection Agency (EPA). 1993. Technical Basis for Deriving Sediment

Quality Criteria for Nonionic Organic Contaminants for the Protection of Benthic Organisms by

Using Equilibrium Partitioning. EPA-822-R-93-011. Office of Water, Washington, D.C.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 123

U.S. Environmental Protection Agency (EPA). 1993a. Addendum: Methodology for Assessing

Health Risks Associated with Indirect Exposure to Combustor Emissions. Working Group

Recommendations. Office of Solid Waste and Office of Research and Development. Washington,

DC. November 10.

U.S. Environmental Protection Agency (EPA). 1993b. Great Lakes Water Quality Initiative

Criteria Documents for the Protection of Wildlife (Proposed): DDT, Mercury, 2,3,7,8-TCDD,

PCBs. EPA-822-R-93-007 Office of Water, Office of Science and Technology, Washington, DC.

NTIS No. PB93-154722

U.S. EPA (Environmental Protection Agency). 1993h. Wildlife Exposure Factors Handbook:

Volumes I and II. EPA/600/R-93/187a,b. Office of Research and Development, Washington,

DC.

U.S. EPA (Environmental Protection Agency). 1994. Revised Interim Soil Lead Guidance for

CERCLA Sites and RCRA Corrective Action Facilities. Office of Solid Waste and Emergency

Response, Washington, D.C. Directive 9355.4-12.

U.S. EPA (Environmental Protection Agency). 1994. Great lakes water quality initiative 

technical support document for the procedure to determine bioaccumulation factors. Office of

Water and Office of Science and Technology. Washington DC. EPA-822-R-94-002.

U.S. EPA (Environmental Protection Agency). 1995a. User’s Guide for the Industrial Source

Complex (ISC3) Dispersion Models - Volume II. EPA-454/B-95-003b. Office of Air Quality

Planning and Standards. Emissions, Monitoring, and Analysis Division. Research Triangle Park,

NC. 

U.S. EPA (Environmental Protection Agency). 1995b. Compilation of Air Pollutant Emission

Factors, Volume I: Stationary Point and Area Sources. Office of Air Quality Planning And

Standards. Research Triangle Park. NC. January.

U.S. EPA, (Environmental Protection Agency). 1995. Great Lakes Water Quality Initiative

Criteria Documents for the Protection of Aquatic Life in Ambient Water. Office of Water.

EPA820/B-95/004.

U.S. EPA, Environmental Protection Agency. 1995a. Water Quality Guidance for the Great

Lakes System: Supplementary Information Document (SID). EPA-820/B-95/001. U.S.

Environmental Protection Agency, Office of Water, Washington, DC.

U.S. EPA (Environmental Protection Agency). 1992 - 1996. Integrated Risk Information

System. July.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 124

U.S. EPA (Environmental Protection Agency). 1996a. Draft Proposed Guidelines for

Ecological Risk Assessment. Risk Assessment Forum, Washington DC. EPA/630/R-95/002B.

U.S. EPA (Environmental Protection Agency). 1996. Mercury Study Report to Congress. 

Volume V: An ecological assessment of anthropogenic mercury emissions in the United States.

SAB Review Draft. Office of Air Quality Planning and Standards and Office of Research and

Development. EPA 452/R-96/001e.

U.S. EPA (Environmental Protection Agency). 1997. Protocol for Screening Level Ecological

Risk Assessment at Hazardous Waste Combustion Facilities, (Volumes 1 and 2). U.S. EPA

Office of Solid Waste. Internal Review Draft. February 28, 1997.

U.S. EPA (Environmental Protection Agency). 1998. Exposure Factors Handbook. Office of

Research and Development. Washington, DC.

U.S. EPA (Environmental Protection Agency. 1998. Air Characteristic Study: Technical

Background Document. EPA530-R-98-009B. May

USDA (United States Department of Agriculture). 1988. Manual for Applying Fluidized Bed

Combustion Residue to Agricultural Lands. ARS-74. Agricultural Research Service. August.

Van der Putte, I. and P. Part. 1982. Oxygen and chromium transfer in perfused gills of rainbow

trout (Salmo gairdneri) exposed to hexavalent chromium at two different pH levels. Aquatic

Toxicology, 2:31-45.

Venugopal, B., and T.D. Luckey. 1978. Metal toxicity in mammals (2): Chemical toxicity of

metals and metalloids. Plenum Press, N.Y.

Verschuuren, H.G. et al. 1976a. Toxicity of methylmercury in rats-I: Short-term toxicity study.

Toxicology. 6:85-96.

Verschuuren, H.G. et al. 1976b. Toxicity of methylmerury in rats-II: Long term toxicity study.

Toxicology. 6:107-123.

Walker, F. 1971. Experimental argyria: A model for basement membrane studies. Br. J. Exp.

Pathol. 52(6): 589-593. As cited in U.S EPA (Environmental Protection Agency). 1985.

Drinking Water Criteria Document for Silver. Prepared by the Environmental Criteria and

Assessment Office, Cincinnati, OH for the Office of Drinking Water. Also cited in Clement

Associates, Inc.. 1989. Draft: Toxicological Profile for Silver. Prepared for Agency for Toxic

Substances and Disease Registry (ATSDR), U.S. Public Health Service. 
Draft Version: Do Not Cite or Quote June 5, 1998

Page 125

Waslenchuk, D. G., and Windom, H. L. (1978). Factors controlling the estuarine chemistry of

arsenic. Estuarine Coastal Mar. Sci. 7:455-464.

Watras, C. J., J. MacFarlane, and F. M. M. Morel. 1985. Nickel accumulation by Scenedesmus

and Daphnia: Food-chain transport and geochemical implications. Can. J. Fish. Aquat. Sci.

42:724-730.

Wehrli, Bernhard and Werner Stumm. 1989. Vanadyl in natural waters: Adsorption and

hydrolysis promote oxygenation. Geochim. Cosmochim. Acta. 53, 69-77.

Wells, N. 1967. Selenium in horizons of soil profiles. N. Z. J. Geol. Geophys. Vol. 10. Page.

142

White, D. H., and M. T. Finley. 1978. Uptake and retention of dietary cadmium in mallard

ducks. Environmental Research. 17:53-59.

Wide, M. 1984. Effect of short-term exposure to five industrial metals on the embryonic and

fetal development of the mouse. Environmental Research 33:47-53.

Wide, M. 1985. Lead exposure on critical days of fetal life affects fertility in the female mouse. 

Teratology 32:375-380.

Will, M. E., and G. W. Suter, II. 1994. Toxicological Benchmarks for Screening Potential

Contaminants of Concern for Effects on Terrestrial Plants: 1994 Revision. ES/ER/TM-85/R1. 

Prepared for U.S. Department of Energy. 

Will, M. E., and G. W. Suter, II. 1995. Toxicological Benchmarks for Screening Potential

Contaminants of Concern for Effects on Soil and Litter Invertebrates and Heterotrophic Process. 

ES/ER/TM-126/R1. Prepared for U.S. Department of Energy. 

Williams, D. R., and J. P. Gisey, Jr. 1978. Relative importance of food and water resources to

cadmium uptake by Gambusia affinis (Poeciliidae). Environmental Research. 16:326-332.

Wingert-Runge, B., and A.W. Andren. 1994. Desorption behavior of silver from natural

sediments under freshwater and marine conditions. In: A.W. Andren and T.W. Bober (eds.).

Argentum International Conference Proceedings (2nd): Transport, Fate, and Effects of Silver in

the Environment, pp.89-92.University of Wisconsin-Madison, September 11-14.

Wobeser, G., N.O. Nielsen, B. Schiefer. 1976a. Mercury and mink, I. The use of mercury

contaminated fish as a food for ranch mink. Can. J. Comp. Med., 40:34-45.

Wobeser, G., N.O. Nielsen, B. Schiefer. 1976b. Mercury and mink, II. Experimental methyl

mercury intoxication. Can. J. Comp. Med., 40:30-33.
Draft Version: Do Not Cite or Quote June 5, 1998

Page 126

Wong, P.T.S., Y.K. Chau, O. Kramar, and G.A. Bengert. 1981. Accumulation and depuration of

tetramethyllead by rainbow trout. Water Resources 15:621-625.

Wood, C.M., C. Hogstrand, F. Galvez, and R.S. Munger. 1996b. The physiology of waterborne

silver toxicity in freshwater rainbow trout (Oncorhynchus mykiss) 2. The effects of silver

thiosulfate. Aquat. Toxicol. 35(2):111-125.

World Health Organization, 1981. Environmental Health Criteria- Arsenic - Environmental

Aspects, Geneva, 1989.

World Health Organization, 1989. Environmental Health Criteria 85 - Lead - Environmental

Aspects, Geneva, 1989.

World Health Organization, 1989. Environmental Health Criteria 86 - Mercury - Environmental

Aspects, Geneva, 1989.

Wren, C.D., H.R. Maccrimmon, and B.R. Loescher. 1983. Examination of bioaccumulation and

biomagnification of metals in a Precambrian shield lake. Water, Air, Soil Pollution. 19:277-291.

Xu, H., Allard, B., and Grimvall, A. (1988). Influence of pH and organic substance on the

adsorption of As(V) on geologic materials. Water, Air, Soil, Pollut. 40:293-305.

Yan-Chu, H. (1994). Arsenic distribution in soils. In: J. O. Nriagu (Ed.), Arsenic in the

Environment. Part I: Cycling and Characterization. John Wiley & Sons, Inc. pp. 17-49.

Zahid, Z. R., Z. S. Al-Hakkak, and A. H. H. Kadhim. 1990. Comparative effects of trivalent and

hexavalent chromium on spermatogenesis of the mouse. Toxicology and Environmental

Chemistry 25:B1-136. 

Zmudzki, J., G.R. Bratton, C. Womac, and L. Rowe. 1983. Lead poisoning in cattle: 

reassessment of the minimum toxic oral dose. Bulletin of Environmental Contamination and

Toxicology 30:435-441.

Zuiderveen, Jeffrey A. and Wesley J. Birge. 1995. Interactions of silver and metal chelators on 

Ceridaphnia dubia survival and reproduction. Columbus College, Columbus Georgia, Uuniversity

of Kentucky, Lexington, Kentucky In: A.W. Andren and T.W. Bober (co-chairs). Argentum

International Conference Proceedings (3rd): Transport, Fate, and Effects of Silver in the

Environment. Held at the University of Wisconsin-Madison on August 6-9, 1995.