risk assessment for the evaluation of kiln stack emissions

Prepared for:

Lone Star Industries

by:

Stephen G. Zemba, Ph.D., P.E.

Michael R. Ames, Sc.D.

Mathew J. Alvarado

July 2001

Risk Assessment for the Evaluation ofKiln Stack Emissions and RCRAFugitive Emissions from the Lone StarAlternate Fuels Facility, Greencastle,Indiana

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Contents

1 Introduction and background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1–1

2 Facility characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–12.1 Basic facility information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–12.2 Sources of stack and fugative emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–52.3 Identifying Compounds of Potential Concern (COPC) . . . . . . . . . . . . . . . . . . . 2–62.4 Physical, chemical and toxicological properties of the COPCs . . . . . . . . . . . . 2–152.5 Determining COPC emission rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–162.6 Justification for the use of non-default values for mercury speciation and

partitioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2–25

3 Air dispersion and deposition modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–13.1 Geographic setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–13.2 Source descriptions and parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–13.3 Meteorologic data and processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–53.4 Receptor locations and elevations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–113.5 Pollutant scavenging coefficients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–143.6 ISCST3 modeling run setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–233.7 ISCST3 modeling results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3–24

4 Exposure scenario selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4–1

5 Estimation of media concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–15.1 COPC concentrations in soil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–45.2 COPC concentrations in produce, grain, and vegetation . . . . . . . . . . . . . . . . . . 5–75.3 COPC concentrations in livestock and related farm products . . . . . . . . . . . . . 5–105.4 COPC concentrations in surface water . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–11

5.4.1 COPC loading to Cagles Mill Lake . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–115.4.2 COPC dissipation from Cagles Mill Lake . . . . . . . . . . . . . . . . . . . . . . 5–185.4.3 COPC partitioning in Cagles Mill Lake . . . . . . . . . . . . . . . . . . . . . . . 5–19

5.5 COPC concentrations in fish . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5–225.5.1 The use of a site-specific value for BAFfish for mercury . . . . . . . . . . . 5–23

6 Quantifying exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6–1

7 Risk and hazard characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7–1

8 Uncertainty evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–18.1 Facility characterization—emission uncertainties . . . . . . . . . . . . . . . . . . . . . . . 8–2

8.1.1 Extrapolation of organics’ risks using TOE measurements . . . . . . . . . . 8–2

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8.1.2 Alternate treatments of COPCs below detection limits in stack tests . . 8–38.1.3 MACT-based vs. measured emission rates . . . . . . . . . . . . . . . . . . . . . . 8–5

8.1.3.1 PCDD/PCDFs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–58.1.3.2 Mercury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–68.1.3.3 Chlorine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–7

8.1.4 Mercury speciation and distribution in emissions . . . . . . . . . . . . . . . . . 8–88.2 Air dispersion and deposition modeling uncertainties . . . . . . . . . . . . . . . . . . . . 8–9

8.2.1 Possibly inaccurate default parameters for dry and wet deposition . . . . 8–98.2.2 Interactions between local topology and modeling results . . . . . . . . . 8–118.2.3 Superposition of maximum concetration and deposition values . . . . . 8–11

8.3 Estimation of media concentration uncertainties . . . . . . . . . . . . . . . . . . . . . . . 8–118.3.1 Use of a non-zero kse in watershed soil concentration calculations . . 8–118.3.2 Site-specific, empirical BAFfish values . . . . . . . . . . . . . . . . . . . . . . . . . 8–128.3.3 Uncertainty in the dfault values for Bachicken and Bachicken, and

Qschicken for PCDDs and PCDFs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–138.4 Uncertainties in quantifying exposure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–14

8.4.1 Location of drinking water intakes . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–148.4.2 Assumption that a farm could be located at the maximum

impact location . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8–158.5 Risk and hazard characterization uncertainties . . . . . . . . . . . . . . . . . . . . . . . . 8–16

8.4.1 Treatment of COPCs with no toxicological data . . . . . . . . . . . . . . . . . 8–168.4.2 Inherent uncertainties in toxicological data . . . . . . . . . . . . . . . . . . . . . 8–17

9 Ecological Risk Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–19.1 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–1

9.1.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–29.1.2 Assessment Endpoints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–29.1.3 Conceptual Site Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–39.1.4 Analysis Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–4

9.2 Study area characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–59.3 Selection of ecological chemicals of concern . . . . . . . . . . . . . . . . . . . . . . . . . . 9–6

9.3.1 Selection of inorganic chemicals and metals . . . . . . . . . . . . . . . . . . . . . 9–69.3.2 Selection of organic chemicals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–7

9.3.2.1 Terrestrial scoring algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . 9–79.3.2.1.1 Inhalation scoring algorithm . . . . . . . . . . . . . . . 9–99.3.2.1.2 Ingestion Scoring Algorithm . . . . . . . . . . . . . . . 9–9

9.3.2.2 Aquatic Scoring Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . 9–109.3.2.2.1 Bioconcentration (Kow) based algorithm . . . . . 9–119.3.2.2.2 Solubility based algorithm . . . . . . . . . . . . . . . . 9–11

9.3.2.3 Selection based on professional judgement . . . . . . . . . . . . . . . 9–129.4 Exposure point concentrations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–139.5 Toxicological data and calculation of Ecological Benchmark Values (EBVs) 9–16

9.5.1 Calculation of air EBVs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–179.5.2 Calculation of soil EBVs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–189.5.3 Calculation of surface water EBVs . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–189.5.4 Calculation of sediment EBVs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–199.5.5 Calculation of species-specific ingestion EBVs . . . . . . . . . . . . . . . . . 9–20

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9.6 Selection of indicator species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–219.7 Risk characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–22

9.7.1 Calculation of hazard quotients for air . . . . . . . . . . . . . . . . . . . . . . . . 9–239.7.2 Calculation of hazard quotients for soil . . . . . . . . . . . . . . . . . . . . . . . . 9–239.7.3 Calculation of hazard quotients for surface water . . . . . . . . . . . . . . . . 9–239.7.4 Calculation of hazard quotients for sediment . . . . . . . . . . . . . . . . . . . 9–249.7.5 Calculation of species-specific ingestion hazard quotients . . . . . . . . . 9–24

9.7.5.1 Lead . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–259.7.5.2 Mercury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–26

9.8 Uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–289.9 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9–34

10 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10–1

11 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11–1

Appendix I Cambridge Environmental, 2000 Risk Assessment Workplan (RAWP)

Appendix II Coumpounds Included in Recertification of Compliance (ROC) and Products ofIncomplete Combustion (PIC) Stack Testing

Appendix III Coumpounds of Potential Concern (COPC) Properties Tables

Appendix IV Air Dispersion Modeling and Data Files

Appendix V Calculated Coumpounds of Potential Concern (COPC) Concentrations inEnvironmental Media

Executive Summary

Lone Star Industries operates a cement kiln near Greencastle, Indiana (hereafter theLSI/Greencastle facility) that has the capacity to produce upwards of 1,600,000 tons of portlandand masonry cement per year. LSI began producing cement at this site in 1925, built the currentfacility in 1969, and most recently added a preheater in 2000. Because the cement kiln is a largeindustrial facility, it is subject to a number of different regulations and requirements designed toensure that any emitted pollutants are released in small enough quantities that they do notadversely affect the health of nearby residents or harm the environment. In 1987 the facilitybegan to burn waste solvents in the kiln and has demonstrated compliance with all applicablehazardous waste regulations and emissions limits since that time.

Traditionally, criteria pollutants emitted from the stack of the LSI/Greencastle have received themost attention, and are well-monitored. Criteria pollutants include small particles (particulatematter, PM10), sulfur dioxide (SO2), nitrogen oxides (NO and NO2, or NOx), lead (Pb), andcarbon monoxide (CO). The U.S. Environmental Protection Agency (U.S. EPA) has establishedNational Ambient Air Quality Standards (NAAQS) for each criteria pollutant designed to protectpublic health with an adequate margin of safety. The Indiana Department of EnvironmentalManagement (IDEM) and the U.S. Environmental Protection Agency (U.S. EPA) have requiredthe LSI/Greencastle facility to undertake detailed testing and analysis to demonstrate that itspollutant emissions do not contribute to concentrations in ambient air that might exceed theNAAQS established for those pollutants. These efforts include on-going ambient monitoring forPM10.

Although the “criteria” pollutants are released in the greatest quantities, there are many othercompounds that the LSI/Greencastle facility releases in small quantities, and the U.S. EPA paysconsiderable attention to the facility because it burns combustible liquids that qualify ashazardous wastes. These numerous non-“criteria” pollutants are the focus of this study, theextensive and conservative nature of which is prompted by the U.S. EPA’s cautious regulationsconcerning any facility disposing of hazardous wastes. However, most emissions from theLSI/Greencastle facility are typical of those that are emitted from cement kilns that do not burnhazardous waste fuels because they originate from the limestone feedstock and the primary fuelused by the plants.

The hazardous wastes burned by the LSI/Greencastle facility typically comprise spent solventsand other combustible waste liquids generated by various industries and manufacturers. Acement kiln serves as an ideal environment for hazardous waste combustion. It subjects thewastes to a high temperature over a long residence time, thereby promoting highly efficientdestruction of the organic compounds that comprise the bulk of the hazardous waste fuels.

1 Testing has shown that the majority of volatile organic compounds released from cementkilns originate from the limestone feed stock and are not related to the waste fuels.

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Testing has demonstrated that more than 99.99% of organic compounds are destroyed (i.e.,burned) within the LSI/Greencastle kiln. The wastes are used by the LSI/Greencastle facility as asource of fuel in its cement kiln, because the production of cement clinker requires a substantialinput of energy to heat and calcine the raw limestone feedstock.

A very small portion of the organic waste constituents, however, may escape destruction, andother compounds may be produced in small amounts as products of incomplete combustion, ormay evolve from the rock aggregate1. Any metals present in waste fuels are not destroyed, andalthough most of these are removed by pollution control equipment or become part of the clinkerproduct, small levels are emitted to the environment. The fact that the LSI/Greencastle releasessmall quantities of compounds is not, however, unusual. For example, automobiles emit amyriad of copmounds that, if breathed at concentrations present in the tailpipe, could behazardous to health. From experience, however, people are exposed to undiluted auto exhaustonly for limited (if any) times, and tailpipe emissions disperse rapidly once introduced to theatmosphere. Thus, like any other source of pollution, the relevant issue regarding thecompounds released from the LSI/Greencastle is the degree to which they become available topeople, accounting for both dispersion and dilution in the atmosphere, but also considering allplausible ways through which exposure might occur.

The eventual fate of any compounds released to the air must also be considered, as somecompounds are capable of entering and concentrating within soil, water, and plants, therebybecoming available to animals and people through means other than inhalation. Continuing withthe example of automobile emissions, consider the case of lead, which was ubiquitous in air inthe years when it was widely used as a gasoline additive. During the 1970s and 1980s,unhealthy levels of lead were present in the air in many areas across the United States. Thevirtual elimination of lead from gasoline, however, has reduced levels of lead in air toinsignificant levels (except in areas near mines, smelters, or other major sources of leademissions). The legacy of many years of lead emissions remains, however, in soils to which thelead deposited. Soils near roads and highways exhibit elevated levels of lead, and provide anongoing media of exposure to past emissions.

This report focuses on the evaluation of the small levels of compounds that are — or could be —released by the LSI/Greencastle facility, and evaluates the various ways that the compoundscould be contacted by people, starting with the direct inhalation of the compounds while they arepresent in air, followed by indirect pathways whereby compounds deposit to the ground, becomeincorporated within soils and foodstuffs, and then consumed either inadvertently (within soil) orpurposely (within people’s diets). The consideration of both direct and indirect exposurepathways is termed multi-pathway exposure assessment, and represents the attempt to develop

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upper-end estimates of a person’s total potential exposure to compounds released from theLSI/Greencastle facility.

This risk assessment is based on worst-case measurements of the compounds that are releasedfrom the LSI/Greencastle facility. Drawing from experience with similar facilities, the U.S. EPArequired LSI/Greencastle to determine the presence of an extensive list of compounds, and toquantify the rates at which any of these compounds are released, both from the stack of the kiln(the largest source of emissions at the facility) and from storage and handling of the waste fuels. Two series of stack emissions testing were performed with the kiln operating under stressedconditions designed to maximize emissions rates. Basing a risk assessment on thesemeasurements results is an overestimation of the possible hazards caused by the plant and adds amargin of safety to the evaluation. Table ES-1 is a list of the compounds measured in eitherstack emissions or in waste fuels, and hence considered in the risk assessment. It should benoted that many of the compounds are present independent of the fact that the LSI/Greencastlefacility utilizes waste fuels, and instead tied to the composition of the aggregate minerals or theprocess involved in the manufacture of cement clinker. It should also be noted that some of thecompounds have both beneficial and deleterious effects on human health. Zinc, for exampleserves as an essential nutrient, but excessive amounts can be harmful.

Given estimates of the rates at which these compounds are, or may be, released from theLSI/Greencastle facility, a series of models is used to predict the concentrations and distributionof the compounds that occur throughout the environment. These models are based on empiricaldata and physical principles, and have been developed by the U.S. EPA and others with theknowledge that models are imprecise. To insure that the models do not underestimate the degreeto which compounds might accumulate in the environment and food chain, most uncertaintiesare resolved in a manner that over predicts the concentrations that are likely to occur. Themodeling is thus designed to make high-end estimates of the degree to which people may beexposed to compounds released by the LSI/Greencastle facility.

The philosophy of developing high-end exposure estimates also influences the scenariosexamined with the risk assessment. These scenarios focus on a model of the people, animals,and plants living in the vicinity of the LSI/Greencastle facility that have the highest potential toencounter compounds emitted by the facility. Table ES-2 lists the exposure scenarios consideredwithin the risk assessment. The goal of estimating high-end exposure scenarios is met in threeways:

• scenarios are evaluated at locations where the highest concentrations are predicted tooccur due to emissions from the LSI/Greencastle facility;

• the types of personal exposure scenarios considered are those for people that consumelarge amounts of the foods that tend to accumulate compounds from the environment;and

• the rates at which compounds are encountered (e.g., through the amount of foodconsumed) are assumed to be at high-end or higher-than-average values.

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Table ES-1 Compounds considered in the risk assessment.

Metals/Inorganics Organic compoundsAluminum Acenaphthene EthanolAntimony Acenaphthylene Ethyl AcetateArsenic Acetone EthylbenzeneBarium Acetonitrile Ethyl Ether Beryllium Acetophenone FluorantheneCadmium Acrylonitrile FluoreneChromium (total) Anthracene HexaneChromium (hexavalent) Benzaldehyde Hexanone, 2-Cobalt Benzene Indeno(1,2,3-cd)pyreneCopper Benz(a)anthracene IodomethaneLead Benzo(ghi)perylene Isobutyl AcetateManganese Benzo(a)pyrene MethanolMercuric chloride Benzo(e)pyrene Methyl tert-butyl etherMercury Benzo(b)fluoranthene Methyl ethyl ketoneMethyl mercury Benzo(k)fluoranthene Methyl isoamyl ketoneNickel Benzonitrile Methyl isobutyl ketoneSelenium Benzyl alcohol Methylene chlorideSilver Bis(2-ethylhexyl)phthalate Methyl naphthalene, 2-Thallium Bromomethane NaphthaleneVanadium Butanol, n- Octane, n-Zinc Butyl acetate PeryleneChlorine Carbon disulfide PhenanthreneHydrogen chloride Carbon tetrachloride Phenol

Chlorobenzene Propanol, 2-Polychlorinated dibenzo(p)dioxinsand furans (PCDD/PCDFs) andpolychlorinated biphenyls (PCBs)

Chloroform Propanol, n-Chrysene Propyl acetateCresol, m- Pyrene

2,3,7,8-TCDD Cresol, o- Pyridine1,2,3,7,8-PCDD Cresol, p- Styrene1,2,3,4,7,8-HxCDD Cumene Tetrachloroethylene1,2,3,6,7,8-HxCDD Cyclohexanone Tetrahydrofuran1,2,3,7,8,9-HxCDD Diacetone alcohol Toluene1,2,3,4,6,7,8-HpCDD Dibenz(ah)anthracene Trichloroethane, 1,1,1-OCDD Dibenzofuran Trichloroethylene2,3,7,8-TCDF Dichloroethane, 1,2- Trimethylbenzene, 1,2,4-1,2,3,7,8-PCDF Dichloroethylene, 1,1- Trimethylbenzene, 1,3,5-2,3,4,7,8-PCDF Diethylene glycol Xylene, m-1,2,3,4,7,8-HxCDF Dimethylphenol, 2,4- Xylene, o-2,3,4,6,7,8-HxCDF Di-n-butylphthalate Xylene, p-1,2,3,7,8,9-HxCDF1,2,3,4,7,8,9-HpCDFOCDFCoplanar PCBsTotal PCBs

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The exposure scenarios listed in Table ES-2 reflect the first two criteria. The individualsconsidered in the human health risk assessment do not represent actual people, but rather serveas typical examples of the populations that are modeled to encounter higher-than-averageexposure to compounds released by the LSI/Greencastle facility. The hypothetical people thatare studied include a resident, a subsistence farmer, and a subsistence fisher. Philosophically,the resident exposure scenario is intended to characterize a person who engages in typicalactivities and who lives in the vicinity of the location where emissions from the facility areexpected to produce the highest concentrations in the environment, and hence have the greatestpotential to affect soil, homegrown vegetables, and drinking water that can serve as indirectavenues of exposure. The subsistence farmer and fisher represent high-end exposure scenariosof individuals who derive a substantial portion of their food from home-grown or local sources. Like the resident, both the subsistence farmer and fisher are assumed to live in the vicinity of thelocation predicted to be most affected by emissions from the LSI/Greencastle facility, butsupplement the resident’s exposure profile with the consumption of locally-derived foods thattend to accumulate compounds to the greatest degree. Thus, the subsistence farmer is assumedto raise a substantial portion of his or her meats, eggs, and dairy products in the vicinity of thelocation where the influence of the LSI/Greencastle facility is predicted to be highest. Similarly,the subsistence fisher, who depends primarily on fish as a source of dietary protein, is assumedto catch a substantial portion of his or her fish at the Cagles Mill Lake, the water body predictedto be most affected by facility emissions that is also of sufficient size to support a subsistencefisher.

It should be noted that, in constructing the profile of assumptions for an exposure scenario, eachindividual assumption is not taken at an extreme value, but rather the suite of assumptions isdesigned to produce a high-end exposure estimate that remains within plausible limits. Thus,there may be individuals who consume more of a particular type of food than that assumed in therisk assessment, but there are likely to be few (if any) people who live at the location mostaffected by facility emissions, grow and raise the majority of their own food, live at this locationand in this manner for thirty years, and hence receive a greater degree of exposure to compoundsfrom the LSI/Greencastle facility than is estimated for the hypothetical exposure scenarios.

Table ES-2 also indicates two generic and nine specific scenarios examined to evaluate potentialrisks to plants and animals. The generic scenarios for terrestrial and aquatic communities aredesigned to address general risks to the plants and animals, while the specific scenarios focus onanimals that are known to be sensitive to certain pollutants, or are representative of classes ofanimals that, due to their dietary habits, are likely to gain exposure to higher-than-average levelsof compounds released by the LSI/Greencastle facility. Similar to the human health assessment,environmental exposure scenarios are evaluated at locations that are predicted to be affected to arelatively high degree by LSI/Greencastle facility emissions.

Exposure rates are estimated for each of the compounds in Table ES-1, and for each of thehypothetical exposure scenarios listed in Table ES-2. These rates of exposure are then comparedwith data and information on the exposure levels of compounds that may cause adverse effectson health. Two types of comparisons are made within the human health risk assessment. First,the likelihood that each emitted compound might cause cancer is evaluated. In this case, the

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Table ES-2 Summary of Risk Assessment Exposure Scenarios

Receptor Exposure Pathways Location

Human health risk assessment — adults and children a

Resident InhalationIngestion of vegetables, drinking water, andsoil

Maximum impact point

Subsistence farmer InhalationIngestion of vegetables, drinking water, andsoilIngestion of home-raised meats and eggs


Subsistence fisher InhalationIngestion of vegetables, drinking water, andsoilIngestion of locally-derived fish

Maximum impact point &Cagles Mill watershed b

Ecological risk assessment — generic receptors

Terrestrial communities Exposure to soil contaminants Maximum impact point

Aquatic communities Exposure to surface water contaminantsExposure to sediment contaminants

Cagles Mill watershed

Ecological risk assessment — indicator species

Deer mouse Ingestion of plants Maximum impact point

Meadow vole InhalationIngestion of plants and soil


Northern bobwhite Ingestion of plants and soil Maximum impact point

American woodcock Ingestion of animals (worms), plants, and soil Maximum impact point

Kingfisher Ingestion of fish Cagles Mill watershed

Bald eagle Ingestion of fish, birds, and mammals Cagles Mill watershed &Maximum impact point b

Mink Ingestion of fish, birds, and mammals Cagles Mill watershed &Maximum impact point b

Red fox Ingestion of mammals, plants, birds, and soil Maximum impact point

Red-tailed hawk Ingestion of mammals, birds, and soil Maximum impact pointa Adult and child receptors are considered separately and combined (for lifetime exposure scenarios)b Only the fish portion of the diet is evaluated at the Cagles Mill watershed

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incremental, or excess, risk of getting cancer is calculated by multiplying the predicted exposurerates with compound-specific estimates of potency for each compound that is known orsuspected to cause cancer in humans. The excess cancer risks are estimates of a person’sadditional risk of getting cancer in his or her lifetime, above and beyond the background levelthat people get cancer from all causes, which is 1 in 2 for men, and 1 in 3 for women. A frequentbenchmark used by regulators for incremental cancer risk is 1 in 100,000, which represents anincrease in cancer risk of 0.003% for a woman and 0.002% for a man.

The total estimated lifetime incremental risks of cancer are listed in Table ES-3. These valuesreflect the sum of the estimates for all known or potentially carcinogenic compounds included inLSI/Greencastle facility emissions. The compounds that contribute principally to each cancerrisk estimate are also presented in Table ES-3. The incremental risk levels due toLSI/Greencastle facility emissions are larger for the subsistence farmer and fisher scenarios,reflecting the conservative nature of the risk assessment and the potential importance of indirectexposure pathways. Objectively, the lifetime incremental cancer risk estimates are quite small,especially when compared with the background (overall) risk of getting cancer. As can be seenfrom the values in Table ES-3, the highest cancer risks associated with emissions from theLSI/Greencastle facility total an incremental risk of 1 in 1,000,000, which are an order ofmagnitude smaller than the regulatory benchmark of 1 in 100,000, and represent an increase ofonly 0.0002 – 0.0003% above background cancer incidence levels.

Table ES-4 presents risk estimates for compounds that, at sufficient levels of exposure, couldcause adverse health effects other than cancer. Although such health effects include diseasesthat affect different organs which differ among compounds, these broad categories of potentialhealth effects are grouped because they are evaluated in a similar manner. For each compound,the predicted level of exposure is compared with a level of exposure that is believed to be safe,i.e., a level that can be tolerated without risk to health (unlike incremental cancer risk, where arisk is assumed for any level of exposure). The comparison is made as a hazard quotient,calculated for a given compound as the predicted level of exposure to LSI/Greencastle emissionsto a safe level (termed a reference dose or reference concentration). Two types of hazardquotients are assessed to reflect different types of exposures to compounds emitted from theLSI/Greencastle facility. Chronic hazard quotients are calculated to assess health effects thatmight be associated with exposure to compounds that could occur over extended periods of time,while acute hazard quotients are evaluated to gauge the nature of exposure to elevatedconcentrations of compounds in air that are predicted possibly to occur on an occasional basis.

The magnitude of the hazard quotient compared with a value of one determines the extent of thepotential risk. If the hazard ratio is smaller than one, the level of predicted exposure toLSI/Greencastle facility emissions is lower than the level thought to be potentially harmful, andno adverse effects on health would be expected. If the hazard ratio is greater than one, the levelof exposure exceeds the level thought to be potentially harmful, and the possibility of adversehealth effects might exist. However, since the reference doses and concentrations used tocharacterize safe values frequently embody safety factors, it is incorrect to conclude that hazardratios greater than one will in fact correspond to that actual incidence of health effects.

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Table ES-4 indicates that the highest sum of these hazard quotients or the overall hazard index is0.02 for chronic risks and 0.006 for short-term risks. These values represent the sum of all of thehazard ratios for the individual compounds, and strictly, hazard ratios should be separated intocategories of specific health effects. However, because the sum of all values is well below one,consideration of the aggregate hazard indices is sufficient to conclude that, based on the riskassessment, that:

• compounds released from the LSI/Greencastle facility do not cause adverse health effectsin the local population.

Hazard indices developed to evaluate potential risks to the environment are summarized in TableES-5. The hazard index values reflect the results of analyses similar to those of chronic risks tohuman health. Long-term, repeated exposure to compounds released from the LSI/Greencastlefacility was evaluated for each of eleven different scenarios and compared with benchmarklevels that are expected to be safe for environmental receptors. The aggregate hazard indices,which reflect the sum of compound-specific hazard ratios, are all substantially smaller than one. Thus:

• compounds released from the LSI/Greencastle facility are not expected to harm theenvironment.

Table ES-3 Summary of Incremental Cancer Risk Estimates a

Receptor Incremental cancerrisk estimate

Principal exposurepathway(s) contributing to riskestimate

Principal compound(s)contributing to riskestimate b

Resident 8 in 100,000,000 c Ingestion of drinkingwater, vegetables

Hexavalent chromium,cadmium

Subsistence farmer 1 in 1,000,000 Ingestion of beef,milk, chicken, and eggs

Hexavalent chromium,PCDD/PCDF

Subsistence fisher 2 in 10,000,000 Ingestion of drinkingwater, fish

Hexavalent chromium,cadmium,PCDD/PCDF

a The risk estimates shown here include risks due to both direct (report Table 7-10) and indirect(report Table 7-9) exposures. The estimates are based on continuous operation of the facility, usingcompound emission rates measured under stressed operating conditions, and for the exposurepathways shown in Table ES-2. b Hexavalent chromium was not detected in the recent emissions testing of the facility but isincluded in this risk estimate as if it is emitted at half of its average detection limit.c Incremental cancer risks shown here are reported in the body of the report in scientific notation; arisk of 8 in 100,000,000 may be also shown as 8 × 10–8 or 8 E-8.

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Table ES-4 Summary of Hazard Indices Used to Evaluate Risks of Non-Cancer Health Effects

Receptor Hazard Index Principal exposurepathway(s) contributing torisk estimate

Principal compound(s)contributing to riskestimate

Chronic Exposure Scenarios

Resident 0.0006 Ingestion of vegetables Thallium, antimony,mercuric chloride

Subsistence farmer 0.01 Ingestion of beef, milk,and vegetables

Thallium, antimony,mercuric chloride

Subsistence fisher 0.02 Ingestion of fish Methyl mercury

Acute Exposure Scenarios

All 0.006 Inhalation Methanol, glycol ethers

Table ES-5 Summary of Hazard Indices for Ecological Risk Assessment Scenarios

Exposure Scenario Hazard Indexa Principal compound(s)contributing to risk estimate

Air (Inhalation) 0.004 Zinc

Soil Community 0.03 Chromium

Surface Water 0.001 Pyrene

Sediment 0.0007 Chromium, mercury, copper

Deer Mouse 0.1 Lead, aluminum

Meadow Vole 0.2 Aluminum, lead

Northern Bobwhite 0.02 Aluminum, lead, cobalt

American Woodcock 0.3 Aluminum, lead, zinc

Mink 0.007 Mercury, benzene

Bald Eagle 0.02 Mercury

Kingfisher 0.05 Mercurya These values, based on the measured emission rates of compounds, do not appear in Chapter 9.They can be calculated from the estimated hazard indices in Chapter 9 by multiplying by the ratioof the average measured emission rates to the MACT-apportioned emission rates.

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The risk estimates presented in Tables ES-3 to ES-5 correspond to the estimates of emissions fromthe LSI/Greencastle facility when it is operating under stressed operating conditions, at fullcapacity, and are inclusive of potential process upset conditions. More detailed information onthese risk estimates is presented in Tables 7-9 through 7-12 of the risk assessment report. Since thefacility does not always operate at full capacity (e.g., it is shut down for periods of maintenanceeach year), the emission rates, and hence risk estimates, are likely overestimated. Since the facilityis tested under stressed conditions, normal emission rates are probably lower than those measured. Even so, a series of risk estimates is presented in the risk assessment report (see Tables 7-5 through7-8) based upon the highest of three measured emission rates developed during facility testing. These risk estimates tend to be about twice as large as the best-estimate values summarized inTables ES-3 through ES-5. This factor of two would not alter conclusions relative to typicalregulatory risk criteria, as incremental cancer risks would remain well below 1 in 100,000, andhazard indices well below one. Thus, basing risk estimates on the highest measured emission rateswould not lead to risk estimates of significant concern.

Because of recent state-of-the-art air pollution prevention upgrades, the LSI/Greencastle facility is avery low emitting facility. LSI/Greencastle is, however, legally permitted to release compounds atemission rates significantly higher than those measured. While it is not anticipated that emissionswill ever approach or exceed the levels allowed by U.S. EPA and IDEM regulations, the riskassessment report actually focuses on these limits, since they are of regulatory concern to the U.S.EPA. Tables 7-1 through 7-4 of the risk assessment report, as well as all of the tables in Chapter 9(the ecological risk assessment), reflect risk estimates based upon hypothetical, legally permittedemission levels. Specifically, the risk assessment evaluates the Maximum Achievable ControlTechnology (MACT) emission limits promulgated by the U.S. EPA under the provisions of theClean Air Act. The U.S. EPA’s MACT limits are based on the best-performing facilities, and thusreflect emission limits that can be met by modern, state-of-the-art facilities that employ the bestavailable control technologies to limit pollutant emissions. Emissions of a particular cement kilnare highly influenced by the nature of the mineral aggregate that it processes. This factor, incombination with the recent modernization of the LSI/Greencastle facility, results in actual facilityemissions that are many times smaller than MACT limits. Table ES-6, which compares measuredemission rates from the LSI/Greencastle facility to MACT limits, reflects the fact that:

• the facility emits significantly lower levels of compounds than allowed by the U.S. EPA’sMACT limits.

The risk estimates developed on MACT emission limits in some cases exceed typical target risklevels by small margins. For example, the incremental cancer risk to the farmer is a little less thanthree times the target of 1 in 100,000 if the facility operated at MACT limits at all times. Similarly,a few of the environmental hazard indices based on continuos operation at the MACT limits exceedone (reflecting the point where potential exposure levels exceed those gauged to be safe). Giventhat measured emissions — as tested under stressed operating conditions designed to produce thehighest possible emission rates — were substantially lower than MACT limits suggests that there isa negligible chance that emissions could ever reach such levels. Even if they did, the fact thattarget risk levels are exceeded in a few cases does not mean that the facility would presentsignificant risks if it somehow managed to release compounds at levels as high as those of theMACT limits. As discussed in various places in the report, the risk assessment calculations are

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designed in a biased manner to overestimate actual risks in an attempt to compensate for variousuncertainties:

• even at the MACT-based emission limits, which the facility will not continuously operate asmodeled, health risks will likely remain within acceptable limits and emissions’ impacts willbe well below background levels.

The degree to which risks based on MACT emissions might be overestimated is reflected within theintermediate modeling results. As described in Chapter 9, the ecological risks predicted for twoMACT compounds — mercury and lead — exceed the target criterion of one. The exposureestimates for these two metals depend most strongly on the predicted levels of metals that willaccumulate in soil. The predicted concentrations in soil, however, are in each case only a smallincrement to the natural background level that exists ubiquitously in soil (see Table 9.18). Theimplication from this finding is not that natural background corresponds to a larger (and possiblyunacceptable) risk, but rather that the risk assessment methods, overestimate the risks as expected.

Table ES-6 LSI/Greencastle Stack Measurements Compared with MACT Emission Limits

Pollutant Measured Stack-GasConcentration atLSI/Greencastle(average of three runs) a

U.S. EPA MACT b

Emission LimitPercentage of MACTLimit

Particulate mattercontaining non-volatile metals (e.g.,antimony, nickel,selenium, thallium)

0.044 kg per Mg of feedmaterial

0.15 kg per Mg offeed material 29%

Low volatility metals(arsenic, beryllium,chromium)

14 :g/dscm @7% O2content 56 :g/dscm 25%

Semi-volatile metals(cadmium and lead)

3.1 :g/dscm @7% O2content 240 :g/dscm 1.3%

Mercury compounds 5.0 :g/dscm @7% O2content 120 :g/dscm 4.2%

Chlorine andhydrogen chloride 1.7 parts per million 130 parts per million 1.3%

Dioxins and furans 0.0015 ng/dscm TEQ@7% O2 content 0.4 ng/dscm TEQ 0.38%

a Abbreviated units in this table include: kg for kilograms (1,000 g), Mg for megagrams (1,000,000g), :g for micrograms (0.000001 g), dscm for dry standard cubic meter, ng for nanograms(0.000000001 g), and TEQ for toxicity equivalent quotient.b MACT = Maximum Achievable Control Technology

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A similar interpretation can be made of the predicted incremental risks from exposure topolychlorinated dibenzo(p)dioxins and furans (PCDD/PCDF). For this group of compounds, theMACT-based emission limit translates to an incremental cancer risk estimate for hypotheticalsubsistence farmers in excess of the typical target level of 1 in 100,000 (as described above). Simple consideration of actual farming practices in the area of the LSI/Greencastle facility,however, yields risk levels below the target criterion. Moreover, even for the hypothetical case, theunderlying exposure level is only 10 – 20% of the typical background exposure to PCDD/PCDF(from the general environment and dietary intake —see Table 7-13). When viewed from theperspective of the measured PCDD/PCDF emission rate corresponding to only 0.38% of theMACT-based limit, the PCDD/PCDF exposure due to LSI/Greencastle facility emissions is only asmall percentage of the background exposure to PCDD/PCDF experienced by the general U.S.population.

Overall, it has been found that the LSI/Greencastle facility is expected to have no significant impacton the health of the local population or the local environment.

• Emissions of a wide range of compounds from the LSI/Greencastle cement kiln havebeen measured and, even under worst-case operating conditions, they are well belowthe U.S. EPA’s applicable MACT limits.

• The highest expected personal exposures to these compounds by direct and indirectpathways are estimated to produce less than a 0.0003% increase in the risk of cancer,and are well below the U.S. EPA’s reference dose and concentration levels for non-cancer effects.

The reader is encouraged to explore additional portions of the risk assessment report. The report isorganized in the logical progression of the risk assessment, starting with the description ofcompound emission rates, and followed subsequently by air dispersion modeling, environmentalfate-and-transport modeling, exposure estimation, and culminating with the calculation of riskestimates to human health and the environment, along with a discussion of uncertainties. Sufficientdetail is provided to reproduce the calculations if desired, but the qualitative descriptions of theunderlying approaches, assumptions, and philosophies are likely of greater value to the generalreader. Through these descriptions, a sense for the risk assessment process can be gained from thereport without the need to understand the mathematical details of its numerous equations, tables,and numerical values.

2 In the U.S., men have a 1 in 2 chance of developing cancer in their lifetime, and womenhave a 1 in 3 chance (American Cancer Society, 1996). It should also be noted that regulatoryrisk thresholds (such as a 1 in 100,000 incremental cancer risk allowable for a combustionfacility) are based on projected, or modeled, risks of contracting cancer that tend to be estimatedin a manner that is believed to overpredict actual risk. These factors should be kept in mindwhen comparing to background cancer incidence rates, which are measured, actuarial risks.

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1 Introduction and backgroundLone Star Industries operates a cement kiln near Greencastle, Indiana (hereafter theLSI/Greencastle facility) that has the capacity to produce upwards of 1,600,000 tons of portland andmasonry cement per year. LSI began producing cement at this site in 1925, built the current facilityin 1969, and most recently added a preheater in 2000. Because the cement kiln is a largeindustrial facility, it is subject to a number of different regulations and requirements designed toensure that any emitted pollutants are released in small enough quantities that they do not adverselyaffect the health of nearby residents or harm the environment. In 1987 the facility began to burnwaste solvents in the kiln and has demonstrated compliance with all applicable hazardous wasteregulations and emissions limits since that time.

Among the U.S. EPA's previous draft recommendations concerning combustion facilities is thatairborne emissions from boilers and industrial furnaces (BIFs) that combust hazardous wastes beanalyzed via multi-pathway risk assessments. Since then, the role of multi-pathway riskassessments has been affected, but not necessarily displaced, by recently Maximum AchievableControl Technology (MACT) regulations aimed at cement kilns that utilize hazardous waste-derived fuels (WDF). MACT regulations allow regional branches of the U.S. EPA to require multi-pathway risk assessments at their discretion based upon facility-specific conditions andcircumstances.

The goal of a multi-pathway risk assessment is to determine whether the emissions from aparticular facility pose significant risks to public health or the environment, as defined by stringentregulatory guidance. For example, BIF regulations have historically allowed a facility’s emissionsto pose an excess (incremental) cancer risk estimate of 10–5 (1 in 100,000), This is a relativelyconservative limit compared with the background cancer incidence (50,000 in 100,000 for men, and33,000 in 100,000 for women).2

A multi-pathway risk assessment for a combustion facility (such as that described herein) focusesonly on the risks due to compounds emitted from the facility, and does not consider compoundsalready present in the environment for other reasons (e.g., due to natural background or emissionsfrom other anthropogenic sources). As such, the risk assessment addresses only the incrementalrisk due to emissions from the particular facility under evaluation, and not the cumulative risk due

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to all sources of environmental exposure to compounds (i.e., the facility combined with backgroundand all other sources).

Lone Star Industries (LSI) operates a cement kiln near Greencastle, Indiana that qualifies as a BIFand burns WDF. The U.S. EPA Region 5 (Region 5) originally requested a health risk assessmentas part of the RCRA Part B and BIF permitting requirements for the LSI/Greencastle facility. Aninitial scope-of-work for a multi-pathway health risk assessment was submitted to Region 5(Cambridge Environmental, 1995), but subsequent developments in regulatory guidance demandedrevision of portions of the original scope-of-work. The scope-of-work evolved through discoursebetween LSI/Greencastle and Region 5 to incorporate significant changes and enhancements thathad been made in the U.S. EPA’s risk assessment guidance (Region 5, 1998). Pursuant to thisdiscussion and through various iterations of the scope-of-work and workplan, a final, approved RiskAssessment Workplan (RAWP) was submitted to the U.S. EPA in December 2000 (CambridgeEnvironmental, 2000). A copy of the RAWP is included for reference in Appendix I. The RAWPcontains a more detailed history of its development, and also provides important technicalinformation used in the development of the multi-pathway risk assessment.

Much of the risk assessment for the LSI/Greencastle facility is based on the U.S. EPA’s draftHuman Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities (hereafterHHRAP, U.S. EPA, 1998a). The HHRAP is quite detailed and builds upon previous U.S. EPAguidance. The HHRAP is currently available in draft form, including an addendum documentissued to correct errors and omissions (U.S. EPA 1999). The HHRAP is used as the framework forthe LSI/Greencastle risk assessment as is consistent with contemporary risk assessment guidanceand sound scientific knowledge.

Comprehensive stack testing serves as the primary source of information on pollutant emissionsfrom the LSI/Greencastle facility (Recertification of Compliance [ROC] testing, GossmanConsulting, 2001a; Product of Incomplete Combustion [PIC] Risk Burn testing, GossmanConsulting, 2001b). However, the new facility’s MACT limitations are also important in theevaluation of emission rates. Since the LSI/Greencastle is permitted to emit pollutants up to thelevels that correspond to MACT limits, the primary results of this risk assessment are predicated onthe assumption emissions occur at MACT levels at all times, even though emission rates of thepollutants regulated by the MACT regulations, as measured under worst-case operating conditions,are much lower. The multi-pathway risk assessment attempts to predict, through the use ofmodeling, pollutant properties, and site-specific information, the disposition of pollutants in theenvironment, and hence estimate how they may be contacted by people and animals, and whethersuch contact presents significant risks to health.

A number of refinements to the HHRAP guidance are included in the RAWP (Appendix I), andadditional enhancements are described in the body of the risk assessment report. As stated above,the overall goal of these refinements is to achieve better consistency with scientific knowledge. The interactive relationship with Region 5 that developed during the evolution of the RAWP will becontinued to finalize the contents of the LSI/Greencastle risk assessment so that it provides aprotective, yet realistic, assessment of potential risks to both human health and the environment.

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This risk assessment report follows the HHRAP’s suggested outline and content. Subsequentsections describe elements of the risk assessment as discussed in the HHRAP and (as appropriate)in the context of conditions specific to the LSI/Greencastle facility. The report is organized into aseries of chapters that describe the sequential steps of the multi-pathway risk assessment, with eachstep built upon those that preceded. The LSI/Greencastle facility is described in Chapter 2, andpollutant emissions, termed compounds of potential concern (COPCs), are quantified. Chapter 3describes the detailed modeling study designed to estimate the levels of COPCs in air and in wetand dry deposition that result from emissions from sources at the LSI/Greencastle facility. Chapters4 through 6 describe the procedures used to estimate the levels COPCs that could be contacted bypeople in their environment and diet, focusing on categories of individuals likely to receive thehighest levels of exposure. Potential risks to human health that could result from such exposure areestimated in Chapter 7, focusing (as is traditional in risk assessments) on the incremental chancethat exposure to the facility’s emissions might lead to the development of cancer or other adversehealth effects. Uncertainties of the human health risk assessment are discussed in Chapter 8. Potential risks to the environment are assessed within Chapter 9, repeating many of the same stepscovered in Chapters 4 through 8 in order to assess potential exposure to COPCs and risks that mightbe experienced by plants and animals living in the vicinity of the LSI/Greencastle facility. Chapter10 summarizes the overall results of the multi-pathway risk assessment, discussing the implicationsof the findings as integrated from previous chapters. Finally, the technical appendices contain thedetailed information needed to reproduce the calculations of the risk assessment.

3 The slurry consists of water, limestone, and other minerals. Water in the slurry evaporatesand is emitted from the kiln stack, while the limestone and minerals engage in chemical reactionsthat net the clinker product and carbon dioxide (which, like the water, is released from the stack).

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2 Facility characterization

Lone Star Industries, Inc. (LSI) operates a kiln that produces Portland cement clinker near the Cityof Greencastle, Putnam County, Indiana on County Road 150W. The LSI/Greencastle facilityproduces Portland Cement clinker in a rotary kiln. Raw materials fed to the kiln include shale,sand, and limestone, which are currently fed as a wet slurry. At the facility’s present designcapacity, a slurry feed rate of 430 tons per hour is used to produce 184 tons of cement clinker.3 Thekiln and its contents are heated by co-firing pulverized coal and hazardous waste fuel (HWF). Flue-gas cleaning is accomplished principally through the use of an electrostatic precipitator. A portionof the flue-gas that bypasses the electrostatic precipitator is cleaned through a spray tower (forcontrol of sulfur dioxide) and a baghouse (for particulate control).

Detailed process descriptions of the LSI/Greencastle facility are provided in the ROC and PIC RiskBurn reports (Gossman Consulting, 2001a; Gossman Consulting, 2001b). For convenience,summary excerpts from these reports are provided in the following sections.

2.1 Basic facility information

A process schematic of the LSI/Greencastle facility is included as Figure 2.1 (as reproduced fromFig 1.2.1.2 from the ROC test report [Gossman Consulting, 2001a]). The basic systems thatcomprise the cement clinker production facility are:

• the Kiln and Auxiliary Equipment;• the Alkali By-Pass Baghouse Dust Collecting Device; and• the Greencastle Recycled Dust System.

These elements are briefly described below. Descriptions are also provided for the hazardous wastefuel (HWF) operation and the cement kiln dust landfill, which are also part of the LSI/Greencastlefacility. The components of the LSI/Greencastle facility are depicted in plan map format in Figure2.2, which is also reproduced from its previous presentation as Drawing 1.2.3 of the Trial Burn TestPlan (Gossman Consulting, 1999).

Kiln and Auxiliary Equipment

Cement kilns such as the LSI/Greencastle facility are horizontally inclined rotating cylinders thatare refractory-lined and internally-fired. The wet raw material is fed to a hammer mill where it isflash-

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Drawn by: Date:

Cooling / Combustion Air

Quench Air

Clinker

A.P.C.D. Stack

Clinker

Calciner

HeatExchanger

SHWF

LHWF

AlkaliBy-PassA.P.C.D.(Baghouse)

PreheaterA.P.C.D.(E.S.P.)

Clinker Cooler

Coal MillA.P.C.D.(Baghouse)

Stack

Hammermill

Raw Feed(Slurry)

Process Gas Flow

Process Material Flow

Fuels Flow

Lone Star Ind.

Greencastle FacilityPreheater/Precalciner

Kiln System Schematic

Air

Main Stack

Dryer

RecyledDust

Kiln

THC / COCEM Sample Line

3

2

4

1

5

12

3

4

5

6

HWF Solids

Coal

(See Section 1.2.2.2)

Waste

6

8

712

3

4

5

6

Slurry Feed

HWF Liquids

CKD Wasted

Fly-Ash

7

8

Quench Water

SOx ReductionLime Injection9

Quench Water

9SOx ReductionLime Injection

Dec. 26, 2000

Sampling PointDescriptions

Clinker

Fly-Ash

Figure 2.1 Process schematic of the LSI/Greencastle facility.

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INSERT FOR FIGURE 2.2 GOES HERE

Figure 2.2 Plan map of the LSI Greencastle facility.

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dried by hot gases from the fired calciner. This dries the slurry and sends it to the preheater beforeit passes through the precalciner furnace and then into the cement kiln. The preheated/precalcinedmaterial is further heated as it travels through the kiln. Combustion gases flow in the oppositedirection. As the material progresses through the kiln, it undergoes physical and chemical changes. The production of cement requires that the solid material be heated to approximately 2,650/F to2,700/F, while the gaseous material reaches temperature in excess of 3,800/F. The clinkerproduced from this process is conveyed through a modified Fuller reciprocating grate cooler with afixed inlet. The cooler uses 12 separate cooling fans which are used to supply the left, center, andright zones of the cooler in the fixed inlet and the first Controlled Flow Grate System compartmentto provide more accurate control of the cooling air. The cooled clinker is then stored forsubsequent grinding, during which approximately 5% gypsum is added to produce Portland cement,the final product. Exhaust gases from the kiln pass through an electrostatic precipitator thatremoves most of the particulate matter from stack gases, which are released from a 225-foot highsmokestack.

Alkali By-Pass Baghouse Dust Collecting Device

A portion of the kiln combustion gases by-pass the preheater/precalciner tower. These gases arecooled, dedusted and exhausted into the main stack. This alkali by-pass allows a significant portionof chlorine, alkali metals (sodium and potassium) and sulfates to be removed from the recirculatingload of elements that are vaporized in the kiln burning zone and condensed in the preheater. Thesegases are very hot, about 2,100/F. Quench air and recirculated dust is added and then the still veryhot gases cooled in a water spray tower. These cooled gases (now about 300/F) pass through a dustremoval cyclone and into a baghouse. An alkali by-pass ID fan discharges these gases to the mainstack. The dust removed in the baghouse is wasted as cement kiln dust.

Greencastle Recycled Dust System

Dust from the precipitator is collected and conveyed by screw conveyors and an elevator to astorage dust bin. From the storage dust bin, the dust is weighed and pneumatically conveyed to theduct just upstream of the hammer mill dryer where it is recycled. The recycled dust may also besent to a waste dust bin. This provides the option to remove dust from the system. The signal fromthe weigh cells is transmitted to the control room whereby the control room operator controls theamount of dust returned to the raw material.

Hazardous Waste Fuels Operation

The LSI/Greencastle facility is capable of burning both solid and liquid waste fuels. Solid wastesare a minor component of the waste-derived fuel (WDF) operation, and are generated as separationbyproducts of the liquid fuel streams. Solid wastes are placed in small plastic containers (one orthree gallon capacity) and are fed into the kiln through an air cannon on a periodic basis (asnecessary). Liquid fuels constitute the bulk of the hazardous wastes burned in the kiln. Liquidwastes are received by tanker truck. Each shipment is sampled as tanker trucks enter the

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LSI/Greencastle facility. Shipment sampling occurs at the truck sampling platform (Figure 2.2),which is located adjacent to the WDF testing lab where sample composition is determined. Thewaste shipment is then transferred from the tanker trucks to the WDF tank farm at the WDF truckoff-loading area using vapor recovery techniques to minimize fugitive losses. The WDF tank farmcomprises a series of eight tanks with a total capacity of 400,000 gallons, plus associated pumpsand piping. Storage tanks are equipped with pressure relief valves to minimize breathing losses.

Cement Kiln Dust Landfill

The LSI/Greencastle facility operates a landfill on its property to dispose a portion of the cementkiln dust (CKD) generated from cement clinker production. Specifically, CKD generated by thealkali by-pass baghouse is landfilled in a 16.2 acre area located northeast of the main productionarea. The CKD landfill is regulated by the Indiana Department of Environmental Management. The entire CKD landfill is covered with a vegetated soil cap The landfill itself is engineered tominimize run-on and run-off. Any run-off is captured and directed to a sediment pond before it isdischarged. In addition, groundwater quality is monitored at numerous locations to ensure that theCKD landfill is not contaminating groundwater.

Although it covers 16.2 acres, active land filing of CKD is undertaken on a very small working facewhere it is compacted and then covered with soil as the working face is moved. Best managementpractices (BMPs) are followed to minimize fugitive dust emissions. The CKD is wetted prior totransportation from the discharge bin. CKD is deposited wet on the working face and thencompacted. On dry days, the haul road is wetted as well as the working face.

2.2 Sources of stack and fugitive emissions

Following the recommendations of the HHRAP guidance and discussions in the most recent RAWP(Cambridge Environmental, 2000) emissions from the LSI/Greencastle facility have been assessedquantitatively from three sources:

• the cement kiln stack;• the processing and storage area where waste fuels are stored and blended; and • the hatches of tanker trucks which are opened for short periods for waste sampling.

Emissions from the kiln stack have been assessed for all compounds positively detected in the stackgasses as part of either the ROC tests, or the Products of Incomplete Combustion (PIC) tests(Gossman 2001b), Tentatively Identified Compounds (TICs) from these tests for which sufficienttoxicological data exists, all of the compounds identified in the HWF and assessed for fugitiveemissions, polychlorinated biphenyls (PCBs), polychlorinated dibenzo(p)dioxins and furans(PCDDs and PCDFs), and total organics (designed to gauge the total amount of organic compoundspresent in stack emissions, including those that were not specifically identified by analytical

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methods). Total organics in the emissions (TOE) were evaluated during the PIC Risk Burn as thesum of identified and unidentified VOCs (referred to as Field Gas Chromatograph [FGC]components), SVOCs (referred to as Total Chromatographic Organics [TCO] components), andnon-volatile components (compounds with a boiling point over 300/C, or gravimetric [GRAV]components).

The latter two sources are characterized for fugitive emissions of volatile organic compounds thathave been detected in the Hazardous Waste Fuel (HWF) for analyses referenced in theRecertification of Compliance (ROC) tests (Gossman 2001a) between 1994 and 2000.

As described in the RAWP, process upset emissions are not addressed because:

• the PIC Risk Burn and ROC tests which are the source for the measured emission rates usedin the risk assessment were conducted under worst-case stack test conditions to producemaximum emission rates of COPCs that will be equal to or greater than emission rates underall allowable operating conditions, and

• the kiln is designed to automatically halt hazardous waste feed based on various operatinglimits to prevent short-term emission excursions,

As recommended in the HHRAP guidance and discussed in the RAWP, fugitive emissions ofcement kiln dust (CKD) were considered qualitatively, and therefore not included in thequantitative risk assessment. The procedures used to collect, transport, and manage CKD aredescribed in the facility description that appears at the beginning of this chapter, along with adiscussion of the on-site CKD landfill. Management practices designed to mitigate fugitiveemissions are also included. It should be noted that the CKD landfill is regulated under permit bythe Indiana Department of Environmental Management (IDEM).

2.3 Identifying Compounds of Potential Concern (COPC)

The selection of compounds of potential concern (COPCs) will follow the algorithm depicted inFigure 2.3 (which is adapted directly from Figure 2-3 of the HHRAP). Basically, a compound willbe included in the risk assessment if (i) it is detected in stack emission testing, or (ii) if it is notdetected in stack emission testing, but is a detected constituent of waste fuel. Compounds that willbe eliminated from consideration are those that neither are detected in stack emissions nor aredetected constituents of waste fuel.

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Figure 2.3 Algorithm for selecting compounds of potential concern (reproduced from Figure 2-3 of the HHRAP)

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The process of identifying COPCs begins with the analyses of the HWF and the stack emissions forthe recent ROC and PIC Risk Burns. Compounds that were part of the ROC analyses included thefollowing inorganic compounds covered by MACT emission limits:

• mercury;• particulate matter metals (PMs): including antimony, cobalt, manganese, nickel and

selenium;• low-volatile metals (LVMs): arsenic, beryllium, and chromium (both trivalent and

hexavalent);• semi-volatile metals (SVMs): cadmium and lead;• hydrogen chloride / chlorine

Two additional metals were included in the analysis which are associated with RCRA’s Boiler andIndustrial Furnace (BIF) regulations:

• barium and thallium;

and several metals that were specifically requested for inclusion by the U.S. EPA;

• aluminum, copper, silver, vanadium, and zinc;

are also included as COPCs.

Based on the HHRAP guidance mercury is treated in the risk assessment calculations in threeforms:

• elemental vapor-phase mercury (Hg0) which is modeled only to assess the risk due to directinhalation;

• ionic mercury which is treated as mercuric chloride (HgCl2); and • methyl mercury (CH3Hg) which is not emitted from the facility but is assumed to be formed

in the environment from other mercury species.

Organic compounds, present in hazardous waste fuel (HWF) and stack emissions (as eitherunburned hydrocarbons, compounds volatilized from aggregate materials, or products ofincomplete combustion [PICs], constitute a much larger number of potential COPCs. Compoundsor classes of compounds which have been identified in HWF analyses from 1994 to 2000 werelisted in the results of the ROC test report (Gossman 2001a, Tables 2.2A and B) and are given herein Table 2-1. All 36 components detected in any of these tests of the waste are included as COPCs. Both cresols and xylenes were measured as totals of types m-, o-, and p-; they are treated in the riskassessment calculations as if the three types are present in equal amounts. For the three classes ofcompounds given as components of the HWF (aliphatic compounds, alkyl benzenes, and glycolethers), a single compound has been chosen to represent the class in the risk assessmentcalculations. The selections were based on the likelihood that the specific compound would be

4 PAHs are also included within the list of analytes for semi-volatile organic compound(SVOC) testing. A specific method for PAHs is being included, however, to achieve detectionlimits lower than those possible with the general SVOC scan. Should a particular PAH bedetected by both methods, the higher result will be used in the risk assessment (assuming bothmeasurements meet data quality objectives). 5 PCBs were not included in the previous RAWP (Cambridge Environmental Inc., 1999) andhave been added per the request of the U.S. EPA Region 5. 6 Testing will not be used to establish the total PCDD/PCDF emission rate, but rather thedistribution of PCDD/PCDF congeners. The total PCDD/PCDF emission rate to be used in therisk assessment will correspond to the MACT emission limit.

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present in fugitive emissions from the waste storage and handling areas (this led to the selection oflower molecular weight/higher vapor pressure compounds), and on the availability of toxicologicaldata for the compound. Hexane was selected to represent the class of aliphatic compounds withinthe waste, cumene (i.e. isopropyl benzene) for alkyl benzenes, and diethylene glycol for glycolethers.

Measurements of organic compounds in the stack gasses were performed through comprehensivetesting during the PIC Risk Burn in the following classes:

• volatile organic compounds (VOCs);• semi-volatile organic compounds (SVOCs);• polycyclic aromatic hydrocarbons (PAHs);4

• polychlorinated biphenyls (PCBs);5

• polychlorinated dibenzo(p)dioxins and furans (PCDD/PCDFs);6 and• total organics.

Within the first three classes (VOCs, SVOCs, and PAHs) 53 different compounds were detected,141 were tested for but not detected, and there were 175 Tentatively Identified Compound (TICs). Several compounds were analytes in more than one test. Table 2-2 lists the compounds detectedamong the VOC, SVOC, and PAH testing, the test method which produced the highest measuredconcentration, and whether the compound was also detected in the HWF. Analyses for SVOCswere performed using U.S. EPA Method 0010, and VOCs were analyzed using both Method 0030,and 0040 (as per the approved QAPP). A complete list of the compounds assessed in stackemissions testing, including those not detected and those tentatively identified are given inAppendix II.

During the PIC Risk Burns, emission rates for PCBs, PCDDs, and PCDFs were also assessed.Congener-specific analyses were performed for the 14 coplanar, ‘dioxin-like’ PCBs for ToxicityEquivalent Quotient (TEQ) evaluation, and levels of PCB homologs (those congeners with a givennumber of chlorine atoms) were measured in order to evaluate total PCB emissions. The 17congeners of PCDDs and PCDFs with chlorine atoms substituted in the 2,3,7, and 8 positions werealso analyzed individually for TEQ evaluation.

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Table 2.1. Average percentages of organic components of Hazardous Waste Fuel (HWF)

Component / year CAS number(s) 1994 1995 1996 1997 1998 1999 2000

Acetone 67-64-1 1.9 3.7 2.1 2.7 2.19 3.4 4.36 Acetonitrile 75-05-8 0.02 0.2 0.1 0.1 0.58 0.2 0.32 Aliphatics (hexane) 110-54-3 20.18 15 17.8 18.9 22.2 18.8 17.2 Alkyl benzenes(Cumene) 98-82-8 20.6 23.4 23.5 20.2 11.73 11.9 11.6

Benzene 71-43-2 0.6 0.3 0.5 0.4 0.1 0.3 0.15 Butanol, n– 71-36-3 0.6 4.9 0.6 2.2 0.89 0.8 0.98 Butyl acetate 123-86-4 2.6 3.3 1.2 1.7 1 1.9 2

Cresols (m-, o-, p-) 108-39-4, 95-48-7, 106-44-5 2.71 1.6 1

Cyclohexanone 108-94-1 0.3 0.4 Diacetone alcohol 123-42-2 0.19 0.2 0.1 Dichloroethane, 1,2- 107-06-2 0.2 Ethanol 64-17-5 0.8 3.1 1.2 1.1 1 3 2.24 Ethyl acetate 141-78-6 1 0.5 0.7 1.7 1.7 1.8 0.99 Ethyl ether 60-29-7 0.61 0.3 Ethylbenzene 100-41-4 3 1.8 5.8 2.6 2.11 2.6 3.79 Glycol ethers(diethylene glycol) 110-80-5 3.39 1.1 1.6 1.4 0.49 0.5 0.7

Isobutyl acetate 110-19-0 0.24 0.1 0.1 Methanol 67-56-1 0.2 5.4 1 1.1 1.43 2.3 2.33 Methyl tert-butyl ether 1634-04-4 0.3 0.2 0.2 Methyl ethyl ketone 78-93-3 6.8 5.4 5 6.9 3.99 2.9 2.16 Methyl isoamyl ketone 106-68-3 0.2 Methyl isobutyl ketone 108-10-1 3.5 2.6 1.4 4.5 3.04 3 1.1 Methylene chloride 75-09-2 0.5 0.7 0.3 0.4 0.45 0.5 0.93 Naphthalene 91-20-3 0.01 Phenol 108-95-2 1.7 0.5 0.5 1.3 0.83 0.6 0.3 Propanol, 2- 67-63-0 2 6.1 4.2 2.8 3.58 5.6 2.74 Propanol, n– 71-23-8 0.8 1.3 0.3 0.7 0.4 0.4 Propyl acetate 109-60-4 0.09 1 0.6 Pyridine 110-86-1 0.1 Styrene 100-42-5 0.3 1.5 4.28 4.1 3 Tetrachloroethylene 127-18-4 0.1 0.1 0.2 0.52 0.3 0.2 Tetrahydrofuran 109-99-9 0.2 1.5 0.6 0.4 1.3 0.9 2.33 Toluene 108-88-3 12.2 6.7 9.8 14.7 17.67 17.4 24.42 Trichloroethane, 1,1,1- 71-55-6 0.6 0.2 0.3 0.1 0.76 0.9 0.22 Trichloroethylene 79-01-6 0.1 0.2 0.3 0.3 0.39 0.4 0.32

Xylenes (m-, o-, p-) 108-38-3, 95-47-6, 106-42-3 16.3 12.6 18.2 14 12.91 12.2 13.2

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Table 2-2. Organic compounds identified in the stack emissions during the PIC Risk Burn(Gossman, 2000b).

Compound CAS number

Primarytest

emissionrate

Alsodetectedin waste

Acenaphthene 83-32-9 PAHAcenaphthylene 208-96-8 PAHAcetone 67-64-1 0030 TAcetonitrile 75-05-8 0040 TAcetophenone 98-86-2 0010Acrylonitrile 107-13-1 0040Anthracene 120-12-7 0010Benzene 71-43-2 0040 TBenzo(a)anthracene 56-55-3 PAHBenzo(ghi)perylene 191-24-2 PAHBenzo(a)pyrene 50-32-8 PAHBenzo(e)pyrene 192-97-2 PAHBenzo(b)fluoranthene 205-99-2 PAHBenzo(k)fluoranthene 207-08-9 PAHBenzyl alcohol 100-51-6 0010Bis(2-ethylhexyl)phthalate 117-81-7 0010Bromomethane 74-83-9 0030Carbon disulfide 75-15-0 0030Carbon tetrachloride 56-23-5 0030Chlorobenzene 108-90-7 0030Chloroform 67-66-3 0030Chrysene 218-00-0 PAHCresol, o- 95-48-7 0010 TCresol, m-, p- 108-39-4, 106-44-5 0010 TDibenzo(ah)anthracene 53-70-3 PAHDibenzofuran 132-64-9 0010Dichloroethene, 1,1- 75-35-4 0030Dimethylphenol, 2,4- 105-67-9 0010Di-n-butylphthalate 84-74-2 0010Ethylbenzene 100-41-4 0040 T

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Table 2-2 (continued). Organic compounds identified in the stack emissions during the PIC RiskBurn (Gossman, 2000b).

Compound CAS number

Primarytest

emissionrate

Alsodetectedin waste

Fluoranthene 206-44-0 0010Fluorene 86-73-7 PAHHexanone, 2- 591-78-6 0030Indeno(1,2,3-cd)pyrene 193-39-5 PAHIodomethane 74-88-4 0030Methyl ethyl ketone 78-93-3 0040 TMethylene chloride 75-09-2 0040 TMethyl naphthalene, 2- 91-57-6 0010Naphthalene 91-20-3 PAH TOctane 111-65-9 0030Perylene 198-55-0 PAHPhenanthrene 85-01-8 0010Phenol 108-95-2 0010 TPyrene 129-00-0 PAHStyrene 100-42-5 0030 TTetrachloroethylene 127-18-4 0030 TToluene 108-88-3 0040 TTrichloroethane, 1,1,1- 71-55-6 0030 TTrimethylbenzene, 1,2,4- 95-63-6 0030Trimethylbenzene, 1,3,5- 108-67-8 0040Xylene, m-,p- 108-38-3, 106-42-3 0040 TXylene, o- 95-47-6 0040 T

As described in section 2.3 of HHRAP and depicted in Figure 2.1 n this report, the 30 TICs foundat the highest concentrations in the stack gasses were considered for inclusion in the list of COPCs. A list of these compounds is given in Table 2.3. Of those compounds listed only two,benzaldehyde and benzonitrile had available toxicological data in either the HHRAP Appendices,the U.S. EPA Integrated Risk Information System (IRIS, 2001) or the California Office ofEnvironmental Health Hazard Assessment and Air Resources Board’s Consolidated Table ofOEHHA/ARB Approved Risk Assessment Health Values (OEHHA, 2000). These two compoundsare considered directly in the risk assessment as COPCs, while other TICs are evaluatedqualitatively in the assessment of risk assessment uncertainties.

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Table 2.3. Thirty Tentatively Identified Compounds (TICs) in order of estimated emission rateaverage emission rate as measured during the PIC Risk Burn Tests (Gossman 2001b).

TIC CASNumber

Toxicologicaldata available

Methane 74-82-8Ethylene 74-85-1Acetylene 74-86-22-hexanol 626-93-7 3-pentanone 96-22-0Benzaldehyde 100-52-7 TN-butane 106-97-8Butane, 2-methyl- 78-78-4 1-hexanol 111-27-3 Propane 74-98-6Ethane 74-84-0Benzofuran 271-89-6Indene 95-13-6Pentene 138-86-3 Dodecane 112-40-3 2-methylpentane 107-83-5 2h-pyran-2-one, tetrahydro-3,6-dimethyl-Benzonitrile 100-47-0 T Pentane, 2,3-dimethyl- 565-59-3 2-pentanol, 4-methylTetradecane 629-59-4 N-nonane 111-84-2N-undecane 1120-21-4Hexadecane 544-76-3Butanoic Acid, Methyl Ester 623-42-7Cyclopropane, 1-heptyl-2-methyl-Pentadecane 629-62-9Heptane 142-82-5 1-octene 111-66-0 N-nonene 124-11-8

Thus, included in the final list of COPCs are: all of the metals, chlorine species, VOCs, SVOCs, andPAHs identified in the ROC and PIC stack emissions tests, two TICs from the PIC tests withtoxicological data available, all components measured in the HWF; the PCBs are included as TEQsand total PCBs; the individually measured PCDD and PCDF congeners are included separately. All ofthe COPCs are modeled in the risk assessment as being emitted from the cement kiln stack, whilethose COPCs identified in the HWF are also modeled as being present in fugitive emissions from theHWF handling and storage areas of the facility. A complete list of the 119 COPCs evaluated in therisk assessment is given in Table 2.4.

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Table 2.4. All COPC considered in the risk assessment fate and transport calculations

Metals/Inorganics OrganicsAluminum Acenaphthene EthanolAntimony Acenaphthylene Ethyl AcetateArsenic Acetone EthylbenzeneBarium Acetonitrile Ethyl Ether Beryllium Acetophenone FluorantheneCadmium Acrylonitrile FluoreneChromium (total) Anthracene HexaneChromium (hexavalent) Benzaldehyde Hexanone, 2-Cobalt Benzene Indeno(1,2,3-cd)pyreneCopper Benz(a)anthracene IodomethaneLead Benzo(ghi)perylene Isobutyl AcetateManganese Benzo(a)pyrene MethanolMercuric chloride Benzo(e)pyrene Methyl tert-butyl etherMercury Benzo(b)fluoranthene Methyl ethyl ketoneMethyl mercury Benzo(k)fluoranthene Methyl isoamyl ketoneNickel Benzonitrile Methyl isobutyl ketoneSelenium Benzyl alcohol Methylene chlorideSilver Bis(2-ethylhexyl)phthalate Methyl naphthalene, 2-Thallium Bromomethane NaphthaleneVanadium Butanol, n- Octane, n-Zinc Butyl acetate PeryleneChlorine Carbon disulfide PhenanthreneHydrogen chloride Carbon tetrachloride Phenol

Chlorobenzene Propanol, 2-PCDDS / PCDFs/ PCBs Chloroform Propanol, n-2,3,7,8-TCDD Chrysene Propyl acetate1,2,3,7,8-PCDD Cresol, m- Pyrene1,2,3,4,7,8-HxCDD Cresol, o- Pyridine1,2,3,6,7,8-HxCDD Cresol, p- Styrene1,2,3,7,8,9-HxCDD Cumene Tetrachloroethylene1,2,3,4,6,7,8-HpCDD Cyclohexanone TetrahydrofuranOCDD Diacetone alcohol Toluene2,3,7,8-TCDF Dibenz(ah)anthracene Trichloroethane, 1,1,1-1,2,3,7,8-PCDF Dibenzofuran Trichloroethylene2,3,4,7,8-PCDF Dichloroethane, 1,2- Trimethylbenzene, 1,2,4-1,2,3,4,7,8-HxCDF Dichloroethylene, 1,1- Trimethylbenzene, 1,3,5-2,3,4,6,7,8-HxCDF Diethylene glycol Xylene, m-1,2,3,7,8,9-HxCDF Dimethylphenol, 2,4- Xylene, o-1,2,3,4,7,8,9-HpCDF Di-n-butylphthalate Xylene, p-OCDFCoplanar PCBsTotal PCBs

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2.4 Physical, chemical and toxicological properties of the COPCs

A significant amount of physical, chemical and toxicological information is required for each COPCto model its transport from the Greencastle facility into the surrounding air, soil, water, and biota, andultimately assess potential health risks it presents to the surrounding population. The preferred andprimary source of these data were the HHRAP’s Chemical-Specific Input Tables (Appendix A-3) theAcute Inhalation Exposure Criteria (AIEC) (Appendix A-4). Of the 119 COPCs treated in the riskanalyses, 85 had physical, chemical and toxicological data available from this source. When datawere not available in the HHRAP, information from the U.S. EPA Office of Air Quality Planning andStandards’ WATER9 software (U.S. EPA 2001a), and the National Library of Medicine’s HazardousSubstances Databank (HSDB, 2001) was used to obtain COPC-specific physical and chemicalproperties. Of primary importance, these sources provided values for each COPC’s octanol/waterpartitioning coefficient (Kow), a parameter used to derive the other media-specific partitioningcoefficients and biotransfer factors for plants and animals (as based on the guidelines and algorithmscontained in the HHRAP Appendix A-3). Toxicological data for COPCs not contained in the HHRAP(Appendix A-3) were obtained from the IRIS database or (as second preference) the CARB database. Appendix III contains a complete list of the COPCs and their physical, chemical, and toxicologicalproperties.

Exceptions have been made for two COPC groups relative to the use of HHRAP default properties. The first of these is mercury for which a recalculation has been done for the effective fraction ofatmospheric mercuric chloride which is present in the vapor-phase (Fv). The justification for thischange and steps taken to recalculate the value used in this report are given below in section 2.6. Additionally, a site-specific, empirically-calculated overall bioaccumulation factor (BAF) of mercuricchloride and methyl mercury in fish has been calculated and substituted for the HHRAP default value. The justification for this change and the method used to calculate the value used in this report aregiven in section 5.5.1.

The second COPC group for which some non-default properties have been used is the class of PCDDsand PCDFs, for which an apparently incorrectly calculated biotransfer factor for chicken and eggs(Bachicken and Baeggs) has been replaced. The values for these parameters in the original HHRAPAppendix Table A-3 were found to have been calculated incorrectly from the original research results(Stephens et al. 1995). The error arose because the BCF value for chicken and chicken eggs in theoriginal reference was multiplied by the soil consumption rate of 0.02 kg (DW)/day, when in fact itshould have been divided by the consumption rate. This error was corrected in the Erratamemorandum (U.S. EPA 1999) described above. However, as noted in the External Peer Review ofthe HHRAP (U.S. EPA 2000a):

The bioconcentration factors (BCF) presented for eggs and chicken in Table 3 of Stephens etal. (1995) should be applied to the transfer of dioxins/furans from feed, rather than soil, sincethe fraction of feed that is soil is already incorporated in deriving the BCF values. In otherwords, in calculating Ba values for egg and chicken, the BCF values in Table 3 should bedivided by the daily feed intake (0.2 kg DW/day), rather than the daily soil intake (0.02 kgDW/day).

Therefore the values for Bachicken and Baeggs given in the Errata document have been reduced by a factorof 10 for inclusion in the calculations for this report.

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2.5 Determining COPC emission rates

A variety of different COPC emission rate calculations were employed in the air dispersion anddeposition modeling portion of the risk assessment calculations, each of which was designed toprovide a conservative (high-end) estimate of the actual emission rates of the individual COPCs. Themethods for calculating these emission rates were described in the RAWP (Cambridge Environmental,2000). Some of the methods included initial screening emissions calculations that were extremelyconservative (e.g. treating each metal included in the PM class of compounds as being emitted at theMACT limit). Where these estimates produced risk levels above acceptable limits, a more realistic,though still conservative emission estimate was employed.

For COPCs, and classes of COPCs which are subject to MACT emission concentration limits, theemission rate of the class of COPCs were set to correspond to the MACT concentration limits, withthe components of each class apportioned within the total according to their distribution as measuredduring the ROC and PIC Risk Burns. The simplest example of this apportionment method is for theclass of MACT COPCs referred to as semi-volatile metals (SVM), comprising cadmium (Cd) and lead(Pb). The MACT emission limit for SVM is 240 :g/dscm; this value is converted to an emission rateby multiplying the concentration by the median stack flow rate in from the ROC and PIC Risk Burnsof 117.3 dscms (dry standard cubic meters per second). This gives a MACT emission limit for SVMsof 0.0282 g/s. The apportionment of cadmium and lead within this total SVM emission rate is basedon the mean emission rates for these two metals in the ROC testing: a Cd emission rate of 3.91×10–5

g/s, and a Pb emission rate of 3.36×10–4 g/s; giving a total SVM emission rate of 3.75×10–4 g/s. Thus,10.4% of the MACT SVM emissions, or 2.94×10–3 g/s, is assessed as Cd and 89.6% of the MACTSVM emissions or 2.52×10–2 g/s are assessed as Pb. Such an apportionment methodology was appliedto all of the COPCs covered by MACT emission limits:

• mercury;• particulate matter metals (PMs): including antimony, cobalt, manganese, nickel and selenium

[the MACT emission limit for PM is 0.15 kg PM/Mg feed, which converts to an emission rateof 10.74 g/s based on a kiln feed rate of 284 tons per hour (Gossman, 2001a) and the stackflow rate of 117.3 dscms (described above.)];

• low-volatile metals (LVMs): arsenic, beryllium, and chromium (both trivalent and hexavalent);• semi-volatile metals (SVMs): cadmium and lead;• hydrogen chloride (HCl) / chlorine (Cl2) [The MACT emissions limit for hydrogen

chloride/chlorine is expressed on a volume/volume basis (130 ppm), and consequently isconverted into two mass/volume limits based on the molecular weights of the two species andthe standard, gas-phase mole volume of 0.0224 m3/mole]; and

• polychlorinated dibenzo(p)dioxins and furans (PCDD/PCDFs).

The PM, LVM and HCl/Cl2 COPCs were apportioned in a similar manner, splitting the total MACTemission rate among the components according to the relative amounts measured in the ROC test. The use of this apportionment method for mercury is more complicated, and differs from the methodproposed in the RAWP. The justification for this change is related principally to consideration of theROC stack test results, and is described in Section 2.6. Essentially, consideration of the location in thesampling train where mercury was detected, combined with consideration of cement kiln reactionchemistry and equilibrium partitioning between vapor and particles, indicates the bulk of mercury in

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kiln stack emissions is present in elemental form. Conservative allowances for oxidized species havebeen included, however, to evaluate worst-case impacts within the watershed/aquatic analysis.

The MACT emissions limit for PM is 0.15 kg PM/ Mg feed which has been converted to an emissionrate of 10.74 g/s based on a feed rate of 284 tons per hour (Gossman, 2001a), and the stack flow rateof 117.3 dscms described above. The MACT emissions limit for hydrogen chloride/chlorine isexpressed on a volume/volume basis (130 ppm), and so must be converted into two mass/volumelimits based on the molecular weight of the two species and the standard, gas-phase mole volume of0.0224 m3/mole.

Because the MACT emissions limit for total PCDDs and PCDFs is expressed on a TEQ basis, theapportionment of the COPC congeners were distributed based on their TEQ emission rates rather thantheir mass emission rates. This was done by multiplying each congener’s average measured emissionrate by the congener’s TEF value to determine its TEQ emission rate. These values were then dividedby the total TEQ emission rate to determine each congener’s TEQ emission fraction. Finally the TEQfractions were multiplied by the MACT TEQ emission rate of 0.4 ng TEQ/s to generate the congener’sTEQ-based, apportioned emission rate within the MACT limit.

Also, because most of the test results for specific PCDD and PCDF congeners from the 2000 PIC RiskBurn were below detection limits, the apportionment of the 17 COPC congeners within the MACTemission limit was performed using the results of the 1992 COPC Trial Burn (Gossman, 1992). Theemission rates for the two congeners were below detection limits for all of the 1992 tests (2,3,4,6,7,8Hexa-CDF and octa-CDF) were assumed to be emitted at the lowest measured average emission rateamong all of the other congeners. The congener distributions in the 2000 PIC and 1992 COPC testsare qualitatively similar, with the congener 2,3,4,7,8 Penta-CDF accounting for more than half of themeasured TEQ concentration. Figure 2.2 shows the TEQ distributions for

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0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

PCD

D/P

CD

F TE

Q fr

actio

ns

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17Congener number (see table)

1992 COC 2000 PIC ND=0 2000 PIC ND=DL/2

# congener1 2,3,7,8-TCDD2 1,2,3,7,8-PCDD3 1,2,3,4,7,8-HxCDD4 1,2,3,6,7,8-HxCDD5 1,2,3,7,8,9-HxCDD6 1,2,3,4,6,7,8-HpCDD7 OCDD8 2,3,7,8-TCDF9 1,2,3,7,8-PCDF10 2,3,4,7,8-PCDF11 1,2,3,4,7,8-HxCDF12 1,2,3,6,7,8-HxCDF13 2,3,4,6,7,8-HxCDF14 1,2,3,7,8,9-HxCDF15 1,2,3,4,6,7,8-HpCDF16 1,2,3,4,7,8,9-HpCDF17 OCDF

Figure 2.2 Distribution of TEQ emission fractions for PCDD and PCDF congeners measured in the1992 COPC and 2000 PIC testing.

the 1992 COPC test and for the 2000 PIC tests with non-detected congeners at zero TEQ and at halfthe detection limit.

Table 2.5 contains the emission rates for the inorganic COPCs covered by MACT limits, including theapportioned emission rate for classes of COPCs emitted at the limit, the emission rates measured in the2000 ROC and PIC Risk Burns, and the 2000 ROC measured emission rates expressed as a percent ofthe MACT limit rates. Table 2.6 contains the emission rates for the PCDDs and PCDFs, includingeach congener’s apportionment within the MACT TEQ emission limit, and the results of the 2000 PICRisk Burn results to the MACT limit for both non-detected values entered as zero, and as half of thedetection limit. The measured emissions are also expressed as a percent of the MACT emission rate.

The emission rates used in the risk assessment calculations for the organic COPCs which weremeasured in the 2000 PIC Risk Burn testing (VOCs, SVOCs, and PAHs) are based directly on thestack testing results. For those organic COPCs which were detected in any of the analyses for theseclasses the emission rates are set at the lesser of the maximum measured emission rate and the 95%upper confidence limit of the mean emission rate among the measurements for the three test burn runs. This method was also applied to the COPCs which were only tentatively identified in the PIC analyses(TICs). For COPCs which were included in the risk assessment due to their presence in the HWF,which were included in the PIC Risk Burn analyses, but which were not detected in the stack gasses,the stack emission rate used in the assessment is the COPC’s highest mean detection limit among thevarious analyses.

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Some of the COPCs which were included because of their presence in the HWF were not part of thePIC Risk Burn analytical matrices. The stack emission rates for these compounds were calculatedbased on the facility’s minimum demonstrated destruction and removal efficiency (DRE), an HWFinput rate of 12.8 tons per hour, and the HWF composition as shown above in Table 2.1.

Fugitive emissions are non-stack releases of volatile compounds associated with hazardous wastestorage and handling. Procedures for RCRA estimating fugitive emissions are described in theHHRAP guidance. These procedures derive from regulatory guidance designed to estimate fugitiveemissions of volatile compounds from industrial facilities. As applied to the Greencastle facility,fugitive emissions can result from:

• breathing and working losses from storage tanks;• pumping wastes from tanker trucks into storage tanks;• leaking flanges, valves, pumps, and other equipment; and• sampling of incoming tanker trucks.

A portion of the work of estimating RCRA fugitive emissions was developed and documented by theGreencastle facility in a recent application to install a new hazardous waste storage tank (Lone StarIndustries, 1999). A copy of this process information report is provided in Appendix B of the RAWP,which is itself Appendix I of this report. Relevant process information in the report includes:

• A description of the waste fuels facility describing the procedures and equipment used tohandle, process, and store hazardous waste;

• Diagrams and maps that indicate relevant facility structures and potential points of fugitiveemissions;

• Information on waste composition and properties; and• Emission calculations for volatile organic compounds designated as Hazardous Air Pollutants

within the context of the Clean Air Act.

2–20

Table 2.5 Emission rates for inorganic COPCs covered by MACT limits.

Inorganic COPCssubject to MACTemission limits

MACT classemission limitor COPCapportionedpercent

Emission rateapportionedwithin MACTlimit (g/s)

Measuredemission rate(g/s)

Percent ratioof measuredemission rateto apportionedMACTemission rate

Particulate Matter 0.15 kg/Mgfeed 10.58 3.08 29.1 %

Aluminum 2.95% 3.13 E-1 9.10 E-2 29.1 %Antimony 0.0028 % 2.98 E-4 8.67 E-5 29.1 %Barium 0.038 % 3.97 E-3 1.15 E-3 29.1 %Cobalt 0.0023 % 2.40 E-4 6.99 E-5 29.1 %Copper 0.017% 1.80 E-3 5.24 E-4 29.1 %Manganese 0.088 % 9.28 E-3 2.70 E-3 29.1 %Nickel 0.0066 % 7.03 E-4 2.04 E-4 29.1 %Selenium 0.0014 % 1.44 E-4 4.20 E-5 29.1 %Silver 0.0043 % 4.51 E-4 1.31 E-4 29.1 %Thallium 0.016 % 1.64 E-3 4.78 E-4 29.1 %Vanadium 0.0060 % 6.33 E-4 1.84 E-4 29.1 % Zinc 0.034 % 3.58 E-3 1.04 E-3 29.1 %Low VolatilityMetals 56 :g/dscm 6.57 E-3 1.64 E-3 25.3 %

Arsenic 4.5 % 2.98 E-4 7.55 E-5 25.3 %Beryllium 0.5 % 3.32 E-5 8.36 E-6 25.3 %Chromium (total) 95.0 % 6.24 E-3 1.58 E-3 25 .3%Chromium(hexavalent)

3.6 % of Cr(total) 2.30 E-4 5.80 E-5 25.3 %

Semi-Volatile Metals 240 :g/dscm 0.0282 3.75 E-4 1.3 %

Cadmium 10.4 % 0.00294 3.91 E-5 1.3 %Lead 89.6 % 0.0252 3.36 E-4 1.3 %MercuryCompounds* 120 :g/dscm 0.0141 5.88 E-4 4.2 %

Elemental Mercury 80 % 0.0113 5.73 E-4 5.1 %Mercuric chloride (p) 10 % 0.00141 4.02 E-6 2.8 %Mercuric chloride (v) 10 % 0.00141 1.09 E-5 7.7 %Chlorine/HydrogenChloride 130 ppm 48.3 for Cl2**

24.8 for HClChlorine 10.2% 4.91 0.062 1.26%Hydrogen chloride 89.8% 22.3 0.281 1.26%

* The apportionment of the three mercury species within the MACT limited emission rate, and thespecies’ distribution within the total measured mercury emissions is discussed in section 2.6.** Because the MACT limit and the apportionment for the chlorine gasses are based on volumefractions (ppm), they translate into two different mass-based MACT emission rates.

2–21

Table 2.6 Emission rates for the PCDDs and PCDFs, including each congener’s apportionment withinthe MACT TEQ emission limit, and the results of the 2000 PIC Risk Burn results to the MACT limitfor both non-detected values entered as zero, and as half of the detection limit.

Inorganic COPCssubject to MACTemission limits

MACTemission limit

or 1992COPC

congenerapportionedpercent TEQ

TEQEmission rateapportioned

within MACTlimit

(ng TEQ/s)

Emission rateapportioned

within MACTlimit for fateand transport

modeling(g/s)

TEQMeasured

emission ratefrom 2000ROC tests

ND=0 /ND=DL/2

Percent ratioof measured

TEQ emissionrate to

apportionedTEQ MACTemission rate

PCDDs and PCDFs 0.4 ngTEQ/dscm 47 — 0.18 / 0.71

ng TEQ/s 0.38 / 1.5 %

2,3,7,8-TCDD 23.8 % 12.0 1.12 E-8 0 / 0.13 0 / 0.2871,2,3,7,8-PCDD 8.6 % 4.02 8.04 E-9 0 / 0.10 0 / 0.2161,2,3,4,7,8-HxCDD 3.7 % 1.75 1.75 E-8 0 / 0.035 0 / 0.0751,2,3,6,7,8-HxCDD 6.4 % 3.02 3.02 E-8 0 / 0.039 0 / 0.0841,2,3,7,8,9-HxCDD 6.0 % 2.83 2.83 E-8 0 / 0.035 0 / 0.0751,2,3,4,6,7,8-HpCDD 5.0 % 2.35 2.35 E-7 0 / 0.0039 0 / 0.008OCDD 0.1 % 0.00624 6.24 E-8 0 / 0.00093 0 / 0.002

2,3,7,8-TCDF 7.1 % 3.34 3.34 E-8 0.0095 /0.033 0.020 / 0.070

1,2,3,7,8-PCDF 1.7 % 0.0811 1.62 E-8 0.010 / 0.018 0.021 / 0.0392,3,4,7,8-PCDF 29.8 % 0.14 2.80 E-8 0.11 / 0.19 0.24 / 0.411,2,3,4,7,8-HxCDF 4.4 % 2.05 2.05 E-8 0.019 / 0.27 0.041 / 0.0561,2,3,6,7,8-HxCDF 2.0 % 0.0931 9.31 E-9 0.017 / 0.023 0.36 / 0.0502,3,4,6,7,8-HxCDF 0.3 % 0.0163 1.63 E-9 0.011 / 0.018 0.23 / 0.0381,2,3,7,8,9-HxCDF 0.4 % 0.0210 2.10 E-9 0 / 0.013 0 / 0.028

1,2,3,4,6,7,8-HpCDF 0.4 % 0.0203 2.03 E-8 0.00198 /0.0032 0.004 / 0.007

1,2,3,4,7,8,9-HpCDF 0.03 % 0.00163 1.63 E-9 0 / 0.0022 0 / 0.005OCDF 0.003 % 0.000163 1.63 E-9 0 / 0.00064 0 / 0.001

2–22

Table 2.7 Stack emission rates (and basis for value) for organic COPCs.

COPCStack

emission rate (g/s)

Basis forrate COPC

Stackemission

rate(g/s)

Basis forrate

Acenaphthene 1.19 E-4 PIC meas. Ethyl acetate 3.87 E-3 HWFAcenaphthylene 4.10 E-4 PIC meas. Ethylbenzene 1.08 E-3 PIC meas.Acetone 3.74 E-2 PIC meas. Ethyl ether 4.20 E-4 HWFAcetonitrile 1.27 E-2 PIC meas. Fluoranthene 1.02 E-4 PIC meas.Acetophenone 2.98 E-3 PIC meas. Fluorene 1.15 E-4 PIC meas.Acrylonitrile 5.57 E-3 PIC meas. Glycol ethers 4.24 E-3 HWFAnthracene 1.71 E-4 PIC meas. Hexane 6.00E-2 HWFBenzaldehyde 4.19 E-3 PIC TIC Hexanone, 2- 1.62 E-3 PIC meas.Benzene 2.25 E-2 PIC meas. Indeno(1,2,3-cd)pyrene 3.17 E-7 PIC meas.Benz(a)anthracene 4.08 E-6 PIC meas. Iodomethane 4.40 E-2 PIC meas.Benzo(ghi)perylene 1.14 E-6 PIC meas. Isobutyl acetate 2.03 E-4 HWFBenzo(a)pyrene 5.06 E-7 PIC meas. Methanol 6.35 E-3 HWFBenzo(e)pyrene 1.39 E-6 PIC meas. Methyl tert-butyl ether 3.23 E-4 HWFBenzo(b)fluoranthene 2.11 E-6 PIC meas. Methyl ethyl ketone 5.98 E-3 PIC meas.Benzo(k)fluoranthene 1.61 E-6 PIC meas. Methyl isoamyl ketone 9.24 E-5 HWFBenzonitrile 1.92 E-3 PIC TIC Methyl isobutyl ketone 1.41 E-4 PIC DLBenzyl alcohol 1.29 E-4 PIC meas. Methylene chloride 1.80 E-3 PIC meas.Bis(2-ethylhexyl)phthalate 1.53 E-3 PIC meas. Methyl naphthalene, 2- 2.02 E-3 PIC meas.

Bromomethane 1.60 E-3 PIC meas. Naphthalene 2.43 E-3 PIC meas.Butanol, n- 5.06 E-3 HWF Octane, n- 2.17 E-3 PIC meas.Butyl acetate 6.32 E-3 HWF. Perylene 1.07 E-7 PIC meas.Carbon disulfide 1.02 E-2 PIC meas. Phenanthrene 1.55 E-3 PIC meas.Carbon tetrachloride 3.59 E-5 PIC meas. Phenol 2.41 E-3 PIC meas.Chlorobenzene 8.89 E-4 PIC meas. Propanol, 2- 1.25 E-2 HWFChloroform 1.62 E-4 PIC meas. Propanol, n- 1.80 E-3 HWFChrysene 6.35 E-6 PIC meas. Propyl acetate 7.80 E-4 HWFCresol, m- 1.08 E-3 PIC meas. Pyrene 1.03 E-4 PIC meas.Cresol, o- 5.53 E-4 PIC meas. Pyridine 3.82 E-4 PIC DLCresol, p- 1.08 E-3 PIC meas. Styrene 4.39 E-3 PIC meas.Cumene 1.28 E-4 PIC TIC Tetrachloroethylene 3.38 E-4 PIC meas.Cyclohexanone 3.23 E-4 HWF Tetrahydrofuran 3.34 E-3 HWFDiacetone alcohol 2.26 E-4 HWF Toluene 9.13 E-3 PIC meas.Dibenz(ah)anthracene 1.86 E-6 PIC meas. Trichloroethane, 1,1,1- 3.69 E-5 PIC meas.Dibenzofuran 7.27 E-4 PIC meas. Trichloroethylene 7.80 E-5 PIC DLDichloroethane, 1,2- 4.99 E-5 PIC DL Trimethylbenzene, 1,2,4 5.62 E-4 PIC meas.Dichloroethylene, 1,1- 1.54 E-4 PIC meas. Trimethylbenzene, 1,3,5 2.69 E-4 PIC meas.Dimethylphenol, 2,4- 2.16 E-4 PIC meas. Xylene, m- 3.76 E-3 PIC meas.Di-n-butylphthalate 6.67 E-5 PIC meas. Xylene, o- 1.10 E-3 PIC meas.

2–23

Table 2.7 (continued) Bases for stack emission rates for organic COPCs.

PIC meas. the lesser of the 95%UCL of the mean and the maximum measured rate for identified compounds;

PIC TIC the lesser of the 95%UCL of the mean and the maximum measured rate for TICs;

HWF the rate of the COPC being fed into the kiln as part of the HWF and the minimum DRE value measured in the PIC Risk Burn;

PIC DL the detection limit for a COPC which was in the HWF and included in the PIC Risk Burn testing, but not detected.

The methods described in storage tank application serve as the basis for the calculation of COPCfugitive emissions from the entire storage and handling area. The estimated emission rate for eachCOPC in the new tank application is directly proportional to the COPC mass fraction in the HWF. Inorder to estimate the emission rate for the full set of HWF components listed in Table 2-1 the COPCmass fractions are first multiplied by the ratio of emission rates to mass fractions calculated in the newtank application. These emission rates were then multiplied by a factor of four to account for the full400,000 gallon HWF storage capacity for the entire facility relative to the 100,000 gallon HWFstorage capacity evaluated in the new tank application.

Calculations have also been performed for fugitive emissions during initial HWF tanker trucksampling, during which the tanker hatch is open to the atmosphere for a short time upon its arrival atthe facility. These estimates utilize a mass transfer model, and the same waste composition data fromTable 2-1. The equation to be used to estimate instantaneous vapor emissions during HWF samplingis:

e A h Copening vaptan ker = ⋅ ⋅where the terms are:

etanker emission rate of vapor when the tanker port is open;Aopening the area of the hatch opening;h the mass transfer velocity, which depends on the compound diffusivity in air,

kinematic viscosity, and wind speed; andCvap the estimated equilibrium vapor concentration of the compound of concern in

the headspace of the tanker truck.

Equilibrium vapor concentrations Cvap will be developed using compound-specific vapor pressures andRaoult’s Law for estimating equilibria of vapors with liquid mixtures.

2–24

CMF V

pMW

MW

vapa p

aair

=⋅ ⋅

⋅⎛⎝⎜

⎞⎠⎟

ρ

Da Density of ambient air (g/m3)MF Mole fraction of the COPC in the HWF (unitless)Vp Vapor pressure of the COPC (atm)pa Ambient atmospheric pressure (atm)MW Molecular weight of the COPC (g/mole)MWair Effective molecular weight of air (g/mole)

The mass transfer velocity h was estimated using the empirical correlation (Incropera and DeWitt,1981):

h ScD

da= ⋅ ⋅ ⋅

⋅0 664

10001 2 1 3. Re / /

with:

Re =⋅d uν

and

ScDa

=ν

where the terms are:

Re Reynolds number for the open sampling port (unitless)Sc Schmidt number for the COPC in air (unitless)Da Diffusivity of the COPC in air (m2/s)d Diameter of the sampling portu Average wind velocity (m/s)< Kinematic viscosity of air (m2/s)

Values of the instantaneous emission rates etanker were time-averaged for inclusion in the modeling toaccount for the time of individual truck sampling and the frequency at which trucks are sampled:

e N e sampletanker,avg tanker tanker= ⋅ ⋅ τ

where the additional terms are:

etanker,avgTime-averaged tanker emission rate, appropriate for use in dispersion modelingNtanker Number of tanker trucks sampled per unit time (e.g., number of trucks per hour)Jsample Time required to sample a single truck.

10 Due to the presence of alkaline compounds, mercuric chloride does not form in substantialamounts in cement kilns because the chloride more readily reacts with the sodium and potassiumpresent in the stack gas. Even under circumstances where the Na and K concentrations arerelatively low, chlorides will form with the large quantities of Ca before other metal chloridesform.

2–25

Values for the parameters Ntanker and Jsample were determined to be 72 trucks per week, and 3 minutesper truck, based upon operating records and practices at the Greencastle facility.

2.6 Justification for the use of non-default values for mercury speciationand partitioning

As stated in the RAWP, the HHRAP default parameters for Hg emissions speciation and partitioningwere to be used in the risk assessment calculations unless better data were identified or collected. TheHHRAP recommendations for modeling Hg emissions are that 20% of mercury should be assumed tobe particle-bound HgCl2, 60% should be assumed to be vapor-phase HgCl2, and 20% should beassumed to be vapor-phase elemental Hg. Based on the original reference on which the HHRAPdistribution is based, data contained in the 1997 U.S. EPA Mercury Study Report to Congress (U.S.EPA, 1997a), the results of the 2000 ROC Hg tests (Gossman 2001a), and a qualitative understandingof the physical and chemical conditions present in cement kiln and stack, a different distribution of Hgin the stack emissions is employed in the risk assessment calculations. However, despite qualitativeevidence to the contrary, the assumption that the soluble, ionic Hg species present in the stackemissions is HgCl2, will be maintained as recommended in the HHRAP (albeit at a reduced fractionalpresence).10

The reference cited for the HHRAP recommended default Hg distribution is Petersen, et al. (1995), which presents mercury speciation data in its Table 2 (referenced to the original German paper ofAxenfeld, et al., 1991) as the distribution for “Waste incinerators”. However, the incinerators towhich these speciation values are attributed are uncontrolled municipal waste combustors [this sameattribution is also given Volume III, Table 4-2 of the 1997 U.S. EPA Mercury Study Report toCongress (U.S. EPA, 1997a)]. The speciation distribution given in this table for hazardous wasteincinerators is 58% elemental Hg vapor, 20% divalent Hg, and 22% particulate Hg. Importantly, forPortland cement manufacturing facilities, the values are 80% elemental Hg vapor, 10% divalent Hg,and 10% particulate Hg.

The method used during the ROC tests to measure Hg in the cement kiln stack gasses is U.S. EPAMethod 0060: Multi-Metals Sampling Train which is described fully in the Final ROC Test Report(Gossman, 2000a, Volume II). Figure 2-1, which is reproduced from the ROC report, shows thesections of the sampling train used for collection of the different forms of metals. The Glass fiberfilter is employed to collect particulate forms, the HNO3 / H2O2 impingers are for soluble forms, andthe KMnO4 / H2SO4 impinger is employed specifically for the collection of vapor-phase elemental Hg. Following the sampling run, separate Hg analyses are preformed on:

1. the rinse and digestion solutions from the probe and filter,2. the contents and rinse solutions form the HNO3 / H2O2 impingers,

2–26

( )C CT

Tfactual part

std

probew= ⋅ −0 6975 1.

3. a rinse of the empty, middle impinger,4. the contents and rinse solutions from the KMnO4 / H2SO4 impingers, and5. a final HCl rinse of the KMnO4 / H2SO4 impingers.

Table 2.8 gives the analytical results for these five Hg analyses fro the 3 trial runs; the only portion ofthe sampling train in which Hg was measured above the detection limit was in the KMnO4 / H2SO4impingers, indicating that only elemental, vapor-phase Hg was positively identified in the emissions.

Table 2.8 Results from ROC Hg tests for the 5 solutions analyzed during the 3 test runs.

Solution analyzed Hg speciescaptured

Amount of Hg detected (:g)

Run 1 Run 2 Run 3Probe and filterrinse Hg2+ Particulate <0.2 <0.2 <0.2

Contents and rinsefrom the HNO3 /H2O2 impinger

Hg2+ Vapor <6.34 <6.03 <5.98

Empty impingerrinse Hg2+ Vapor <0.36 <0.41 <0.43

Contents and rinsefrom the KMnO4 /H2SO4 impinger

Hg0 Vapor 18.3 15.8 8.02

Final HCl rinse Hg0 Vapor <0.46 <0.46 <0.46

Because the detection limits for Hg2+ in the HNO3 / H2O2 impinger solution and rinse is significantlyhigher than the limits for any of the other stages, and because the ratio between the emission rates ofHg2+ and Hg0 is a critical parameter in Hg deposition rates and a subsequent health risks, Hg2+ vapor-phase emission rates have been estimated based on Hg2+ particulate detection limits and thepartitioning calculations described below.

An estimate of the vapor/particle partitioning of mercuric chloride within the sampling train can beperformed through consideration of the sampling probe characteristics and the specific measurementsobtained in stack testing during the recent ROC test. Equilibrium conditions are assumed to holdwithin the sampling train and glass filter, which is maintained at a temperature of 248°F = 120°C. Thenecessary stack parameters include the measured particle concentration Cpart (reported on a dry basis atstandard temperature) and the moisture content fw. The actual concentration of particles in the probe atthe filter is calculated as:


2–27

θ = ⋅ ⋅0 01. A CTSP actual

Φ =⋅+ ⋅

cp cL

o

θθ

Cactual concentration of particles in the probe at actual probe conditions (g/m3)Cpart particle concentration, as reported at standard temperature on a dry basis (gr/dscf,

grains per dry standard cubic foot)Tstd standard temperature (20°C = 293.15°K)Tprobe temperature of the sampling probe (120°C = 393.15°K)fw fractional water content0.6975 dimensional factor to convert units of grains/ft3 (gr/ft3) to grams/m3 (g/m3).

The concentration of particles in the probe is used in conjunction with the surface area per unit massof the particles (ATSP) to calculate the surface area of the particles per unit volume (2):

where the additional variables and their respective units are:

2 particle surface area to volume ratio (cm2/cm3)ATSP surface area of particles per unit mass (m2/g)0.01 dimensional factor to convert units of m2/m3 to cm2/cm3

Following U.S. EPA (2000b), the fraction of the compound that can be expected to partition toparticles is given as:

where the additional terms and units are:

M fraction of the compound absorbed to particles (unitless)c constant related to the heat of desorption of the particle surface and the heat of

vaporization of the compound (Pa-cm)pL" saturation liquid-phase vapor pressure of the pure compound at ambient

temperature (Pa).

For a compound that is a solid at standard conditions, pL" is estimated as the sub-cooled liquid vapor

pressure from the solid-phase vapor pressure pS":

( )p p

S T T

R TLo

So f m probe

probe= ⋅

−

⋅

⎛

⎝

⎜⎜

⎞

⎠

⎟⎟exp

∆

where the additional terms and units are:

2–28

)Sf entropy of fusion (J/mol-°K)Tm melting point of the compound (°K)R Universal Gas Constant, equal to 8.314 J/mol-°K

Weast (1988) provides data to calculate )Sf from the thermodynamic relationship:

∆∆ ∆

SH G

Tff f

=−

At a temperature of T=298.15°K, )Hf = –53.6 kcal/mol and )Hf = –42.7 kcal/mol for mercuricchloride (Weast, 1988). These values yield an entropy of fusion value of:

( )∆S f =

− −°

× = − − °536 42 7

29815418681

15306. .

..

.kcal / molK

Jkcal

J / mol K

Also, the solid-phase vapor pressure of mercuric chloride at the probe temperature can be estimatedfrom the correlation

pSo

aT bprobe= ×

− ⋅+

⎛

⎝⎜⎜

⎞

⎠⎟⎟

10101325760

0 05223., Pamm Hg

where a and b are empirical constants of 85,030 and 10.888, respectively (Weast, 1988). With thesevalues, a solid-phase vapor pressure

pSo = 52 08. Pa

is calculated at the probe temperature Tprobe = 393.15°K. Given a melting temperature of 276°C = 549.15°K, the sub-cooled liquid-phase vapor pressure is estimated as:

pLo = 0 0358. Pa

To estimate M, U.S. EPA (2000b) recommends the use of a value of 17.2 Pa-cm for the value of theparameter c, and a representative (mid-range) value for the surface area-to-mass ratio ATSP is 5.5 m2/g.. With these values, the above equations were used to estimate run-specific values of M, as listed in thefollowing Table 2.9. The average value of M is 0.271, or 27.1%, over the three stack test runs.

Table 2.9 Calculations for estimation of M (fraction of mercuric chloride sorbed to particles) in ROCstack testing

2–29

Parameter Run 1 Run 2 Run 3

Cpart (gr/dscf)(as reported in particulate stack test)

0.0119 0.0118 0.0127

fw(as reported in particulate stack test)

0.338 0.347 0.325

Cactual (g/m3) (calculated) 0.0134 0.0131 0.0146

2 (cm2/cm3) (calculated) 0.000739 0.000723 0.000804

M (calculated) 0.266 0.262 0.283

Based on the vapor to particle fractionation ratios calculated above, it is possible to estimate thedistribution of Hg forms within the sampling probe. Table 2.10 shows these values for calculationsusing half the detection limits for the non-detected Hg particulate measurements and the Hg analysisof the final HCl impinger rinse, and a calculated value for vapor-phase Hg2+ based on the particulatemeasurements and the ratios M from Table 2.9.

Table 2.10 Calculated Hg emission partitioning for the three ROC test runs.

Hg species Hg (:g)

Run 1 Run 2 Run 3

Hg2+ Particulate 0.10 0.10 0.10

Hg2+ Vapor 0.28 0.28 0.25

Hg0 Vapor 18.5 16.0 8.25

In order to incorporate the above site-specific emissions speciation and partitioning information intothe equations for Hg transport and fate employed in the HHRAP guidance, it is necessary torecalculate the effective HgCl2 emission rate, Q, and vapor fraction, Fv. This is performed by re-applying the methods and parameters used in the HHRAP for determining both the portion of emittedHg which is deposited locally vs. that which enters the global Hg cycle, and the fraction of HgCl2deposited locally which is derived from its pressence the vapor-phase. The additioanl parametersrequired for this calculation are the ambient partitioning fraction of HgCl2 between the vapor andparticulate-phases, and the fraction of each of the Hg forms which is deposited locally.

A vapor-to-particulate partitioning calculation, as was performed above for HgCl2 in the samplingprobe, could be performed for ambient temperature and particle concentrations and would result in theestimation that greater than 99% of HgCl2 will be found in the particulate-phase. However, becausethe condensation of HgCl2 onto particles as the stack plume disperses and cools is a complex dynamicprocess it woud be extremely difficult to model in the area around the facility. Therefore, it isassumed that 50% of the ambient HgCl2 is in the vapor-phase and 50% is in the particulate-phase.

2–30

This estimation is supported by the 50% Hg2+ / 50% HgP distribution cited in the U.S. EPA Report toCongress (1997a) for portland cement manufacturing, and is only slightly different than the 48% Hg2+ /52% HgP distribution cited for hazardous waste incinerators.

The results of combining the fraction of Hg in the emissions between Hg0 and HgCl2 from Table 2.10,the assumed partioning of ambient HgCl2 between the vapor- and particualte-phases, and the portionof each of these forms which are deposited locally instead of entering the global Hg cycle (taken fromthe HHRAP guidance Figure 2-4) are presented in Table 2.11. Based on the calculation formatoutlined in Figure 2-4 from the HHRAP, an effective HgCl2-specific emission rate, Q, of 1.4% of thetotal Hg emission rate is calculated as the sum of the fractions of locally deposited vapor-phase HgCl2(0.92%) and particulate-phase HgCl2 (0.49%). Similarly, the effective vapor fraction of HgCl2, Fv, of65% is calculated as the ratio of locally deposited HgCl2 (0.92% + 0.49%) derived from the vapor-phase HgCl2 (0.92%).

Table 2.11 Values used for the calculation of the effective emission rate and effective ambient vaporfraction for HgCl2.

Hg species Portion of emissions Portion of species

deposited in modeledregion

Portion of total Hgemissions deposited in

modeled region

Hg0 97% 1% 1.0%

HgCl2 vapor 1.35% 68% 0.92%

HgCl2 particulate 1.35% 36% 0.49%

1 ISCST3 = Industrial Source Complex – Short-Term

3–1

3 Air dispersion and deposition modeling

Detailed air dispersion and deposition modeling was conducted with the ISCST31 model, assuggested by the HHRAP draft guidance (U.S. EPA, 1998a). Ambient concentrations of allchemicals of potential concern were predicted over an extensive modeling grid centered aboutthe LSI/Greencastle facility to identify the pattern and magnitude of worst-case impacts due tofacility emissions of pollutants. Both wet and dry deposition of were also modeled per thedemands of the multi-pathway risk assessment.

The ISCST3 air dispersion model requires a substantial number of inputs. Relevant study-specific parameters are described in this chapter. For parameters not explicitly described,regulatory default modeling assumptions recommended by the U.S. EPA were employed toassign input parameters.

The predominant land use in the environs of the LSI/Greencastle facility is rural. The city ofGreencastle, though possibly urban in character, does not cover enough relevant land area toinfluence the overall character of the dispersion environment. Therefore, rural land use isassumed for the ISCST3 modeling study.

3.1 Geographic setting

The Lone Star Industries Greencastle (LSI/Greencastle) facility is located approximately onemile south of the city of Greencastle, Indiana. The LSI/Greencastle property coversapproximately two square miles of land area. The configuration of the LSI/Greencastle facilityis depicted as an overlay on a topographic map within Figure 3.1.

3.2 Source descriptions and parameters

Emissions from three different sources were modeled to characterize operations associated withthe handling and burning of hazardous waste. These sources were:

• the cement kiln stack;• the processing and storage area where waste fuels are stored and blended; and• the sampling platform area.located adjacent to the facility’s on-site laboratory, where

newly received shipments of hazardous waste are sampled from incoming tanker trucks.

3–2

Figure 3.1 Location of the LSI/Greencastle facility (in green) in relation to its environs. The map projection extends 20 km (west-to-east, in the horizontal) by 20 km(south-to-north, in the vertical). The map projection also corresponds to thebasic inner/outer modeling grid.

3–3

Table 3.1 lists the parameter values used to model the dispersion of pollutant emissions from thethree sources of interest. The cement kiln stack, which is responsible for the bulk of the mass ofpollutant emissions from the facility, is also the most straightforward source to characterize. TheISCST3 model requires specification of the physical stack height, the diameter of the flue fromwhich the effluent is released, and the flow velocity and temperature of the effluent at its releasepoint. The values for these parameters used in modeling stack emissions are summarized inTable 3.1. Physical parameters and dimensions were obtained from a recent air dispersionmodeling study conducted to satisfy Title V permitting requirements (August Mack, 1998). Thestack-gas flow velocity and temperature were selected at the median values obtained in therecent PIC Risk Burn and ROC tests (Gossman Consulting Inc., 2001a; 2001b).

Parameters to model the two sources of fugitive vapor emissions were assigned based upon theirphysical characteristics. Emissions from the waste fuel processing and storage area wereassumed to occur uniformly over the storage/blending area and assigned an initial mixed(dispersed) height of 5 m because they could evolve from valves, pumps, vents, etc. at varyingpoints up to the approximate height of the storage tanks. The tanker sampling platform iselevated to facilitate the collection of waste samples from the hatches atop incoming tankertrucks for subsequent analysis and characterization in the LSI/Greencastle on-site laboratory. This process is accomplished through opening of the tanker hatches for a brief period of time. The parameters assigned to the platform area are designed to simulate vapors emanating from thetanker hatch while it is open to the ambient air.

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Table 3.1 Modeling parameters for source characterization

Parameter(s) Value(s) Source(s)

Cement kiln stack (point source)Stack location (UTM coordinates) 511,507 m East

4,385,123 m NorthAugust Mack (1998)

Stack-base elevation (above meansea level)

228.3 m August Mack (1998)

Stack height 68.58 m August Mack (1998)

Stack inner (flue) diameter 3.5052 m August Mack (1998)

Stack-gas temperature 464.8°K Gossman Consulting Inc, (2001a;2001b). Three-run average valuesover eight different test conditionsranged from 464.3°K to 467.6°K

Stack-gas velocity 27.0 m/s Gossman Consulting Inc, (2001a;2001b). Three-run average valuesover eight different test conditionsranged from 26.0 m/s to 27.9 m/s.

Building downwash heights 33.53 – 68.58 m August Mack (1998)

Building downwash widths 6.7 – 49 m August Mack (1998)

Waste fuel processing and storage area (area source)Center of source 511,306 m East

4,385,086 m NorthAugust Mack (1998). Based on

facility configuration.

Dimensions of source 25.3 m by 22.2 m August Mack (1998). Based onfacility configuration.

Height of source Ground-level Professional judgement

Initial source mixing height 5 m Professional judgement, based onheight of tanks and equipment

Hazardous waste/tanker sampling area (area source)Center of source 511,185 m East

4,385,038 m NorthAugust Mack (1998). Based on

facility configuration.

Dimensions of source 0.45 m by 0.45 m Professional judgement regardingthe area of open tanker hatch.

Height of source 3.5 m Professional judgement regardingheight of tanker trucks

Initial source mixing height 0 m Professional judgement

2 SAMSON = Surface and Meteorological Surface Observation Network 3 SCRAM = Support Center Regulatory Air Modeling 4 The combination of Indianapolis and Peoria meteorological data has been used in the most recent air dispersionmodeling for the Greencastle facility (August Mack, 1998); previous modeling analyses relied on Dayton, Ohio forthe source of upper air data (Johnson, 1991; Calby, 1991). The choice of the upper air station (Peoria vs. Dayton) isnot expected to significantly affect model predictions.

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3.3 Meteorologic data and processing

Following standard and commonly accepted practice (as described in section 3.5 of theHHRAP), meteorologic data from proximate weather stations were utilized. Indianapolis is theclosest representative source for surface wind observations, and is also the source ofprecipitation measurements. Use of Indianapolis meteorologic data has been approved asrepresentative for the LSI Greencastle facility by both the U.S. EPA Region 5 and the IndianaDepartment of Environmental Management (IDEM) in previous regulatory modeling.

Surface data for Indianapolis were obtained from a combination of the SAMSON2 meteorologicdatabase (NCDC, 1993) and the U.S. EPA's SCRAM3 website. Upper air measurements (used toderive mixing heights) were taken from a weather station in Peoria, IL (as available on theSCRAM website).4 The SAMSON database was used for surface observations becauseprecipitation data (needed to conduct wet deposition modeling) were not available from theSCRAM website. Thus, the SCRAM database is used only as a source of mixing height data.

A modeling period from 1986–1990 has been selected to provide an overlap between theSAMSON and SCRAM data sources. The Meteorological Processor for Regulatory Models(MPRM, available from the U.S. EPA’s SCRAM webpage) was used to process data files andproduce meteorologic input files appropriate for the ISCST3 model. The advantage of theMPRM preprocessor is its ability to treat seasonal variation in deposition parameters (asdescribed below). The HHRAP endorses the use of the MPRM.

MPRM requires the specification of a number of parameters related to land-use and area-specificconsiderations. These parameters are listed in Table 3.2 along with preliminary values, selectedprimarily from representative default values recommended in the HHRAP. Two parameterswere assigned seasonal values based on information provided in the HHRAP. The winter,spring, summer, and fall seasons were assumed to correspond to the monthsDecember–February, March–May, June–August, and September–November, respectively. Notethat, for the purpose of modeling over a calendar year, the winter season is not contiguous. Thealbedo value for the winter season assumes snow cover for about half of the period.

Both meteorologic data files and MPRM log files are included in the electronic data AppendixA.

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Table 3.2 Parameter values for meteorologic data processing

Parameter Value Rationale

Anemometer height 20 feet Based on the station summaryinformation compiled by the National

Climatic Data Center (NCDC)

Minimum Monin-Obhukov length

2 m HHRAP recommendation foragricultural (open) land use

Surface roughnessheight at measurement

site

0.1 m HHRAP default recommendation formeteorological data collected at aNational Weather Service station

Surface roughnessheight for local area

(application site)

0.051–0.634 mvaries per season and winddirection (see Table 3.3)

Based on local land use andmeteorologic data, as described in the

text, following HHRAP guidance

Noon-time albedo Winter 0.3 Based on the HHRAP recommendationfor cultivated land without significant

snow coverSpring 0.14

Summer 0.20

Fall 0.18

Bowen ratio Winter 1.5 HHRAP recommendation for cultivatedlands

Spring 0.3

Summer 0.5

Fall 0.7

Anthropogenic heat flux 0 W/m2 HHRAP recommendation for rural areas

Local land use was examined in some detail in preparation of the risk assessment for theLSI/Greencaastle facility because it determines some of the fundamental inputs (especially theair dispersion modeling study). Topographic maps served as the principal source of informationregarding land use, supplemented by personal reconnaissance of the area and conversations withLone Star employees familiar with the area. The city of Greencastle, located to the north of thefacility, is the only area characterized as urban within the vicinity of the facility. Lands within afew miles of the facility are both open and forested. Open lands are used for residential,agricultural, and commercial purposes (e.g., quarrying operations). Forested lands includemostly deciduous trees.

5 The 3-km radius centered about the cement kiln includes portions of the Cloverdale,Reelsville, Clinton Falls, and Greencastle quadrangles (topographic maps published by the U.S.Geological Survey).

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To more accurately characterize local land use, a radius of 3 kilometers was considered centeredat the kiln stack. Transparencies were overlaid atop a composite of topographic maps,5 and landuse was apportioned into four categories — urban, forested, water, and open — based ondesignations indicated on the topographic map. Determinations were made for forty equal areasegments within each of sixteen principal wind directions from the facility. Land use withineach of the sixteen principal sectors was tabulated and summed within a spreadsheet; theresulting percentages are summarized in Table 3.3.

The first aspect of Table 3.3 relevant to air dispersion modeling is the percentage of land use thatfalls into the urban category. Averaged over the sixteen principal sectors, only 6.1% of the landin the vicinity of the cement kiln facility is urban. Based on Auer’s method (as described in theHHRAP), general land use is classified as rural for the purpose of air dispersion modeling.

The second use of land use characterization is the derivation of the average surface roughnesslengths (z0) that are used as parameters in meteorologic data processing. To derive an average z0for each season and sector, season-specific z0 values appropriate for each land use category areweighted by the fractions of land use in each sector. Seasonal values of z0 for each land use arederived from data in the HHRAP. Values of 1 m and 0.0001 m are assumed for urban land andwater, respectively, independent of season. Season-specific roughness lengths for forested andopen lands are based on values listed in the HHRAP for deciduous forest and cultivated land,respectively.

Seasonal sector-averaged surface roughness heights are listed in the final four columns of Table3.3. Since the MPRM model is limited to the consideration of twelve wind sectors, the sixteenvalues of roughness lengths in Table 3.3 must be reduced for use in MPRM. Based on simplicityand the pattern of values, the sixteen values were collapsed to eight by combining adjacentsectors and weighting by relative wind frequencies. Data for these calculations are provided inTable 3.4. The wind frequencies listed in Table 3.4 represent the fractions of winds depicted inthe wind rose for the Indianapolis, Indiana airport data (Figure 3.2). Note that the wind rosedepicts winds blowing from a sector toward the facility, and hence are opposite in sense from thedesignations in Table 3.4. As an example, the average local roughness length for the summerseason for the W/WNW combined sector is calculated as:

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Table 3.3 Land use in the vicinity of Lone Star’s Greencastle facility and determination ofsector-specific roughness heights

Land use categoryWeighted roughness heights z0 (m)

on a seasonal basisUrban Forested Water Open

Season Surface roughness height z0 (m)Winter 1 0.5 0.0001 0.01Spring 1 1 0.0001 0.03

Summer 1 1.3 0.0001 0.2Fall 1 0.8 0.0001 0.05

Direction relative tofacility

Percentage of land within land usecategory Winter Spring Summer Fall

N 53.1 6.3 40.6 0.567 0.606 0.694 0.602NNE 44.4 3.1 3.1 49.4 0.464 0.490 0.583 0.493NE 8.8 2.5 88.8 0.053 0.114 0.291 0.114

ENE 8.1 91.9 0.050 0.109 0.289 0.111E 22.5 77.5 0.120 0.248 0.448 0.219

ESE 10.6 89.4 0.062 0.133 0.317 0.130SE 21.9 78.1 0.117 0.242 0.441 0.214

SSE 11.3 88.8 0.065 0.139 0.324 0.134S 13.1 86.9 0.074 0.157 0.344 0.148

SSW 15.6 84.4 0.087 0.182 0.372 0.167SW 20.0 5.6 74.4 0.107 0.222 0.409 0.197

WSW 20.6 4.4 75.0 0.111 0.229 0.418 0.203W 38.1 61.9 0.197 0.400 0.619 0.336

WNW 36.3 1.9 61.9 0.187 0.381 0.595 0.321NW 21.3 1.9 76.9 0.114 0.236 0.430 0.208

NNW 0.6 40.0 0.6 58.8 0.212 0.424 0.644 0.356Average percentage

of land use forcategory

6.1 18.6 1.3 74.0

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Table 3.4 Combined sector-averaged local surface roughness heights for use in MPRM meteorological data processing

Directionrelative

to facility

Sector-averaged roughness height(m) from Table ?

Frequency of windsthat proceed from the

facility in the directionof the indicated sector

Combined sectordirection and

azimuthal degreerange (0°=north)

Combined sector-averaged roughnessheight (m) for use in MPRM modeling

Winter Spring Summer Fall Winter Spring Summer Fall

N 0.567 0.606 0.694 0.602 0.072 N/NNE(348.75°–33.75°) 0.512 0.544 0.634 0.544 NNE 0.464 0.490 0.583 0.493 0.083

NE 0.053 0.114 0.291 0.114 0.115 NE/ENE(33.75°–78.75°) 0.051 0.112 0.290 0.113ENE 0.050 0.109 0.289 0.111 0.094

E 0.120 0.248 0.448 0.219 0.061 E/ESE(78.75°–123.75°) 0.090 0.188 0.379 0.172ESE 0.062 0.133 0.317 0.130 0.066

SE 0.117 0.242 0.441 0.214 0.065 SE/SSE(123.75°–168.75°) 0.092 0.193 0.385 0.176SSE 0.065 0.139 0.324 0.134 0.060

S 0.074 0.157 0.344 0.148 0.051 S/SSW(168.75°–213.75°) 0.080 0.169 0.357 0.157SSW 0.087 0.182 0.372 0.167 0.044

SW 0.107 0.222 0.409 0.197 0.043 SW/WSW(213.75°–258.75°) 0.109 0.226 0.414 0.200WSW 0.111 0.229 0.418 0.203 0.045

W 0.197 0.400 0.619 0.336 0.035 W/WNW(258.75°–303.75°) 0.191 0.389 0.605 0.327WNW 0.187 0.381 0.595 0.321 0.051

NW 0.114 0.236 0.430 0.208 0.061 NW/NNW(303.75°–348.75°) 0.159 0.323 0.529 0.277NNW 0.212 0.424 0.644 0.356 0.053

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Figure 3.2 Wind rose of 1986–1990 meteorological data for the Indianapolis, Indiana airport

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3.4 Receptor locations and elevations

The NAD 27 reference datum for the coordinates was used in the air dispersion modeling study(as will be documented in the risk assessment report). Much of the work in defining sitecoordinates and receptor locations was developed in a previous permit application submitted tothe Indiana Department of Environmental Management (IDEM). Additional receptors wereadded to the risk assessment study to extend the modeling domain, and elevations at the UTMcoordinates were derived from digital elevation model (DEM) data available from the U.S.Geological Survey. Where possible, coordinates of new receptors were converted to the NAD27 data to maintain a consistent reference. In some cases, the reference datum used by the U.S.Geological Survey was not definitive, and may have been either NAD 27 or NAD 83. However,uncertainty introduced by the reference datum in these cases is negligible. In the region ofinterest, the difference between the UTM coordinates based on NAD 27 and those based onNAD 83 is insignificant, as the two differ by 1 m or less in both the west–east and south–northdirections.

The main receptor grid includes a combination of gridded (regularly spaced) locations anddiscrete locations placed along the facility property boundary. The receptor grid features closespacing (~100 m) near the source and more coarse coverage at greater distances. The receptorgrid was sufficiently extensive to allow the highest projected impacts to be refined within 100 m. The main modeling grid extended at least 10 km in each direction from the source location, andcovered the area depicted in the Figure 3.1 topographic map. Given the large number ofreceptors, the main modeling grid was split into two grids, labeled “inner” and “outer,” forISCST3 modeling purposes.

A third grid, termed the “watershed” grid, was established to model projected impactsthroughout the Cagles Mill Reservoir watershed, which encompasses a drainage area of about300 square miles. Digital boundaries for the watershed were obtained from on-line GeographicInformation System (GIS) files available from the Indiana Geological Survey, and elevations foreach receptor were interpolated from digital elevation files. Figure 3.3 depicts the relationship ofthe Cagles Mill watershed to the location of the LSI Greencastle facility.

Specific receptor locations of the inner, outer, and watershed grids are depicted in Figure 3.4 There are 784, 936, and 761 receptors in the inner, outer, and watershed grids, respectively. Theouter and watershed grids overlap slightly, as shown in Figure 3.4. Receptors are spaced atincrements of 500 meters in the main (inner and outer) modeling grids except in areas along andadjacent to the LSI/Greencastle property boundary, where 100 m spacing was used to refinelocations of highest projected impacts. Receptor locations in Cagles Mill Lake watershed arespaced at increments of 1,000 m (1 km), which was found to be sufficient to resolve gradients inpredictions given the distance the watershed is situated from the LSI/Greencastle facility.

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Figure 3.3 Cagles Mill Lake watershed (shown in dark outline). The lake is located at thesouthwestern edge of the watershed. The LSI/Greencastle facility, highlightedin green, is located to the northwest of the watershed.

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4355000.0

4360000.0

4365000.0

4370000.0

4375000.0

4380000.0

4385000.0

4390000.0

4395000.0

4400000.0

4405000.0

4410000.0

495000.0 500000.0 505000.0 510000.0 515000.0 520000.0 525000.0 530000.0 535000.0 540000.0 545000.0 550000.0

Inner GridWaterGridOuter Grid

Figure 3.4 Receptor locations considered in the ISCST3 modeling study. The LSI/Greencastle facility is located inthe center of the “inner” modeling grid. The axes indicate the Universal Trans-Mercator (UTM)coordinates, expressed in meters according to the NAD 27 reference datum.

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3.5 Pollutant scavenging coefficients

For particles and their associated pollutants, dry deposition parameters are calculatedautomatically by the ISCST3 model based upon meteorologic conditions and particle sizeproperties. Wet deposition calculations for particles, however, rely on user input for establishingscavenging coefficients. Thus, the ISCST3 model requires both the specification of a particle-size distribution and the explicit specification of wet scavenging coefficients. Since a facility-specific particle size distribution was not obtained for the LSI/Greencastle facility, the defaultdistribution recommended in the HHRAP (U.S. EPA, 1998) is used. Information regarding theassumed particle size distribution is presented in Table 3.5. Two sets of mass fractions arespecified for pollutants that are expected to be found in different portions of particles:

• mass-weighted values, for pollutants that are likely to be distributed uniformlythroughout particles in the stack emissions; and

• surface-weighted values, for pollutants that are likely to condense (or form) onto thesurfaces of existing (seed) particles as combustion gases cool prior to their release fromthe stack.

Values for wet scavenging coefficients, which vary with particle size, were assigned valuesbased on information in the HHRAP (Section 3.7.2.6). Values for frozen precipitation (snowand ice) were assumed to be one-third as large as the values for liquid precipitation (rain),consistent with recommendations in the HHRAP (U.S. EPA, 1998). Assumed values for the wetscavenging coefficients are listed in Table 3.5 as a function of particle size.

Table 3.5 Particle size distributions and wet scavenging coefficients for particle-boundchemicals of potential concern (COPCs)

Particlediameter

(:m)

Fraction of particles assigned toparticle diameter

Wet scavenging coefficient(hr/mm-s)

Mass-weighted Surface-weighted Liquid precipitation(rain)

Frozen precipitation(ice and snow)

0.35 0.22 0.49 7 × 10–5 2 × 10–5

0.7 0.08 0.17 5 × 10–5 2 × 10–5

1.1 0.08 0.13 6 × 10–5 2 × 10–5

2.0 0.11 0.09 1.3 × 10–4 4 × 10–5

3.6 0.10 0.05 2.6 × 10–4 9 × 10–5

5.5 0.07 0.02 3.9 × 10–4 1.3 × 10–4

8.1 0.10 0.02 5.2 × 10–4 1.7 × 10–4

12.5 0.11 0.01 6.7 × 10–4 2.2 × 10–4

15.0 0.13 0.02 6.7 × 10–4 2.2 × 10–4

6 A similar U-shaped tendency is characteristic of dry particle deposition as well.

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Little guidance regarding the deposition of gases is provided in the HHRAP, and the limitedamount of information that is presented in the HHRAP inadequately characterizes vapordeposition. In modeling vapor deposition, the HHRAP’s suggested convention of consideringonly wet deposition explicitly within the ISCST3 model has been followed. Thus, dry depositionhas been calculated as a parameter within fate and transport modeling (as described by theparameter Vdv in Appendix B of the HHRAP).

Also consistent with the HHRAP, wet deposition rates have been calculated by the ISCST3program. There is, however, a fair degree of uncertainty associated with the modeling of wetdeposition. Wet vapor scavenging coefficients are not well understood, nor is detailed guidanceprovided for calculating wet vapor deposition. The HHRAP suggests that vapors be treated assmall particles, which may seem intuitively correct, but is in fact inaccurate from a physicalperspective. Plotted as a function of particle size, wet deposition scavenging coefficients followa U-shaped curve that reaches a minimum for particles about a micron in diameter. For largeparticles (i.e., particles greater than a micron in diameter), scavenging coefficients decrease asparticle diameters decrease in conjunction with a greater ability for particles to deflect aroundraindrops (and hence resist scavenging). A reversal occurs, however, for sub-micron sizedparticles, for which attractive electrostatic effects become large enough to overcome momentum-based forces and cause scavenging coefficients to increase as particle size decreases.6 Theseelectrostatic effects do not apply to gases; hence a different approach is required.

A numerical example illustrates how the treatment of vapors as small particles might lead toerroneous results. Consider benzene, which has a non-dimensional Henry’s Law constant H of0.22. With a typical mixing height of 750 m (the average AM/PM value for Peoria, IL), thescavenging coefficient is:

This example value markedly differs from the values published in the HHRAP (which are basedon the treatment of vapors as small particles). The value of 1.7×10–4 (mm-s/hr)–1 listed in theHHRAP (p. 3-52) is five orders of magnitude greater than the value based on Henry’s Lawequilibrium. Since the Henry’s Law calculations should in general overestimate the scavengingcoefficient (the compound is required to diffuse into precipitation from the air), adoption of thegeneric values listed in the HHRAP would greatly and inappropriately overestimate the wetdeposition of any vapors with appreciable Henry’s Law constants.

To more accurately predict wet vapor deposition, a mass-balance, equilibrium-based scavengingcoefficient has been developed based on Henry’s Law partitioning. The model is not taken froma specific reference, but is rather a statement of mass conservation, as derived from firstprinciples. The model calculates the maximum amount of a vapor that could dissolve into agiven depth of rainfall within a specified period, based on an equilibrium governed by Henry’sLaw. It is assumed that the chemical vapor reaches an equilibrium between vapor and dissolved

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phases in the air column during a precipitation event. The maximum possible scavengingcoefficient for a compound that dissolves into water is derived from this mass balance.

The wet scavenging coefficient model is based on the amount of the chemical that deposits inprecipitation, calculated as:


Cair the average concentration of the vapor in air;S the precipitation scavenging coefficient;Dmix the atmospheric mixing height;R the rate of precipitation; andJ the time during which precipitation occurs.

The Henry’s Law equilibrium condition requires that:

where H is the Henry’s Law constant. Combining the previous two expressions, the scavengingrate can be estimated as:

A very similar model is presented on page 4-9 of EPA’s Mercury Study Report to Congress(U.S. EPA, 1997a). If one considers a pollutant that simply dissolves into water, the chemicalreaction terms drop out of the U.S. EPA (1997a) model, and one obtains a simple relationshipbetween the washout ratio W (which equals the concentration of the chemical in rainwaterdivided by the concentration of the chemical in air) and the non-dimensional Henry’s Lawconstant H:

By definition, the scavenging coefficient S is related to the washout ratio W and the atmosphericmixing height Dmix (Seinfeld, 1986):

7 EPA’s (1997b) study of mercury was motivated by Congress’s mandate in the 1990 CleanAir Act Amendments that required EPA to perform a comprehensive analysis of mercury.

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Combining the above equations, one finds the same relationship proposed for calculating thescavenging coefficient:

Consideration of chemical-specific Henry’s Law constants could conceivably require numerousruns of the ISCST3 model. As an alternative, each chemical was placed into one of threecategories on the basis of their Henry’s Law constants, and each of these categories wereassigned a single set of wet scavenging coefficients (with the exception of mercury species, asdiscussed further on). For high and moderately high H values, equilibrium partitioning, based ona single surrogate value of H was used, with application of the above equation for S. Forchemicals with low Henry’s Law constants, the small particle default values consistent withexamples in the HHRAP guidance was used. Values for scavenging coefficients are listed inTable 3.6; these values were based on expectations regarding the distribution of Henry’s Lawcoefficients, as described in the Risk Assessment Workplan (Cambridge Environmental, 2000). The initial categories were determined to be sufficient for wet deposition modeling, and werethus maintained.

Unfortunately, it is not possible to empirically validate modeled wet vapor scavengingcoefficients because there are little or no relevant measured data available for comparison. TheHHRAP offers essentially no guidance on selecting scavenging coefficients for vapor deposition— example values are listed without discussion or justification. If one examines the U.S. EPA’srecommendations on scavenging coefficients contained in other guidance documents, one findsthat the only empirical basis for their estimates stems from data collected for nitric acid, theproperties of which are relevant to few (if any) of the COPCs likely to be identified for the LSIGreencastle facility.

For example, in the EPA’s Mercury Study Report to Congress (U.S. EPA, 1997a), the“empirical” data for mercury vapor scavenging are in fact based on a scavenging ratio estimatefor nitric acid. Both nitric acid and divalent mercury are thought to behave similarly in water —both are readily soluble, and their rapid dissociation upon entering solution allows a greateramount of each compound to dissolve into water than would be predicted by Henry’s Lawequilibrium alone. The assumed analogy between mercury and nitric acid, however, is set forthon heuristic arguments, and has not been adequately confirmed by experimentation.

Lacking sufficient experimental data, the EPA has also developed models for estimatingscavenging coefficients, again mostly in the context of estimating mercury deposition.7 SinceEPA has considered mercury in detail in the Mercury Study Report to Congress (U.S. EPA,1997a), similar values of wet scavenging coefficients are proposed to be used specifically formercury species. The Mercury Study Report to Congress characterizes wet deposition by thewashout ratio W (described in the previous response to comment # 9). As described above, thescavenging coefficient S is estimated from the washout ratio W by:

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where Dmix is the atmospheric mixing height. Washout ratios of 1,200 and 1,600,000 are used bythe U.S. EPA (1997a) in the Mercury Study Report to Congress. Using the average mixingheight of 750 m for the Peoria, IL mixing height data (twice-daily averaged over a 1984–1991period), the liquid scavenging coefficients for mercury vapor are calculated as:

Note that the value of the liquid scavenging coefficient for divalent mercury vapor is about 3½times larger than the value that is assumed by default for chemicals with low Henry’s Lawcoefficients (this lower value would have been assumed based upon the default informationcontained in the HHRAP). As for other vapors, scavenging coefficients for ice/snow will beassigned to be one-third of the values estimated for liquids.

As discussed by the U.S. EPA (2000b), a comparison can be made between the proposed wetscavenging coefficient (Table 3.6) and detailed estimates of below-cloud nitric acid scavengingcoefficients presented by Seinfeld (1986). According to Seinfeld (1986, p. 199), nitric acid has aHenry’s Law constant of 4.8×10–9 atm-m3/mol, which places it in the “low” category of Table3.6, from which a wet scavenging coefficient of 1.7×10–4 (s-mm/hr)–1 would be assigned to nitricacid. In Table 16.2 of Seinfeld (1986), values of wet scavenging coefficients for twelve differentmodeling scenarios ranged (in equivalent units) from 1.3×10–5 to 1.2×10–4 (s-mm/hr)–1. Thus,the proposed value of 1.7×10–4 (s-mm/hr)–1 that would be used for the wet scavenging coefficientis somewhat higher (i.e., more conservative) than the upper-end value listed for the range ofprecipitation/droplet conditions considered by Seinfeld (1986).

The above comparison for nitric acid suggests that the proposed scavenging coefficient fordivalent mercury vapor may serve to overpredict the wet deposition rate for this species. Nitricacid is infinitely soluble in water, and it readily dissociates when scavenged by rainfall. Theequilibrium Henry’s Law model proposed for estimating scavenging coefficients does not modelnitric acid accurately at equilibrium, since the dissolved-phase dissociation within the waterphase would also need to be considered (as described in equation 16.22 of Seinfeld [1986]). Ifthe water-phase dissociation is accounted for, the equilibrium scavenging coefficient for nitricacid would be many orders of magnitude greater than the values discussed above. Importantly,however, the modeling of nitric acid deposition by Seinfeld (1986) indicates that equilibrium isnot reached within falling raindrops, implying that nitric acid scavenging rates are limited bydynamic considerations. It is in a sense fortuitous that the proposed algorithms reflected inTable 3.6 capture (within an order of magnitude) the dynamic rates of nitric acid scavengingmodeled by Seinfeld (1986). Given that nitric acid is readily scavenged by precipitation, one

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would expect the same dynamic constraints to wet scavenging would also apply to species suchas divalent mercury vapor, i.e., that the range of scavenging ratios presented by Seinfeld (1986)likely reflects upper-end estimates of wet scavenging ratios for all gases. Hence, the proposedscavenging coefficient for divalent mercury vapor, which is about five time greater than thehighest value estimated by Seinfeld (1986, Table 16.2) for nitric acid, may significantlyoverestimate the rate of divalent mercury vapor deposition in precipitation. To maintainconsistency with the Mercury Report to Congress, the value of 5.9 ×10–4 listed in Table 3.6 willbe used in the risk assessment. Additional discussion and sensitivity calculations, however, willlikely be presented in the uncertainty analysis to investigate the importance of wet depositionmodeling assumptions, especially with regard to divalent mercury vapor.

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Table 3.6 Gas scavenging coefficients used in ISCST3 modeling

Range of Hdim, in units ofatm-m3/mol

(non-dimensional Hvalues in parentheses) b

Proposedliquid

scavengingcoefficient (s-

mm/hr)–1

Rationale Proposedscavenging

coefficient forfrozen

precipitation(s-mm/hr)–1

Rationale

Vapors other than mercury

High

Hdim $ 1×10–3

(H $ 4×10–2)

7.4 ×10–9Based on Equation 2.5

with H = 0.05 (non-dimensional)and Dmix = 750 m a

2.5 ×10–9

Values based on theassumption that

snow/sleet isroughly a as

efficient atscavenging relative

to rainfall (HHRAP, p. 3-52)

Moderately High

1×10–7 # Hdim < 1×10–3

(4×10–6 # H < 4×10–2)

1.9 ×10–6Based on Equation 2.5with H = 0.0002 (non-dimensional) and Dmix

= 750 m a

6.2 ×10–7

Low

Hdim < 1×10–7

(H < 4×10–6)

1.7 ×10–4Representative value

for small particlesfrom HHRAP example

(p. 3-51) c

5.6 ×10–5

Values for mercury (Hg) vapors

Elemental Hg 4.4 ×10–7Based on washout

ratio of 1,200 (U.S.EPA, 1997a) and Dmix

= 750 m a

1.5 ×10–7Values based on the

assumption thatsnow/sleet isroughly a as

efficient atscavenging relative

to rainfall (HHRAP, p. 3-52)

Divalent Hg 5.9 ×10–4Based on washoutratio of 1,600,000

(U.S. EPA, 1997a) andDmix = 750 m a

2.0 ×10–4

Notes: a A mixing height of 750 m is the average value (AM/PM) for Peoria, Illinois (the source of upper air

mixing height data) b The dimensional and non-dimensional Henry’s Law constants are related by:

where T is temperature and R is the Universal Gas Constant. Assuming a temperature of 25°C (298°K),the product RT is about 40.9 mol/atm-m3.

c Also corresponds to the value predicted by S =1/(DmixH) with H = 0.0000022 (non-dimensional) and Dmix= 750 m.

8 The GDISCDFT dry vapor deposition algorithms have now been incorporated into theISCST3 model. The GDISCDFT modeling as described was developed prior to the release ofthe updated ISCST3 model. 9 The value assigned to the pollutant reactivity parameter (800) in the U.S. EPA (1997a) studyexceeded all of the values listed in the draft documentation to the GDISCDFT model, includingthat for nitric acid vapor (18 — the highest value listed).

3–21

At the time the HHRAP was developed, the ISCST3 model did not contain algorithms tocalculate dry deposition rates of gases, and consequently dry vapor deposition was insteadincorporated directly in the HHRAP model equations (Appendix B). Little information,however, is provided in the HHRAP concerning the estimation of dry gas deposition velocities. A default dry gas deposition velocity (parameter Vdv) of 3 cm/s is suggested in Appendix B ofthe HHRAP for all chemicals, based on references to experimental values for nitric acid. Thevalue of 3 cm/s is at the upper range of empirical gas deposition values reported for nitric acid(Seinfeld, 1986), and almost certainly overestimates the deposition of less reactive and lesssoluble gases.

The U.S EPA’s algorithms for estimating gas deposition velocities were initially incorporatedinto GDISCDFT, a once draft version of the ISCST3 model.8 This GDISCDFT model wasinvestigated to better estimate chemical-specific deposition velocities for use in risk assessmentcalculations, and also to account for area-specific land use and meteorologic data. A descriptionof the use of GDISCDFT is provided in Appendix B of this risk assessment. The GDISCDFTmodel predicts average deposition velocities significantly lower than the HHRAP’s defaultrecommendation. Based on the GDISCDFT modeling, a value of 0.36 cm/s is proposed as aconservative value for the gas deposition velocity Vdv for chemicals of limited solubility andreactivity, subject to the limitations discussed below for mercuric chloride (and possibly otherreactive and corrosive gases).

The HHRAP’s default deposition velocity of 3 cm/s is perhaps motivated by the U.S. EPA’sconsideration of an appropriate deposition velocity for mercuric chloride vapor, as described inthe Mercury Report to Congress (U.S. EPA, 1997a). Therein, the U.S. EPA makes theassumption that, based on the fact that both chemicals are readily soluble in water, the depositionvelocities of mercuric chloride and nitric acid are similar. To arrive at the deposition velocity of3 cm/s, the U.S. EPA applies the same modeling algorithms contained in the GDISCDFT model(as described above and in Appendix B), but assigns an arbitrarily high value to one of themodeling parameters (the pollutant reactivity parameter).9 The reason for assigning thisarbitrary value is not stated, but by inference appears to be an attempt to eliminate the cuticleresistance term in the model equations. The effect of assuming an arbitrarily-high reactivityparameter was to increase deposition velocity values to the order of 3 cm/s, which the U.S. EPA(1997a) judged to compare more favorably with nitric acid (HNO3) deposition velocitiespredicted by another model (Walcek et al., 1986).

Limited empirical measurements of nitric acid deposition to vegetative surfaces support the useof relatively high deposition velocities (~1–4 cm/s). Based on these measurements, researchershave concluded that the leaf cuticle seems to provide little or no resistance to nitric aciddeposition, whereas the cuticle does inhibit the deposition of gases such as sulfur dioxide andozone, which must enter plants through stomata. Thus, for nitric acid, the arbitrary assignment

3–22

of a high pollutant reactivity by the U.S. EPA (1997a), which forces the deposition velocitymodel to eliminate the cuticle resistance term, is consistent with empirical studies.

Per the request of the U.S. EPA, additional model calculations similar to those described inAppendix B were performed with the GDISCDFT model using an arbitrarily high value (800)for the pollutant reactivity parameter. Similar to the U.S. EPA’s finding, an average depositionvelocity of about 3 cm/s resulted, consistent with both the HHRAP’s default recommendationand empirical measurements of nitric acid’s deposition velocity. It is noted, however, that theGDISCDFT model guidance, in listing values for the pollutant reactivity parameter, provided avalue of 18 for nitric acid. This value, if used in the GDISCDFT with other best-estimateparameter values, yields an average deposition velocity of about 0.4 cm/s, which is generallysmaller than empirically-determined values. Thus, to force the GDISCDFT model to predictdeposition velocities consistent with observed data, the pollutant reactivity used as input to themodel must be set at a much larger value than that suggested in the model’s guidance.

The reason, however, that nitric acid deposition to leaves is unimpeded by the cuticle does notseem to be known. In reviewing the literature, no studies were found that described themechanism whereby nitric acid passes through the cuticle. It is not obvious that high solubilityin water should be related to a chemical’s ability to penetrate the waxy, largely lipid tissue thatcomposes the leaf cuticle. Moreover, sulfur dioxide, which has a relatively high solubility inwater, is known to be resisted by the leaf cuticle. Since mercuric chloride’s solubility in coldwater (6.9 g/100 cc; from CRC, 1978) is lower than sulfur dioxide’s (22.8 g/100 cc; from CRC,1978), the suggestion that mercuric chloride should deposit to leaves in a manner analogous tonitric acid on the basis of commonly high solubilities is not supported by the contradictorytendency of sulfur dioxide.

Thus, some factor other than solubility is likely responsible for nitric acid’s high deposition rateinto leaves, and solubility is perhaps not a reliable indicator of mercuric chloride’s ability tobypass the cuticular resistance and readily deposit to leaves (as does nitric acid). One arguablysimilar property shared by nitric acid and mercuric chloride is reactivity — both chemicals burnhuman skin when contacted. Since human skin serves some of the same functions as a leaf’scuticle, it is plausible that both would react with lipids present in the skin/cuticle. Reactivitymay in fact be the reason that nitric acid deposition is not resisted by the cuticle. Since mercuricchloride is highly corrosive, it might plausibly behave in a similar manner.

Thus, two different vapor deposition velocities were used in the risk assessment:

• For chemicals that are known to be reactive or corrosive (mercuric chloride, strong acidsand bases, etc.), the default HHRAP vapor deposition velocity of 3 cm/s was used; and

• For chemicals not known to be reactive, corrosive, or strongly polar (based on a tendencyto strongly dissociate into ions in water), a vapor deposition velocity of 0.36 cm/s wasused (based upon the modeling described in Appendix B).

Further discussion and investigation of the importance of assumptions regarding gaseousdeposition velocities is provided in the uncertainty section of the risk assessment.

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3.6 ISCST3 modeling run setup

Three different sources and various types of COPCs required the ISCST3 model to be run for anumber of different scenarios to differentiate the stack and fugitive sources, particle-boundCOPCs and vapors, and varying rates of scavenging. Separate ISCST3 runs were conducted for:

• mass-weighted particle-bound chemicals (stack);• surface-weighted particle-bound chemicals (stack);• vapors with high Henry’s Law constants (stack, fuel storage/blending, and platform

sampling);• vapors with moderately high Henry’s Law constants (stack, fuel storage/blending, and

platform sampling);• vapors with low Henry’s Law constants (stack, fuel storage/blending, and platform

sampling);• mercury vapors, both elemental and divalent species (stack).

These thirteen scenarios are described in Table 3.7, which provides two-letter “Id” designationsthat are used to differentiate filenames. Each scenario was also assigned a nominal emission rateso that model predictions could be scaled easily to COPC-specific emission rates. Thesenominal emission rates are also listed in Table 3.7. Total nominal emission rates were set tofactors of 10 g/s. It was necessary to assign large values in some cases (e.g., cases with lowvapor scavenging rates) so that the ISCST3 model provided output with sufficient numbers ofsignificant figures.

In addition, fifteen different ISCST3 model runs were required for each scenario to account forfive different modeling years and three different modeling grids. Thus, a total of 195 (13×15)individual ISCST3 modeling runs were performed.

A copy of all of the 195 ISCST3 input files is provided in electronic Appendix A. A uniformconvention was used to name the ISCST3 input files according to the format:

Idyyg.inp

where Id represents the two-letter scenario Id (ME, SE, VL, VM, VH, MM, MH, TL, TM,TH, FL, FM, or FH);

yy indicates the model year of the meteorologic data (19yy, where yy is 86, 87, 88,89, or 90); and

g species the modeling grid (i for inner, o for outer, and w for the Cagles Millwatershed).

3–24

Table 3.7 Description of ISCST3 modeling runs

Pollutant type/category Id Nominal emission rate Modeled parameters

Stack particles — mass-weighted

ME 1 g/s Air concentration, dry and wetdeposition

Stack particles — surface-weighted

SE 1 g/s Air concentration, dry and wetdeposition

Stack vapors — low scavenging rate

VL 1,000,000 g/s Air concentration andwet deposition

Stack vapors — moderate scavenging rate

VL 100,000 g/s Air concentration andwet deposition

Stack vapors — high scavenging rate

VL 100 g/s Air concentration andwet deposition

Stack vapors — elemental mercury (Hg0)

MM 100,000 g/s Air concentration andwet deposition

Stack vapors — oxidized mercury (Hg2+)

MH 100 g/s Air concentration andwet deposition

Fuel storage/blending vapors —low scavenging rate

TL 17.77 g/s-m2

(10,000 g/s over entire area)Air concentration andwet deposition

Fuel storage/blending vapors —moderate scavenging rate

TM 0.1777 g/s-m2

(100 g/s over entire area)Air concentration andwet deposition

Fuel storage/blending vapors —high scavenging rate

TH 0.0001777 g/s-m2


Sampling platform vapors —low scavenging rate

FL 5,059.5 g/s-m2

(1,000 g/s over entire area)Air concentration andwet deposition

Sampling platform vapors —moderate scavenging rate

FM 505.95 g/s-m2


Sampling platform vapors —high scavenging rate

FH 5.0595 g/s-m2


3–25

3.7 ISCST3 modeling results

Each of the 195 ISCST3 model runs produced an output file that was named with the sameconvention as its input file (see the preceding section), with the model output file extension of“.out” replacing the “.inp extension of the input file. The 195 different output files are includedas part of electronic Appendix A.

A utility program was written to process the large number of the ISCST3 modeling runs. Theutility program was developed in the Pascal programming language within the Windows-basedDelphi software environment, and runs as an MS-DOS based application. The source code(“readall.dpr”) and executable version (“readall.exe”) of the utility program are included as partof electronic Appendix A.

For a given scenario, the “readall” utility was designed to extract model predictions from thefifteen output files to provide an integrated compilation of individual modeling estimates at eachreceptor location. For each receptor location, five-year annual average values were constructedfor the predictions of the ground-level concentration in air, annual dry deposition (for particle-bound COPCs only), and annual wet deposition. Additionally, the highest prediction of theground-level COPC concentration in air was determined over the five-year modeling period. The thirteen summary data files (one for each emission scenario) produced by the “readall”program are included in the electronic Appendix A. They are named xxISC.SUM, where xx isthe two-letter abbreviation assigned to individual emission scenarios (as indicated in Tables 3.7and 3.8).

The “readall” utility was also designed to renormalize the ISCST3 model predictions for eachscenario so that they correspond to a uniform 1 g/s emission rate. Table 3.8 summarizes thehighest values of ISCST3 model predictions for the thirteen different scenarios, and Figure 3.5illustrates the locations of the highest predicted values relative to the LSI/Greencastle facilityand the three emission sources. Taken together, Figure 3.5 and Table 3.8 illustrate that thelocations of projected worst-case impacts are located either on or close to the facility boundaryin one of two clusters: one to the northeast and one to the west of the source locations. Examining Figure 3.5, the highest values of predicted wet deposition rates uniformly occur atlocations on the facility property line. The highest projected values of airborne concentrationsand dry deposition for stack emissions occur a few hundred meters downwind of the propertyline (to the northeast of the sources), while the highest projected values of airborneconcentrations from the fugitive vapor sources are predicted along the facility property line tothe west of the sources.

Table 3.8 indicates that the magnitudes of the worst-case projected airborne concentrations donot differ greatly among various forms of COPCs emitted from the same source, although somevariability is introduced by differing rates of deposition. Of the stack emission scenarios, thecase of mass-weighted particles has the highest rate of dry deposition, which (because ofremoval) leads to the lowest average annual and 1-hour concentrations in air. Pollutantdeposition has less effect on the predicted concentrations of vapors in air. The projectedairborne concentrations for the sampling platform and fuel storage/blending sources are

3–26

markedly higher than those for the stack because the emissions originate either at or nearground-level.

The similarity in the magnitude of the projected impacts among scenarios from each sourcereflects a similar geographic pattern of impacts. A representative series of color-coded plots isprovided to illustrate typical patterns in the model predictions. The color-coded plots weregenerated by the MATLAB software program, as interpolated from the predictions of theISCST3 model. Figures 3.6–3.10 present a complete set of model predictions for a singleemission scenario — mass-weighted particles released from the cement kiln stack — for theinner modeling grid. The prediction of the highest maximum 1-hour average concentration(Figure 3.6) occurs in a similar location to that of the highest annual average concentration(Figure 3.7), although the plateau of elevated values for the annual-average case extends fartherto the northwest than it does for the maximum 1-hour average values. The patterns of wet andtotal deposition (Figures 3.9 and 3.8) are similar to each other, and differ from the predictions ofannual-average concentrations (Figure 3.7) in that the peak values occur directly on the propertyline to the northwest of the stack. This similarity occurs because wet deposition dominates totaldeposition close to the source, as indicated by the plot of dry deposition (Figure 3.10), whichshows a distinct peak downwind of the property boundary similar to that of the annual-averageconcentration pattern (Figure 3.7). Uniquely, the pattern of dry deposition predictions shows aregion of elevated predictions further to the north that is absent from Figure 3.7.

Figure 3.11 depicts the pattern of annual-average concentration estimates over the combinedinner and outer receptor grids, and thus is an extension of the pattern depicted in Figure 3.7. Theouter grid predictions (Figure 3.11) show elevated ground-level concentrations extending morethan ten kilometers toward the northeast (the predominant downwind direction from theLSI/Greencastle facility), although the peak values are most pronounced near the facilityboundary. The extended region of elevated impacts projected to the northeast of the facility isalso likely tied to several hills near the facility and the topographic ridge that separates thewatersheds of Deer and Walnut Creeks.

Figures 3.12 and 3.13 depict predictions of ground-level, annual-average concentrations in airover the Cagles Mill watershed. In these plots, the LSI/Greencastle facility is indicated in blacksilhouette. Also, the color-coded scales on these figures differ from those of other annual-average concentrations (e.g., Figure 3.7), and thus the peak values/colors on Figures 3.12 and3.13 correspond to lower overall concentration levels. Comparison of the color-coded scales ofFigures 3.12 and 3.13 illustrates the overall effect of COPC deposition. Because COPC removalis higher in the case of the mass-weighted particle (ME) scenario than for the vapor low-scavenging (VL) scenario, more of the COPC is removed by the time is reaches the Cagle Millwatershed, and hence the peak values of the ME scenario scale (Figure 3.12) are about tenpercent lower than those of the VL scenario scale Figure (3.13).

Finally, Figures 3.14 and 3.15 depict the patterns of annual-average ground-level concentrationsfor the fugitive vapor emission scenarios from the sampling platform (low-scavenging FLscenario) and the storage/blending area (high-scavenging TH scenario), respectively. Bothscenarios reflect similar patterns, exhibiting maximum values to the west of the emission sourcesdirectly on the facility property line. The patterns of the two figures look similar despite the

3–27

difference in vapor scavenging, which is not significant enough to affect the patterns of near-source predictions. The fact that maximum predictions occur on the facility boundary is atypical consequence of releases that occur from or near ground-level.

3–28

Table 3.8 Worst-case ISCST3 modeling predictions

Scenario IdAnnualaverage

concentrationin air

(:g/m3 per g/s)

Annual average deposition rate(g/m2-yr per g/s)

Highest 1-hour concentration

in air(:g/m3 per g/s)Wet Dry Total

Stack particles — mass-weighted

SE 0.0142 0.0164 0.00157 0.0168 1.72

Stack particles — surface-weighted

ME 0.0130 0.0341 0.00854 0.0365 1.53

Stack vapors — low scavenging rate

MH 0.0144 0.0601 NM NM 1.79

Stack vapors — moderate scavenging rate

MM 0.0144 0.0000944 NM NM 1.79

Stack vapors — high scavenging rate

TH 3.55 0.0359 NM NM 792

Stack vapors — elemental mercury (Hg0)

TM 3.55 0.000571 NM NM 792

Stack vapors — oxidized mercury (Hg2+)

TL 3.55 0.00000228 NM NM 792

Fuel storage/blending vapors —low scavenging rate

FH 4.49 0.0543 NM NM 1080

Fuel storage/blending vapors —moderate scavenging rate

FM 4.50 0.000762 NM NM 1080

Fuel storage/blending vapors —high scavenging rate

FL 4.50 0.00000298 NM NM 1080

Sampling platform vapors —low scavenging rate

VL 0.0144 0.00000159 NM NM 1.79

Sampling platform vapors —moderate scavenging rate

VH 0.0144 0.0250 NM NM 1.79

Sampling platform vapors —high scavenging rate

VM 0.0144 0.000405 NM NM 1.79

NM = Not modeled with ISCST3

3–29

1: TL, TM, TH, FL, FM, FH

1: SE, ME, MH, MM, VL, VM, VH

A: TL, TM, TH, VL, VM, VH

A: SE, ME, MH, MM, VL, VM, VH

W: TH

W: FL, FM, FH

W: SE, ME, MM, VL, VM, VHW: TL, TMW: MH

D: SE, ME

4382500

4383000

4383500

4384000

4384500

4385000

4385500

4386000

4386500

4387000

509500 510000 510500 511000 511500 512000 512500 513000

Property Boundary1: 1-Hour AirA: Annual AirW: Annual Wet DepositionD: Annual Dry DepositionPlatform SourceTank Farm SourceKiln Stack Source

Figure 3.5 Locations of worst-case (highest) predicted concentrations in air and deposition rates

3–30

Figure 3.6 Predicted maximum 1-hour concentrations in air (:g/m3 per g/s) for the mass-weighted particle (ME) scenario for stackemissions for the inner modeling grid. The highest predicted concentration is projected to the northeast of the stack.

3–31

Figure 3.7 Predicted annual average concentrations in air (:g/m3 per g/s) for the mass-weighted particle (ME) scenario for stackemissions for the inner modeling grid. The highest predicted concentration is projected to the northeast of the stack.

3–32

Figure 3.8 Predicted total deposition rate (g/m2 per g/s) for the mass-weighted particle (ME) scenario for stack emissions for theinner modeling grid. The highest predicted deposition is projected to the northeast of the stack on the property line.

3–33

Figure 3.9 Predicted wet deposition rate (g/m2 per g/s) for the mass-weighted particle (ME) scenario for stack emissions for theinner modeling grid. The highest predicted deposition is projected to the northeast of the stack on the property line.

3–34

Figure 3.10 Predicted dry deposition rate (g/m2 per g/s) for the mass-weighted particle (ME) scenario for stack emissions for theinner modeling grid. The highest predicted deposition is projected to the northeast of the stack.

3–35

Figure 3.11 Predicted annual average concentrations in air (:g/m3 per g/s) for the mass-weighted particle (ME) scenario for stackemissions for the inner and outer modeling grids. The highest predicted concentration is projected to the northeast ofthe stack.

3–36

Figure 3.12 Predicted annual average concentrations in air (:g/m3 per g/s) for the mass-weighted particle (ME) scenario for stackemissions for the Cagles Mill watershed modeling grid. Note that the colot-coded scale differs from previous figures.

3–37

Figure 3.13 Predicted annual average concentrations in air (:g/m3 per g/s) for the vapor low-scavenging(VL) scenario for stackemissions for the Cagles Mill watershed modeling grid. Note that the similarity to Figure 3.12, constructed for adifferent stack emission scenario.

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Figure 3.14 Predicted annual average concentrations in air (:g/m3 per g/s) for the vapor emission low-scavenging (FL) scenario forthe sampling platform area for the inner modeling grid. The highest predicted concentration is projected to the west ofthe source area.

3–39

Figure 3.15 Predicted annual average concentrations in air (:g/m3 per g/s) for the vapor emission high-scavenging (TH) scenariofor the storage/blending area for the inner modeling grid. The highest predicted concentration is projected to the westof the source area. Note the similarity to Figure 3.14.

4–1

4 Exposure scenario selectionA multi-pathway exposure assessment extends the evaluation of the direct inhalation of contaminants,which is derived from the air dispersion and deposition analysis, to consider a variety of indirectpathways that include the deposition of contaminants to soil, water, and vegetation, and theirsubsequent transfer and accumulation in the food-chain. The predicted exposure to contaminantsresulting from a facility’s emissions depends not only upon the levels of those emissions, but alsoupon the characteristics of the local lands and its uses by the local population. As recommended in theHHRAP, the following scenarios have been considered for the evaluation of the population’s potentialexposure to COPCs emitted from the LSI/Greencastle facility:

• Residents (adults and children); and• Subsistence farmers (adults and children);• Subsistence fishers (adults and children);

Children are distinguished from adults because their rates of exposure to compounds (as expressed perunit body weight) are frequently higher, and they may be subject to different types of health risks (e.g.,developmental effects).

Consideration of land use in the vicinity of Lone Star’s Greencastle facility suggests locations forevaluation of each receptor. Both resident and subsistence farmer receptors have been evaluated at thelocations of highest projected facility impacts to lands outside of the facility property. Residencesborder the facility property, and much of the land in the vicinity of the facility either is or could beused for farming. Subsistence farming is not known to be practiced in the vicinity, but future land usecannot be predicted with certainty, and hence the HHRAP recommends consideration of ahypothetical subsistence farmer who could live near the facility in the future.

In order to evaluate each exposure pathway, specific exposure locations must be selected. For theexposure estimations of residents and subsistence farmers, the most conservative approach is toconsider the location with the highest possible exposure levels. The selection of such a location iscomplicated by the fact that there are differences in the locations of maximum predicted exposures dueto emissions from the various sources at the facility and the various atmospheric exposure pathways. For each source type, the locations of projected maxima differ for ground-level concentrations in air,and for dry and wet deposition. For the ground-level sources, the highest projected impacts arepredicted at the facility property line; for stack emissions, the maximum projected impacts arepredicted to occur at some distance beyond the property line at which the elevated plume touchesdown (on average). These differences in the spatial patterns of the projected impacts are shown inFigure 3.3. Although there are differences, there are also similarities among the locations. Many ofthe predicted maxima occur to the northeast of the LSI/Greencaslte facility. Even in the cases wheremaxima are predicted to the west, the spatial patterns of the predictions indicate values of similar)albeit lower) magnitude to the northeast. This, for the sake of simplicity and to overcome thiscomplication in a conservative way, the exposure evaluations for residents and subsistence farmers

11 Fishing in the ponds on the facility property is limited to Lone Star employees and istherefore not subsistent in character.

4–2

have been performed at the maximum projected concentrations among all of the air and depositionlevels, as if all of the maxima occurred at the same location.

In contrast to residents and farmers, the subsistence fishing scenario is constrained to locations wherefish can be obtained (lakes, ponds, rivers, streams, etc.). There are a number of locations in thevicinity of the facility where fishing is known to occur, including ponds on the facility property.11 Further, the demands of the subsistence fishing scenario require a water body of sufficient size toserve as a reliable food supply over a lengthy period. Based on a review of maps, fishing informationavailable from the Indiana Department of Natural Resources, an area tour, and conversations withlocal fishers, Cagles Mill Lake is judged to be the fishing resource closest to the facility that couldserve as a viable location for a subsistence fisher.

Cagles Mill Lake is located about 16 km to the south of Lone Star’s Greencastle facility, and wascreated in 1952 for flood control of the Eel and White Rivers by the US Army Corps of Engineerswhich maintains and monitors the lake for this purpose from their Louisville District Office. TheIndiana Department of Natural Resources actively manages the recreational facilities and activities atthe lake, which include fishing. The lake has a drainage area of 756 km2, an average surface area of5.67 km2, and an average depth of 6.1 m (IDEM, 1998). The lake and its drainage area are shown inFigure 3.3.

Although Cagles Mill Lake is not a source of drinking water, the concentrations of COPCs in thewater of Cagles Mill Lake have also been included in the evaluation of potential health impacts due tothe consumption of drinking water from surface sources. Most drinking water in the area in derivedfrom groundwater. The nearest known surface water drinking water intakes are those located on theDeer Creek and used for the Putmanville Correctional Facility (IDEM, 2001a). Although theseintakes are not located in the Cagles Mill Lake watershed, the additional effort involved in furtherwatershed modeling was deemed to be unnecessary. The difference between estimating health risksfor surface water COPC concentrations at the Cagles Mill Lake rather than at the Deer Creek will beaddressed in the uncertainty evaluations in Chapter 8.

In addition to assessment of the effects of chronic direct and indirect exposures to COPCs emittedfrom the LSI facility, an acute risk scenario is considered to evaluate the potential for facilityemissions to adversely affect nearby residents over short time periods via the direct inhalation ofCOPCs. The potential for such acute health effects is evaluated using the maximum 1-hour averageCOPC concentrations from the air dispersion modeling per HHRAP guidance.

For each of the exposure scenarios described above, Table 4.1 (adapted from the HHRAP) delineatesthe exposure pathways which have been examined. The total COPC exposure of local residents thatmay keep limited livestock for personal consumption (e.g., chickens, goats, etc.) may be evaluated in aconservative manner through the examination of the exposures to subsistence farmers (and hence isnot considered separately). The difference between subsistence and less intensive farming practiceswill be treated qualitatively in the uncertainty section of this report.

Table 4.1 Exposure routes that will be considered in the risk characterization (adapted from theHHRAP, Table 4-1).

4–3

Exposure Pathways

Exposure Scenarios

Subs

iste

nce

Farm

er

Subs

iste

nce

Farm

er C

hild

Adu

lt R

esid

ent

Chi

ld R

esid

ent

Subs

iste

nce

Fish

er

Subs

iste

nce

Fish

er C

hild

Acu

te R

isk

Inhalation of vapors and particles • • • • • • •Incidental ingestion of soil • • • • • •Ingestion of drinking water from surface water sources • • • • • •Ingestion of homegrown produce • • • • • •Ingestion of homegrown beef • •Ingestion of milk from homegrown cows • •Ingestion of homegrown chicken • •Ingestion of eggs from homegrown eggs • •Ingestion of homegrown pork • •Ingestion of fish • •Ingestion of breast milk by infant • • •

5–1

5 Estimation of media concentrationsIn order to evaluate the impact of kiln stack and RCRA fugitive emissions from the LSI/Greencastlefacility, the concentrations of each COPC needs to be estimated in a variety of media, specifically:air, soil, natural vegetation, fruit and vegetable crops, livestock and related farm products, surface anddrinking water supplies, and fish. A wide range of fate and transport parameters are needed to conductsuch a multi-pathway assessment, including compound-specific properties of COPCs, which werediscussed in Chapter 2, and site-specific land-use characteristics, which will be described in therelevant sections below. Table 5.1 contains the required general default parameters from the HHRAPguidance for time durations, and air, water and soil properties, as well as site-specific parameters forthe Cagles Mill Lake watershed. For each medium addressed in the calculations, detailed algorithmsand equations are applied, as described in the HHRAP’s Chapter 5 and its Appendix B. The HHRAPalgorithms are primarily based on previous guidance set forth by the U.S. EPA and other regulatoryagencies. The HHRAP algorithms and default assumptions are used except where site-specificconsiderations suggest the use of different models and assumptions. Deviations form the HHRAPguidance and its default parameters are noted in the descriptions of the calculations and the impacts ofthese deviations are addressed in the uncertainty evaluations in Chapter 8.

The concentration estimates for a given medium are frequently passed on to another mediumfollowing the natural progression for the transport of compounds in the environment (e.g. soilconcentrations progress to vegetation concentrations which progress to livestock concentrations). Eventually these concentrations are incorporated into human exposure estimates which then lead toestimates of possible health impacts. Air concentrations and depositions rates for each COPC havebeen described in Chapter 3, and have been used to calculate concentrations in other environmentalmedia in the following order: soil, produce, animal tissue, water, fish. Only the equations andparameters used to calculate COPC concentrations are given in the text below. The COPC-specificproperties required for the calculations are given in full in Appendix III, and the calculated COPCconcentrations for each medium are given in Appendix V.

5–2

Table 5.1 General and site-specific parameters and properties required for the calculation of COPCconcentrations in various environmental media.

Parameter name Symbol Value Units ReferenceTime duration parametersTime period at beginning ofcombustion T1 0 yrs HHRAP Table B-1-1

Length of exposure, child T2 6 yrs HHRAP Table B-1-1Length of exposure, adultperiod for resident andsubsistence fisher

T2 24 yrs HHRAP Table B-1-1

Length of exposure,subsistence farmer T2 40 yrs HHRAP Table B-1-1

Time period of combustion tD 100 yrs HHRAP Table B-1-1Standard air and waterparametersTemperature ambient Ta 298.1 °K HHRAP Eqn. 5-6ADry deposition velocity Vdv 3 cm/s HHRAP Table B-1-1Air density Da 1200 g/m3 HHRAP Table B-2-8Water density Dw 1 g/cm3 HHRAP Eqn. 5-41Bvon Karman's constant k 0.4 unitless HHRAP Table B-4-20Viscous sublayer thickness 8z 4 unitless HHRAP Table B-4-20Viscosity of water :w 0.0169 g/cm-s HHRAP Table B-4-20Viscosity of air :a 1.81 E-4 g/cm-s HHRAP Table B-4-21Drag coefficient Cd 0.0011 unitless HHRAP Eqn. 5-41B

Ideal gas constant R 8.21 E-5 atm-m3/mol-Kat 20°C HHRAP Eqn. 5-40

Temperature correctionfactor 2 1.026 unitless HHRAP Eqn. 5-40

Soil related parametersPrecipitation, annual average P 107 cm/yr USGS, 1999Irrigation, annual average I 0.1 cm/yr USGS, 1999Evapotranspiration, annualaverage Ev 66 cm/yr USGS, 1999

Surface runoff, annualaverage RO 36 cm/yr USGS, 1999

Soil mixing zone depth,untilled Zs 1 cm HHRAP Table B-1-1

Soil mixing zone depth,tilled Zs 20 cm HHRAP Table B-1-1

Soil bulk density BD 1.5 g/cm3 HHRAP Table B-1-1Soil solids particle density Ds 2.7 g/cm3 HHRAP Errata, page 18Soil volumetric watercontent 2sw 0.2 unitless HHRAP Table B-1-3,

and USDA (1981)Soil volumetric watercontent 2v 0.24 unitless HHRAP Errata, page 18

Soil bioavailability Bs 1 unitless HHRAP Table B-3-10Soil pH pH 6.2 unitless USDA, 1982

5–3

Table 5.1 (continued) General and site-specific parameters and properties required for the calculationof COPC concentrations in various environmental media.

Parameter name Symbol Value Units ReferenceRainfall factor RF 200 yr–1 Wischmeire, 1978Erodability factor K 0.39 ton/acre HHRAP Table B-4-13Length slope factor LS 1.5 unitless HHRAP Table B-4-13Cover management factor C 0.1 unitless HHRAP Table B-4-13Supporting practice factor PF 1 unitless HHRAP Table B-4-13Sediment delivery ratiocoefficient a 1.06 unitless interpolated from values

in HHRAP Table B-4-14Sediment delivery ratioexponent b 0.125 unitless HHRAP Table B-4-14

Sediment delivery ratio SD 0.0824 unitless HHRAP Table B-4-14Unit soil loss Xe 2.62 kg/m2-yr HHRAP Table B-4-13Watershed parametersWater temperature Twk 293 °K HHRAP Eqn. 5-30Water body surface area Aw 5.67 E+6 m2 IDEM, 1998Total watershed area A(L) 7.56 E+8 m2 IDEM, 1998Percent imperviouswatershed area 0.86% IDEM, 2001b

Impervious watershed area A(I) 6.50 E+6 m2 product of above 2 rows

Wind speed, average annual W 4.177 m/saveraged from 1986 -1990 hourly data inISCS3 air modeling

Volume flow through waterbody Vfx 3.32 E+8 m3/yr USGS, 2001

Suspended solids, total TSS 21.5 mg/L USACE, 2001Deposition rate, suspendedsolids Dss 1825 m/yr HHRAP Eqn.5-36C

Depth, total water body dz 6.13 m IDEM, 1998Water column depth dwc 6.1 m IDEM, 1998Benthic sediment depth dbs 0.03 m HHRAP Table B-4-15Porosity, bed sediment 2bs 0.6 unitless HHRAP Table B-4-16Concentration, bed sediment Cbs 1 g/cm3 HHRAP Table B-4-16Fish lipid content flipid 0.07 unitless HHRAP Table B-4-28Organic content of bottomsediment OCsed 0.04 unitless HHRAP Table B-4-28

5–4

( )( ) ( )

CsD

ks tD TtD

ks tDks

Tks T

kss=

⋅ −⋅ +

− ⋅⎛⎝⎜

⎞⎠⎟− +

− ⋅⎛

⎝⎜⎜

⎞

⎠⎟⎟

⎡

⎣⎢⎢

⎤

⎦⎥⎥1

11exp exp

( )[ ]Cs

D ks tDkstD

s=⋅ − − ⋅1 exp

5.1 COPC concentrations in soil

The incremental concentrations of COPCs in soils due to emissions from the LSI Greencastle facilityare dependent on the COPC’s air-to-soil deposition rate, the rate at which the COPC is lost from ordegraded in the soil, and the length of time over which these processes have occurred. Two equationsare required to calculate the concentrations based on whether they are to be estimated at given momentin time, or averaged over a period of time. The former calculation is applied to COPCs beingevaluated for noncancer health risks, which are not assumed to be dependent on cumulative exposures;the latter calculation is applied to COPCs being evaluated for cancer risks, which are based on lifetimeaverage COPC exposures. Some COPCs are evaluated for cancer and noncancer risks, therefore bothcalculations have been performed for all COPCs. Because the deposition of COPCs to the soil isassumed to be constant over the operating lifetime of the LSI/Greencastle facility and the loss ofCOPCs from the soil is proportional to their concentrations, the equations predict COPC levels in soilto increase over time asymptotically approaching a steady state value at which the deposition and lossterms would be equal. Therefore, in order to estimate the highest levels of COPCs in soil to which anindividual might be directly or indirectly exposed, COPC concentrations are calculated for noncancerrisks at the end of the facility’s predicted lifetime, and for cancer risks are averaged over anindividual’s assumed exposure duration up to the end of the facility’s predicted lifetime.

The equation used to calculate soil concentrations of COPCs evaluated for cancer risks is:

and the equation used to calculate soil concentrations of COPCs evaluated for noncancer risks is:


Cs Average soil concentration over exposure duration (mg COPC/kg soil);Ds Deposition term (mg COPC/kg soil/yr);T1 Time period at the beginning of combustion (yr);ks COPC soil loss constant due to all processes (yr–1);tD Time period over which deposition occurs (time period of combustion) (yr); CstD Soil concentration at time tD (mg/kg).

Default values for T1=0, and tD=100 years are taken from HHRAP Appendix Table B-1-1; the valuesfor Ds, and ks are calculated below.

5–5

( ) ( ) ( )[ ]DsQ

Z BDF Vdv Cyv Dywv Dydp Dywp F

sv v=

⋅⋅

⎡

⎣⎢

⎤

⎦⎥ ⋅ ⋅ ⋅ ⋅ + + + ⋅ −

1000 31536 1.

ks ksg kse ksr ksl ksv= + + + +

The deposition term, Ds, is calculated from the COPC atmospheric concentrations and deposition ratesdetermined by the ISCST3 modeling described in Chapter 3. The ISCST3 values for unitized wet anddry deposition of particles and vapors are combined with the COPC emission rates (described inChapter 2) and converted into a soil concentration deposition term Ds by including the soil mixingdepth and density in the denominator:


Ds Deposition term (mg COPC/kg soil-yr);100 Units conversion factor (mg-m2/kg-cm2);Q COPC emission rate (g/s);Zs Soil mixing zone depth (cm);BD Soil bulk density (g soil/cm3 soil);Fv Fraction of COPC air concentration in vapor-phase (yr–1);0.31536 Units conversion factor (m-g-s/cm-:g-yr);Vdv Dry deposition velocity (cm/s);Cyv Unitized yearly average air concentration in the vapor-phase (:g-s/g-m3);Dywv Unitized yearly average wet deposition from vapor-phase (s/m2-yr);Dydp Unitized yearly average dry deposition from particle-phase (s/m2-yr);Dywp Unitized yearly average wet deposition from particle-phase (s/m2-yr).

The calculation of COPC emission rates, Q, were described in Chapter 2. Based on HHRAPAppendix Table B-1-1, two soil mixing zone depths have been modeled to account for differenttransport and exposure scenarios: 20 cm for tilled soils, and 1 cm for untilled soils. The soil bulkdensity, BD, is 1.5 g/cm3, and the vapor-phase deposition velocity, Vdv, is 3 cm/s. The fraction ofeach COPC concentration in air in the vapor-phase, Fv, is a COPC-specific parameter.

The loss rate for COPCs from soils is the sum of several terms:


ks COPC soil loss constant due to all processes (yr–1);ksg COPC loss constant due to biotic and abiotic degradation (yr–1);kse COPC loss constant due to soil erosion (yr–1);ksr COPC loss constant due to surface runoff (yr–1);ksl COPC loss constant due to leaching (yr–1);ksv COPC loss constant due to volatilization (yr–1).

Based on HHRAP Appendix Table B-1-2, kse is taken as zero for all COPC’s at the point ofmaximum emissions impact, but is included in the soil concentration calculations within the watershedas discussed below in Section 5-4; ksg values are COPC-specific and are based on HHRAP AppendixTables A-3 and Howard et al. (1991). The other loss terms are calculated as follows:

5–6

ksv Ke Kt= ⋅

KeH

Z K R T BDs ds a=

× ⋅⋅ ⋅ ⋅ ⋅

31536 107.

( )[ ]kslP I RO E

Z BD Kdv

sw s s sw

=+ − −

⋅ + ⋅θ θ1 /

( )ksrRO

Z Kd BDsw s s sw

=⋅

⋅+ ⋅

⎛

⎝⎜⎜

⎞

⎠⎟⎟θ θ

11 /

Losses of COPCs due to surface runoff and leaching are dependent on the COPC’s soil-waterpartitioning coefficient and the amount of water available for these processes:


ksr COPC loss constant due to surface runoff (yr–1);ksl COPC loss constant due to leaching (yr–1);RO Average annual surface runoff from pervious areas (cm/yr);P Average annual precipitation (cm/yr) ;I Average annual irrigation (cm/yr);Ev Average annual evapotranspiration (cm/yr);2sw Soil volumetric water content (mL water/cm3 soil);Zs Soil mixing zone depth (cm);Kds Soil-water partition coefficient (mL water/g soil);BD Soil bulk density (g soil/cm3 soil).

Based on HHRAP Appendix Tables B-1-4 and B-1-5, and data from the USGS (1999), site-specificvalues used are RO = 36 cm/yr, P = 107 cm/yr, I = 0.1 cm/yr, and E = 66 cm/yr; default values usedfor BD = 1.50 g/cm3 and 2sw = 0.2 mL/cm3, and COPC-specific values are used for Kds.

The calculation of the COPC loss constant due to volatilization, ksv, is described in the HHRAP Erratameomorandum (U.S. EPA, 1999, pages 17-19) as the product of the gas equilibrium coefficient, Ke,and the gas-phase mass transfer coefficient, Kt:

The equilibrium coefficient, Ke, is given by:

5–7

KDZ

BDt

a

s ssw= −

⎛⎝⎜

⎞⎠⎟ −

⎛

⎝⎜

⎞

⎠⎟1

ρθ


Ke COPC gas equilibrium coefficient (s/yr-cm);3.1536×107 Units conversion (s/yr);H Henry’s Law constant (atm-m3/mol);Zs Soil mixing zone depth (cm);Kds Soil-water partition coefficient (mL/kg);R Ideal gas constant (atm-m3/mol-K);Ta Average ambient air temperature (K);BD Soil bulk density (g soil/cm3 soil).

The gas-phase mass transfer coefficient, Kt, is given by:


Kt Gas-phase mass transfer coefficient (cm/s);Da Diffusion coefficient of COPC in air (cm2/s);Zs Soil mixing zone depth (cm);BD Soil bulk density (g soil/cm3 soil);Ds Density of soil solids (g/cm3);2sw Volumetric soil water content (unitless).

Based on HHRAP Appendix Table B-1-3 and the Errata memorandum (U.S. EPA, 1999), defaultvalues are used Zs = 1 cm (untilled) or 20 cm (tilled), Ta = 298 °K, BD = 1.50 g/cm3, 2sw = 0.2 mL/cm3,and Ds = 2.7 g/cm3. The ideal gas constant, R, is 8.205 ×10–5 atm-m3/mol-K. COPC-specific values areused for H, Kds and Da.

5.2 COPC concentrations in produce, grain, and vegetation

Natural vegetation and agricultural produce are assumed to receive COPCs through three mechanisms:direct deposition of particulate COPCs, direct air-to-plant transfer of vapor-phase COPCs, and uptakeof COPCs in soils through the plant’s root system. The wide range of vegetation and produce forwhich COPC concentrations need to be estimated is divided within the HHRAP guidance into thefollowing categories: aboveground, belowground, and protected produce; forage; silage; and grain. For types of plants with edible portions below ground or otherwise protected from direct atmosphericdeposition and transfer, only COPC uptake through the plant’s root system is modeled. The equationsand parameters needed to calculate COPC concentrations by all three mechanisms have beenevaluated in the HHRAP for each plant type, and are described below.

5–8

( ) ( )[ ] ( )[ ]Pd

Q F Dydp Fw Dywp Rp kp TpYp kpi

v i i

i=

⋅ ⋅ − ⋅ + ⋅ ⋅ ⋅ − − ⋅

⋅

1 000 1 1, exp

The concentration of COPCs in the exposed and edible portions of vegetation due to directatmospheric deposition of particles is calculated by:


Pdi Plant (aboveground produce) concentration due to direct (wet and dry) deposition(mg COPC/kg DW);

1,000 Units conversion factor (mg/g);Q COPC emission rate (g/s);Fv Fraction of COPC air concentration in vapor-phase (unitless);Dydp Unitized yearly average dry deposition from particle-phase (s/m2-yr);Fw Fraction of COPC wet deposition that adheres to plant surfaces (unitless);Rpi Interception fraction of the edible portion of plant for the ith plant group (unitless);kp Plant surface loss coefficient (yr–1);Tpi Length of plant exposure to deposition per harvest of the edible portion of the ith

plant group (yr);Ypi Yield or standing crop biomass of edible portion of the ith plant group (kg DW/m2).

Values of Rp, kp, Tp, and Yp for the various plant groups are given in Table 5.2. Values for aboveground produce are from HHRAP Appendix Table B-2-7, and the values for forage and silage fromTable B-3-7. Based on HHRAP Appendix Table B-3-7, Fw is 0.2 for anions and 0.6 for cations andall organic COPCs examined in this report. Table 5.2 Parameters for calculating the direct particle-phase deposition of COPCs to exposedvegetation and produce.

Rp (unitless) kp (yr–1) Tp (yr) Yp (kg DW/m2)

Abovegroundproduce 0.39 18 0.164 2.24

Forage 0.5 18 0.12 0.24

Silage 0.46 18 0.16 0.8

The concentration of COPCs in the exposed and edible portions of vegetation due to direct transferfrom the vapor-phase is calculated by:

5–9

Pr = ⋅Cs Br

Pv Q FCyv Bv VG

vag ag

= ⋅ ⋅⋅ ⋅

ρα

Pr =⋅ ⋅

⋅

Cs RCF VGKd

rootveg

s 1kg / L


Pv Concentration of COPC in the plant resulting from air-to-plant transfer (:g COPC/gDW);

Q COPC emission rate (g/s);Fv Fraction of COPC air concentration in vapor-phase (unitless);Cyv Unitized yearly average air concentration from vapor-phase (:g- s/g-m3);Bvag COPC air-to-plant biotransfer factor ([mg COPC/g DW]/[mg COPC/g air])

(unitless);VGag Empirical correction factor for aboveground produce (unitless);Da Density of air (g/m3).

The parameter Bvag is COPC-specific; the parameter VGag is 0.01 for COPCs with a log Kow greaterthan 4, and 1.0 for COPCs with a log Kow less than 4.

The concentration of COPCs in vegetation due to transfer from soil through the roots of vegetation iscalculated for exposed and protected aboveground produce, forage, silage, and grain by:

and for belowground produce by:


Pr Concentration of COPC in produce due to root uptake (:g COPC/g DW);Br Plant-soil bioconcentration factor for produce (unitless);VGrootveg Empirical correction factor for belowground produce (unitless);Kds Soil-water partition coefficient (mL/kg);Cs Average soil concentration over exposure duration (mg COPC/kg soil);RCF Root concentration factor (unitless).

5–10

( )( )A F Qp P Qs Cs Bs Baj i ij ij j j= ⋅ ⋅ + ⋅ ⋅ ⋅∑

The values for Br for each aboveground plant type, and Kds and RCF for belowground produce areCOPC-specific and either derived from HHRAP Appendix Table A-3, or from the correlations inHHRAP Appendix A-3. Although some types of vegetation, such as forage, are not likely to be grownin tilled soil, the HHRAP recommends (page 5-20) that the COPC concentrations in soil be derivedfrom the tilled soil calculations to reflect the depth of the plants’ root zone.

5.3 COPC concentrations in livestock and related farm products

The COPC concentrations in animal tissues (beef, pork, chicken) and dairy products (milk, eggs) aredetermined by the COPC concentrations in the various parts of the animal’s diets (including soil), eachcomponent’s intake rate, and COPC-to-animal product biotransfer functions:


Aj Concentration of COPC in animal product j (mg COPC/kg);Fi Fraction of plant type i grown in contaminated soil and ingested by the animal

(unitless);Qpij Quantity of plant type i eaten by animal type j each day (kg DW plant/day);Pi Concentration of COPC in plant type i eaten by the animal type j (mg/kg DW);Qsj Quantity of soil eaten by animal type j each day (kg soil/day);Cs Average soil concentration over exposure duration (mg COPC/kg soil);Bs Soil bioavailability factor (unitless).

The intake rates (Q’s) for each animal group are shown in Table 5.3 (HHRAP Appendix B-3-10 forbeef, B-3-11 for milk, B-3-12 for pork, B-3-13 for eggs and B-3-14 for chicken). Both the fraction ofplants grown in contaminated soil, Fi, and the soil bioavailability factor, Bs, are assumed to be equal toone. All soil ingested by farm animals is assumed to be untilled.

Table 5.3 Intake rates of various vegetation types and soil required for the calculation of COPCconcentrations in farm animals and animal products.

Intake rates(kg/day)

forage silage grain soil

beef 8.8 2.5 0.47 0.5

milk 13.2 4.1 3 0.4

pork 0 3.3 1.4 0.37

chicken/eggs 0 0 0.2 0.022

5–11

5.4 COPC concentrations in surface water

As described in Chapter 3, the nearest large body of water to the LSI Greencastle facility is the CaglesMill Lake, which is located between 15 and 20 km to the south of the facility. The lake has a surfacearea of 5.67 km2, a mean depth of 6.1 m, and is located in a 756 km2 portion of the Mill Creekwatershed (IDEM, 1998). The watershed stretches to the east and north from the lake, and is generallybetween 10 and 35 km from the facility. The location of the lake and watershed is shown in Figure 3.3in the Air Dispersion and Deposition chapter of this report.

The concentrations of COPCs in Cagles Mill Lake have been calculated using the following equation,which includes terms for the total input (loading) and loss (outflow and dissipation) of COPCs fromthe water body:

( )CL

Vf f k A d dwtotT

x wc wt W wc bs

=⋅ + ⋅ ⋅ +


Ctot Total water body COPC concentration (including water column and bed sediment)(g COPC/m3 water body);

LT Total COPC load to the water body (g/yr);VfX Average volumetric flow rate through the water body (m3/yr);fwc Fraction of total water body COPC concentration in the water column (unitless);kwt Overall total water body COPC dissipation rate constant (yr–1);Aw Water body surface area (m2);dwc Depth of water column (m);dbs Depth of upper benthic sediment layer (m).

The average volumetric flow rate through Cagles Mill Lake is as 3.32×108 m3/yr based on anaveraging of daily measurements taken by the USGS from October 1, 1979 through September 30,1999 (USGS, 2001). The surface area of Cagles Mill Lake is 5.67×106 m2, and the average depth ofthe water column is 6.1 m (IDEM, 1998). The depth of the upper benthic sediment layer is taken as0.03 m based on HHRAP Appendix Table B-4-15. Because the terms for COPC loading, dissipation,and fractionation are each dependent on the calculation of several additional terms, the determinationsof LT, kwt, and fwc are described separately below.

5.4.1 COPC Loading to Cagles Mill Lake

The total COPC loading to the water body is comprised of direct wet and dry deposition of particulate-phase COPCs, direct wet deposition and diffusion of vapor-phase COPCs, runoff of COPCs frompervious and impervious surfaces within the watershed, erosion of COPC containing soils from withinthe watershed into the water body, and internal chemical or biological transformation of COPCs. Thefollowing equation gives the sum of these terms; the calculation of each of these terms are definedbelow.

5–12

L L L L L L LT DEP dif RI R E I= + + + + +


LT Total COPC load to the water body (g/yr);LDEP Total (wet and dry) particle-phase and wet vapor-phase COPC direct deposition

load to the water body (g/yr);Ldif Vapor-phase COPC diffusion (dry deposition) load to the water body (g/yr);LRI Runoff load from impervious surfaces (g/yr);LR Runoff load from pervious surfaces (g/yr);LE Soil erosion load (g/yr);LI Internal transfer (g/yr).

Each of the loading terms are calculated as follows:

The direct wet deposition of atmospheric vapor-phase COPCs and the total wet and dry deposition ofatmospheric particulate-phase COPCs is simply the product of their average watershed unitizeddeposition rates (as determined by the ISCST3 air modeling described in Chapter 4), their emissionrates, and the surface area of the lake.

( )[ ]L Q F D F D ADEP V ywwv V ytwp W= ⋅ ⋅ + − ⋅ ⋅1


LDEP Total (wet and dry) particle-phase and wet vapor-phase COPC direct depositionload to the water body (g/yr);

Q COPC emission rate (g/s);FV Fraction of COPC air concentration in the vapor-phase (unitless);Dywwv Unitized yearly (water body and watershed) average wet deposition from vapor-

phase (s/m2-yr);Dytwv Unitized yearly (water body and watershed) average total (wet and dry); deposition

from particulate-phase (s/m2-yr);AW Water body surface area (m2).

5–13

Atmospheric vapor-phase COPCs are also transferred to surface waters by direct air-to-water diffusionas determined by the COPC’s emission rate, unitized air concentration, vapor fraction, and Henry’slaw constant, by a COPC-specific mass transfer coefficient (calculated as shown below), and by thelake’s surface area.

LK Q F C A

HR T

difV V ywv W

wk

=⋅ ⋅ ⋅ ⋅ ⋅ ×

⋅

−1 10 6


Ldif Vapor-phase COPC diffusion (dry deposition) load to the water body (g/yr);KV Overall COPC transfer rate coefficient (m/yr);Q COPC emission rate (g/s);FV Fraction of COPC air concentration in the vapor-phase (unitless);Cywv Unitized yearly (water body and watershed) average air concentration from vapor-

phase (:g-s/m2-yr);AW Water body surface area (m2);10–6 Units conversion factor (g/:g);H Henry’s Law constant (atm-m3/mol);R Universal gas constant (atm-m3/mol-K);Twk Water body temperature (K).

The value for Kv, the overall COPC transfer rate coefficient, is determined using the following seriesof equations:

K K KH

R TV L Gwk

Twk= + ⋅⋅

⎛⎝⎜

⎞⎠⎟

⎛

⎝⎜⎜

⎞

⎠⎟⎟ ⋅−

− −

−1

1 1

293θ


KV Overall COPC transfer rate coefficient (m/yr);KL Liquid-phase transfer rate coefficient (m/yr);KG Gas-phase transfer rate coefficient (m/yr);H Henry’s Law constant (atm-m3/mol);R Universal gas constant (atm-m3/mol-K);Twk Water body temperature (K);2 Temperature correction factor (unitless).

For quiescent lakes or ponds:

5–14

( )K C Wk

DL da

w z

w

w w= ⋅ ⋅

⎛⎝⎜

⎞⎠⎟ ⋅ ⋅

⋅⎛⎝⎜

⎞⎠⎟ ⋅ ×−

0 5

0 5 0 33 0 67

731536 10.

. . .

.ρρ λ

µρ


KL Liquid-phase transfer rate coefficient (m/yr);Cd Drag coefficient (unitless);W Average annual wind speed (m/s);Dw Diffusivity of COPC in water (cm2/s);Da Density of air (g/cm3);Dw Density of water (g/cm3);k von Karman’s constant (0.4, unitless);8z Dimensionless viscous sublayer thickness (unitless);:w Viscosity of water corresponding to water temperature (g/cm-s);3.1536×107 Units conversion factor (s/yr);

and

( )K C Wk

DG dz

w

w w= ⋅ ⋅ ⋅

⋅⎛⎝⎜

⎞⎠⎟ ⋅ ×−

0 50 33 0 67

731536 10.. .

.λ

µρ


KG Gas-phase transfer rate coefficient (m/yr);Cd Drag coefficient (unitless);W Average annual wind speed (m/s);Dw Diffusivity of COPC in water (cm2/s);Da Density of air (g/cm3);k von Karman’s constant (0.4, unitless);8z Dimensionless viscous sublayer thickness (unitless);:w Viscosity of water corresponding to water temperature (g/cm-s);3.1536×107 Units conversion factor (s/yr).

The loading of COPCs to the lake by direct surface runoff of rainwater from impervious surfaceswithin the watershed is calculated similarly to the direct deposition of COPCs but with the impervioussurface area of the watershed substituted for surface area of the water body itself:

( )[ ]L Q F Dywwv F Dytwp ARI V V I= ⋅ ⋅ + − ⋅ ⋅1


LRI Runoff load from impervious surfaces (g/yr);Q COPC emission rate (g/s);

5–15

FV Fraction of COPC air concentration in the vapor-phase (unitless);Dywwv Unitized yearly (water body and watershed) average wet deposition from vapor-

phase (s/m2-yr);Dytwv Unitized yearly (water body and watershed) average total (wet and dry) deposition

from particulate-phase (s/m2-yr);AI Impervious watershed area receiving COPC deposition (m2).

The value for AI, the impervious watershed area receiving COPC deposition, has been estimated as6.50×106 m2, based on a total watershed area of 7.56×108 m2, and a fraction of the watershed coveredby impervious surfaces impervious fraction of 0.86%. The impervious fraction was based on the valuegiven for the Eel-Big Walnut watershed (IDEM, 2001b). Because the largest city within thiswatershed (Greencastle) is not within the Cagles Mill Lake watershed, the use of the Eel-Big Walnutimpervious fraction is probably overestimates the value of AI for Cagles Mill Lake.

The next two loading terms (LR , the COPC loading due to water runoff from pervious surfaces, andLE, the COPC loading due to the erosion of soil) are proportional to the average COPC concentrationsin the watershed soils. The COPC concentrations in the watershed soils were estimated using thesame equations as were employed in Section 5.2 with the following input values, parameters, andadditions:

! The COPC air concentration and deposition terms (Cyv, Dywv, Dydp, and Dywp) are evaluatedfor the average values over the entire watershed rather than at the location of maximumimpact,

! the soil mixing zone depth is assumed to be 1 cm, the value for untilled soil, based on theevaluation that the land within the watershed is not primarily used as cropland (IDEM,2001b), and

! a non-zero term for the COPC loss constant due to soil erosion, kse, has been used as describedbelow.

For calculating kse, the loss rate for COPCs from the soil within an area due to the erosion of soil fromthe area, the HHRAP gives the following equation:

( )kseX SD ERBD Z

Kd BDKd BD

e

s

s

sw s

=⋅ ⋅ ⋅

⋅⋅

⋅

+ ⋅

01.θ


kse COPC soil loss constant due to erosion (yr–1);0.1 Units conversion factor (1,000 g-kg/10,000 cm2-m2);Xe Unit soil loss (kg/m2-yr);SD Sediment delivery ratio (unitless);ER Soil enrichment ratio (unitless);Kds Soil-water partition coefficient (mL water/g soil);

5–16

BD Soil bulk density (g soil/cm3 soil);Zs Soil mixing zone depth (cm);2sw Soil volumetric water content (mL water/cm3 soil).

The unit soil loss, Xe, and the sediment delivery ratio, SD are calculated using equations describedbelow. The HHRAP default values of 1.5 g/cm3 for BD, 1 cm for Zs, and 0.2 mL water/cm3 for 2sw areused. Kds is a COPC-specific property.

The HHRAP guidance recommends that the constant kse should be set equal to zero based on theassumption that the amount of contaminated soil eroding off of the site being evaluated is counteredby a roughly equal amount of contaminated soil eroding onto the site. While this is perhaps a validassumption for receptor sites the size of a residential property or farm, it is not a valid assumption forthe evaluation of a watershed as a whole because, by definition, there is no flow of water (or byextension soil eroded by flowing water) into a watershed from areas outside its boundary. COPCsemitted from the LSI Greencastle facility and subsequently bound to watershed soils that are erodedfrom the land areas of the watershed are not replaced by COPCs emitted from the LSI Greencastlefacility eroding into the watershed. Additionally, if the loading of COPCs into the water body by theerosion of watershed soils is included in the transport modeling (by the water body loading term LE,described below), then this must be balanced by the loss of COPCs from the same soils. For thesereasons a non-zero value for kse has been used in the calculation of average COPC concentrationswithin the watershed.

The loading to the water body caused by runoff of dissolved COPCs from pervious soils is calculatedby:

( )L RO A ACs BD

Kd BDR L Isw s

= ⋅ − ⋅⋅

+ ⋅⋅

θ0 01.


LR Runoff load from pervious surfaces (g/yr);RO Average annual surface runoff from pervious areas (cm/yr);AL Total watershed area receiving COPC deposition (m2);AI Impervious watershed area receiving COPC deposition (m2);Cs Average soil concentration over exposure duration (in watershed soils) (mg COPC/

kg soil);BD Soil bulk density (g soil/cm3 soil);2sw Soil volumetric water content (mL water/cm3 soil);Kds Soil-water partition coefficient (mL water/g soil);0.01 Units conversion factor (kg-cm2/mg-m2).

The values for RO, AL, and AI are site-specific as described in Table 5.1; Cs is calculated as describedin Section 5.1 for untilled soils, with the inclusion of a term for COPC loss by erosion, kse. The

5–17

HHRAP default values of 1.5 g/cm3 for BD, and 0.2 mL water/cm3 for 2sw are used. Kds is a COPC-specific property.

The loading due to COPCs associated with eroding soils entering the water body is calculated by:

( )L X A A SD ERCs Kd BD

Kd BDE e L Is

sw s= ⋅ − ⋅ ⋅ ⋅

⋅ ⋅+ ⋅

⋅θ

0 001.


LE Soil erosion load (g/yr);Xe Unit soil loss (kg/m2-yr);AL Total watershed area receiving COPC deposition (m2);AI Impervious watershed area receiving COPC deposition (m2);SD Sediment delivery ratio (watershed) (unitless);ER Soil enrichment ratio (unitless);Cs Average soil concentration over exposure duration (in watershed soils) (mg COPC/

kg soil);BD Soil bulk density (g soil/cm3 soil);2sw Soil volumetric water content (mL water/cm3 soil);Kds Soil-water partition coefficient (mL water/g soil);0.001 Units conversion factor (mg/g).

The soil enrichment ratio, ER, is 1 for inorganic COPCs and 3 for organic COPCs. HHRAP defaultvalues from Appendix Table B-4-11 of 1.5 g/cm3 are used for BD, and 0.2 mL water/cm3 for 2sw. Kdsis a COPC-specific property. The value for unit soil loss for the watershed, Xe, is calculated byapplying the Universal Soil Loss Equation (USLE):

X RF K LS C PFE = ⋅ ⋅ ⋅ ⋅ ⋅907184047

.


Xe Unit soil loss (kg/m2-yr);RF USLE rainfall (or erosivity factor) (yr–1);K USLE erodability factor (ton/acre);LS USLE length-slope factor (unitless);C USLE cover management factor (unitless);PF USLE supporting practice factor (unitless);907.18 Units conversion factor (kg/ton);4047 Units conversion factor (m2/acre).

5–18

The value of 200 for RF was taken from Figure 1 of Wischmeire (1978), while values of 0.39 tons peracre for K, 1.5 for LS, 0.1 for C, and 1 for PF are based on default values found in HHRAP AppendixTable B-4-13.

The sediment delivery ratio, SD is calculated as 0.082 by the empirical correlation:

( )SD a AL

b= ⋅

−


SD Sediment delivery ratio (watershed) (unitless);a Empirical intercept coefficient (unitless);b Empirical slope coefficient (unitless);AL Total watershed area receiving COPC deposition (m2).

Values for the coefficients a and b are derived from HHRAP Appendix Table B-4-14. The slopecoefficient, b, is 0.125. The value of 1.06 for the intercept coefficient, a, has been logarithmicallyinterpolated based on the value of 292 square miles (7.56×106 m2) for AL and the intercept coefficientsfor watersheds of 100 square miles and 1000 square miles (1.2 and 0.9 respectively).

5.4.2 COPC dissipation from Cagles Mill Lake

The dissipation rate of COPCs from the water body is the sum of losses through volatilization from thewater surface and burial to bottom sediments:

k f k f kwt wc v bs b= ⋅ + ⋅


kwt Overall total water body dissipation rate constant (yr–1);fwc Fraction of total water body COPC concentration in the water column (unitless);kv Water column volatilization rate constant (yr–1);fbs Fraction of total water body COPC concentration in the benthic sediment (unitless);kb Benthic burial rate constant (yr–1).

The two loss terms are given by:

( )kK

d Kd TSSvv

z sw

=⋅ + ⋅ ⋅ × −1 1 10 6


kv Water column volatilization rate constant (yr–1);

5–19

Kv Overall COPC transfer rate coefficient (m/yr);dz Total water body depth;Kdsw Suspended sediments/surface water partition coefficient (L water/kg suspended

sediments);TSS Total suspended solids concentration (mg/L);1×10-6 Units conversion factor (kg/mg); and

kX A SD Vf TSS

A TSSTSS

C dbe L x

w BS bs=

⋅ ⋅ ⋅ × − ⋅⋅

⎛

⎝⎜

⎞

⎠⎟ ⋅

⋅ ×⋅

⎛⎝⎜

⎞⎠⎟

−1 10 1 103 6


kb Benthic burial rate constant (yr–1);Xe Unit soil loss (kg/m2-yr);AL Total watershed area receiving COPC deposition (m2);SD Sediment delivery ratio (watershed) (unitless);Vfx Average volumetric flow rate through the water body (m3/yr);TSS Total suspended solids concentration (mg/L);Aw Water body surface area (m2);CBS Bed sediment concentration (g/cm3);dbs Depth of upper benthic sediment layer (m);1×10-6 Units conversion factor (kg/mg);1×103 Units conversion factor (g/kg).

Values for the watershed’s unit soil loss, Xe, and sediment delivery ratio, SD, were calculated based onequations described above. Values for the total watershed area, AL, the water boby area, AW, averagevolumetric flow rate, Vfx, and total suspended solids concentration, TSS, have been based on site-specific data also described above, and HHRAP default values from Appendix Table B-4-16 wereused for the bed sediment concentration, CBS, and the depth of the upper benthic sediment layer, dbs.

5.4.3 COPC partitioning in Cagles Mill Lake

It is neccesary to calculate the partitioning of COPCs within the water body in order to account forCOPC loss to outflow (the Vfx @fwc term in the equation for Cwtot), and to employ the correct COPCconcentrations in the calculations for COPC concentrations in fish and in drinking water. Thepartitioning divides concentrations of the compounds between the water column and the benthicsediments, and within the water column between concentrations in the dissolved-phase and bound tosuspended sediments. The fraction of each COPC within the water column is given by:

( )( ) ( )f

Kd TSS d d

Kd TSS d d Kd C d dwcsw wc z

sw wc z bs bs BS bs z

=+ ⋅ ⋅ × ⋅

+ ⋅ ⋅ × ⋅ + + ⋅ ⋅

−

−

1 1 10

1 1 10

6

6 θ

5–20

the balance of each COPC in the water body is contained within the benthic sediment:

f fbs wc= −1


fwc Fraction of total water body COPC concentration in the water column (unitless);fbs Fraction of total water body COPC concentration in benthic sediment (unitless);Kdsw Suspended sediments/surface water partition coefficient (L water/kg suspended

sediment);TSS Total suspended solids concentration (mg/L);1×10-6 Units conversion factor (kg/mg);dz Total water body depth (m);2bs Bed sediment porosity (Lwater/Lsediment);Kdbs Bed sediment/sediment pore water partition coefficient (L water/kg bottom

sediment);CBS Bed sediment concentration (g/cm3 [equivalent to kg/L]);dwc Depth of water column (m);dbs Depth of upper benthic sediment layer (m).

The average total water column depth, dz, of 6.1 m is based on data from the IDEM (1998). Thevalues for 2bs of 0.6, CBS of 1 g/cm3, and dbs of 0.03 m, are default values for HHRAP Appendix TablesB-4-15 and B-4-16. The partitioning coefficients Kdsw, and Kdbs are COPC-specific.

The concentration of total suspended solids (TSS) within the water column can be estimated using thefollowing equation:

( )TSS

X A A SDVf D A

e L I

x ss W=

⋅ − ⋅ ⋅ ×+ ⋅

1 103


TSS Total suspended solids concentration (mg/L);Xe Unit soil loss (kg/m2-yr);AL Total watershed area receiving COPC deposition (m2);AI Impervious watershed area receiving COPC deposition (m2);SD Sediment delivery ratio (watershed) (unitless);1×103 Units conversion factor (L/m3);Vfx Average volumetric flow rate through the water body (m3/yr);Dss Suspended solids deposition rate (a default value of 1,825 for quiescent lakes and

ponds) (m/yr);Aw Water body surface area (m2).

5–21

As recommended in the HHRAP the TSS concentration calculated using the above equation has beencompared with an annual average measured value in order to evaluate the watershed-specific valuesused in calculating the unit soil loss, Xe. The U.S. Army Corps of Engineers, which maintains theCagles Mill Lake for flood control purposes, has measured TSS levels at three locations on the lakesurface and at various depths since 1973. Data from 249 TSS measurements were obtained from theCorps’ Louisville District Office (USACE, 2001). Because most of the measurements were taken inthe summer months when TSS levels were higher, average TSS concentrations were first calculatedfor each calendar month (e.g. for all measurements taken in any June). Because there were nomeasurements taken in any December or January, levels for these months were estimated byinterpolating between the average November and February levels. Finally, an annual average wasobtained using the 12 month-based averages. The TSS concentration calculated in this way from themeasured values is 21.5 mg/L; the value calculated using the equation above is 15.2 mg/L. Becausethese values are in reasonable agreement it is deemed that the value for the watershed unit soil loss, Xehas been estimated sufficiently well.

The concentration of each COPC within the water body (Cwtot) is apportioned between the watercolumn (Cwctot), which has both dissolved-phase COPCs (Cdw) and COPCs bound to suspendedsediments, and COPCs sorbed to the bed sediments (Cbs) as follows:

C f Cd d

dwctot wc wtotwc bs

wc= ⋅ ⋅

+


Cwctot Total COPC concentration in water column (mg COPC/L water column);fwc Fraction of total water body COPC concentration in the water column (unitless);Cwtot Total water body COPC concentration, including water column and bed sediment

(mg COPC/L water column);dwc Depth of water column (m);dbs Depth of upper benthic sediment layer (m);

CC

Kd TSSdwwctot

sw=

+ ⋅ ⋅ × −1 1 10 6


Cdw Dissolved-phase water concentration (mg COPC/L water);Cwctot Total COPC concentration in water column (mg COPC/L water column);Kdsw Suspended sediments/surface water partition coefficient (L water/kg suspended

sediment);TSS Total suspended solids concentration (mg/L);1×10–6 Units conversion factor (kg/mg); and

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C f CKdKd C

d ddsb bs wtot

bs

bs bs BS

wc bs

bs= ⋅ ⋅

+ ⋅⎛⎝⎜

⎞⎠⎟ ⋅

+⎛⎝⎜

⎞⎠⎟

θwhere the terms are:

Csb COPC concentration sorbed to bed sediment (mg COPC/kg sediment);fbs Fraction of total water body COPC concentration in benthic sediment (unitless);Cwtot Total water body COPC concentration, including water column and bed sediment

(mg COPC/L water column);Kdbs Benthic sediments/sediment pore water partition coefficient (L water/kg sediment);2bs Bed sediment porosity (Lwater/Lsediment);CBS Bed sediment concentration (g/cm3);dwc Depth of water column (m);dbs Depth of upper benthic sediment layer (m).

The distribution fractions, fwc and fbs, have been calculated based on equations described above. Thedepth of the water column, dwc, and the total suspended solids concetration, TSS, are site-specificparameters. The depth of the upper benthic sediment layer, dbs, the bed sediment porosity, 2bs, and thebed sediment concentration, CBS,, are HHRAP default parameters from Appendix Table B-4-16. Finally, the partitioning coefficients, Kdsw and Kdbs, are COPC-specific properties.

5.5 COPC concentrations in fish

The concentration of COPCs in fish is calculated using either a COPC-specific bioconcentration factor(BCF, for compounds with a log Kow less than 4.0), a COPC-specific bioaccumulation factor (BAF, forcompounds with a log Kow greater than 4.0), or a biota-sediment accumulation factor (BSAF, forcompounds which are extremely hydrophobic and listed as such in the HHRAP Appendix Tables A-3:PCDDs, PCDFs, and PCBs). Depending on which factor is appropriate, one of three equations hasbeen used to calculate COPC concentrations in fish tissue:

C C BCFfish dw fish= ⋅

C C BAFfish dw fish= ⋅

CC f BSAF

OCfishsb lipid fish

sed=

⋅ ⋅


Cfish Concentration of COPC in fish (mg COPC/kg FW tissue);Cdw Dissolved-phase COPC concentration in water (mg COPC/L);

5–23

Csb Concentration of COPC sorbed to bed sediment (mg COPC/kg bed sediment);BCFfish Bioconcentration factor for COPC in fish (L/kg);BAFfish Bioaccumulation factor for COPC in fish (L/kg);BSAFfish Biota-to-sediment accumulation factor for COPC in fish (unitless);flipid Fish lipid content (unitless);OCsed Fraction of organic carbon in bottom sediment (unitless).

The COPC concentrations dissolved in lake water and sorbed to bed sediments were calculated asdescribed above; the BCFfish, BAFfish, and BSAFfish values are based on HHRAP Appendix Tables A-3or guidance for their calculation in HHRAP Appendix A-3; a site-specific value for the BAFfish ofmercury has been used in the calculations. Justification for and a derivation of the value used isdescribed in below. An flipid value of 0.07, and a OCsed value of 0.04 were based on default values fromHHRAP Appendix Table B-4-28.

5.5.1 The use of a site-specific value for the BAFfish for mercury

The bioaccumulation factor (BAF) recommended for methyl mercury, MHg, in Appendix Table A-3-140 of the HHRAP is 6.8 ×106 L/kg. This value, according to the guidance in Appendix Table B-4-27, is to be applied to the total of the dissolved-phase concentrations of Hg2+ and MHg. This BAFvalue is for trophic level 4 (piscivorus) fish and is referenced to the 1997 U.S. EPA Mercury StudyReport to Congress Volume III: Fate and Transport of Mercury in the Environment (The U.S. EPAMercury Report, 1997a). This BAF value is found specifically in Appendix D of the U.S. EPAMercury Report in section D.3.4.1 “Bioaccumulation Factors Directly Estimated from Field Data –Methyl mercury in Piscivorus Fish.” The definition given for the BAF is: “Average Methyl mercuryconcentrations in piscivorus fish (trophic level 4) divided by average dissolved Methyl mercuryconcentrations in water, accumulated by all possible routes of exposure.” This BAF is not derivedfrom the MHg concentration in trophic level 4 fish divided by dissolved total mercury concentration inwater as described in the HHRAP. Hence the HHRAP-recommended value is inappropriate.

There are several options for estimating mercury concentrations in fish based on the application of amore valid combination of a BAF and a predicted water concentration. The first of these optionswould be to apply the HHRAP default BAF to the dissolved MHg concentration in the water, asdescribed in the BAF definition in the U.S. EPA Mercury Report. A second approach would be toapply a BAF defined in the U.S. EPA Mercury Report Appendix section D.3.5.2 for the total mercuryin trophic level 4 fish divided by the total dissolved mercury in the water; this BAF value is 5.0×105

L/kg. The final method proposed here is to apply a BAF derived from measurements taken formercury in trophic level 4 fish and in water from the site in question—Cagles Mill Lake. The basisand calculation of this site-specific BAF are given below, and estimates of fish mercury concentrationswhich result from the use of all of these approaches are shown in Table 5-6.

Cagles Mill Lake was created in 1952 for flood control purposes by the US Army Corps of Engineers. As such, various measurements of the lake’s condition are monitored by the Corps’ Louisville DistrictOffice. Among these measurements are the total mercury concentration (both dissolved and bound tosuspended sediments) in the lake water, which has been measured at various depths in the lake on 18

5–24

occasions since 1979 (USACE, 2001) as show in Table 5-4. As can be seen in the table, only a fewmeasurements taken after 1986 were above the detection limits, which decreased from 1.0 ng/L in1987 down to 0.16 ng/L in 1997.

Table 5.4 Total mercury in Cagles Mill Lake (ng/L). Depth of measurement values have beenrounded to the nearest five foot increment.

samplingdepth (ft) /date

0 10 20 25 30 35 40 45 50 65 70

9/6/1979 8.6 6.7 7.7 7.410/3/1979 3.3 4.8 3.8 4.07/28/1981 <1.0 <1.0 <1.0 <1.0 <1.07/28/1982 11.3 6.0 23.0 19.0 14.07/19/1983 2.6 11.0 11.0 6.0 6.07/18/1984 1.2 <1.0 3.4 1.6 1.66/18/1986 2.8 2.8 2.87/9/1987 <1.0 <1.06/28/1988 <1.0 <1.0 <1.07/13/1989 <1.0 <1.0 <1.06/13/1990 <1.0 <1.07/9/1991 <1.0 <1.0 <1.06/18/1992 1.3 <1.0 <1.07/28/1993 0.5 <0.13 0.188/3/1995 0.99 <0.2 <0.28/2/1996 <0.2 <0.28/19/1997 <0.16 <0.16

The second piece of data required to calculate a site-specific BAF value is a measurement ofmercury in fish from Cagles Mill Lake. These data. The available data for Hg concentrations in fishfrom Cagles Mill Lake were obtained from the Indiana Department of Environmental Management(IDEM, 2001c) are shown in Table 5.5. Although the number of fish sampled is rather small, themeasurements are well within the range of values found throughout Indiana. For comparison, the1990-1995 weighted median mercury concentrations in all Indiana waters for carp was 0.166 mg/kg(with a standard deviation of 0.125 mg/kg), and for largemouth bass was 0.197 mg/kg (with astandard deviation of 0.170 mg/kg) (IDEM, 2001c).

Table 5.5 The available fish Hg concentration data for Cagles Mill Lake. Measurements for 1986are of skin-off fillets, and for 1996 are of scaleless, skin-on fillets (IDEM, 2001c).

Datecollected Species Number Mean Hg

(mg/kg)Mean size(cm / in)

5–25

08/07/86 Carp 3 0.250 53.5 / 21.1

07/08/96 Carp 4 0.119 41.7 / 16.4

07/08/96 LargemouthBass 1 0.195 39.8 / 15.7

07/08/96 LargemouthBass 1 0.168 34.1 / 13.4

In order to calculate a reasonably conservative, site-specific BAF for Hg in trophic level 4 fishrelative to total Hg in the water, the maximum measured fish concentration is divided by an averagetotal Hg concentration in the water from 1987 to 1997, with the non-detected values included at halfthe detection limits for the same monitoring period. An even more conservative approach (i.e., onewhich would produce a higher BAF) would be to substitute non-detected values with half of themost recent, lowest detection limit for the water concentrations. However, because the total Hgconcentrations appear to have declined from levels above the 1987 detection limit of 1.0 ng/L, andbecause detectable levels of Hg were found from 1992 to 1995, the use of time year-specificdetection limits should provide a reasonably conservative BAF. Using these values of 0.4 ng totalHg/L water, and 0.195 mg total Hg/kg fish, gives a BAF of 4.8×105 L/kg (total Hg fish/total Hgwater).

12 Note that these levels exceed current measured Hg concentrations in Cagles Mill Lake. Although this may appear inconsistent with the fact that the calculated concentrations are meantto be incremental values due to emissions from the LSI/Greencastle facility, it must beremebered that modeling calculations are derived from a MACT-based mercury emission ratewhich is 19.8 times greater than the facility’s actual emission rate.

5–26

Table 5.6 Estimates for the incremental Hg concentrations in fish in Cagles Mill Lake due toMACT-bsed Hg emissions from the LSI Greencastle facility, for the four BAF values and calulationbases described above.

BAF sourcedescription

Type of Hgmeasured inwater

Calculatedwaterconcentration(ng/L)

Type of Hgmeasured infish

BAF (L/kg)

Calculatedfishconcentration (mg/kg)

HHRAPguidance

totaldissolvedmercury

0.30 methyl-mercury 6.8×106 2.0

U.S. EPAMercuryReport

dissolvedmethyl-mercury

0.16 methyl-mercury 6.8×106 1.1

U.S. EPAMercuryReport

totaldissolvedmercury

0.30 total mercury 5.0×105 0.15

Cagles MillLake site-specific

total mercury 0.96 total mercury 4.8×105 0.47

Several factors must be considered in the evaluation of which BAF and calculation method to applyfor estimating mercury levels in fish. Because the first method applies a BAF derived for dissolvedmethyl mercury to total dissolved Hg, it is likely to incorrectly overestimate mercury levels in fish. In order to assess the remaining methods, it is first necessary to examine the calculatedconcentrations for the various forms of Hg in Cagles Mill Lake due to emissions from the LSIGreencastle facility. The calculated total Hg and dissolved Hg concentrations (0.96 and 0.30 ng/Lrespectively)12 shown in the table above are within the range of total Hg measured in the lake andreferenced in the U.S. EPA Mercury Report (Volume III, Table 3-7, U.S. EPA, 1997a). However,the calculated fraction of methyl mercury to total mercury, 17% (0.16 ng/L divided by 0.96 ng/L), issomewhat higher than the range of values cited in the U.S. EPA report (1.0 - 14%).

Because the compound of concern in evaluating health effects of mercury in fish is methyl mercury,and the modeling estimates a concentration for this form in the dissolved-phase, it might seem

5–27

appropriate to use a BAF based on these two forms. However, the dissolved-phase methyl mercuryconcentration calculated in the modeling contains too much uncertainty to justify this approach. Thepartitioning of mercuric chloride and methyl mercury between the dissolved- and solid-phases isbased on the concentration of total suspended sediments in the lake, TSS, and the water-to-suspendedsediments partitioning coefficients, Kdsw. Although the partitioning calculations described in theHHRAP guidance and employed here use a site-specific value for TSS, they do not employ site-specific values for the partitioning coefficients Kdsw for mercuric chloride or methyl mercury, bothof which are given the value of 100,000 L/kg. The source for these Kdsw values is the 1997 U.S.EPA Mercury Report, Vol. III, Appendix section B.1.2.1.5 (U.S. EPA, 1997a), which gives a rangeof values for these coefficients—from 1,380 to 270,000 L/kg for Hg2+, and from 94,000 to 250,000L/kg for MHg. As can be seen in the equations for total COPC concentrations in the water column,Cwctot, and for dissolved-phase COPC concentrations in the water column, Cdw (described in Section5.4.3), the partitioning of the compound between the dissolved- and solid-phases in the watercolumn is far more sensitive to the values of Kdsw than is the partitioning between the total watercolumn and the benthic sediments. The sensitivity of Cdw to variations in Kdsw extends to asensitivity of estimated health risks posed by fish consumption if Cdw is used to calculate mercurylevels in fish.

Therefore, because of the variability in reported Kdsw values, the sensitivity of the predicted risks tothis parameter, the fact that no site-specific values are available or readily estimated, and the factthat the fraction of methyl mercury calculated using the HHRAP equations and default parameters isoutside of the range previously reported by the U.S. EPA, it is appropriate to use a biotransfercalculation based on total mercury concentrations. This avoids the large uncertainty in the final riskestimates which is inherent in the use of a default values for Kdsw in the calculation of mercurypartitioning between the dissolved- and solid-phases.

Finally, it is important to note that the bioaccumulation of Hg in fish is not a simple chemicalpartitioning but is dependent on a variety of parameters as the Hg progresses up the food chain totrophic level 4 fish. The transformation of mercury from inorganic species into methyl mercury andthe subsequent biotransfer of methyl mercury up the food chain at a specific location is affected notonly by the simple physical properties of the lake, but also by its surface and sediment chemistry andby the various species which make up its biological community. The U.S. EPA’s Mercury Report toCongress (U.S. EPA, 1997a; Vol. III, page 8-2), states that “the BAF value contains a substantiallevel of uncertainty.” The HHRAP guidance (Appendix Table B-4-27) specifically notes that “TheCOPC-specific BAF values may not accurately represent site-specific water body conditions,because estimates of BAFs can vary, based on experimental conditions.” As such, it is deemedprudent to use a site-specific bioaccumulation factor for the estimation of mercury concentrations infish which might be consumed as part of the exposure scenario for subsistence fishers. As seen inTable 5.6, this approach—the use of an empirical BAF based on total mercuryconcentrations—results in incremental mercury concentrations in fish well within the range of all ofthe methods considered, and higher than any mercury concentrations measured in fish from CaglesMill Lake.

6–1

6 Quantifying exposureAn exposure assessment builds upon the estimation of concentrations of COPCs in various media bydefining, through various assumptions, the rates and frequencies at which receptors might breathe,ingest, and otherwise contact the media to which COPCs have migrated. Exposure assumptions arein general designed to estimate a high-end level of exposure (although not necessarily the highestpotential degree of exposure). The calculation of human exposures to COPCs depends on (1) theCOPC’s concentration in media relevant to the exposure scenario being considered; (2) the rate atwhich the individual consumes (i.e., ingests or inhales) the given medium; (3) the frequency andduration of the exposure; and in order to normalize the exposure for body size, (4) the individual’sweight. Exposures can be expressed in a generalized way by the following equation:

IC CR EF ED

BW ATgen =⋅ ⋅ ⋅

⋅where the terms are:

Igen Intake–the amount of COPC at the exchange boundary (mg/kg/day); forevaluating exposure to noncarcinogenic COPCs, the intake is referred to asaverage daily dose (ADD); for evaluating exposure to carcinogenic compounds,the intake is referred to as lifetime average daily dose (LADD);

C COPC concentration in media of concern (e.g., mg/kg for soil or mg/L for surfacewater);

CR Consumption rate–the amount of contaminated medium consumed per unit timeor event (e.g., kg/day for soil or L/day for water);

EF Exposure frequency (days/year);ED Exposure duration (years);BW Average body weight of the receptor over the exposure period (kg);AT Averaging time–the period over which exposure is averaged (days); for

carcinogens, the averaging time is 25,550 days, based on a lifetime exposure of70 years; for noncarcinogens, averaging time equals ED (years) multiplied by 365days per year.

Exposures to COPCs occur due to the direct inhalation of the compounds, and due to their ingestionwithin food, water and soils. The calculation of COPC intake rates by indirect pathways arecontained in the HHRAP Appendices C-1-1 through C-1-5, with the total given in Appendix C-1-6:

I I I I I I II I I

ind soil prod beef milk pork poultry

eggs fish dw

= + + + + +

+ + +

6–2


Iind Total daily intake of COPC by indirect pathways (mg/kg-day);Isoil Daily intake of COPC from soil (mg/kg-day);Iprod Daily intake of COPC from above ground produce (mg/kg-day);Ibeef, Imilk, Daily intake of COPC from beef, milk, pork, poultry, eggs, and fishIpork, Ipoultry, respectively (mg/kg-day);Ieggs, IfishIdw Daily intake of COPC from drinking water (mg/kg-day).

Depending on the exposure scenario selected for analysis some of these intake terms may be set tozero (see Table 4.1). Separate individual intake rates for adults and children are calculated using theequations below and parameters from Table 6.1.

The intake of COPCs due to the incidental ingestion of soil is calculated by:

IC CR F

BWsoils soil soil=⋅ ⋅


Isoil Daily intake of COPC from soil (mg/kg-day);Cs Average soil concentration over exposure duration (mg/kg);CRsoil Consumption rate of soil (kg/day);Fsoil Fraction of soil that is contaminated (unitless);BW Body weight (kg).

The COPC concentration in soil is calculated as described in Section 5.1 for untilled soil. Defaultvalues for CRsoil and BW for adults and children are listed in Table 6.1, and the parameter Fsoil isassumed to be 1 (HHRAP Appendix Table C-1-1).

The intake of COPCs due to the ingestion of produce is calculated by:

( )( ) ( ) ( )[ ]I Pd Pv CR CR CR Fprod ag ag ag ag pp pp bg bg= + + ⋅ + ⋅ + ⋅ ⋅Pr Pr Pr


Iprod Daily intake of COPC from produce (mg/kg-day DW);Pd, Pv, Pr Average COPC concentration in produce over exposure duration due

to direct deposition, air-to-plant transfer, and root uptake respectively(mg/kg), with the subscripts ag, pp, and bg referencing above ground,protected and below ground produce respectively;

6–3

CRag, CRpp, CRbg Consumption rate of above ground, protected and below groundproduce respectively (kg/kg-day DW);

F Fraction of produce that is contaminated (unitless).

The calculations of COPC concentrations in produce due to the listed mechanisms are described insection 5.2. Default values for the parameters CRag, CRpp, and CRbg for adults and children are listedin Table 6.1. The parameter F is assumed to be 1 for subsistence farmers and their children, and0.25 for residents and subsistence fishers and their children (HHRAP Appendix Table C-1-2).

The intake of COPCs due to the ingestion of beef, milk, pork, poultry, eggs, and fish is calculatedby:

I A CR Fi i i i= ⋅ ⋅where the terms are:

Ii Daily intake of COPC from animal tissue or product i (mg/kg-day);Ai Average COPC concentration in animal tissue or product i over exposure duration

(mg/kg FW);CRi Consumption rate of animal tissue or product i (kg/kg-day FW);Fi Fraction of animal tissue or product i that is contaminated (unitless);

The calculations of COPC concentrations in animal tissues are described in section 5.3. Defaultvalues for the parameters CRbeef, CRmilk, CRpork, CRchicken, and CReggs for adults and children are listedin Table 6.1, and the corresponding parameter Fi is assumed to be 1 and is applicable only to thesubsistence famer and child exposure scenarios (HHRAP Appendix Table C-1-3). The calculationof COPC concentrations in fish are described in Section 5.5. Default values for the parameters CRfishfor adults and children are listed in Table 6.1, and the parameter Ffish is assumed to be 1 and isapplicable only to the subsistence fisher and child exposure scenarios (HHRAP Appendix Table C-1-4).

The intake of COPCs due to the ingestion of drinking water is calculated by:

IC CR F

BWdwdw dw dw=

⋅ ⋅


Idw Daily intake of COPC from drinking water (mg/kg-day);Cdw Dissolve-phase water concentration over exposure duration (mg/L);CRdw Consumption rate of drinking water (L/day);Fdw Fraction of drinking that is contaminated (unitless);BW Body weight (kg).

6–4

ADIC IR ET EF ED

BW ATa=⋅ ⋅ ⋅ ⋅ ⋅

⋅ ⋅0 001

365.

The COPC concentrations in surface waters (Cagles Mill Lake) are calculated as described inSection 5.4. Default values for CRdw and BW for adults and children are listed in Table 6.1, and theparameter Fdw is assumed to be 1, based on HHRAP Appendix Table C-1-5.

Table 6.1 Parameters for calculation of human exposure to COPCs by indirect pathways.

Parameter adult childBody weight (kg) BW 70 15Consumption ratessoil adult (kg/day) CRsoil 0.0001 0.0002above ground produce (kg/kg-day DW) CRag 0.0003 0.00042produce protected (kg/kg-day DW) CRpp 0.00057 0.00077below ground produce (kg/kg-day DW) CRbg 0.00014 0.00022beef (kg/kg-day DW) CRbeef 0.00114 0.00051milk (kg/kg-day DW) CRmilk 0.00842 0.01857pork (kg/kg-day DW) CRpork 0.00053 0.000398poultry (kg/kg-day DW) CRchicken 0.00061 0.000425eggs (kg/kg-day DW) CReggs 0.00062 0.000438fish (kg/kg-day FW) CRfish 0.00117 0.000759drinking water (L/day) CRdw 1.4 0.67

The COPC exposure levels by indirect pathways which result from these calculations are used inChapter 7 to estimate the incremental cancer risks and noncancer hazard quotients due to emissionsfrom the LSIGreencastle facility.

Exposures to COPCs by direct inhalation is calculated using the following equation from theHHRAP Appendix Tables C-2-1 and C-2-2:


ADI Average daily intake of COPC via direct inhalation (mg COPC/kg-day);Ca Total COPC air concentration over exposure duration (:g/m3);IR Inhalation rate (m3/hr);ET Exposure time (hr/day);EF Exposure frequency (days/yr);ED Exposure duration (yr);BW Body weight (kg);AT Averaging time (yr);0.001 Conversion factor (:g/mg);365 Conversion factor (days/year).

6–5

Cm h f

fmilkfat =⋅ × ⋅ ⋅

⋅1 100 693

91

2.

ADDC f f IR ED

BW ATantmilkfat milk

antinf

inf=

⋅ ⋅ ⋅ ⋅

⋅3 4

The total COPC concentrations in air are calculated as the sum of the 5-year average concentrationsat the maximum impact locations using the ISCST3 modeling described in Chapter 3. Defaultvalues (as listed in HHRAP Appendix Tables C-2-1, and C-2-2) for inhalation rates, IR, are 0.30m3/hr for children, and 0.63 m3/hr for adults; the exposure time, ET, is 24 hr/day; the exposurefrequency, EF, is 350 days/year; the exposure durations, ED, are 6, 30, or 40 years (depending onthe exposure scenario described in Chapter 4); the body weights, BW, are 15 kg for children, and 70kg for adults; and the averaging times, AT, are 6, 30, or 40 years for noncancer hazard calulations,and 70 years for the calculation of cancer risks.

The special exposure scenarios of nursing infants exposed to PCDDs and PCDFs through theingestion of contaminated breast milk requires the calculation of COPC concentrations in the breastmilk as described by the following equation from HHRAP Appendix Table C-3-1:


Cmilkfat Concentration of COPC in milk fat of breast milk for a mother in a specificexposure scenario (pg/kg milkfat);

m Average maternal intake of PCDDs and PCDFs for each adult exposure scenario(mg COPC/kg BW-day);

h Half-life of PCDDs and PCDFs in adults (days);f1 Fraction of ingested PCDDs and PCDFs that are stored in fat (unitless);f2 Fraction of mother’s weight that is fat (unitless);1×109 Conversion factor (pg/mg);0.693 Conversion factor (ln2, to convert half-life to decay rate constant).

The average maternal intakes of PCDDs and PCDFs for each adult exposure scenario are calcualtedusing the equations for adult COPC exposures described above. Default values (as listed in HHRAPAppendix Table C-3-2) for the half-life of PCDDs and PCDFs in adults, h, is 2,555 days; fraction ofingested PCDDs and PCDFs that are stored in fat, f1, is 0.9; and the fraction of mother’s weight thatis fat, f2, is 0.3.

The exposure of nursing infants to PCDDs and PCDFs is then evaluated using the followingequation from HHRAP Appendix Table C-3-2:


6–6

ADDinfant Average daily intake of COPC to infant exposed to contaminated breast milk (pgCOPC/kg-day);

Cmilkfat Concentration of COPC in milk fat of breast milk for a mother in a specificexposure scenario (pg/kg milkfat);

f3 Fraction of a mother’s breast milk that is fat (unitless);f4 Fraction of ingested COPC that is absorbed (unitless);IRmilk Ingestion rate of breast milk by the infant (kg/day);ED Exposure duration (yr);BWinfant Body weight (kg);AT Averaging time (yr).

The concentration of COPC in the milk fat of breast milk is calculated using the equation above. Default values (as listed in HHRAP Appendix Table C-3-2) for the fraction of a mother’s breastmilk that is fat, f3, is 0.04; the fraction of ingested COPC that is absorbed, f4, is 0.9; the ingestion rateof breast milk by the infant, IRmilk, is 0.8 kg/day; the exposure durations, ED, is 1 year); the bodyweight of the infant, BWinfant, is 10 kg; and the averaging time, AT, is 1 year.

7–1

7 Risk and hazard characterizationThe assessment of human health risks due to stack and fugitive emissions from the LSI Greencastlefacility are incremental in nature, and do not reflect a person’s total or cumulative risks fromexposure to compounds in the environment, since there are background levels of compounds presentin the atmosphere that are unrelated to operation of the cement kiln. Incremental risks are examinedin conjunction with the regulatory framework that treats facilities as independent entities. Consequently, it is important to recognize the incremental focus of the risk estimates in generalbears no relationship to risks corresponding to a person’s total exposure to compounds present in theenvironment.

Two categories of incremental risks of chronic health effects have been considered: cancer and non-carcinogenic endpoints. Dose-response relationships for carcinogens are characterized by unit riskfactors and potency slope factors. These factors are derived for assessing exposures via inhalationand ingestion pathways, respectively. Dose-response data for non-carcinogenic health effects arederived in a similar manner. Reference concentrations and reference doses are used to assess thelikelihood of chronic (noncancer) health effects from inhalation and oral exposure, respectively. Both cancer and non-cancer risks have been evaluated for direct exposures (e.g. inhalation ofdirectly emitted COPCs) and indirect exposures (e.g. food chain and drinking water related).

As described in Chapter 2, data to evaluate the chronic toxic effects of the contaminants of concernhave been obtained principally from two U.S. EPA databases: Integrated Risk Information System(IRIS) and Health Effects Assessment Summary Tables (HEAST). Some additional toxicologicaldata has also been derived from the U.S. EPA Region III’s Risk-Based Concentration Table (U.S.EPA 2001b). However, current toxicologic data are not available for all of the contaminants ofconcern (e.g., for tentatively identified compounds that are not on standard lists of hazardous airpollutants). The HHRAP itself recommends compound-specific toxicologic data, some of whichderive from IRIS and HEAST, as well as other sources. Those COPCs that do not havetoxicological data available from these sources have been carried through the fate and transportcalculations and their toxicity will be evaluated qualitatively based on surrogate toxicity data forchemically–similar COPCs and will be addressed in the uncertainty section of this report.

Carcinogenic risks are calculated as the product of long-term average dose (concentration forinhalation exposure) and carcinogenic potency (unit risk). The exposure periods listed in Table 4.1are used to assess incremental cancer risk. Individual risk estimates have been summed acrosscompounds and exposure pathways to provide a total estimate of incremental cancer risk due toemissions from the LSI Greencastle facility.

Similarly, hazard ratios have been calculated for noncarcinogenic endpoints as the ratio of theestimated dose (or concentration) derived from facility-related emissions to the reference dose (or

7–2

concentration) identified in the toxicity assessment. An overall hazard ratio has been constructed asthe sum of all hazard ratios calculated for individual exposure routes and compounds. For hazardindeces that exceed a value of one, a target-specific analysis is conducted (if appropriate) toinvestigate different types of noncancer health risks.

In addition to chronic hazard indices, acute hazard ratios will be calculated as the ratio of modeledshort-term exposure points concentrations in air to Acute Inhalation Exposure Criteria (AIEC), asdescribed in the HHRAP guidance. AIEC are listed for a number of compounds in Appendix A ofthe HHRAP. Some AIEC values have been updataed following the hierarchy described in theHHRAP. For example, some values are taken from a recently revised report issued by the Office ofEnvironmental Health Hazard Assessment (OEHHA) at the California Environmental ProtectionAgency (CalEPA, OEHHA, 2000). Since the reference exposure levles (RELs) in this reportsupercede the formerly acute toxic effects levels (ATELs) that are currently used in the HHRAPguidance, they are also used to update the AIECs.

As described above, cancer risks are a conservative, high-end estimate of the incremental probabilitythat an individual will develop cancer as a result of a specific exposure to a carcinogenic compound;they are estimated by multiplying an individual’s lifetime average daily dose (LADD) of acompound (mg/kg-day) by the compound’s cancer slope factor (CSF), (mg/kg-day)–1. The LADDfor each COPC and exposure scenario has been calculated in Chapter 6 based on results contained inchapters 2 through 5; the COPC CSFs are contained in the COPC Properties Tables in Appendix III.An individual’s overall cancer risk due to a given facility’s emissions is the sum of the cancer risksfrom all of the compounds of concern, and thus includes potential cancers of all types.

Noncancer risk agents are assumed to exhibit a threshold below which no adverse effects areexpected to be observed. As such, noncancer health hazards are evaluated by comparing anindividual’s exposure to a compound against a reference dose (RfD) for oral exposures or areference concentration (RfC) for inhalation exposures. The ratio of an individual’s exposure to acompound to the compound’s reference exposure level is the known as the hazard quotient for thatcompound and exposure:

HQADDRfD

or HQCRfC

a= =


HQ Hazard quotient (unitless)ADD Average daily dose (mg/kg-day)Ca Total COPC air concentration (mg/m3)RfD Reference dose (mg/kg-day)RfC Reference concentration (mg/m3)

7–3

As for the estimation of cancer risks, the values for ADD and Ca in the above equation have beencalculated in Chapter 6 based on results contained in chapters 2 through 5; the COPC RfDs and RfCsare contained in the COPC Properties Tables in Appendix III. Because of the threshold assumptioninherent in RfDs and RfCs, HQs below 1 are considered to be protective of human health. Additionally, an individual’s total noncarcinogenic hazard due to a given facility’s emissions isreferred to as the hazard index (HI), which is calculated as the sum of the hazard quotients for all ofthe compounds of concern. A stated in the HHRAP guidance, the HI concept involves aconsiderable oversimplification of an individual’s potential to experience adverse health effects dueto a facility’s emissions because it assumes that the effects of different COPCs are additive, eventhough they may include different (i.e., unrelated) health effects and compounds that may actsynergistically or antagonistically with each other.

Tables 7.1 through 7.13 contain the estimated cancer risks and hazard quotients for each COPCemitted from the LSI Greencastle facility and for which the appropriate toxicological data wasavailable. The tables are arranged in three main groups of four tables each.

The first group of tables contains the estimated cancer risk and hazard quotients based on themodeling of COPCs subject to MACT limits at their apportioned, MACT-based emission rates andother COPCs being emitted at the lesser of their 95% UCL mean their maximum measured emissionrates. The values in these tables express the maximum risks which the facility might legally posebecause they are derived from the maximum emission rates that the MACT regulations will allow. Table 7.1 is for individual cancer risks for the six indirect exposure scenarios described in Chapter 4;Table 7.2 for individual cancer risks due to direct inhalation of the COPCs (two values are includedfor adults because of the different exposure durations assumed for resident adults and subsistencefarming adults); Table 7.3 is for individual hazard quotients for the six indirect exposure scenarios;and Table 7.4 for individual chronic and acute hazard quotients due to direct inhalation of theCOPCs.

The second group of tables contains the estimated cancer risk and hazard quotients based on themodeling of COPCs subject to MACT limits at their maximum measured emission rates and otherCOPCs being emitted at the lesser of their 95% UCL mean their maximum measured emission rates. Those COPCs which were not detected in the measurements modeled as being emitted at theirdetection limits. The values in these tables express the maximum risks which the facility mightactually pose because they are derived from the maximum of the measured emission rates. Table7.5 is for individual cancer risks for the six indirect exposure scenarios described in Chapter 4; Table7.6 for individual cancer risks due to direct inhalation of the COPCs (two values are included foradults because of the different exposure durations assumed for resident adults and subsistencefarming adults); Table 7.7 is for individual hazard quotients for the six indirect exposure scenarios;and Table 7.8 for individual chronic and acute hazard quotients due to direct inhalation of theCOPCs.

The third group of tables contains the estimated cancer risk and hazard quotients based on themodeling of all COPCs at their average measured emission rates, with those COPCs that were notdetected in the measurements modeled as being emitted at 1/2 their detection limits. The values in

7–4

these tables express the risks which the facility most likey poses because they are derived from theaverage measured emission rates. Table 7.9 is for individual cancer risks for the six indirectexposure scenarios described in Chapter 4; Table 7.10 for individual cancer risks due to directinhalation of the COPCs (two values are included for adults because of the different exposuredurations assumed for resident adults and subsistence farming adults); Table 7.11 is for individualhazard quotients for the six indirect exposure scenarios; and Table 7.12 for individual chronic andacute hazard quotients due to direct inhalation of the COPCs.

Finally, Table 7.13 contains the estimated average exposure levels of adults, children, and nursinginfants to PCDDs and PCDFs by indirect pathways. As described in the HHRAP guidance (Section2.3.1.2), these exposures are on a Toxicity Equivalent Quotient, TEQ, basis and are used to evaluatepossible noncancer hazards associated with these compounds by comparing the estimated exposureswith national average background exposure levels of 1 to 3 pg TEQ/kg-day for adults and 60 pgTEQ/kg-day for infants.

7–5

Table 7.1 COPC-specific lifetime cancer risks due to indirect exposure for six exposure scenariosand for COPCs subject to MACT limits modeled at MACT-based emission rates, and other COPCsthe lesser of the 95% UCL mean and the maximum measured rates. Boldfaced compounds are thosesubject to MACT limits.

Cancer Risk, indirect exposure

residentadult

residentchild

farmingadult

farmingchild

fishingadult

fishingchild

Arsenic 1.4 E-8 5.1 E-9 5.5 E-8 1.2 E-8 2.0 E-8 6.0 E-9Beryllium 2.6 E-8 1.6 E-8 3.8 E-8 1.9 E-8 3.6 E-8 1.7 E-8Cadmium 1.5 E-6 4.9 E-7 5.8 E-6 1.3 E-6 4.6 E-6 9.2 E-7Chromium, hexavalent 2.8 E-7 1.0 E-7 4.6 E-6 1.2 E-6 3.0 E-7 1.1 E-7Acrylonitrile 8.7 E-15 3.1 E-15 9.4 E-15 3.1 E-15 2.7 E-14 5.7 E-15Benzene 4.9 E-11 1.3 E-11 1.9 E-10 4.0 E-11 5.0 E-11 1.3 E-11Benz(a)anthracene 1.9 E-10 4.0 E-11 8.7 E-10 1.8 E-10 7.1 E-10 1.1 E-10Benzo(a)pyrene 6.0 E-10 1.1 E-10 7.1 E-9 1.8 E-9 7.6 E-10 1.3 E-10Benzo(b)fluoranthene 2.7 E-10 4.6 E-11 1.6 E-9 3.6 E-10 4.1 E-10 6.6 E-11Benzo(k)fluoranthene 7.6 E-11 1.3 E-11 4.2 E-10 9.6 E-11 8.5 E-11 1.4 E-11Bis(2-ethylhexyl)phthalate

7.9 E-11 2.0 E-11 2.7 E-9 7.1 E-10 1.2 E-9 1.8 E-10

Carbon tetrachloride 8.2 E-14 2.1 E-14 4.0 E-13 8.2 E-14 8.9 E-14 2.2 E-14Chloroform 5.8 E-14 1.5 E-14 2.7 E-13 5.6 E-14 5.9 E-14 1.5 E-14Chrysene 5.4 E-12 1.1 E-12 2.8 E-11 6.6 E-12 1.6 E-11 2.6 E-12Dibenz(ah)anthracene 1.2 E-8 2.1 E-9 2.8 E-7 7.3 E-8 1.2 E-8 2.1 E-9Dichloroethane, 1,2- 4.0 E-11 1.0 E-11 2.0 E-10 4.1 E-11 4.0 E-11 1.0 E-11Dichloroethylene, 1,1- 6.5 E-13 1.7 E-13 3.0 E-12 6.3 E-13 7.0 E-13 1.8 E-13Indeno(1,2,3-cd)pyrene 4.4 E-10 8.6 E-11 3.4 E-8 9.0 E-9 4.5 E-10 8.7 E-11Methylene chloride 2.7 E-11 6.8 E-12 1.3 E-10 2.7 E-11 2.7 E-11 6.8 E-12Tetrachloroethylene 2.0 E-11 5.0 E-12 9.8 E-11 2.0 E-11 2.0 E-11 5.1 E-12Tetrahydrofuran 1.2 E-9 3.1 E-10 5.9 E-9 1.2 E-9 1.2 E-9 3.1 E-10Trichloroethylene 1.6 E-11 4.1 E-12 8.0 E-11 1.6 E-11 1.6 E-11 4.1 E-12PCDDs/PCDFs 2.0 E-7 9.9 E-8 1.6 E-5 2.5 E-6 3.6 E-6 6.1 E-7Coplanar PCBs 2.6 E-12 8.1 E-13 2.9 E-11 6.0 E-12 8.7 E-12 1.7 E-12Total PCBs 2.9 E-13 8.8 E-14 3.2 E-12 6.6 E-13 9.5 E-13 1.9 E-13Sum 2.0 E-6 7.1 E-7 2.7 E-5 5.2 E-6 8.6 E-6 1.7 E-6

7–6

Table 7.2 COPC-specific lifetime cancer risks due to direct inhalation for three exposure scenariosand for COPCs subject to MACT limitsmodeled at MACT-based emission rates, and other COPCsthe lesser of the 95% UCL mean and the maximum measured rates. Boldfaced compounds are thosesubject to MACT limits.

Cancer Risk, inhalation

residentand fishing

adultall children farming

adult

Arsenic 6.4 E-9 2.3 E-9 6.9 E-9Beryllium 4.0 E-10 1.4 E-10 4.3 E-10Cadmium 2.7 E-8 9.5 E-9 2.8 E-8Chromium, hexavalent 1.4 E-8 4.9 E-9 1.5 E-8Acrylonitrile 2.1 E-9 7.6 E-10 2.3 E-9Benzene 3.7 E-9 1.3 E-9 4.0 E-9Benz(a)anthracene 4.8 E-12 1.7 E-12 5.1 E-12Benzo(a)pyrene 5.9 E-12 2.1 E-12 6.3 E-12Benzo(b)fluoranthene 2.5 E-12 8.8 E-13 2.6 E-12Benzo(k)fluoranthene 1.9 E-13 6.7 E-14 2.0 E-13Bis(2-ethylhexyl)phthalate 3.4 E-11 1.2 E-11 3.7 E-11Carbon tetrachloride 3.0 E-12 1.1 E-12 3.3 E-12Chloroform 2.3 E-11 8.4 E-12 2.5 E-11Chrysene 7.4 E-14 2.6 E-14 7.9 E-14Dibenz(ah)anthracene 2.2 E-11 7.7 E-12 2.3 E-11Dichloroethane, 1,2- 6.6 E-10 2.3 E-10 7.0 E-10Dichloroethylene, 1,1- 4.4 E-11 1.6 E-11 4.7 E-11Indeno(1,2,3-cd)pyrene 3.7 E-13 1.3 E-13 3.9 E-13Methylene chloride 2.3 E-10 8.2 E-11 2.5 E-10Tetrachloroethylene 9.8 E-11 3.5 E-11 1.1 E-10Tetrahydrofuran 1.5 E-9 5.5 E-10 1.6 E-9Trichloroethylene 4.8 E-10 1.7 E-10 5.1 E-10sum PCDD/PCDF 1.1 E-8 4.0 E-9 1.2 E-8coplanar PCBs TEQ 1.7 E-12 6.2 E-13 1.8 E-12PCB mixture 1.9 E-13 6.7 E-14 2.0 E-13Sum 6.7 E-8 2.4 E-8 7.2 E-8

7–7

Table 7.3 COPC-specific hazard quotients due to indirect exposure for six exposure scenarios andfor COPCs subject to MACT limits modeled at MACT-based emission rates, and other COPCs thelesser of the 95% UCL mean and the maximum measured rates. Boldfaced compounds are thosesubject to MACT limits.

Hazard Quotient, indirect exposure

residentadult

residentchild

farmadult

farmchild

fishingadult

fishingchild

Antimony 8.4 E-5 1.5 E-4 2.6 E-4 4.1 E-4 1.3 E-4 1.8 E-4Arsenic 7.3 E-5 1.4 E-4 2.2 E-4 3.1 E-4 1.0 E-4 1.6 E-4Barium 5.4 E-6 9.5 E-6 2.0 E-5 3.8 E-5 6.3 E-5 5.0 E-5Beryllium 4.5 E-6 1.4 E-5 4.6 E-6 1.6 E-5 6.2 E-6 1.5 E-5Cadmium 4.9 E-4 7.1 E-4 2.0 E-3 2.8 E-3 1.7 E-3 1.5 E-3Chromium, total 9.2 E-7 9.2 E-7 1.4 E-5 7.7 E-6 4.5 E-6 1.5 E-5Chromium, hexavalent 5.3 E-6 9.7 E-6 6.4 E-5 1.1 E-4 5.7 E-6 1.0 E-5Cobalt 3.5 E-7 7.1 E-7 6.3 E-6 9.1 E-6 3.5 E-7 7.1 E-7Mercuric chloride 8.9 E-4 3.0 E-3 3.1 E-3 7.5 E-3 9.6 E-4 3.1 E-3Methyl mercury 6.0 E-5 1.8 E-4 8.2 E-5 2.6 E-4 5.8 E-1 4.1 E-1Nickel 3.1 E-6 6.1 E-6 2.6 E-5 4.4 E-5 7.5 E-6 9.3 E-6Selenium 1.9 E-6 3.2 E-6 7.5 E-5 1.5 E-4 8.4 E-6 7.8 E-6Silver 7.3 E-6 1.1 E-5 7.2 E-4 1.6 E-3 3.7 E-5 3.2 E-5Thallium 1.7 E-3 3.6 E-3 4.6 E-2 5.2 E-2 1.7 E-3 3.7 E-3Zinc 2.2 E-6 3.7 E-6 6.2 E-6 9.8 E-6 4.2 E-5 3.1 E-5Acenaphthene 2.9 E-9 4.6 E-9 7.2 E-9 1.1 E-8 2.8 E-8 2.2 E-8Acetone 1.2 E-5 1.6 E-5 4.6 E-5 6.3 E-5 1.2 E-5 1.6 E-5Acetonitrile 4.3 E-6 5.5 E-6 1.6 E-5 2.2 E-5 4.3 E-6 5.5 E-6Acetophenone 4.5 E-7 6.5 E-7 1.2 E-6 1.8 E-6 5.2 E-7 7.0 E-7Acrylonitrile 3.8 E-11 6.8 E-11 3.0 E-11 6.8 E-11 1.2 E-10 1.2 E-10 Anthracene 9.1 E-9 1.3 E-8 2.9 E-8 4.6 E-8 7.9 E-8 6.2 E-8Benzaldehyde 2.3 E-7 3.1 E-7 7.8 E-7 1.1 E-6 2.4 E-7 3.2 E-7Benzene 2.3 E-7 3.0 E-7 8.5 E-7 1.2 E-6 2.4 E-7 3.0 E-7Benzyl alcohol 3.3 E-8 5.6 E-8 4.7 E-8 8.3 E-8 3.8 E-8 5.9 E-8Bis(2-ethylhexyl)phthalate 6.6 E-7 8.4 E-7 1.7 E-5 3.0 E-5 1.0 E-5 7.5 E-6Bromomethane 4.3 E-8 5.7 E-8 1.5 E-7 2.1 E-7 4.4 E-8 5.7 E-8Butanol, n- 2.7 E-7 4.2 E-7 6.3 E-7 9.6 E-7 2.9 E-7 4.3 E-7Carbon disulfide 2.3 E-9 3.0 E-9 8.0 E-9 1.1 E-8 2.4 E-9 3.1 E-9Carbon tetrachloride 2.1 E-9 2.7 E-9 7.4 E-9 1.0 E-8 2.3 E-9 2.9 E-9Chlorobenzene 6.7 E-9 8.8 E-9 2.4 E-8 3.3 E-8 8.3 E-9 1.0 E-8Chloroform 2.2 E-9 2.9 E-9 7.8 E-9 1.1 E-8 2.3 E-9 3.0 E-9Cresol, m- 1.0 E-6 1.8 E-6 9.8 E-7 2.0 E-6 1.8 E-6 2.3 E-6Cresol, o- 1.2 E-6 1.9 E-6 2.4 E-6 3.8 E-6 1.8 E-6 2.4 E-6Cresol, p- 4.0 E-6 7.0 E-6 4.8 E-6 9.1 E-6 6.7 E-6 8.9 E-6Cumene 1.1 E-6 1.4 E-6 3.9 E-6 5.4 E-6 1.1 E-6 1.4 E-6

7–8

Table 7.3 (continued) COPC-specific hazard quotients due to indirect exposure for six exposurescenarios and for COPCs subject to MACT limits modeled at MACT-based emission rates, and otherCOPCs the lesser of the 95% UCL mean and the maximum measured rates. Boldfaced compoundsare those subject to MACT limits.


residentadult

residentchild

farmadult

farmchild

fishingadult

fishingchild

Cyclohexanone 1.3 E-9 1.8 E-9 3.7 E-9 5.3 E-9 1.3 E-9 1.9 E-9Dibenzofuran 1.5 E-7 2.2 E-7 4.0 E-7 6.4 E-7 1.5 E-7 2.2 E-7Dichloroethane, 1,2- 3.6 E-7 4.6 E-7 1.3 E-6 1.8 E-6 3.6 E-7 4.6 E-7Dichloroethylene, 2.8 E-10 3.7 E-10 9.8 E-10 1.4 E-9 3.0 E-10 3.8 E-10 Dimethylphenol, 2,4- 1.6 E-7 2.8 E-7 1.4 E-7 3.0 E-7 4.0 E-7 4.5 E-7Di-n-butylphthalate 4.0 E-9 5.8 E-9 1.5 E-8 2.3 E-8 1.3 E-7 9.4 E-8Ethylacetate 4.3 E-9 5.6 E-9 1.5 E-8 2.1 E-8 4.3 E-9 5.7 E-9Ethylbenzene 2.6 E-7 3.3 E-7 9.6 E-7 1.3 E-6 2.6 E-7 3.4 E-7Ethyl ether 3.6 E-10 4.7 E-10 1.3 E-9 1.8 E-9 3.6 E-10 4.7 E-10Fluoranthene 9.2 E-8 1.3 E-7 1.9 E-7 3.0 E-7 6.4 E-6 4.6 E-6Fluorene 1.0 E-8 1.7 E-8 2.6 E-8 4.3 E-8 1.5 E-7 1.2 E-7Hexanone, 2- 2.2 E-8 3.0 E-8 7.8 E-8 1.1 E-7 2.3 E-8 3.0 E-8Methanol 1.1 E-7 1.4 E-7 4.1 E-7 5.6 E-7 1.1 E-7 1.4 E-7Methyl ethyl ketone 2.5 E-6 3.2 E-6 9.2 E-6 1.3 E-5 2.5 E-6 3.2 E-6Methyl isobutyl ketone 1.5 E-5 1.9 E-5 5.5 E-5 7.5 E-5 1.5 E-5 1.9 E-5Methylene chloride 1.4 E-7 1.8 E-7 5.2 E-7 7.1 E-7 1.4 E-7 1.8 E-7Naphthalene 1.1 E-7 1.5 E-7 3.5 E-7 5.0 E-7 2.6 E-7 2.5 E-7Phenol 7.4 E-7 1.2 E-6 1.6 E-6 2.5 E-6 8.8 E-7 1.3 E-6Pyrene 3.3 E-7 4.9 E-7 6.9 E-7 1.1 E-6 2.0 E-5 1.4 E-5Pyridine 5.0 E-8 6.4 E-8 1.9 E-7 2.6 E-7 5.0 E-8 6.5 E-8Styrene 2.2 E-7 2.8 E-7 8.2 E-7 1.1 E-6 2.2 E-7 2.9 E-7Tetrachloroethylene 8.8 E-8 1.1 E-7 3.3 E-7 4.5 E-7 8.9 E-8 1.1 E-7Tetrahydrofuran 1.8 E-6 2.4 E-6 6.8 E-6 9.3 E-6 1.8 E-6 2.4 E-6Toluene 6.1 E-7 7.8 E-7 2.3 E-6 3.1 E-6 6.1 E-7 7.8 E-7Trichloroethane,1,1,1- 2.3 E-7 2.9 E-7 8.4 E-7 1.2 E-6 2.3 E-7 2.9 E-7Trichloroethylene 5.7 E-7 7.3 E-7 2.1 E-6 2.9 E-6 5.7 E-7 7.3 E-7Trimethylbenzene,1,2,4 1.1 E-9 1.4 E-9 3.9 E-9 5.4 E-9 2.2 E-9 2.2 E-9Trimethylbenzene,1,3,5 3.7 E-10 5.0 E-10 1.3 E-9 1.8 E-9 7.4 E-10 7.6 E-10Xylene,m- 2.9 E-8 3.8 E-8 1.1 E-7 1.5 E-7 3.0 E-8 3.8 E-8Xylene,o- 2.9 E-8 3.7 E-8 1.1 E-7 1.5 E-7 2.9 E-8 3.7 E-8Xylene,p- 3.0 E-8 3.8 E-8 1.1 E-7 1.5 E-7 3.0 E-8 3.8 E-8Total PCBs 1.7 E-8 2.6 E-8 1.4 E-7 1.9 E-7 5.5 E-8 5.5 E-8Sum (Hazard Index) 3.4 E-3 8.0 E-3 5.4 E-2 6.6 E-2 5.9 E-1 4.2 E-1

7–9

Table 7.4 COPC-specific chronic and acute hazard quotients due to inhalation exposure scenarios andfor COPCs subject to MACT limits modeled at MACT-based emission rates, and other COPCs thelesser of the 95% UCL mean and the maximum measured rates. Boldfaced compounds are thosesubject to MACT limits.

Chronic Hazard Quotient, inhalation Acute HazardQuotient, inhalationadult child

Antimony 2.0 E-6 4.4 E-6 3.1 E-7Arsenic 2.6 E-6 5.7 E-6 2.4 E-3Barium 7.6 E-5 1.7 E-4 4.0 E-6Beryllium 1.6 E-8 3.5 E-8 5.1 E-6Cadmium 1.4 E-4 3.1 E-4 1.5 E-4Chromium, total 1.1 E-8 2.5 E-8 6.4 E-6Chromium, hexavalent 1.5 E-5 3.4 E-5 2.3 E-6Cobalt 1.1 E-8 2.4 E-8 —Copper 7.2 E-6 1.6 E-5 2.8 E-5Lead — — 1.0 E-3Manganese 4.4 E-4 9.9 E-4 —Mercuric chloride 2.6 E-4 5.9 E-4 2.7 E-2 Mercury 4.9 E-4 1.1 E-3 1.4 E-2 Nickel 9.6 E-8 2.1 E-7 1.8 E-4Selenium 7.7 E-8 1.7 E-7 7.6 E-5Silver 2.4 E-7 5.3 E-7 2.3 E-6Thallium 5.6 E-5 1.2 E-4 1.9 E-5Vanadium — — 3.3 E-5Zinc 3.1 E-8 6.9 E-8 —Chlorine 2.6E-01 5.7E-01 —Hydrogen chloride 1.2E-02 2.6E-02 —Acenaphthene 5.9 E-9 1.3 E-8 —Acetone 2.3 E-5 5.2 E-5 —Acetonitrile 2.8 E-5 6.3 E-5 1.6 E-5Acetophenone 8.9 E-8 2.0 E-7 1.8 E-7Acrylonitrile 2.9 E-5 6.5 E-5 4.6 E-7Anthracene 1.6 E-9 3.6 E-9 —Benzaldehyde 1.3 E-7 2.8 E-7 —Benzene 1.4 E-5 3.1 E-5 2.8 E-4Benzo(a)pyrene — — 9.1 E-10Benzyl alcohol 1.2 E-9 2.7 E-9 3.5 E-9Bromomethane 3.3 E-6 7.4 E-6 4.9 E-8Carbon disulfide 1.5 E-7 3.4 E-7 5.9 E-6Carbon tetrachloride 1.5 E-7 3.3 E-7 5.1 E-10Chlorobenzene 1.6 E-7 3.4 E-7 4.6 E-9Chloroform 5.6 E-6 1.3 E-5 8.1 E-7Chrysene — — 3.8 E-8Cresol, m- 6.3 E-8 1.4 E-7 2.9 E-8

7–10

Table 7.4 (continued) COPC-specific chronic and acute hazard quotients due to inhalation exposurescenarios and for COPCs subject to MACT limits modeled at MACT-based emission rates, and otherCOPCs the lesser of the 95% UCL mean and the maximum measured rates. Boldfaced compoundsare those subject to MACT limits.


Cresol, o- 2.0 E-6 4.4 E-6 1.5 E-8Cresol, p- 2.0 E-6 4.5 E-6 2.9 E-8Cumene 6.2 E-5 1.4 E-4 —Dibenz(ah)anthracene — — 1.1 E-10Dibenzofuran 5.4 E-7 1.2 E-6 —Dichloroethane,1,2- 4.7 E-6 1.0 E-5 1.1 E-8Dichloroethylene,1,1- 5.0 E-8 1.1 E-7 3.5 E-9Dimethylphenol,2,4- 3.2 E-8 7.2 E-8 —Di-n-butylphthalate 2.0 E-9 4.4 E-9 —Ethylbenzene 4.4 E-6 9.8 E-6 2.7 E-6Fluoranthene 7.6 E-9 1.7 E-8 —Fluorene 8.6 E-9 1.9 E-8 —Glycol Ethers 2.4 E-5 5.4 E-5 2.4 E-3Hexane 1.2 E-4 2.7 E-4 —Hexanone, 2- 3.5 E-6 7.7 E-6 —Methanol 4.1 E-6 9.0 E-6 1.5 E-3Methyl tert-butyl ether 4.3 E-8 9.6 E-8 —Methyl ethyl ketone 8.7 E-6 1.9 E-5 5.5 E-4Methyl isobutyl ketone 4.7 E-5 1.1 E-4 4.6 E-6Methylene chloride 3.2 E-7 7.0 E-7 8.5 E-5Naphthalene 8.5 E-6 1.9 E-5 5.5 E-8Phenol 5.5 E-7 1.2 E-6 6.1 E-5Propanol,2- 7.2 E-7 1.6 E-6 2.7 E-4Pyrene 9.8 E-9 2.2 E-8 —Pyridine 7.6 E-6 1.7 E-5 1.7 E-7Styrene 2.7 E-6 5.9 E-6 4.1 E-5Tetrachloroethylene 8.1 E-7 1.8 E-6 8.9 E-10Tetrahydrofuran 9.3 E-6 2.1 E-5 —Toluene 5.3 E-5 1.2 E-4 2.3 E-4Trichloroethane, 1,1,1- 1.7 E-5 3.9 E-5 9.7 E-10Trichloroethylene 2.5 E-5 5.5 E-5 3.5 E-7Trimethylbenzene, 1,2,4- 9.8 E-7 2.2 E-6 —Trimethylbenzene, 1,3,5- 4.7 E-7 1.0 E-6 —Xylene, m- 9.5 E-7 2.1 E-6 1.0 E-4Xylene, o- 9.6 E-7 2.1 E-6 1.0 E-4Xylene, p- 9.6 E-7 2.1 E-6 7.9 E-6PCB mixture 8.8 E-9 2.0 E-8 —Sum (Hazard Index) 2.7 E-1 6.0 E-1 5.0 E-2

7–11

Table 7.5 COPC-specific lifetime cancer risks due to indirect exposure for six exposure scenarios andmaximum measured emission rates for COPCs subject to MACT limits, and other COPCs emitted atthe lesser of the 95% UCL mean and the maximum measured rates. Boldfaced compounds are thosesubject to MACT limits.


residentadult

residentchild

farmingadult

farmingchild

fishingadult

fishingchild


7.9 E-11 2.0 E-11 2.7 E-9 7.1 E-10 1.2 E-9 1.8 E-10

Carbon tetrachloride 8.2 E-14 2.1 E-14 4.0 E-13 8.2 E-14 8.9 E-14 2.2 E-14Chloroform 5.8 E-14 1.5 E-14 2.7 E-13 5.6 E-14 5.9 E-14 1.5 E-14Chrysene 5.4 E-12 1.1 E-12 2.8 E-11 6.6 E-12 1.6 E-11 2.6 E-12Dibenz(ah)anthracene 1.2 E-8 2.1 E-9 2.8 E-7 7.3 E-8 1.2 E-8 2.1 E-9Dichloroethane,1,2- 4.0 E-11 1.0 E-11 2.0 E-10 4.1 E-11 4.0 E-11 1.0 E-11Dichloroethylene,1,1- 6.5 E-13 1.7 E-13 3.0 E-12 6.3 E-13 7.0 E-13 1.8 E-13Indeno(1,2,3-cd)pyrene 4.4 E-10 8.6 E-11 3.4 E-8 9.0 E-9 4.5 E-10 8.7 E-11Methylene chloride 2.7 E-11 6.8 E-12 1.3 E-10 2.7 E-11 2.7 E-11 6.8 E-12Tetrachloroethylene 2.0 E-11 5.0 E-12 9.8 E-11 2.0 E-11 2.0 E-11 5.1 E-12Tetrahydrofuran 1.2 E-9 3.1 E-10 5.9 E-9 1.2 E-9 1.2 E-9 3.1 E-10Trichloroethylene 1.6 E-11 4.1 E-12 8.0 E-11 1.6 E-11 1.6 E-11 4.1 E-12PCDDs/PCDFs 6.0 E-9 3.0 E-9 5.0 E-7 7.9 E-8 1.1 E-7 1.9 E-8Coplanar PCBs 2.6 E-12 8.1 E-13 2.9 E-11 5.9 E-12 8.7 E-12 1.7 E-12Total PCBs 2.9 E-13 8.8 E-14 3.1 E-12 6.4 E-13 9.5 E-13 1.9 E-13Sum 1.3 E-7 4.7 E-8 2.3 E-6 5.5 E-7 3.0 E-7 7.3 E-8

7–12

Table 7.6 COPC-specific lifetime cancer risks due to direct inhalation for three exposure scenariosand maximum measured emission rates for COPCs subject to MACT limits, and other COPCsemitted at the lesser of the 95% UCL mean and the maximum measured rates. Boldfaced compoundsare those subject to MACT limits.


residentand fishing

adultall children farming

adult

Arsenic 1.8 E-9 6.4 E-10 1.9 E-9Beryllium 1.0 E-10 3.6 E-11 1.1 E-10Cadmium 3.8 E-10 1.4 E-10 4.1 E-10Chromium, hexavalent 4.1 E-9 1.5 E-9 4.4 E-9Acrylonitrile 2.1 E-9 7.6 E-10 2.3 E-9Benzene 3.7 E-9 1.3 E-9 4.0 E-9Benz(a)anthracene 4.8 E-12 1.7 E-12 5.1 E-12Benzo(a)pyrene 5.9 E-12 2.1 E-12 6.3 E-12Benzo(b)fluoranthene 2.5 E-12 8.8 E-13 2.6 E-12Benzo(k)fluoranthene 1.9 E-13 6.7 E-14 2.0 E-13Bis(2-ethylhexyl)phthalate 3.4 E-11 1.2 E-11 3.7 E-11Carbon tetrachloride 3.0 E-12 1.1 E-12 3.3 E-12Chloroform 2.3 E-11 8.4 E-12 2.5 E-11Chrysene 7.4 E-14 2.6 E-14 7.9 E-14Dibenz(ah)anthracene 2.2 E-11 7.7 E-12 2.3 E-11Dichloroethane,1,2- 6.6 E-10 2.3 E-10 7.0 E-10Dichloroethylene,1,1- 4.4 E-11 1.6 E-11 4.7 E-11Indeno(1,2,3-cd)pyrene 3.7 E-13 1.3 E-13 3.9 E-13Methylene chloride 2.3 E-10 8.2 E-11 2.5 E-10Tetrachloroethylene 9.8 E-11 3.5 E-11 1.1 E-10Tetrahydrofuran 1.5 E-9 5.5 E-10 1.6 E-9Trichloroethylene 4.8 E-10 1.7 E-10 5.1 E-10sum PCDD/PCDF 3.3 E-10 1.2 E-10 3.6 E-10coplanar PCBsTEQ 1.7 E-12 6.2 E-13 1.8 E-12PCB mixture 1.9 E-13 6.7 E-14 2.0 E-13Sum 1.6 E-8 5.6 E-9 1.7 E-8

7–13

Table 7.7 COPC-specific hazard quotients due to indirect exposure for six exposure scenarios andmaximum measured emission rates for COPCs subject to MACT limits, and other COPCs emitted atthe lesser of the 95% UCL mean and the maximum measured rates .Boldfaced compounds are thosesubject to MACT limits.


residentadult

residentchild farm adult farm child fishing

adultfishingchild

Antimony 3.0 E-5 5.4 E-5 9.3 E-5 1.5 E-4 4.8 E-5 6.6 E-5Arsenic 2.0 E-5 3.8 E-5 6.1 E-5 8.7 E-5 2.9 E-5 4.4 E-5Barium 1.7 E-6 3.0 E-6 6.5 E-6 1.2 E-5 2.0 E-5 1.6 E-5Beryllium 1.2 E-6 3.5 E-6 1.2 E-6 4.1 E-6 1.6 E-6 3.8 E-6Cadmium 7.0 E-6 1.0 E-5 2.9 E-5 4.1 E-5 2.4 E-5 2.2 E-5Chromium, total 2.4 E-7 2.4 E-7 3.7 E-6 2.0 E-6 1.2 E-6 4.0 E-6Chromium, hexavalent 1.6 E-6 2.9 E-6 1.9 E-5 3.3 E-5 1.7 E-6 2.9 E-6Cobalt 1.1 E-7 2.2 E-7 2.0 E-6 2.8 E-6 1.1 E-7 2.2 E-7Mercuric chloride 2.9 E-5 9.3 E-5 9.0 E-5 2.2 E-4 2.9 E-5 9.3 E-5Methyl mercury 1.8 E-6 5.3 E-6 2.2 E-6 7.3 E-6 1.8 E-2 1.3 E-2Nickel 9.6 E-7 1.9 E-6 8.2 E-6 1.4 E-5 2.3 E-6 2.9 E-6Selenium 6.7 E-7 1.0 E-6 2.2 E-5 4.3 E-5 2.4 E-6 2.2 E-6Silver 3.4 E-6 5.3 E-6 3.3 E-4 7.2 E-4 1.7 E-5 1.5 E-5Thallium 6.7 E-4 1.4 E-3 1.8 E-2 2.0 E-2 6.8 E-4 1.5 E-3Zinc 8.1 E-7 1.4 E-6 2.3 E-6 3.6 E-6 1.5 E-5 1.2 E-5Acenaphthene 2.9 E-9 4.6 E-9 7.2 E-9 1.1 E-8 2.8 E-8 2.2 E-8 Acetone 1.2 E-5 1.6 E-5 4.6 E-5 6.3 E-5 1.2 E-5 1.6 E-5 Acetonitrile 4.3 E-6 5.5 E-6 1.6 E-5 2.2 E-5 4.3 E-6 5.5 E-6 Acetophenone 4.5 E-7 6.5 E-7 1.2 E-6 1.8 E-6 5.2 E-7 7.0 E-7 Acrylonitrile 3.8 E-11 6.8 E-11 3.0 E-11 6.8 E-11 1.2 E-10 1.2 E-10 Anthracene 9.1 E-9 1.3 E-8 2.9 E-8 4.6 E-8 7.9 E-8 6.2 E-8 Benzaldehyde 2.3 E-7 3.1 E-7 7.8 E-7 1.1 E-6 2.4 E-7 3.2 E-7 Benzene 2.3 E-7 3.0 E-7 8.5 E-7 1.2 E-6 2.4 E-7 3.0 E-7 Benzyl alcohol 3.3 E-8 5.6 E-8 4.7 E-8 8.3 E-8 3.8 E-8 5.9 E-8 Bis(2-ethylhexyl)phthalate 6.6 E-7 8.4 E-7 1.7 E-5 3.0 E-5 1.0 E-5 7.5 E-6 Bromomethane 4.3 E-8 5.7 E-8 1.5 E-7 2.1 E-7 4.4 E-8 5.7 E-8 Butanol, n- 2.7 E-7 4.2 E-7 6.3 E-7 9.6 E-7 2.9 E-7 4.3 E-7 Carbon disulfide 2.3 E-9 3.0 E-9 8.0 E-9 1.1 E-8 2.4 E-9 3.1 E-9 Carbon tetrachloride 2.1 E-9 2.7 E-9 7.4 E-9 1.0 E-8 2.3 E-9 2.9 E-9 Chlorobenzene 6.7 E-9 8.8 E-9 2.4 E-8 3.3 E-8 8.3 E-9 1.0 E-8 Chloroform 2.2 E-9 2.9 E-9 7.8 E-9 1.1 E-8 2.3 E-9 3.0 E-9 Cresol, m- 1.0 E-6 1.8 E-6 9.8 E-7 2.0 E-6 1.8 E-6 2.3 E-6 Cresol, o- 1.2 E-6 1.9 E-6 2.4 E-6 3.8 E-6 1.8 E-6 2.4 E-6 Cresol, p- 4.0 E-6 7.0 E-6 4.8 E-6 9.1 E-6 6.7 E-6 8.9 E-6 Cumene 1.1 E-6 1.4 E-6 3.9 E-6 5.4 E-6 1.1 E-6 1.4 E-6

7–14

Table 7.7 (continued) COPC-specific hazard quotients due to indirect exposure for six exposurescenarios and measured emission rates for COPCs subject to MACT limits, and other COPCs emittedat the lesser of the 95% UCL mean and the maximum measured rates. Boldfaced compounds arethose subject to MACT limits.


residentadult

residentchild

farmadult

farmchild

fishingadult

fishingchild

Cyclohexanone 1.3 E-9 1.8 E-9 3.7 E-9 5.3 E-9 1.3 E-9 1.9 E-9 Dibenzofuran 1.5 E-7 2.2 E-7 4.0 E-7 6.4 E-7 1.5 E-7 2.2 E-7Dichloroethane, 1,2- 3.6 E-7 4.6 E-7 1.3 E-6 1.8 E-6 3.6 E-7 4.6 E-7 Dichloroethylene, 2.8 3.7 E-10 9.8 E-10 1.4 E-9 3.0 E-10 3.8 E-10 Dimethylphenol, 2,4- 1.6 E-7 2.8 E-7 1.4 E-7 3.0 E-7 4.0 E-7 4.5 E-7 Di-n-butylphthalate 4.0 E-9 5.8 E-9 1.5 E-8 2.3 E-8 1.3 E-7 9.4 E-8 Ethylacetate 4.3 E-9 5.6 E-9 1.5 E-8 2.1 E-8 4.3 E-9 5.7 E-9 Ethylbenzene 2.6 E-7 3.3 E-7 9.6 E-7 1.3 E-6 2.6 E-7 3.4 E-7 Ethyl ether 3.6 E-10 4.7 E-10 1.3 E-9 1.8 E-9 3.6 E-10 4.7 E-10Fluoranthene 9.2 E-8 1.3 E-7 1.9 E-7 3.0 E-7 6.4 E-6 4.6 E-6Fluorene 1.0 E-8 1.7 E-8 2.6 E-8 4.3 E-8 1.5 E-7 1.2 E-7Hexanonoe, 2- 2.2 E-8 3.0 E-8 7.8 E-8 1.1 E-7 2.3 E-8 3.0 E-8Methanol 1.1 E-7 1.4 E-7 4.1 E-7 5.6 E-7 1.1 E-7 1.4 E-7Methyl ethyl ketone 2.5 E-6 3.2 E-6 9.2 E-6 1.3 E-5 2.5 E-6 3.2 E-6Methyl isobutyl ketone 1.5 E-5 1.9 E-5 5.5 E-5 7.5 E-5 1.5 E-5 1.9 E-5Methylene chloride 1.4 E-7 1.8 E-7 5.2 E-7 7.1 E-7 1.4 E-7 1.8 E-7Naphthalene 1.1 E-7 1.5 E-7 3.5 E-7 5.0 E-7 2.6 E-7 2.5 E-7Phenol 7.4 E-7 1.2 E-6 1.6 E-6 2.5 E-6 8.8 E-7 1.3 E-6Pyrene 3.3 E-7 4.9 E-7 6.9 E-7 1.1 E-6 2.0 E-5 1.4 E-5Pyridine 5.0 E-8 6.4 E-8 1.9 E-7 2.6 E-7 5.0 E-8 6.5 E-8Styrene 2.2 E-7 2.8 E-7 8.2 E-7 1.1 E-6 2.2 E-7 2.9 E-7Tetrachloroethylene 8.8 E-8 1.1 E-7 3.3 E-7 4.5 E-7 8.9 E-8 1.1 E-7Tetrahydrofuran 1.8 E-6 2.4 E-6 6.8 E-6 9.3 E-6 1.8 E-6 2.4 E-6Toluene 6.1 E-7 7.8 E-7 2.3 E-6 3.1 E-6 6.1 E-7 7.8 E-7Trichloroethane, 1,1,1- 2.3 E-7 2.9 E-7 8.4 E-7 1.2 E-6 2.3 E-7 2.9 E-7Trichloroethylene 5.7 E-7 7.3 E-7 2.1 E-6 2.9 E-6 5.7 E-7 7.3 E-7Trimethylbenzene, 1,2,4 1.1 E-9 1.4 E-9 3.9 E-9 5.4 E-9 2.2 E-9 2.2 E-9Trimethylbenzene, 1,3,5 3.7 E-10 5.0 E-10 1.3 E-9 1.8 E-9 7.4 E-10 7.6 E-10Xylene, m- 2.9 E-8 3.8 E-8 1.1 E-7 1.5 E-7 3.0 E-8 3.8 E-8Xylene, o- 2.9 E-8 3.7 E-8 1.1 E-7 1.5 E-7 2.9 E-8 3.7 E-8Xylene, p- 3.0 E-8 3.8 E-8 1.1 E-7 1.5 E-7 3.0 E-8 3.8 E-8Total PCBs 1.7 E-8 2.6 E-8 1.4 E-7 1.9 E-7 5.5 E-8 5.5 E-8Sum (Hazard Index) 8.2 E-4 1.7 E-3 1.9 E-2 2.2 E-2 1.9 E-2 1.5 E-2

7–15

Table 7.8 COPC-specific chronic and acute hazard quotients due to inhalation exposure scenarios andmaximum measured emission rates for COPCs subject to MACT limits, and other COPCs emitted atthe lesser of the 95% UCL mean and the maximum measured rates. Boldfaced compounds are thosesubject to MACT limits.


Antimony 7.1 E-7 1.6 E-6 1.1 E-7Arsenic 7.1 E-7 1.6 E-6 6.7 E-4Barium 2.4 E-5 5.3 E-5 1.3 E-6Beryllium 4.0 E-9 8.9 E-9 1.3 E-6Cadmium 2.0 E-6 4.4 E-6 2.2 E-6Chromium, total 2.9 E-9 6.4 E-9 1.7 E-6Chromium, hexavalent 4.6 E-6 1.0 E-5 6.9 E-7Cobalt 3.4 E-9 7.5 E-9 —Copper 2.8 E-6 6.1 E-6 1.1 E-5Lead — — 1.4 E-5Manganese 2.1 E-4 4.7 E-4 —Mercuric chloride 5.8 E-6 1.3 E-5 6.0 E-4Mercury 5.3 E-6 1.2 E-5 1.5 E-4Nickel 2.9 E-8 6.5 E-8 5.6 E-5Selenium 2.2 E-8 4.9 E-8 2.2 E-5Silver 1.1 E-7 2.4 E-7 1.1 E-6Thallium 2.2 E-5 4.9 E-5 7.4 E-6Vanadium — — 1.1 E-5Zinc 1.1 E-8 2.5 E-8 —Chlorine 4.9 E-3 1.1 E-2 —Hydrogen chloride 2.4 E-4 5.2 E-4 —Acenaphthene 5.9 E-9 1.3 E-8 —Acetone 2.3 E-5 5.2 E-5 —Acetonitrile 2.8 E-5 6.3 E-5 1.6 E-5Acetophenone 8.9 E-8 2.0 E-7 1.8 E-7Acrylonitrile 2.9 E-5 6.5 E-5 4.6 E-7Anthracene 1.6 E-9 3.6 E-9 —Benzaldehyde 1.3 E-7 2.8 E-7 —Benzene 1.4 E-5 3.1 E-5 2.8 E-4Benzo(a)pyrene — — 9.1 E-10Benzylalcohol 1.2 E-9 2.7 E-9 3.5 E-9Bromomethane 3.3 E-6 7.4 E-6 4.9 E-8Carbon disulfide 1.5 E-7 3.4 E-7 5.9 E-6Carbon tetrachloride 1.5 E-7 3.3 E-7 5.1 E-10Chlorobenzene 1.6 E-7 3.4 E-7 4.6 E-9Chloroform 5.6 E-6 1.3 E-5 8.1 E-7Chrysene — — 3.8 E-8Cresol, m- 6.3 E-8 1.4 E-7 2.9 E-8

7–16

Table 7.8 (continued) COPC-specific chronic and acute hazard quotients due to inhalation exposurescenarios and measured emission rates for COPCs subject to MACT limits, and other COPCs emittedat the lesser of the 95% UCL mean and the maximum measured rates. Boldfaced compounds arethose subject to MACT limits.


Cresol, o- 2.0 E-6 4.4 E-6 1.5 E-8Cresol, p- 2.0 E-6 4.5 E-6 2.9 E-8Cumene 6.2 E-5 1.4 E-4 —Dibenz(ah)anthracene — — 1.1 E-10Dibenzofuran 5.4 E-7 1.2 E-6 —Dichloroethane, 1,2- 4.7 E-6 1.0 E-5 1.1 E-8Dichloroethylene, 1,1- 5.0 E-8 1.1 E-7 3.5 E-9Dimethylphenol, 2,4- 3.2 E-8 7.2 E-8 —Di-n-butylphthalate 2.0 E-9 4.4 E-9 —Ethylbenzene 4.4 E-6 9.8 E-6 2.7 E-6Fluoranthene 7.6 E-9 1.7 E-8 —Fluorene 8.6 E-9 1.9 E-8 —Glycol ethers 6.3 E-7 1.4 E-6 1.6 E-3Hexane 3.1 E-6 7.0 E-6 —Hexanone, 2- 3.5 E-6 7.7 E-6 —Methanol 2.7 E-6 5.9 E-6 1.3 E-3Methyl tert-butyl ether 1.1 E-9 2.5 E-9 —Methyl ethyl ketone 8.7 E-6 1.9 E-5 5.5 E-4Methyl isobutyl ketone 4.7 E-5 1.1 E-4 4.6 E-6Methylene chloride 3.2 E-7 7.0 E-7 8.5 E-5Naphthalene 8.5 E-6 1.9 E-5 5.5 E-8Phenol 5.5 E-7 1.2 E-6 6.1 E-5Propanol, 2- 1.9 E-8 4.2 E-8 7.0 E-6Pyrene 9.8 E-9 2.2 E-8 —Pyridine 7.6 E-6 1.7 E-5 1.7 E-7Styrene 2.7 E-6 5.9 E-6 4.1 E-5Tetrachloroethylene 8.1 E-7 1.8 E-6 8.9E-10Tetrahydrofuran 4.9 E-6 1.1 E-5 —Toluene 5.3 E-5 1.2 E-4 2.3 E-4Trichloroethane,1,1,1- 1.7 E-5 3.9 E-5 9.7E-10Trichloroethylene 2.5 E-5 5.5 E-5 3.5 E-7Trimethylbenzene, 1,2,4- 9.8 E-7 2.2 E-6 —Trimethylbenzene, 1,3,5- 4.7 E-7 1.0 E-6 —Xylene, m- 9.5 E-7 2.1 E-6 1.0 E-4Xylene, o- 9.6 E-7 2.1 E-6 1.0 E-4Xylene, p- 9.6 E-7 2.1 E-6 7.9 E-6PCB mixture 8.8E-9 2.0E-8 —Sum (Hazard Index) 5.8 E-3 1.3 E-2 6.0 E-3

7–17

Table 7.9 COPC-specific lifetime cancer risks due to indirect exposure for six exposure scenarios andfor all COPCs modeled at their average measured emission rates. Boldfaced compounds are thosesubject to MACT limits.


residentadult

residentchild

farmingadult

farmingchild

fishingadult

fishingchild


5.7 E-11 1.4 E-11 1.9 E-9 5.1 E-10 8.7 E-10 1.3 E-10

Carbon tetrachloride 7.4 E-14 1.9 E-14 3.6 E-13 7.4 E-14 8.1 E-14 2.0 E-14Chloroform 2.3 E-14 6.0 E-15 1.1 E-13 2.2 E-14 2.3 E-14 6.1 E-15Chrysene 5.1 E-12 1.0 E-12 2.7 E-11 6.2 E-12 1.5 E-11 2.5 E-12Dibenz(ah)anthracene 6.3 E-9 1.2 E-9 1.5 E-7 4.0 E-8 6.4 E-9 1.2 E-9Dichloroethane,1,2- 4.0 E-11 1.0 E-11 2.0 E-10 4.1 E-11 4.0 E-11 1.0 E-11Dichloroethylene,1,1- 2.5 E-13 6.6 E-14 1.2 E-12 2.4 E-13 2.7 E-13 6.9 E-14Indeno(1,2,3-cd)pyrene 3.1 E-10 6.0 E-11 2.3 E-8 6.2 E-9 3.1 E-10 6.0 E-11Methylene chloride 2.7 E-11 6.8 E-12 1.3 E-10 2.7 E-11 2.7 E-11 6.8 E-12Tetrachloroethylene 2.0 E-11 5.0 E-12 9.7 E-11 2.0 E-11 2.0 E-11 5.0 E-12Tetrahydrofuran 1.2 E-9 3.1 E-10 5.9 E-9 1.2 E-9 1.2 E-9 3.1 E-10Trichloroethylene 1.6 E-11 4.1 E-12 8.0 E-11 1.6 E-11 1.6 E-11 4.1 E-12PCDDs/PCDFs 2.9 E-9 1.5 E-9 2.5 E-7 3.9 E-8 5.4 E-8 9.1 E-9CoplanarPCBs 2.6 E-12 8.1 E-13 2.9 E-11 5.9 E-12 8.7 E-12 1.7 E-12TotalPCBs 2.9 E-13 8.8 E-14 3.1 E-12 6.4 E-13 9.5 E-13 1.9 E-13Sum 7.2 E-8 2.7 E-8 1.1 E-6 2.7 E-7 1.8 E-7 4.3 E-8

7–18

Table 7.10 COPC-specific lifetime cancer risks due to direct inhalation for three exposure scenariosand for all COPCs modeled at their average measured emission rates. Boldfaced compounds arethose subject to MACT limits.


resident andfishingadult

all children farmingadult

Arsenic 1.6 E-9 5.8 E-10 1.7 E-9Beryllium 1.0 E-10 3.6 E-11 1.1 E-10Cadmium 3.5 E-10 1.3 E-10 3.8 E-10Chromium, hexavalent 1.8 E-9 6.3 E-10 1.9 E-9Acrylonitrile 1.4 E-9 5.0 E-10 1.5 E-9Benzene 3.5 E-9 1.3 E-9 3.8 E-9Benz(a)anthracene 4.6 E-12 1.6 E-12 4.9 E-12Benzo(a)pyrene 5.6 E-12 2.0 E-12 6.0 E-12Benzo(b)fluoranthene 2.0 E-12 7.0 E-13 2.1 E-12Benzo(k)fluoranthene 7.5 E-14 2.7 E-14 8.1 E-14Bis(2-ethylhexyl)phthalate 2.4 E-11 8.7 E-12 2.6 E-11Carbon tetrachloride 2.8 E-12 9.8 E-13 3.0 E-12Chloroform 9.2 E-12 3.3 E-12 9.9 E-12Chrysene 7.0 E-14 2.5 E-14 7.5 E-14Dibenz(ah)anthracene 1.2 E-11 4.2 E-12 1.3 E-11Dichloroethane,1,2- 6.6 E-10 2.3 E-10 7.0 E-10Dichloroethylene,1,1- 1.7 E-11 6.1 E-12 1.8 E-11Indeno(1,2,3-cd)pyrene 2.5 E-13 9.1 E-14 2.7 E-13Methylene chloride 2.3 E-10 8.2 E-11 2.5 E-10Tetrachloroethylene 9.8 E-11 3.5 E-11 1.0 E-10Tetrahydrofuran 1.5 E-9 5.5 E-10 1.6 E-9Trichloroethylene 4.8 E-10 1.7 E-10 5.1 E-10sumPCDD/PCDF 1.6 E-10 5.8 E-11 1.7 E-10coplanarPCBsTEQ 1.7 E-12 6.2 E-13 1.8 E-12PCBmixture 1.9 E-13 6.7 E-14 2.0 E-13Sum 1.2 E-8 4.3 E-9 1.3 E-8

7–19

Table 7.11 COPC-specific hazard quotients due to indirect exposure for six exposure scenarios andfor all COPCs modeled at their average measured emission rates. Boldfaced compounds are thosesubject to MACT limits.


residentadult


adultfishingchild

Antimony 2.4 E-5 4.3 E-5 7.5 E-5 1.2 E-4 3.8 E-5 5.3 E-5Arsenic 1.8 E-5 3.4 E-5 5.5 E-5 7.9 E-5 2.6 E-5 4.0 E-5Barium 1.6 E-6 2.8 E-6 5.9 E-6 1.1 E-5 1.8 E-5 1.4 E-5Beryllium 1.1 E-6 3.5 E-6 1.2 E-6 4.1 E-6 1.6 E-6 3.8 E-6Cadmium 6.5 E-6 9.5 E-6 2.7 E-5 3.8 E-5 2.2 E-5 2.0 E-5Chromium, total 2.3 E-7 2.3 E-7 3.7 E-6 1.9 E-6 1.1 E-6 3.9 E-6Chromium, hexavalent 6.7 E-7 1.2 E-6 8.0 E-6 1.4 E-5 7.2 E-7 1.3 E-6Cobalt 1.0 E-7 2.1 E-7 1.8 E-6 2.6 E-6 1.0 E-7 2.1 E-7Mercuric chloride 2.2 E-5 7.1 E-5 7.0 E-5 1.7 E-4 2.2 E-5 7.1 E-5Methyl mercury 1.4 E-6 4.1 E-6 1.7 E-6 5.7 E-6 1.4 E-2 9.8 E-3Nickel 9.0 E-7 1.8 E-6 7.7 E-6 1.3 E-5 2.2 E-6 2.7 E-6Selenium 3.3 E-7 5.1 E-7 1.1 E-5 2.1 E-5 1.2 E-6 1.1 E-6Silver 2.1 E-6 3.3 E-6 2.1 E-4 4.5 E-4 1.1 E-5 9.3 E-6Thallium 4.9 E-4 1.1 E-3 1.3 E-2 1.5 E-2 5.0 E-4 1.1 E-3Zinc 6.3 E-7 1.1 E-6 1.8 E-6 2.9 E-6 1.2 E-5 9.1 E-6Acenaphthene 2.8 E-9 4.4 E-9 6.9 E-9 1.1 E-8 2.7 E-8 2.1 E-8Acetone 1.2 E-5 1.6 E-5 4.5 E-5 6.2 E-5 1.2 E-5 1.6 E-5Acetonitrile 4.0 E-6 5.1 E-6 1.5 E-5 2.0 E-5 4.0 E-6 5.1 E-6Acetophenone 4.4 E-7 6.4 E-7 1.2 E-6 1.8 E-6 5.1 E-7 6.9 E-7Acrylonitrile 2.5 E-11 4.5 E-11 2.0 E-11 4.5 E-11 7.7 E-11 8.1 E-11Anthracene 8.7 E-9 1.3 E-8 2.8 E-8 4.4 E-8 7.6 E-8 6.0 E-8Benzaldehyde 2.2 E-7 3.0 E-7 7.5 E-7 1.0 E-6 2.3 E-7 3.1 E-7Benzene 2.2 E-7 2.8 E-7 8.1 E-7 1.1 E-6 2.3 E-7 2.9 E-7Benzylalcohol 3.1 E-8 5.3 E-8 4.4 E-8 7.8 E-8 3.6 E-8 5.6 E-8Bis(2-ethylhexyl)phthalate 4.7 E-7 6.0 E-7 1.2 E-5 2.1 E-5 7.3 E-6 5.3 E-6Bromomethane 3.9 E-8 5.1 E-8 1.4 E-7 1.9 E-7 3.9 E-8 5.1 E-8Butanol,n- 2.7 E-7 4.2 E-7 6.3 E-7 9.6 E-7 2.9 E-7 4.3 E-7Carbon disulfide 1.5 E-9 1.9 E-9 5.2 E-9 7.1 E-9 1.6 E-9 2.0 E-9Carbon tetrachloride 1.9 E-9 2.5 E-9 6.7 E-9 9.3 E-9 2.1 E-9 2.6 E-9Chlorobenzene 4.4 E-9 5.7 E-9 1.5 E-8 2.1 E-8 5.4 E-9 6.5 E-9Chloroform 8.8 E-10 1.2 E-9 3.1 E-9 4.2 E-9 8.9 E-10 1.2 E-9Cresol, m- 9.1 E-7 1.6 E-6 8.9 E-7 1.8 E-6 1.6 E-6 2.1 E-6Cresol, o- 1.2 E-6 1.9 E-6 2.3 E-6 3.7 E-6 1.8 E-6 2.3 E-6Cresol, p- 3.9 E-6 6.7 E-6 4.7 E-6 8.8 E-6 6.3 E-6 8.5 E-6Cumene 1.1 E-6 1.4 E-6 3.9 E-6 5.4 E-6 1.1 E-6 1.4 E-6

7–20

Table 7.11 (continued) COPC-specific hazard quotients due to indirect exposure for six exposurescenarios and for all COPCs modeled at their average measured emission rates. Boldfacedcompounds are those subject to MACT limits.


residentadult

residentchild

farmadult

farmchild

fishingadult

fishingchild

Cyclohexanone 1.3 E-9 1.8 E-9 3.7 E-9 5.3 E-9 1.3 E-9 1.9 E-9Dibenzofuran 1.4 E-7 2.2 E-7 4.0 E-7 6.3 E-7 1.4 E-7 2.2 E-7Dichloroethane,1,2- 3.6 E-7 4.6 E-7 1.3 E-6 1.8 E-6 3.6 E-7 4.6 E-7Dichloroethylene,1,1- 1.1 E-10 1.4 E-10 3.8 E-10 5.3 E-10 1.2 E-10 1.5 E-10Dimethylphenol, 2,4- 1.3 E-7 2.4 E-7 1.2 E-7 2.5 E-7 3.4 E-7 3.8 E-7Di-n-butylphthalate 1.7 E-8 2.5 E-8 6.4 E-8 9.9 E-8 5.6 E-7 4.1 E-7Ethylacetate 4.3 E-9 5.6 E-9 1.5 E-8 2.1 E-8 4.3 E-9 5.7 E-9Ethylbenzene 2.6 E-7 3.3 E-7 9.6 E-7 1.3 E-6 2.6 E-7 3.4 E-7Ethylether 3.6 E-10 4.7 E-10 1.3 E-9 1.8 E-9 3.6 E-10 4.7 E-10Fluoranthene 8.7 E-8 1.2 E-7 1.8 E-7 2.8 E-7 6.1 E-6 4.3 E-6Fluorene 9.0 E-9 1.5 E-8 2.3 E-8 3.8 E-8 1.3 E-7 1.0 E-7Hexanone, 2- 8.0 E-9 1.1 E-8 2.8 E-8 3.9 E-8 8.2 E-9 1.1 E-8Methanol 1.1 E-7 1.4 E-7 4.1 E-7 5.6 E-7 1.1 E-7 1.4 E-7Methyl ethyl ketone 2.5 E-6 3.2 E-6 9.2 E-6 1.3 E-5 2.5 E-6 3.2 E-6Methyl isobutyl ketone 1.5 E-5 1.9 E-5 5.5 E-5 7.5 E-5 1.5 E-5 1.9 E-5Methylene chloride 1.4 E-7 1.8 E-7 5.1 E-7 7.0 E-7 1.4 E-7 1.8 E-7Naphthalene 9.8 E-8 1.3 E-7 3.2 E-7 4.5 E-7 2.3 E-7 2.3 E-7Phenol 7.4 E-7 1.2 E-6 1.6 E-6 2.5 E-6 8.7 E-7 1.2 E-6Pyrene 3.2 E-7 4.8 E-7 6.8 E-7 1.1 E-6 1.9 E-5 1.4 E-5Pyridine 5.0 E-8 6.4 E-8 1.9 E-7 2.6 E-7 5.0 E-8 6.5 E-8Styrene 2.2 E-7 2.8 E-7 8.1 E-7 1.1 E-6 2.2 E-7 2.8 E-7Tetrachloroethylene 8.8 E-8 1.1 E-7 3.3 E-7 4.5 E-7 8.8 E-8 1.1 E-7Tetrahydrofuran 1.8 E-6 2.4 E-6 6.8 E-6 9.3 E-6 1.8 E-6 2.4 E-6Toluene 6.1 E-7 7.8 E-7 2.2 E-6 3.1 E-6 6.1 E-7 7.8 E-7Trichloroethane, 1,1,1- 2.3 E-7 2.9 E-7 8.4 E-7 1.2 E-6 2.3 E-7 2.9 E-7Trichloroethylene 5.7 E-7 7.3 E-7 2.1 E-6 2.9 E-6 5.7 E-7 7.3 E-7Trimethylbenzene, 1,2,4 9.5 E-10 1.2 E-9 3.3 E-9 4.6 E-9 1.9 E-9 1.9 E-9Trimethylbenzene, 1,3,5 2.7 E-10 3.6 E-10 9.1 E-10 1.3 E-9 5.3 E-10 5.4 E-10Xylene, m- 2.9 E-8 3.8 E-8 1.1 E-7 1.5 E-7 3.0 E-8 3.8 E-8Xylene, o- 2.9 E-8 3.7 E-8 1.1 E-7 1.5 E-7 2.9 E-8 3.7 E-8Xylene, p- 3.0 E-8 3.8 E-8 1.1 E-7 1.5 E-7 3.0 E-8 3.8 E-8Total PCBs 1.7 E-8 2.6 E-8 1.4 E-7 1.9 E-7 5.5 E-8 5.5 E-8Sum (Hazard Index) 6.2 E-4 1.3 E-3 1.4 E-2 1.6 E-2 1.5 E-2 1.1 E-2

7–21

Table 7.12 COPC-specific chronic and acute hazard quotients due to inhalation exposure scenariosand for all COPCs modeled at their average measured emission rates. Boldfaced compounds arethose subject to MACT limits.


Antimony 5.7 E-7 1.3 E-6 8.9 E-8Arsenic 6.5 E-7 1.4 E-6 6.1 E-4Barium 2.2 E-5 4.8 E-5 1.2 E-6Beryllium 4.0 E-9 8.8 E-9 1.3 E-6Cadmium 1.8 E-6 4.1 E-6 2.0 E-6Chromium, total 2.8 E-9 6.3 E-9 1.6 E-6Chromium, hexavalent 2.0 E-6 4.3 E-6 3.0 E-7Cobalt 3.1 E-9 7.0 E-9 —Copper 2.1 E-6 4.6 E-6 8.0 E-6Lead — — 1.3 E-5Manganese 1.3 E-4 2.8 E-4 —Mercuric chloride 4.4 E-6 9.9 E-6 4.6 E-4Mercury 4.1 E-6 9.1 E-6 1.2 E-4Nickel 2.7 E-8 6.1 E-8 5.2 E-5Selenium 1.1 E-8 2.4 E-8 1.1 E-5Silver 6.9 E-8 1.5 E-7 6.7 E-7Thallium 1.6 E-5 3.6 E-5 5.5 E-6Vanadium — — 9.4 E-6Zinc 8.9 E-9 2.0 E-8 —Chlorine 3.2 E-3 7.2 E-3 —Hydrogen chloride 1.5 E-4 3.3 E-4 —Acenaphthene 5.7 E-9 1.3 E-8 —Acetone 2.3 E-5 5.1 E-5 —Acetonitrile 2.6 E-5 5.8 E-5 1.5 E-5Acetophenone 8.8 E-8 2.0 E-7 1.8 E-7Acrylonitrile 1.9 E-5 4.3 E-5 3.0 E-7Anthracene 1.6 E-9 3.5 E-9 —Benzaldehyde 1.2 E-7 2.7 E-7 —Benzene 1.3 E-5 2.9 E-5 2.8 E-4Benzo(a)pyrene — — 8.6 E-10Benzylalcohol 1.2 E-9 2.6 E-9 3.3 E-9Bromomethane 3.0 E-6 6.6 E-6 4.4 E-8Carbon disulfide 9.8 E-8 2.2 E-7 3.8 E-6Carbon tetrachloride 1.4 E-7 3.0 E-7 4.6 E-10Chlorobenzene 1.0 E-7 2.2 E-7 3.0 E-9Chloroform 2.2 E-6 4.9 E-6 3.2 E-7Chrysene — — 3.6 E-8Cresol, m- 5.7 E-8 1.3 E-7 2.6 E-8

7–22

Table 7.12 (continued) COPC-specific chronic and acute hazard quotients due to inhalation exposurescenarios and for all COPCs modeled at their average measured emission rates. Boldfacedcompounds are those subject to MACT limits.

Cresol, o- 2.0 E-6 4.4 E-6 1.3 E-8Cresol, p- 2.0 E-6 4.5 E-6 2.6 E-8Cumene 6.2 E-5 1.4 E-4 —Dibenz(ah)anthracene — — 6.0 E-11Dibenzofuran 5.4 E-7 1.2 E-6 —Dichloroethane, 1,2- 4.7 E-6 1.0 E-5 1.1 E-8Dichloroethylene, 1,1- 2.0 E-8 4.3 E-8 1.4 E-9Dimethylphenol, 2,4- 2.7 E-8 6.0 E-8 —Di-n-butylphthalate 8.6 E-9 1.9 E-8 —Ethylbenzene 4.4 E-6 9.8 E-6 2.7 E-6Fluoranthene 7.2 E-9 1.6 E-8 —Fluorene 7.5 E-9 1.7 E-8 —GlycolEthers 6.3 E-7 1.4 E-6 1.6 E-3Hexane 3.1 E-6 7.0 E-6 —Hexanone, 2- 1.2 E-6 2.8 E-6 —Methanol 2.7 E-6 5.9 E-6 1.3 E-3Methyl tert-butyl ether 1.1 E-9 2.5 E-9 —Methyl ethyl ketone 8.6 E-6 1.9 E-5 4.9 E-4Methyl isobutyl ketone 4.7 E-5 1.1 E-4 4.6 E-6Methylene chloride 3.1 E-7 7.0 E-7 8.5 E-5Naphthalene 7.6 E-6 1.7 E-5 5.0 E-8Phenol 5.5 E-7 1.2 E-6 6.1 E-5Propanol, 2- 1.9 E-8 4.2 E-8 7.0 E-6Pyrene 9.5 E-9 2.1 E-8 —Pyridine 7.6 E-6 1.7 E-5 1.7 E-7Styrene 2.6 E-6 5.9 E-6 4.1 E-5Tetrachloroethylene 8.0 E-7 1.8 E-6 3.2 E-10Tetrahydrofuran 4.9 E-6 1.1 E-5 —Toluene 5.3 E-5 1.2 E-4 2.3 E-4Trichloroethane, 1,1,1- 1.7 E-5 3.9 E-5 8.3 E-10Trichloroethylene 2.5 E-5 5.5 E-5 3.5 E-7Trimethylbenzene,1,2,4- 8.4 E-7 1.9 E-6 —Trimethylbenzene,1,3,5- 3.4 E-7 7.5 E-7 —Xylene, m- 9.5 E-7 2.1 E-6 1.0 E-4Xylene, o- 9.6 E-7 2.1 E-6 1.0 E-4Xylene, p- 9.6 E-7 2.1 E-6 7.8 E-6PCBmixture 8.8 E-9 2.0 E-8 —Sum (Hazard Index) 3.9 E-3 8.7 E-3 5.7 E-3

7–23

Table 7.13 Noncancer exposures to PCDD/PCDFs by indirect pathways for six exposure scenarios atMACT-based emission rates (in bold), at maximum measured emission rates with non-detectedcongeners assumed to be present at the maximum detection limit (italic), and at average measuredemission rates with non-detected congeners assumed to be present at 1/2 the detection limit. Nationalaverage background total daily TEQ exposures are: 1 to 3 pg/kg-day TEQ for adults, and 60 pg/kg-day TEQ for nursing infants.

Indirect exposure levels

residentadult


adultfishingchild

PCDD/PCDF totalpg/kg-day TEQ 0.0035 0.0088 0.21 0.22 0.066 0.056

PCDD/PCDF totalpg/kg-day TEQ,nursing infants

0.063 6.27 1.96



0.0019 0.20 0.060



0.00094 0.096 0.029

8–1

8 Uncertainty evaluationThe estimation of the potential, incremental human health effects caused by emissions from theLSI/Greencastle facility relies on a wide variety of data and procedures:

• facility-, site-, and COPC-specific properties and parameters;• environmental transport, fate and exposure modeling assumptions; and• toxicological reference doses and slope factors.

All of these are subject to varying degrees of uncertainty based on whether they are measureddirectly, calculated from basic physical and chemical principles, or extrapolated from indirectmeasurements. In general, the more assumptions required for determining each property orparameter, the more uncertain the resulting value. Uncertainties may arise due to a lack of basicinformation (e.g., toxicological data or measurable emission rates), the need to make predictionsoutside the realm of present or available knowledge (e.g., modeling mercury speciation and transportproperties or predicting future land uses), or the use of overly conservative assumptions in thecalculations (e.g., COPCs emitted at MACT-based rates). The impact of each of these uncertaintieson the overall risk estimates depends on the interactions among the parameters and model (e.g., fate -and-transport uncertainties for COPCs with high toxicities have a much greater impact on the overallrisk estimates than those for COPCs with low toxicities). For this reason, and because the number ofpossible evaluations is so great, the following sections are directed towards the evaluation ofproperty, parameter, modeling, and toxicity uncertainties which have the greatest impacts on theoverall risk estimates.

As described in the RAWP, several specific sources of uncertainties in the risk assessment have beenevaluated with respect to their effect on the overall risk results. Additional uncertainties that havebeen found to have a significant influence on the final results will also be discussed. Whereapplicable, these discussions include quantitative comparisons of the range of possible values forcritical properties and parameters and for various options aimed at reducing the overall uncertainty.Also, significant departures from HHRAP guidance methods or default assumptions are addressedwith regard to their impact on the risk assessment’s overall level of uncertainty.

The uncertainty evaluations in this chapter are arranged in the same basic order as in the assessmentitself. The areas which are discussed are:

• Facility characterization—emissions• Accounting for unmeasured organic compounds by a TOE factor • Emission rates for COPCs emitted below detection limits• MACT-based vs. measured emission rates• Measured rather than default values for mercury speciation and partitioning

fractions • Air dispersion and deposition modeling uncertainties

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• Possibly inaccurate default parameters for dry and wet deposition • Interactions between local topography and modeling results• Superposition of maximum concentration and deposition values

• Estimation of media concentrations• Non-zero values for kse in calculating average watershed soil concentrations• Site-specific, empirical BAFfish values for mercury• Uncertain default values for Bachicken and Baegg, and Qschicken for PCDDs and PCDFs

• Quantifying exposure• COPC concentrations in Cagles Mill Lake for the evaluation of drinking water

exposures• Assumption that a subsistence farm could be located at the maximum impact

location• Risk and hazard characterization

• COPCs without available toxicological data• Inherent uncertainties in toxicological data due to extrapolation from original

research results

8.1 Facility characterization—emission uncertainties

8.1.1 Extrapolation of organics’ risks using TOE measurements

Organic compounds that could not be identified by laboratory analyses during the PIC Risk Burntesting could not be included directly as COPCs in the risk analysis. However, these compounds (iftoxic) may still contribute to the overall risk caused by the LSI/Greencastle facility’s emissions. Inorder to account for the possible underestimation of overall risks due to the emissions of unidentifiedorganic compounds, a Total Organic Emissions (TOE) factor is employed. The TOE factor is theratio of the measured stack TOE to the total measured emissions of identified organic COPCs. Basedon the 2000 PIC Risk Burn results (Gossman, 2001b), the TOE factor is 1.10 using (in thedenominator) the sum of the emission rates of identified and tentatively identified compounds (TICS)emissions, and 1.88 using only the emission rates for the positively identified compounds. Bymultiplying the stack emission rates of all of the identified organic compounds by the TOE factor it ispossible to extrapolate the results of the risk assessment to include the emissions of unidentifiedorganic compounds. This is not done for PCDDs and PCDFs, which are treated at their apportionedMACT emission rates. To produce the most conservative estimate of overall risks from the facility,the TOE factor of 1.88 is used. The results of this extrapolation on the estimated cancer risk factorsand non-cancer hazard quotients are shown below in Table 8.1. In most cases, potential increases inrisk levels are negligible or modest. The highest increase of 4.4% is estimated for the incrementalcancer risk estimate due to direct exposure (e.g., inhalation). The reason that almost doubling theorganic emission rates causes such a small increase in the predicted health risks is that the organicCOPC emissions (without the PCDDs and PCDFs) account for a very small amount of the overallcalculated risks.

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Table 8.1 Estimated increase in health risks with organic COPC emission rates increasedby a TOE factor of 1.88. Some of the increases in risk are only apparent in the‘percent increase’ row due to the use of only two significant figures for the riskand hazard values.

Exposurescenario

Incremental cancer risk, indirect exposure Incremental cancer risk,direct exposure

residentadult

residentchild

farmingadult

farmingchild

fishingadult

fishingchild

res/fishadult child farm

adultwithmeasured rates

2.0 E-6 7.1 E-7 2.7 E-5 5.2 E-6 8.6 E-6 1.7 E-6 6.7 E-8 2.4 E-8 7.2 E-8

with TOErates 2.0 E-6 7.1 E-7 2.7 E-5 5.3 E-6 8.6 E-6 1.7 E-6 7.0 E-8 2.5 E-8 7.5 E-8

percentincrease 0.15% 0.12% 1.1% 1.5% 0.16% 0.14% 4.4% 4.4% 4.4%

Non-cancer individual hazard index,indirect exposure

Non-cancer individual hazardindex, direct exposure

residentadult

residentchild

farmingadult

farmingchild

fishingadult

fishingchild adult child acute

hazardwithmeasuredrates

3.4 E-3 8.0 E-3 5.4 E-2 6.6 E-2 5.9 E-1 4.2 E-1 2.7 E-1 6.0 E-1 5.0 E-2

with TOErates 3.4 E-3 8.0 E-3 5.4 E-2 6.6 E-2 5.9 E-1 4.2 E-1 2.7 E-1 6.0 E-1 5.0 E-2

percentincrease 0.78% 0.56% 0.012% 0.016% 0.0072% 0.0085% 0.023% 0.023% 0.45%

8.1.2 Alternate treatments of COPCs below detection limits in stack tests

The RAWP stated that the uncertainty evaluation would include calculations for alternative treatmentof compounds not detected in the stack testing, but nevertheless considered in the risk assessment. The specific results of some of these alternate treatments have been shown in the tables in Chapter 7. Among the COPCs, several organic compounds were not detected in the PIC Risk Burn tests, butwere included in the modeling of the stack emissions because of their presence in the HWF. Likewise, two inorganic COPCs, hexavalent chromium and selenium, were not detected in the ROCtests but were included in the analyses because they are covered by MACT regulations. The otherclass of COPCs that were not uniformly detected in the recent set of emissions tests were specificcongeners of PCDDs and PCDFs.

The effect of the different treatments of the undetected organic COPCs on the final risk assessmentresults is very minor, as may be inferred by the small effect that the use of the TOE factor had on therisk estimates. The estimated incremental cancer risks for Cr+6 and non-cancer hazard quotients forCr+6 and Se for the different emission rates are shown in Table 8.2. The entries based on ND = DLmax

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for Cr+6 are notably more than a factor of two greater than those based on ND = DLavg/2 because themaximum detection limits among the three test runs were significantly greater than the average detection limits. This effect is not seen for selenium because the detection limits for Se did not differgreatly among the three tests. As can be seen in Table 8.2, the most significant health effects due tothese metals are the cancer risks due to indirect exposure to Cr+6. For example, using the maximumdetection limit for Cr+6 emissions leads to the excess cancer risk estimates for subsistence farmers andtheir children of 1.3 × 10–6 and 3.6 × 10–7, respectively, which account for 65% and 76% of the totalestimated cancer risks for these exposure scenarios (2.0 × 10–6 for adults and 4.7 × 10–7 for children). The use of half of the average detection limit for Cr+6 emissions reduces the total estimated risks tosubsistence farmers to 5.8 × 10–7 for adults and 1.5 × 10–7 for children. Thus, the risk estimates forthe subsistence farmer scenario are somewhat sensitive to the treatment of non-detects.

Table 8.2 Estimated cancer risks for hexavalent chromium and noncancer hazard quotientsfor hexavalent chromium and selenium for different assumed emission rates.

Hexavalentchromiumemission rates

Cancer Risk, indirect exposure to Cr+6 Cancer Risk, inhalationto Cr+6

residentadult

residentchild

farmingadult

farmingchild

fishingadult

fishingchild


adultApportioned intoMACT limits 2.8 E-7 1.0 E-7 4.6 E-6 1.2 E-6 3.0 E-7 1.1 E-7 1.4 E-8 4.9 E-9 1.5 E-8

Measured, with ND = DLmax

8.3 E-8 3.1 E-8 1.3 E-6 3.6 E-7 8.9 E-8 3.1 E-8 4.1 E-9 1.5 E-9 4.4 E-9

Measured, with ND = DLavg/2

3.6 E-8 1.3 E-8 5.8 E-7 1.5 E-7 3.8 E-8 1.3 E-8 1.8 E-9 6.3 E-10 1.9 E-9

Hexavalentchromium, andselenium emissionrates

Noncancer individual hazard quotient,indirect exposure to Cr+6, Se

Noncancer individualhazard quotient, directexposure to Cr+6, Se

residentadult

residentchild

farmadult

farmchild

fishingadult

fishingchild


adultCr+6 apportionedinto MACT limits 5.3 E-6 9.7 E-6 6.4 E-5 1.1 E-4 5.7 E-6 1.0 E-5 1.5 E-5 3.4 E-5 2.3 E-6

Cr+6 measured, withND = DLmax

1.6 E-6 2.9 E-6 1.9 E-5 3.3 E-5 1.7 E-6 2.9 E-6 4.6 E-6 1.0 E-5 6.9 E-7

Cr+6 measured, withND = DLavg/2

6.7 E-7 1.2 E-6 8.0 E-6 1.4 E-5 7.2 E-7 1.3 E-6 2.0 E-6 4.3 E-6 3.0 E-7

Se apportioned intoMACT limits 1.9 E-6 3.3 E-6 7.6 E-5 1.5 E-4 8.4 E-6 7.8 E-6 7.7 E-8 1.7 E-7 7.6 E-5

Se measured, with ND = DLmax

6.7 E-7 1.0 E-6 2.2 E-5 4.3 E-5 2.4 E-6 2.2 E-6 2.2 E-8 4.9 E-8 2.2 E-5

Se measured, with ND = DLavg/2

3.3 E-7 5.1 E-7 1.1 E-5 2.1 E-5 1.2 E-6 1.1 E-6 1.1 E-8 2.4 E-8 1.1 E-5

8.1.3 MACT-based vs. measured emission rates

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The use of different assumptions for the emission rates of specific, non-detected PCDD/PCDFcongeners also has some effect on the total predicted incremental cancer risk levels. Theseconsequences are discussed below in the paragraphs addressing the use of MACT-based emissionrates for some COPCs.

As described in Section 2.5 of this report and shown in Table 2.5, many of the COPCs that are subjectto MACT-based emissions limits, and which are being modeled at these rates, were measured in theROC and PIC Risk Burn emissions’ testing at far lower levels. Among these compounds are threeclasses of compounds that produce some of the highest calculated cancer risks and hazard quotients:PCDDs/PCDFs, mercury, and chlorine. The amount by which measured emissions of each of theseCOPCs are below their MACT limits, and the percent that each COPC, emitted at the MACT limit,contributes to a predicted health risk are addressed below.

8.1.3.1 PCDD/PCDFs

The health risks estimated for potential exposures to PCDD/PCDFs are based on their emission fromthe LSI/Greencastle facility at a MACT-based rate of 47 ng TEQ/s. The mean measured rate in the2000 PIC Risk Burn, however, was 0.18 ng TEQ/s (0.38% of the MACT) if the non-detectedcongeners are assumed not to be present, or 0.71 ng TEQ/s (1.5% of the MACT) if the non-detectedcongeners are assumed to be present at half their detection limits. As a consequence of this verylarge overestimation of the actual emission rates, PCDDs/PCDFs account for from 37% to 62% of thecalculated incremental cancer risk from indirect exposure. The risks with PCDD/PCDFs emitted atMACT limit and at their measured emission rates of 1.5% or 0.38% of this limit are shown in Table8.3.

Table 8.3 Overall cancer risk factors due to indirect exposure to PCDD/PCDFs from theLSI/Greencastle facility, with emission rates based on their hypothetical MACT-based emission limit, and at two different values for their measured emissionrates (based on treatment of non-detected congeners)

PCDDs/PCDFsemission rates

Cancer Risk, indirect exposure Cancer Risk, inhalation

residentadult

residentchild

farmingadult

farmingchild

fishingadult

fishingchild


adultApportioned intoMACT limits 2.0 E-7 9.9 E-6 1.6 E-5 2.5 E-6 3.6 E-6 6.1 E-7 1.1 E-8 4.0 E-9 1.2 E-8

Measured, with ND = DL/2 6.0 E-9 3.0 E-9 5.0 E-7 7.9 E-8 1.1 E-7 1.9 E-8 3.3 E-101.2 E-103.6 E-10

Measured, with ND = 0 2.9 E-9 1.5 E-9 2.5 E-7 3.9 E-8 5.4 E-8 9.1 E-9 1.6 E-105.8 E-111.7 E-10

Non-cancer health effects due to PCDD/PCDFs are evaluated by comparing the calculated TEQexposure rates with national average background exposure rates. The calculated exposure rates for

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PCDD/PCDFs emitted at their MACT limit and at their measured emission rates of 1.5% or 0.38% ofthis limit are shown in Table 8.4. These values are substantially smaller than MACT-basedestimates. Consequently, the relative contribution of LSI/Greencastle facility emissions to anindividual’s overall exposure to PCDD/PCDFs (as given in Table 7-13) is likely to be greatlyoverstated, since it is based on a much higher-than-actual emission rate.

Table 8.4 TEQ exposure rates due to indirect exposure of COPCs from the LSIGreencastle facility, with PCDD/PCDFs apportioned at their hypotheticalMACT-based emission limit, and at two different values for their measuredemission rates

PCDDs/PCDFsemission rates

Total indirect PCDD/PCDF exposure levels pg/kg-day TEQ

residentadult

residentchild

farmadult

farmchild

fishingadult

fishingchild

Apportioned intoMACT limits 0.069 0.060 0.22 0.22 0.070 0.062

Measured, with ND = DL/2 0.0020 0.0017 0.0066 0.0068 0.0020 0.0017

Measured, with ND = 0 0.00096 0.00081 0.0032 0.0033 0.00099 0.00083

8.1.3.2 Mercury

Likewise, the health risks estimated for exposures to mercury compounds are based on their emissionfrom the LSI/Greencastle facility at a MACT-based rate of 0.0141 g/s. The mean mercury emissionrates measured during the 2000 ROC tests were: 5.88 E-4 g/s, based only on mercury in the sampletrain sections where it was detected; or 6.25 E-4 g/s, based on the mercury being present at ½ itsdetection limits in sample train sections where it was not detected and the modeled partitioning ofHgCl2 in the sampling train (see Section 2.6 of this report); and 7.51 E-4 g/s based on the mercurybeing present at 1/2 its detection limits in sampling stages where it was not detected withoutmodeling the partitioning of HgCl2 in the sampling train. Even taking the maximum of these values,the measured mercury emission rate for LSI Greencastle is only 5.3% of the modeled, MACT-basedemission rate. The most significant predicted hypothetical health risk from modeled mercuryemissions is due to the consumption of mercury contaminated fish by a subsistence fisher and child,and the estimated noncancer hazard indices for these individuals are dominated by the hazardquotients for their ingestion of mercury in fish. By reducing the mercury emission rate from theMACT-based rate to the highest estimated rate from the test measurements, the hazard indices aregreatly reduced as shown in Table 8.5. Reducing the emission rate to either of the lower measuredvalues further reduces the estimated hazard.

Table 8.5 Hazard quotients for subsistence fishers and children due to indirect exposure ofCOPCs from the LSI Greencastle facility, the percent of this risk due to mercury being

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modeled at MACT-based its limit, and the risks with mercury emitted at its measuredrates.

Exposure scenario

Noncancer hazard index due to indirectexposures

fishing adult fishing child

Mercury emitted at MACT-based rate 0.58 0.41Percent of risk due to mercury emitted at MACT-based rate 99.2% 97.9%

Mercury emitted at 5.3% of MACT-based rate(based on worst-case assessment of actualemissions)

0.036 0.030

8.1.3.3 Chlorine

Measured emissions of chlorine gas (as both Cl2 and HCl) from the LSI Greencastle cement kilnstack are also only a small portion of the MACT-based rates at which the risk assessment modelingwas performed. The MACT-based apportioned emission rates limits are 4.91 g/s for Cl2, and 22.3 g/sfor HCl; the measured rates are 0.062 g/s for Cl2, and 0.28 g/s for HCl which are 1.26% of theMACT-based apportioned rates. Based on the HHRAP guidance, the only health hazard for whichchlorine is evaluated is its noncancer hazard quotient due to chronic exposures by direct inhalation. The estimated overall noncancer hazard indices due to direct inhalation is dominated by the hazardquotients for the inhalation of chlorine. Reducing the chlorine emissions from the MACT-based ratesto either the average or the maximum measured rates, greatly reduces the hazard indices as shown inTable 8.6.

Table 8.6 Total Hazard Indices for adults and children due to direct inhalation exposure toCOPCs from the LSI Greencastle facility, the percent of this risk due to chlorinebeing modeled at MACT-based its limit, and the risks with chlorine emitted at itsmeasured rates.

Exposure scenarioNoncancer hazard index (HI) due to direct inhalation

adult child

HI with chlorine emitted at apportionedMACT-based rate 0.27 0.60

Percent of hazard due to chlorine emittedat MACT-based rate 99.3% 99.3%

HI with chlorine emitted at maximummeasured rate 0.0058 0.013

HI with chlorine emitted at averagemeasured rate 0.0039 0.0087

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8.1.4 Mercury speciation and distribution in emissions

The estimates of health risks due to mercury ingestion presented in this risk assessment are based onsignificant departures from the HHRAP defaults and guidance in area of mercury speciation anddistribution in the kiln stack emissions. The fact that this topic is the subject of major, currentresearch efforts underlines both the scientific complexities and the modeling uncertainties associatedwith each process’s mechanisms. The kiln stack partitioning of mercury between elemental anddivalent states, and between vapor- and particulate-phases is dependent not only on the properties ofthe relevant mercury species but also on the properties and relative amounts of various othercomponents within the stack gasses. These include the presence and form of various chlorinespecies, and the level and size distribution of the particles within the stack. Both of these factors arefunctions not only of the input streams, but also of the time and temperature history of the stackgasses. The precise modeling of these processes would require a great deal of site-specificinformation that is neither readily available nor easily measured. An important portion of thisinformation was, however, collected in the ROC test, and the test data provide direct evidence ofmercury speciation within the stack gasses. Therefore, the default modeling of mercury speciationwithin the cement kiln stack has been replaced in this risk assessment with measurement-based valuesfor mercury speciation in the kiln stack emissions in order to reduce the uncertainty in the final healthrisk and estimates. Descriptions of the methods used to calculate the necessary parameters aredescribed in Sections 2.6: ‘Justification for the use of non-default values for mercury speciation andpartitioning’.

The choice of mercury partitioning fractions among the three physical/chemical forms has a verysignificant impact on the estimated health risks for subsistence fishers and their children. As can beseen in Tables 7.3, 7.7, and 7.10, the total Hazard Indices (HI) for these exposure scenarios aredominated by the hazard quotient for methyl mercury (MHg). Because an individual’s exposure tomethyl mercury is almost exclusively due to fish ingestion, the other exposure scenarios are notgreatly effected by predicted Hg levels. With Hg emissions modeled at its MACT-based rates, methylmercury accounts for 99% of the adult subsistence fisher’s HI, and 98% of the HI for a childsubsistence fisher. Using measured Hg emission rates for the modeling reduces these percentagesonly slightly: down to 95% for adults and 88% for children.

The primary reason that the partitioning fractions have a large effect on the final hazard quotients isthat, based on HHRAP guidance (HHRAP Figure 2-4), 99% of vapor-phase, elemental mercury (Hg0)emitted from a facility is assumed to enter the global mercury cycle and is not considered in thesubsequent modeling calculations. Only the HgCl2 portion of the total Hg emissions is assumed toelevate MHg levels in local waterbodies and fish. Therefore, the use of the measured Hg0 emissionfraction of 97% (as inferred from the fraction of mercury found in various sample train sections),rather than the HHRAP default fraction of 20%, greatly reduces the estimated MHg levels in fish andhence, the estimated health risks to subsistence fishers and their children.

Despite the large effect this use of non-default parameters has on the final risk estimates, as stated inSection 2.6, it is believed that the use of site-specific, measurement-based values for mercuryspeciation in the kiln stack emissions significantly reduces the uncertainty in the final health riskestimates. The U.S. EPA Mercury Report to Congress (U.S. EPA, 1997a) states that the assumedspeciation and partitioning factors for a given type of Hg emission source contains a considerableamount of uncertainty, that modeling results are very strongly dependent on the assumed emission

13 Lead and cadmium are grouped as semi-volatile metals in the U.S. EPA’s MACTdetermination, as opposed to the low volatility group used to categorize other metals.

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speciation, and that speciated data derived from actual monitoring of sources are a critical researchneed. Because the HHRAP default parameters for stack emission partitioning were derived frommeasurements at uncontrolled municipal waste incinerators, not hazardous waste incinerators orcement kilns, their use for modeling the LSI/Greencastle facility is potentially inappropriate. Furthermore, the overall result of using site-specific parameters for mercury partitioning (and, asdescribed below in Section 8.3.2, for the biotransfer parameter BAFfish), is that the estimated mercuryconcentrations in environmental media up to and including trophic level 4 fish are consistent withlocally measured values.

8.2 Air dispersion and deposition modeling uncertainties

Along with the estimation of facility emissions, the air dispersion modeling and deposition studyserves as one of the backbones of multi-pathway risk assessment, as all exposure routes depend on itspredictions. As with all models, however, uncertainties are inherent to air dispersion modelinganalyses. There is an oft-quoted statement that air dispersion models are accurate to within a “factorof two.” This statement, however, applies to the prediction of pollutant concentrations in air underfairly idealized conditions. The introduction, for example, of abrupt terrain features introduces evengreater uncertainty. Models such as ISCST3 (used in this study) were not initially designed for use inmulti-pathway risk assessments, and the algorithms that have been added over the years to predictpollutant deposition and other enhanced calculations have not received rigorous validation, especiallywhen viewed from a combined (system) perspective. A few elements of uncertainty in the airdispersion modeling and deposition study are discussed below.

8.2.1 Possibly inaccurate default parameters for dry and wet deposition

Both wet and dry deposition estimates are based on models that have received only limitedvalidation. The processes of wet and dry deposition vary in their relative importance based upon thecompound’s properties, with the most basic differences between compounds that partition toparticles, and compounds that remain as gasses in the atmosphere. The models for dry particledeposition are likely reasonable estimators, as their predictions generally fall within the range ofempirical data. The models are sensitive to both surface and meteorological variables, which vary inspace and time in ways that are treated in an average, weighted manner in the modeling. Thus, dryparticle deposition rates are somewhat uncertain, but not demonstrably biased. There is reason tobelieve, however, that wet particle deposition rates are biased high, as the empirical scavengingcoefficients may reflect the observations of “wetted” particles, which would tend to overestimatevalues.

Both wet and dry particle deposition rates are sensitive to the nature of the distribution of thecompound within the particles. The high combustion temperatures in the LSI/Greencastle facilitylikely volatilize a number of different compounds, including relatively volatile metals such as leadand cadmium13 that are likely to condense onto the surface area of existing particles. Althoughempirical evidence suggests that a number of compounds may be best treated as surface-weighted

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contaminants, only PCDD/PCDF is treated as such in the risk assessment. Since the deposition ratesof surface-weighted contaminants are lower than those of mass-weighted contaminants (in which thecompound is assumed to distributed uniformly throughout particles), the potential importance ofindirect exposure pathways for metals such as lead and cadmium are likely overestimated. Based onpredictions of maximum deposition rates, the factors of overestimation may be greater than two forwet deposition, and five for dry deposition. The most meaningful implication on bottom-line riskestimates applies to the hazard quotients for lead in the environmental risk characterization (Chapter9), some of which exceed a value of one. If lead was alternatively treated as a surface-weightedcontaminant, some of the environmental hazard quotients based on MACT emission rates would stillexceed one, but by a lesser degree. Table 8.7 demonstrates that environmental hazard quotients forlead would be reduced by more than a factor of two in each of the three cases where MACT-basedvalues exceed one.

Table 8.7 Sensitivity of select environmental hazard quotients to the assumption of thedistribution of the metal lead within particles

Environmental receptorHazard quotient for lead based on:

treatment of lead as a mass-weighted (volume-weighted)

constituent of particles (aspresented in Chapter 9)

treatment of lead as a surface-weighted constituent of

particles

American woodcock 4.0 1.7

Deer mouse 3.9 1.6

Meadow vole 3.4 1.4

The deposition rates of gasses depend on compound-specific factors such as solubility, reactivity, andvolatility. A fair degree of discussion of gaseous deposition has already been presented in Chapter 3. Therein, an appropriate dry deposition velocity for mercuric chloride is highlighted as a major sourceof uncertainty in the deposition modeling. Like particles, the dry deposition rate of mercuric chlorideand other gases will vary with both surface and meteorologic characteristics. Unlike particledeposition, however, such variability is not considered in the HHRAP algorithms that assume aconstant value for the dry deposition velocity. The specific value of 3 cm/s appears to be within theupper range of values reported in the literature under various conditions for nitric acid (Seinfeld,1986), which is used as a surrogate compound for mercuric chloride. Thus, in addition to theuncertainty of assuming this surrogate relationship (which treats mercuric chloride as a rapidly-depositing species, in the absence of empirical data), the constant deposition velocity assigned tomercuric chloride likely overestimates deposition rates under many conditions. In combination, thesefactors probably overestimate the rate of dry mercuric chloride deposition, although the degree ofuncertainty is large and serves as justification for a conservative approach that tends to overestimate.

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8.2.2 Interactions between local topography and modeling results

The LSI/Greencastle kiln is located within the facility’s quarry at a base elevation lower than thesurrounding terrain. As such, the effective height of the stack is reduced somewhat with respect tolocal terrain features. The general location of the highest projected impacts of the facility lies to thenortheast of the kiln, in particular at a location near a local cemetery, but more generally along aplateau that runs from the southwest to the to the northeast (as depicted in the pattern in Figure 3.7) This terrain feature coincidentally lies in the wind direction most frequently downwind of the cementkiln location (as depicted in Figure 3.2). This coincidence may in fact result from the use of non-site-specific meteorologic data, which were obtained from the Indianapolis Airport. In reality, the terrainmay actually influence wind fields in the vicinity of the LSI/Greencastle facility, and a wind rose forconditions at the facility may have less of a southwest to northeast dominance than that depicted inFigure 3.2. In this case, the air dispersion modeling may in fact consider a higher-than-actualincidence of winds blowing toward the southwest-to-northeast plateau, and hence, through themodels’ assumption of partial plume impingement, over predict the likely values of concentrationsand deposition rates at these locations that are more sensitive to model predictions.

8.2.3 Superposition of maximum concentration and deposition values

A simplifying assumption is made in the modeling that the locations of the maximum of wet and drydeposition rates coincide with the location at which maximum value of compound concentrations arepredicted in air. There are however, differences in the geographic patterns among sources (stack vs.fugitive), and risk estimates for any specific exposure scenario at any specific location will be lowerthan those estimated in the risk assessment simply because all of the maximum values are notpredicted to occur at the same place. The degree of overestimation, however, is not likely to be large,unless the consideration of specific locations based on land use is also factored in, as is done furtheron in section 8.4.2. Also, consideration of multiple specific maxima in the generic case is notjustified given the degree of uncertainty inherent in the model predictions with respect to both theirmagnitudes and spatial distributions.

8.3 Estimation of media concentrations uncertainties

8.3.1 Use of non-zero kse in watershed soil concentration calculations

The justification for the use of a calculated value for COPC loss from soils in the watershed due toerosion, kse, was given in Section 5.4.1. Briefly, the reason cited in the HHRAP guidance for using auniform value of zero for kse is that soil eroding off a site would be replaced by soil eroding onto thesite. However, this assumption cannot be applied to the evaluation of soil concentrations over anentire watershed because by definition no soil erodes into the area being considered. The primaryimpact on predicted health risks caused by using a non-zero value for this parameter (rather than thevalue of zero as recommended by the HHRAP guidance), is that it decreases the mercury exposure ofthe subsistence fisher and child by a factor of 0.33 by reducing the predicted amount of mercury thatenters Cagles Mill Lake. The overall hazard indices for subsistence fishers and children are(respectively) 0.88 and 0.62 employing the default value of zero for kse, compared with the

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respective indices of 0.58 and 0.41 for calculated kse values. While this difference may appear to belarge, it is far smaller than the difference between the modeled MACT-based mercury emission ratesand the actual emission rates (Section 8.1.3.2), less than the effects of the various assumptions onmercury speciation and partitioning in the emissions (Section 8.1.4), and less than the differencesamong the various methods for calculating mercury bioaccumulation in fish (Section 8.3.2). Thus, interms of a sensitivity evaluation, the use of a non-zero kse produces a relatively minor change in thefinal risk assessment.

8.3.2 Site-specific, empirical BAFfish values

The second significant departure from the HHRAP defaults and guidance with regard to mercury is inthe area of the biotransfer of mercury from surface waters to fish. Again, the fact that this topic is thesubject of major, current research efforts underlines both the scientific complexities and the modelinguncertainties associated with the process. The transfer of mercury from a watershed to a water body,the biochemical process of methylation, and the bioaccumulation within edible fish tissues all dependnot only on the levels and forms of mercury in the various media, but also on the physical andchemical conditions present in the watershed soils, its surface and ground waters, its benthicsediments, and on the specific types of micro-organisms and fish that are present in the system.

The proper modeling of these processes would require a great deal of site-specific information that isneither readily available nor easily measured. The Peer Review Comments on the HHRAP explicitlyaddress this issue:

“...major data gaps and limitations associated with fate and transport modeling are...noted[as]: mercury behavior in watersheds, and mercury bioaccumulation in fish...We believe thatthese data gaps are sufficiently large so that regulatory decisions should not be made withoutmore detailed evaluations of these issues” U.S. EPA, 2000a, page 100).

Therefore, the default modeling of the bioaccumulation of mercury in fish tissues has been replacedin this risk assessment with empirically-derived, measurement-based values for mercurybioaccumulation in Cagles Mill Lake. Descriptions of the methods used to calculate the necessaryparameters are described in Section 5.5.1: ‘The use of a site-specific value for the BAFfish formercury’.

A significant point in relation to the use of site-specific, measured and derived parameters rather thanthe HHRAP default parameters is that the former greatly reduces the uncertainty in the calculationsand estimates. The result of using these site-specific parameters is that the estimated mercuryconcentrations in environmental media up to and including trophic level 4 fish, and the ratiosbetween these concentrations, are consistent with locally measured values. The overall riskassessment using a site-specific value for BAFfish still contains significant conservatism in that it iscalculated using values for large, trophic level 4 fish (16" largemouth bass), and because in theexposure calculations it is assumed that subsistence fishers and their children eat only fish of this typeand size, and only from the Cagles Mill Lake.

Finally, in relation to the predicted levels of mercury in Cagles Mill Lake, it should be noted that themeasured concentration of mercury in the lake waters has decreased significantly since it was

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measured at relatively high levels in the late 1970s and early 1980s (see Table 5.4). If it were thecase that the LSI/Greencastle facility was the major source of mercury in the lake, it would beexpected, based on the modeling of mercury accumulation in watershed soils and its erosion into thelake, that the mercury concentrations in the lake would be increasing. Because this has been shownnot to be the case, it is not likely that the facility is the major source of mercury in the lake.

8.3.3 Uncertainty in the default values for Bachicken and Baegg, and Qschicken forPCDDs and PCDFs

Section 2.4 of this report contains the justification for using non-HHRAP default values for thePCDD and PCDF biotransfer parameters Bachicken and Baegg. The values used in the modelingcalculations reflect those derived in the original research paper on the subject (Stephens, 1995), aswell as the comments on this matter in the report from the HHRAP Peer Review Meeting (U.S. EPA2000a). Nevertheless, even after the correction of the calculational errors in the Bachicken and Baegg,there is still some uncertainty regarding the biotransfer of PCDDs and PCDFs into chicken and theireggs. This uncertainty is very significant with respect to the overall risk assessment results because,using the current HHRAP guidance, the corrected values for Bachicken and Baegg, and MACT-basedemission rates, 60% of the calculated cancer risk for subsistence farmers and 50% of the risk for theirchildren is due to PCDD/PCDF exposure by the pathway of soil consumption by chickens.

Uncertainties associated with the HHRAP’s default values for the both of the biotransfer constantsand the soil ingestion rates have been examined in detail within the Peer Review Report. Threesources of uncertainties that are identified in the extrapolation from Stephens’ (1995) experimentaldata to the HHRAP’s default parameters are summarized here. The first source of uncertainty is thatthe soil intake rate, Qschicken, is based on an untested assumption that 10% of a chicken’s diet iscomprised of soil. While this value is similar to one derived for wild turkeys, it might only beapplicable to “free range” chickens. A more typical value for chickens kept by current-day farmersmight be 2 to 3%. The second source of uncertainty is that the default Ba values are derived fromexperimental results for exposures to very high soil concentrations of PCDDs and PCDFs, and withthe assumption that the transfer characteristics of PCDDs and PCDFs from soil are similar to thetransfer characteristics from grain. Data for more realistic exposure scenarios in the same study andby other researchers produce lower transfer rates. Third, even the use of the corrected HHRAPdefault values for Bachicken and Baegg results in estimated levels of PCDDs and PCDFs in chickens andeggs that are too high in relation to the estimated levels for beef and pork (based on typicallymeasured ratios of PCDD and PCDF concentrations in these foods). The Peer Review Reportconcludes that:

• the values for Bachicken and Baegg should perhaps be reduced by “at least one order ofmagnitude;” and, as was similarly found for the BAFfish for mercury,

• “that these data gaps are sufficiently large so that regulatory decisions should not be madewithout more detailed evaluations of these issues”.

Applying a reduction factor of ten to the product of Qschicken with Bachicken and Baegg would result indecreases in the total estimated cancer risks to subsistence farmers of 54%, and to their children of45%. Based on the great uncertainty in the values of these parameters, the likelihood that they are

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significantly overestimated, and their significant impact on the overall risk assessment for subsistencefarmers, the cancer risks for these exposure scenarios are probably overestimated.

8.4 Uncertainties in quantifying exposure

8..4.1 Drinking water at prison

Although the estimates of COPC concentrations in drinking water are based on concentrationscalculated for Cagles Mill Lake, the only surface water that is used for this purpose in the vicinity ofthe LSI/Greencastle facility is the Deer Creek (IDEM, 2001a). Because the location of the surfacewater intakes (at the Putnamville Correctional Facility) are nearer to the LSI/Greencastle facility thanis Cagles Mill Lake, it is likely that the COPC concentrations in drinking water have beenunderestimated in the risk calculations. To assess the potential for this simplification in the modelingto lead to an underestimation of the overall calculated health risks, the concentrations of COPCs indrinking water were recalculated using the maximum COPC air concentrations and deposition ratesrather than the concentrations and deposition rates averaged over the Cagles Mill Lake watershed. This calculation produces an upper bound on the drinking water concentrations; the actualconcentrations which would be expected at the Deer Creek surface water intakes will be betweenthose estimated at Cagles Mill Lake and this maximum level. The impact of this increase in drinkingwater concentrations on the calculated cancer risk factors and noncancer hazard quotients are shownbelow in Table 8.8. The reason that this change causes such a small increase in the predicted healthrisks is that COPC exposures due to drinking water ingestion accounts for a very small amount of thetotal exposures. Thus, even though the concentrations of COPCs in drinking water may have beenunderestimated, this simplification in the modeling does not have a significant impact on the overallhealth risk predictions.

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Table 8.8 Estimated increase in health risks due to COPC concentrations in drinkingwater calculated at maximum air concentrations and deposition rates rather thanCagles Mill Lake watershed average values. Some of the increases in risk areonly apparent in the row labeled ‘percent increase’, due to the use of only twosignificant figures for the risk and hazard values.

Drinking waterconcentrationbased on:

Cancer risk, indirect exposureresident

adultresident

childfarming

adultfarming

childfishingadult

fishingchild

average airconcentrationsover watershed

2.0 E-6 7.1 E-7 2.7 E-5 5.2 E-6 8.6 E-6 1.7 E-6

maximum airvalues 2.1 E-6 7.2 E-7 2.7 E-5 5.2 E-6 8.8 E-6 1.7 E-6

percentincrease 3.7% 5.9% 0.85% 1.5% 2.5% 4.6%

Noncancer hazard quotient, indirect exposureresident

adultresident

childfarming

adultfarming

childfishingadult

fishingchild

average airconcentrationsover watershed

3.4 E-3 8.0 E-3 5.4 E-2 6.6 E-2 5.9 E-1 4.2 E-1

maximum airvalues 3.7 E-3 8.6 E-3 5.4 E-2 6.6 E-2 5.9 E-1 4.2 E-1

percentincrease 9.8% 7.6% 0.53% 0.96% 0.060% 0.15%

8.4.2 Assumption that a farm could be located at the maximum impact location

The risk estimates for residents and subsistence farmers have been performed using the maximumpredicted COPC concentrations in air and deposition rates, and with the assumption that a residenceor farm could exist where the maximum expected impacts (MEIs) occur. However, the predictedmaxima do not occur at the same locations (as discussed in section 8.2.3), and the two farmsidentified as being nearest the LSI/Greencastle facility are somewhat removed from these locations. In order to evaluate the health risks that would correspond to presently existing farms near thefacility, risk calculations were performed for two specific locations based on actual land use,including the type of farming performed in the area (Chrispell, 2001). The location-specific modelpredictions were carried through the fate, transport, exposure, and risk calculations assuming that thefarmers either consume all of the modeled animal products, or only those which have been identifiedas actually being present.

One of the farms has only small livestock present (i.e., chickens and pigs), with its predicted air anddeposition COPC concentrations roughly half the maxima; the other is primarily a cattle farm, issomewhat further from the MEI locations, and has predicted air and deposition COPC concentrations

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roughly one-third the maxima. Table 8.9 shows the calculated incremental cancer risks for adultsubsistence farmers at the maximum impact location, and at the two local farms with their specificproduction/consumption assumptions. Note that, despite the introduction of location-specificexposure assumptions, these risk estimates are all based on COPCs being emitted at the MACT-basedapportioned emission rates, and hence remain hypothetical in nature. Risk estimates based on actualmeasured emission rates are much lower than those given in Table 8.9 (as discussed in section 8.1.3).

As can be seen from the estimates in Table 8.9, the consideration of actual land use patterns results inincremental cancer risk estimates lower than the typical target level of 1 × 10–5. In consideration ofthe tendency for multi-pathway risk assessment to overestimate ratios of indirect to direct exposure,emission of PCDD/PCDFs at the MACT limit (an unlikely scenario) would almost certainlycorrespond to actual incremental cancer risk levels that are within regulatory levels of concern.

Table 8.9 Incremental cancer risk estimates at MACT-based emission rates for an adultsubsistence farmer at the maximum impact and actual farm locations, and forconsumption of all types of farm products or only for animal products actuallypresent. UTM coordinates (m) indicate nearest modeling receptors.

Location Farm products consumed Incrementalcancer risk

Maximum impact location All 2.7 × 10–5

Non-cattle farm(UTM coordinates 511,900 E, 4,386,000 N)

All 1.4 × 10–5

Produce, poultry, eggs, pork 8.9 × 10–6

Cattle farm(UTM coordinates 513,000 E, 4,384,500 N)

All 6.5 × 10–6

Produce, beef, dairy 4.1 × 10–6

8.5 Risk and hazard characterization uncertainties

8.5.1 Treatment of COPCs with no toxicological data

The COPCs that do not have toxicological data available in the reference sources described in Section2.4 have been carried through the risk assessment calculations up to the estimation of their humanhealth effects. In order to evaluate the possible non-cancer health effects caused by the emission ofthese compounds, each has been assigned the reference doses (RfDs) and concentrations (RfCs) of achemically similar, surrogate COPC. Naphthalene was chosen as the toxicological surrogate for allPAHs without toxicological data (because naphthalene is the PAH with the lowest RfD values this isa fairly conservative substitution); acetone was selected for all acetate compounds; methyl isobutylketone was selected for methyl isoamyl ketone and diacetone alcohol (a.k.a. diketone alcohol);

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benzene (which has slightly lower reference levels than cyanide) for benzonitrile (a.k.a.cyanobenzene); bromomethane for iodomethane; hexane for octane; and 2-propanol for n-propanol.

An RfD and RfC for aluminum was derived from animal exposure data from the ATSDR (1999a)Toxicological Profile for Aluminum (Update). An RfD of 0.2 Al mg/kg-day was calculated as 1/10th

of the Minimal Risk Level (MRL) derived from intermediate duration oral exposures of SwissWebster mice to C9H15AlO9 (the reduction is based on the change from intermediate to chronicexposure durations). An RfC of 0.6 Al :g/m3 was calculated as 1/100th

of the No-ObservableAdverse Effects Level (NOAEL) derived from chronic duration inhalation exposures of guinea pigsto Al2(OH)5Cl (the reduction is based on 1/10th to account for interspecies variability and 1/10th toaccount for sensitive subpopulations).

The increases in overall Hazard Indices (HI) due to the use of surrogate toxicological data for COPCswithout standard toxicological data are shown in Table 8.10. The percent increases in hazard indicesare rather small except for the values for direct exposure indices as estimated using measured COPCkiln stack emission rates. The COPCs that are responsible for these large percentage increases arealuminum for chronic exposures, and ethanol for acute exposures. The reason the indices estimatedfor MACT-based emission rates do not change significantly is that these values are dominated by thehigh MACT-based emission rates of chlorine gasses for the chronic indices, and vapor-phase mercuryspecies for the acute indices. Because the specific large increases seen in the Table 8.10 correspondto low original HI values, the final hazard levels for these scenarios are all still well below one. Themaximum of the HI for direct exposures estimated using surrogate data and measured emission ratesis 0.017; and the maximum of the HI for indirect exposures estimated using surrogate data andmeasured emission rates is 0.022.

Table 8.10 Percent increase in overall non-cancer Hazard Indices due to the use of surrogatetoxicological data for COPCs without standard toxicological data.

emissionrates

noncancer individual hazard index,indirect exposure

noncancer individual hazardindex, direct exposure

residentadult

residentchild

farmingadult

farmingchild

fishingadult

fishingchild adult child acute

hazardMACT-based rates

3.5% 2.4% 0.84% 1.1% 0.021% 0.046% 1.9% 1.9% 1.2%

maximummeasuredrates

7.3% 5.2% 1.1% 1.5% 0.32% 0.62% 30% 30% 10%

averagemeasuredrates

8.5% 6.0% 1.4% 1.8% 0.36% 0.71% 44% 44% 11%

14 The tests must be suitable in other respects, and generally performed in accord with "goodlaboratory practice." 15 This discussion is necessarily simplified and greatly condensed; and there are exceptions tothe rules outlined in this portion of the text. Some highly inbred strains of mice, for example, areuniquely susceptible to certain carcinogens — and other species, indeed even outbred strains ofthe same species, will not develop cancer at all under the same scenario of exposures. Somecancers in rats are found to occur in organs that are not present in humans. Decades of researchand analysis have gone into the design, interpretation, and extrapolation of results from chronicrodent bioassays, and there are still improvements to be made. Regardless, the simplificationspresented in the text are essentially accurate.

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8.5.2 Inherent uncertainties in toxicologic data

Perhaps the greatest uncertainty in the risk estimates lies in the models used to predict the toxicologicpotencies (especially the carcinogenic potencies) of the contaminants of interest. It is also the mostdifficult uncertainty to quantify and evaluate, and as such is usually treated in a manner that willoverestimate potential risks.

Consider the case of predicting incremental cancer risk caused by a given level of exposure to aparticular compound that a person may encounter in the environment. In order to gauge whether acompound is a human carcinogen, groups of laboratory rodents are exposed, typically for most or allof their lifetimes, to very large doses of the compound — much higher doses than people typically (ifever) experience. If the doses induce an increased incidence of any type of cancer, compared to therate observed in unexposed control animals, then the compound is deemed a carcinogen.14 Two ormore of such tests with positive results suffice to label the compound a “probable humancarcinogen,” even if no actual or useful data from exposed humans are available.

This qualitative designation of carcinogenicity is, in many cases, entirely appropriate. Rats, mice,and humans are all mammals that develop cancer from a variety of exposures, and while there areabundant differences among the three species, these differences are not so large as to suggest thatcompounds carcinogenic to one species will not be carcinogenic to others.15 But while the qualitativeextrapolation from rodents to humans may be reasonably straightforward, the quantitativeextrapolation required for risk assessment is highly uncertain. This is because the doses at which therodents are tested are typically many thousands of times larger than doses experienced by humans. The central question is, are carcinogenic responses always proportional to dose, such that even atextremely low levels of exposure there is some risk of cancer, and that risk becomes zero only at zerodose? The answer is largely unknown. Knowledge of how specific compounds cause cancer may byhelpful on a case-by-case basis, but such information is in most cases still too rudimentary to driveregulatory decision-making.

The model assumed by the U.S. EPA in deriving carcinogenic potencies (and that used in the riskassessment) assumes that there is a risk of cancer — however small — at any level of exposure, i.e.,that a single molecule can, if encountered in the critical (but not understood) manner, cause cancer. The U.S. EPA has considered alternative types of models in which a threshold level of exposure isassumed to be necessary to cause or promote tumors, and in the case of chloroform in drinking water,has recently determined that the body of empirical evidence supports the threshold model. Similardeterminations may also be likely for other compounds, casting doubt on the validity of low dose

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extrapolations. If other compounds are determined to behave in a manner similar to chloroform,many of the incremental cancer risk estimates within the risk assessment may be found to be zero(i.e., below the threshold level).

With regard to cancer, it is assumed here that all rodent carcinogens are also human carcinogens, andthat all compounds carcinogenic at high doses are also carcinogenic at vanishingly small doses. Evenif these assumptions are valid, however, incremental cancer risk levels are still likely overestimatedon average because the cancer slope factors that are derived by the U.S. EPA are intentionallydesigned to overestimate the true potency. The U.S. EPA quantifies the carcinogenic potency slopefactors as upper confidence limits on mean values, meaning that the values are purposely biased onthe high side to account for uncertainty in the empirical data.

For similar reasons, non-cancer risks are also more likely to be overestimated than they are to beunderestimated. The reference doses and concentrations developed by the U.S. EPA are designed tobe levels that are likely to not cause adverse health effects. Typically, they are based on the weightedevidence of multiple studies in laboratory animals and (sometimes) humans, and are based on levelsthat are observed to be free of health effects or on the lowest levels observed to cause health effects. The data from the toxicologic studies are rarely used directly, but rather are reduced in magnitudethrough the application of one or more safety factors that are designed to ensure that the affects-freelevel observed in laboratory studies also reflects a safe level of exposure for the general population. In deriving reference doses of concentrations from animal study data, safety factors are typicallyapplied to:

• account for the fact that people may be more sensitive to a compound than are animals;• protect individuals who might be more sensitive to the compound than the animals that were

used in the study; and• provide an extra degree of protection when the body of toxicologic data on a particular

compound is limited.

Although there is no reason to assume a particular direction or bias with respect to any of theseuncertainties, all are resolved in the direction of safety. In each case, an adjustment is made to reducethe empirical toxicity data to derive a “safer” level. In the end, the actual safe level for humans maybe substantially higher than the derived reference dose or reference concentration, a factor thatinfluences the interpretation of predicted hazard quotients in excess of one.

The other factor that clouds the interpretation of data from animal studies is the fact that testingtypically occurs at high doses that, in some cases, may affect or compromise bodily systems in waysthat do not occur at the low doses that are characteristic of environmental exposure. For example,making animals ill through the feeding of large quantities of a compound may reduce their ability tofight off diseases and infections unrelated to the compound’s toxicity at normal, everyday levels ofexposure.

In general, the intentional biases used to derive toxicologic data are likely to overestimate actual risklevels. Although it is not possible to quantify the degree of bias, it is by convention a prudentmeasure designed to compensate for other potential uncertainties, and overall, produce bottom-lineestimates of risk such that they err on the high side of actual levels.

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9 Ecological Risk Assessment

The goal of the ecological risk assessment is to provide a qualitative and/or quantitativeevaluation of the potential occurrence of adverse ecological effects as a result of exposure to kilnstack emissions and RCRA fugitive emissions from the LSI/Greencastle Alternative FuelsFacility. The U.S. EPA has established a three-tiered approach for performing ecological riskassessments, corresponding to a screening ecological risk assessment (SERA, Tier I), apreliminary ecological risk assessment (PERA, Tier II), and a detailed ecological risk assessment(DERA, Tier III). This ecological risk assessment follows the Tier I, screening-level approach,which provides an initial evaluation of potential ecological risks using generally conservativeassumptions that are intended to ensure that risks are not underestimated at the site.

The ecological risk assessment follows the protocol for a screening-level ecological riskassessment (Horizon Environmental, 1998) for Lone Star’s Greencastle facility, which has beenpreviously approved by U.S. EPA Region 5. U.S. EPA guidance for ecological risk assessments,as contained in “Guidelines for Ecological Risk Assessment” (U.S. EPA, 1998) and in“Ecological Risk Assessment Guidance for Superfund: Process for Designing and ConductingEcological Risk Assessments, Interim Final” (U.S. EPA, 1997), was also used in preparing thisecological risk assessment. For consistency, equations from the HHRAP are used to perform thefate-and-transport modeling for the ecological risk assessment. There are some minordifferences between the equations in the HHRAP and other U.S. EPA ecological risk assessmentguidance. In cases where the HHRAP methodology differs from that presented in the ecologicalrisk assessment work plan, the HHRAP algorithms were used. The differences in methodologybetween the HHRAP and the ecological risk assessment work plan are discussed in Section 9.8.

9.1 Problem Formulation

Problem formulation is the first step of the ecological risk assessment process. Problemformulation consists of four parts:

• definition of the objective of the ecological risk assessment;• identification of assessment endpoints to adequately reflect the ecosystem they represent;• development of a conceptual site model that describes the key relationships between the

stressors and the assessment endpoints; and

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• an analysis plan.

The following sections describes each of these components of problem formulation for theLSI/Greencastle Alternative Fuels Facility.

9.1.1 Objective

The objective of this ecological risk assessment is to identify those compounds present in stackand RCRA fugitive emissions from the LSI/Greencastle Alternative Fuels Facility that do not —with a high degree of certainty — pose potentially significant ecological risks. As this is ascreening-level ecological risk assessment using conservative assumptions, compounds andpathways of concern that are shown to not pose a potentially significant ecological risk areeliminated from further analysis. If the results of this screening-level ecological risk assessmentindicate that there is the possibility of significant risk to ecological receptors near thecombustion facility, further evaluation may be required for compounds that remain of potentialconcern. This further evaluation would refine the risk assessment for the identified compoundsand pathways, taking into account more detailed, site-specific information.

9.1.2 Assessment Endpoints

In order to evaluate potential ecological risks, it is necessary to define the assessment endpointsto be protected from potential unacceptable exposures. An assessment endpoint is an expressionof the environmental component or value that is to be protected. This ecological risk assessmentfocuses on evaluating potential risks associated with combustion and RCRA fugitive emissionsfor five assessment endpoints:

(1) reproduction, growth, and survival of terrestrial (both avian and mammalian) specieswithin the assessment area;

(2) reproduction, growth, and survival of terrestrial plant species and communities within theassessment area;

(3) maintenance of intact terrestrial and aquatic food chains within the assessment area;(4) reproduction, growth, and survival of aquatic communities (including plant,

invertebrates, and fish); and (5) potential exposures to ecological compounds of concern by rare, threatened, and

endangered species within the assessment area.

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9.1.3 Conceptual Site Model

The conceptual site model identifies the sources for the stressors (in this case the stressors arethe stack and RCRA fugitive emissions from the LSI/Greencastle Alternative Fuels Facility) andthe pathways by which the ecological receptors can be exposed to the stressors. Pathways areidentified by which the compounds can be transported to environmental media, as are thepossible routes of exposure by the receptors to compounds in the environmental media.

Inorganic and organic compounds can be released in fugitive and stack emissions from the LSI/Greencastle facility. The released compounds can be transported to surrounding areas andremain in air where terrestrial birds and mammals may be exposed to compounds through directinhalation of vapor- and particulate-phase compounds. Thus, potential ecological risks from theinhalation of contaminants by terrestrial birds and mammals must be evaluated.

Terrestrial plants may be exposed to airborne compounds via absorption of vapor phasecompounds into leaves, and the deposition and absorption of particulate phase compoundsdeposited onto leaves. Thus, the possible ecological risks to plants from air contaminationshould be evaluated. In addition, plants and soil community organisms, such as earthworms orother soil invertebrates, may also be exposed to contaminants from the LSI/Greencastle facilityas a result of uptake of compounds in soil that have deposited from the air. Thus, the potentialecological risk to plants and the soil community from soil contamination must be evaluated.

Compounds may be deposited directly onto surface water or accumulate in surface water as aresult of runoff of impacted soil/sediment into the surface water body. Fish and other membersof the aquatic ecosystem may be exposed to compounds present in the surface water bodythrough ingestion. Thus, the possible ecological risks to the aquatic ecosystem fromcontamination present in the surface water and sediment must be evaluated.

Herbivores may be exposed to compounds through ingestion of terrestrial plants, soil, andsurface water. Herbivores, fish, and other lower food chain species (i.e., earthworms) may thenbioaccumulate compounds in their tissues. Piscivores (fish-eaters) and carnivores may then beexposed to compounds through ingestion of lower food chain species, in addition to ingestion ofsoil and surface water. Thus, the possible ecological risks from exposure to compounds withinthe diet of birds and mammals must be evaluated.

1 This toxicological data is in addition to the toxicological data presented in Section 9.3,which is used to select COECs following the procedures of the ecological risk assessment workplan (Horizon Environmental, 1998).

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9.1.4 Analysis Plan

This screening-level ecological risk assessment consists of four major parts:

• study area description (focusing on habitat evaluation);• selection of compounds of ecological concern (COECs);• characterization of exposure; and • characterization of effects.

Section 9.2 contains the study area description, describing the types of habitats and species foundin the area surrounding the LSI/Greencastle facility. COECs are then selected using a multi-stage scoring algorithm, as described in Section 9.3. In Section 9.4, conservative exposureparameters are used to predict exposure point concentrations of COECs in air, soil, surfacewater, sediment, and earthworm, fish, mammalian, and bird tissues, based on the measured andestimated emissions from the LSI/Greencastle facility.

Section 9.5 lists the air, soil, surface water, sediment, and ingestion toxicological data availablefor COECs.1 Chronic no observed adverse effect level (NOAEL) toxicological benchmark valuesare used to characterize ecological effects. These chronic NOAEL toxicological benchmarkvalues are obtained from the literature, where available, or are derived using conservativemethods, for each selected indicator species and applicable exposure pathway. Thesetoxicological benchmark values are protective of ecological exposures at the individual level ofexposure (e.g., chronic toxicity value for fish). However, in evaluating assessment endpoints atthe individual level of exposure, it is assumed that the NOAEL values are also protective ofpotential effects at the population and community level, which are generally much more difficultto predict. Section 9.6 describes the selected indicator species, used to estimate the impacts ofingestion of COECs on herbivores, earthworm-eaters, piscivores and carnivores.

Section 9.7 combines the results of the preceding sections to calculate hazard quotients forselected indicator species and ecosystems. A hazard quotient below one indicates that thecompound presents no significant ecological risk to environmental receptors. Hazard quotientsabove one indicate that it is not possible to conclude (on the basis of a screening-levelassessment) that potential risks from exposure to a given compound are insignificant, and thatfurther evaluation may be required. Uncertainties in the ecological risk assessment are discussedin Section 9.8.

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9.2 Study area characterization

The LSI/Greencastle facility is located about a mile south of Greencastle, Indiana, a city of about9,000 inhabitants. As Greencastle is the most significant population center within many miles ofthe LSI/Greencastle facility, the study area is best described as rural in character, though notunpopulated. Much of the land in the study area, especially to the north of the LSI/Greencastlefacility, has been developed for agricultural use.

The LSI/Greencastle facility is located roughly in the center of the Eel-Big Walnut Watershed,which extends 1,211 square miles over portions of nine counties in southwestern Indiana andrepresents the characteristics of the study area. Figure 9.1 shows the three ecoregions that areincluded within the Eel-Big Walnut Watershed (IDEM, 2001b):

• The Interior River Lowland ecoregion, found in the southwestern portion of thewatershed, is characterized by undulating lowland plains with wide, shallow valleys. It ispart of the central U.S. hardwood forests, which are characterized by drought-resistanttrees like oak and hickory (National Geographic, 2002). Most of this region has beenconverted into agricultural land and pasture (National Geographic, 2002). Land uses inthis ecoregion consist of cropland, scattered woodland, and surface coal mining. Therelevant sub-region is the Glaciated Wabash Lowlands, consisting mainly of farmland forcorn, soybean, and wheat, with scattered woodlands and coal mines. Many streams in theregion have gravel bottoms, riffles, and associated fauna.

• The Interior Plateau ecoregion, found in the southeastern portion of the watershed, ischaracterized by heavily dissected hills with narrow, steep valleys, making for morerugged terrain. Like the Interior River Lowland, this area is part of the central U.S.hardwood forests. Land use in this ecoregion consists mostly of forested lands, withsome farming of valley areas. The relevant sub-regions include Crawford Upland and theMitchell Plain. The Crawford Uplands has many medium to high gradient streams, withoaks, mixed mesophytic forest, and specialized plant communities dominating the easternsandstone-limestone cliffs. The Mitchell Plain contains residential and urban areas,although the peripheral hills are wooded. Mesophytic forests, karst wetland communitiesand limestone glades dominate in this sub-region.

• The Eastern Corn Belt Plains ecoregion, found in the northern portion of the watershed,is characterized by level to rolling plains. It is part of the southern Great Lakes forests,made up of rolling hills, extensive interior wetlands and freshwater bodies with sanddunes (National Geographic, 2002). Most of this area has been converted by intensiveindustrial development (National Geographic, 2002). Lands in this ecoregion are usedmostly for cropland, with some scattered woodlands and urban development (thewatershed extends northward to include Indianapolis). The relevant sub-region is the

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@@@Place Figure 9.1 here@@@

2 A town range is an area approximately 6 mi. by 6 mi., containing 36 1 mi. by 1 mi.sectors. Town ranges and sectors are printed in red on USGS topographic maps.

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Loamy, High Lime Till Plains. This sub-region hosts Beech forest, oak and sugar mapleforests, and elm-ash swamp forests. Corn, soybean, and livestock production arecommon in this sub-region.

A significant portion of the land within the study area has been developed for agricultural use,especially in the flat areas to the north. This development has considerably modified the nativebeech forest vegetation of the lands in the northern portion of the study area, and also hasaffected the native oak-hickory forests that still dominate the lands in the southern portion of thestudy area. The rural and diverse nature of the study area supports a wide variety of habitat. Assuch, the scope of the SERA is broadly defined to include a range of different terrestrial andaquatic exposure scenarios.

As shown in Figure 3.5, the points of maximum impact (used to estimate exposure pointconcentrations in air, soil, plants, and terrestrial animal tissue) are all near the property boundaryof the LSI/Greencastle facility, near the border of the Greencastle and Cloverdale quadrangles(Town range 014N004W, Sections 28, 29).2 As Figure 9.1 shows, this area is near the border ofthe Crawford Uplands and the Loamy, High Lime Till Plains.

Similar to the human health risk assessment, the evaluation of aquatic habitats focuses onCagle’s Mill Lake, the most extensive water body in the area of the LSI/Greencastle facility. Cagle’s Mill Lake is a man-made reservoir in the Crawford Uplands sub-region of the InteriorPlateau. It was built by the Army Corps of Engineers as a flood control impoundment (Keller,2000). The Division of Fish and Wildlife of the Indiana Department of Natural Resources hasstocked the reservoir with walleye, and manages the Cagle’s Mill Lake fishery (Keller, 2000).

9.2.1 Endangered, threatened, and rare species

Endangered, threatened and rare species within a 50 km radius of the LSI/Greencastle facility arelisted in Appendix VI. Six endangered, threatened, or rare species are within 10 km of thefacility:

• etheostoma pellucidum, or the Eastern Sand Darter (a fish); • aimophila aestivalis, or Bachman’s Sparrow;• lynx rufus, or the Bobcat;• taxidea taxus, or the American Badger;• opheodrys aestivus, or the Rough Green Snake; and• lutra canadensis, the northern river otter.

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The Eastern Sand Darter and Bachman’s Sparrow are present in the same town range as theLSI/Greencastle facility. In addition, bald eagles have been observed nesting near Cagle’s MillLake, which is used as the exposure location for surface water, sediment, and fish in both thehuman health and the ecological risk assessment.

The bald eagles of Cagle’s Mill Lake are the only endangered species explicitly evaluated in theecological risk assessment, as this was the only one of the local endangered species that haddietary exposure data listed in the Wildlife Exposure Factors Handbook (U.S. EPA, 1993). Risks to the other endangered, threatened, and rare species are evaluated through the use ofindicator species (described in Section 9.6). These indicator species are used to estimate thepotential risks to small mammals, small birds, carnivores, and piscivores, while surface waterecological benchmark values are used to estimate potential risks to aquatic animals.

In order to provide more information on endangered, threatened, or rare species within 10 km ofthe LSI/Greencastle facility, the required habitats and life cycles of these species are discussed inmore detail below.

9.2.1.1 Eastern Sand Darter

The Eastern Sand Darter is a small fish (2.5 inches in length) that is found east of the MississippiRiver in the states of Indiana, Illinois, Kentucky, Michigan, Ohio, West Virginia, Pennsylvania,and New York (NYS DEC, 2002). According to the Indiana Department of Natural Resources,its habitat is the Big Walnut Creek, which passes through the town range that contains theLSI/Greencastle facility and the area of maximum impact, and then proceeds to the Clinton Fallsand Reelsville quadrangles in (see Appendix VI). Although little information is available on thebiology of the eastern sand darter, it is thought to spawn beginning in May and possiblycontinuing into the fall. The sand darter will frequently bury itself in sand in order to hide frompredators, to maintain its position in a fast-flowing stream section, and to ambush prey. Aquaticinsects make up the bulk of the sand darter’s diet (NYS DEC, 2002).

The eastern sand darter is considered of special concern by the Indiana Department of NaturalResources (see Appendix VI). The major cause of declines in eastern sand darter populations isthe loss of habitat, i.e. the loss of clean sandy substrate due to siltation (NYS DEC, 2002). Thebuilding of dams may fragment sand darter populations (NYS DEC, 2002), and the clearing ofland for agriculture may also silt many streams that were previously suited for the sand darter(Cornell, 2002). Thus, historical development of the region for farming has likely degraded thelocal habitat for the eastern sand darter. No toxicological data for the eastern sand darter areavailable from the ECOTOX database (ECOTOX, 2002).

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9.2.1.2 Bachman’s Sparrow

Bachman’s Sparrow generally inhabits open oak trees and pines, old orchards, brusshy hillsidesand abandoned fields and pastures in the early stages of tree invasion with scattered shrubs andbushes (ILDNR, 2002a). The sparrow feeds on mostly grass seeds, with a smaller fraction of thediet consisting of grasshoppers and other insect larvae. Bachman’s sparrows have been observedfeeding insects and insect larvae to their young (ILDNR, 2002a). According to the IndianaDepartment of Natural Resources, its habitat in the Greencastle quadrangle passes through townrange 014N004W, which also contains the area of maximum impact of the LSI/Greencastlefacility (see Appendix VI).

The breeding season for Bachman’s sparrow is estimated to be from early April through August(ILDNR, 2002a). The species has about two broods per season, with 3 to 5 eggs per clutch(ILDNR, 2002a). The species is territorial, with approximately one pair for every two acres inoptimal nesting habitat (ILDNR, 2002a). The species in considered endangered by the IndianaDepartment of Natural Resources (see Appendix VI). The numbers of this species are steadilydeclining for unknown reasons (GMNH, 2000). No toxicological data for Bachman’s sparroware available from the ECOTOX database (ECOTOX, 2002).

9.2.1.3 Rough Green Snake

The Rough Green Snake is from 22-32 inches in length, and is found in mixed hardwood andbottomland forests (FLMNH, 2000). It prefers densely leafed trees and shrubs, often at theedges of fields and near ponds (FLMNH, 2000). According to the Indiana Department ofNatural Resources, the rough green snake is found in the Clinton Fall Quadrangle, to thenorthwest of the area of maximum facility impact (see Appendix VI).

The rough green snake mates in spring and lays 4 to 6 eggs in rotting logs and stumps, under flatrocks and other cover (ILDNR, 2002b). The species feeds on crickets, caterpillars, grasshoppers,spiders, and other soft arthropods (ILDNR, 2002b). The rough green snake is considered ofspecial concern by the Indiana Department of Natural Resources (see Appendix VI). Thepopulation of the rough green snake may be reduced in areas where insecticides are applied. Notoxicological data for the rough green snake are available from the ECOTOX database(ECOTOX, 2002).

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9.2.1.4 North American Badger

The North American Badger is a carnivore that is found in dry, open country (UMMZ, 1996). The species feeds mainly on small mammals, birds, reptiles, and arthropods, which it captures bydigging (UMMZ, 1996). According to the Indiana Department of Natural Resources, badgershave been found in the Cloverdale quadrangle, to the southeast of the area of maximum impactof the LSI/Greencastle facility (see Appendix VI). Mating occurs in early autumn, with one tofive offspring born in the spring (UMMZ, 1996). Badgers are solitary, with approximately 5animals per square kilometer (UMMZ, 1996). The North American Badger is consideredendangered by the Indiana Department of Natural Resources (see Appendix VI), although theU.S. Forest Service believes that the populations of badgers in Indiana are stable, due toincreases in open land and cultivated areas (USFS, 2002a). No toxicological data for the NorthAmerican Badger are available from the ECOTOX database (ECOTOX, 2002).

9.2.1.5 Bobcat

Bobcats are found in the north in broken country including swamps, bogs, conifer stands, androcky ledges, with ledges appearing to be the most important feature (USFS, 2002b). Bobcatswill feed on any prey available, such as insects, fish, amphibians, reptiles, birds, and mammals,although small mammals are the most common (USFS, 2002b). According to the IndianaDepartment of Natural Resources, bobcats have been found in the Cloverdale and Reelsvillequadrangles, to the south of the area of maximum impact of the LSI/Greencastle facility (seeAppendix VI). Habitat features such as thickets, stumps, logging debris, and various types ofrock features provide den sites and resting areas for bobcats (USFS, 2002b). Bobcats areconsidered endangered by the Indiana Department of Natural Resources (see Appendix VI). Notoxicological data for bobcats are available from the ECOTOX database (ECOTOX, 2002).

9.2.1.6 River Otter

The river otter ranges widely along rivers, streams, swamps, and marshes. It forages for foodsuch as rough fish, crayfish, mollusks, crabs, amphibians, rodents, birds, eggs, and small reptiles.According to the Indiana Department of Natural Resources, river otters have been found in theReelsville Quadrangle, to the south of the area of maximum impact of the LSI/Greencastlefacility (see Appendix VI). The species is considered endangered by the Indiana Department ofNatural Resources (see Appendix VI), and no toxicological data on the species are availablefrom the ECOTOX database (ECOTOX, 2002).

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9.3 Selection of ecological compounds of concern

In order to reduce the number of compounds to be considered in the full ecological riskassessment, it is necessary to identify compounds of ecological concern (COECs), thosecompounds emitted from the LSI/Greencastle facility that cover the majority of potentialecological risks. The selection procedure starts with all of the constituents considered in thehuman health risk assessment, including constituents that are present in the hazardous waste feedbut were not detected in the Particles of Incomplete Combustion (PIC) Risk Burn. As discussedbelow, scoring algorithms and professional judgement are used to identify those compounds thattend to bioaccululate in environmental media and therefore present the highest potential risks toecological receptors. The scoring algorithms used are those presented in the ecological riskassessment work plan (Horizon Environmental, 1998). The selected COECs (as determined bythe scoring algorithms) are then carried through the ecological risk assessment, while all otheremitted compounds are assumed to present negligible ecological risks. The implications of thisassumption are discussed in Section 9.8.

As was done for the assessment of risks to human health, two sets of emission rates areconsidered. Primary consideration is given to the MACT emission rates, which includecompounds subject to MACT regulations at their allowable MACT-based emission limits, andall other compounds at high-end emission rates based on facility testing. Most of the tables atthe end of the chapter are based on the MACT emission rates (exceptions are clearly noted). Secondary consideration is also given to the measured emission rates, which include compoundsat high-end values based on the ROC and PIC Risk Burn emissions testing. Since MACTemission rates are equal to or greater than measured emission rates for all compounds, riskestimates found to be below levels of concern for the MACT emission rates are by inferenceacceptably small for the measured emission rates. In some cases, risk estimates based uponMACT emission rates exceed screening-level limits, and the differences between MACT andmeasured emission rates are of potential importance. These compounds serve as the basis ofadditional tables prepared specifically for the measured emission rates.

9.3.1 Selection of inorganic compounds and metals

Inorganic compounds, especially many metals, are known to bioaccumulate in environmentalmedia and organisms. Thus, all metals assessed in the human health risk assessment wereincluded in the ecological risk assessment as COECs, consistent with the methods outlined in theecological risk assessment work plan (Horizon Environmental, 1998).

3 For all organic compounds except polychlorinated dibenzo(p)dioxins and furans (whichare assessed at the MACT emission limit), emission rates are calculated as described in Section2.5 of the human health assessment. Appendix III gives the literature sources of the listedphysical properties.

4 If a NOAEL was available, no LOAEL is given in Table 9.2.

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9.3.2 Selection of organic compounds

Table 9.1 lists organic compounds identified as possible emissions from the LSI/Greencastlefacility, along with their estimated emission rates, octanol-water partition coefficients (Kow), andsolubilities in water, where available.3 Following the human health risk assessment, only twotentatively identified compounds (TICs), benzaldehyde and benzonitrile, are included in Table9.1 (see Section 2.3 of the human health assessment). The impact of the exclusion of other TICsfrom the ecological risk assessment is discussed in Section 9.8.

Following the ecological risk assessment work plan (Horizon Environmental, 1998), the list ofCOECs is narrowed to focus on a smaller group of compounds most likely to present risks to theenvironment. Four separate scoring algorithms (two for terrestrial receptors, and two for aquaticreceptors) are used to select COECs from the organic compounds listed in Table 9.1. Thesescoring algorithms consider four possible exposure pathways: inhalation (for terrestrialorganisms), ingestion (for terrestrial organisms), aquatic exposures based on a compound’sbioaccumulation potential (as estimated by the octanol-water partition coefficient of thecompound), and aquatic exposures based on the compound’s water solubility. The scoringalgorithms and their results are discussed below.

9.3.2.1 Terrestrial scoring algorithms

Two terrestrial scoring algorithms were used to select organic COECs. The first, based oninhalation exposure, is described in Section 9.3.2.1.1, while the second, based on ingestionexposure, is described in Section 9.3.2.1.2.

Both terrestrial scoring algorithms use the terrestrial chronic toxicity values listed in Table 9.2. These toxicity values are based on the lowest available no observed adverse effects level(NOAEL) for a compound in small mammals. This implicitly assumes that plants, birds, andreptiles are not more sensitive to compound exposures than small mammals. If a NOAEL wasunavailable for a compound, an unadjusted lowest observed adverse effects level (LOAEL) wasdivided by 10 to obtain an estimate of the NOAEL for that compound.4

If neither a NOAEL nor a LOAEL were available for a compound, values for chemically similarsurrogates were used. For example, for many polycyclic aromatic hydrocarbons (PAHs) where

5 While coplanar PCBs were treated as dioxins, the total amount of PCB congenersemitted (labeled “PCB congener (total)” in Table 9.1), was treated as a separate compound, withan LOAEL of 0.07 mg/kg-day (HEAST, 1997).

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NOAELNOAEL

TEFiTCDD

i= −2 3 7 8, , , (9.1)

no NOAEL was available, the NOAEL of naphthalene (71 mg/kg-day) was used as aconservative estimate of the chronic terrestrial toxicity value.

NOAELs for dioxin congeners were calculated from the reported NOAEL for 2,3,7,8-TCDD of1 × 10!6 mg/kg-day (RTI, 1999), and the reported toxicity equivalency factors (TEFs) for dioxins(RTI, 1999) using the equation:


NOAELi the calculated NOAEL for compound i (mg/kg-day),NOAEL2,3,7,8-TCDD the reported NOAEL for 2,3,7,8-TCDD (1 × 10!6 mg/kg-day), andTEFi the reported toxicity equivalency factor for compound i (unitless).

The RTI background document reports two sets of TEFs, one for mammals and one for birds, aslisted in Table 9.3. For the purposes of the inhalation and ingestion scoring algorithms, the moreconservative (i.e., larger) TEF was used in calculating the NOAELs for polychlorinated dioxinsand dibenzofurans for scoring purposes. In addition, the emission rate of coplanar PCBs givenin Table 9.1 is calculated on a toxicity equivalent (TEQ) basis to 2,3,7,8-TCDD. Thus, coplanarPCBs were given the same NOAEL as 2,3,7,8-TCDD.5

For a few compounds (e.g., 2-propanol, benzonitrile, butyl acetate, diacetone alcohol,dibenzofuran, ethanol, isobutyl acetate, methyl isoamyl ketone, n-octane, n-propanol, propylacetate, and tetrahydrofuran) neither NOAELs, LOAELs, nor toxicological data for chemicallysimilar surrogates were available. Thus, inhalation and ingestion scores were not calculated forthese compounds. The effect of the exclusion of these compounds from the list of COECs isdiscussed in Section 9.8.

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ScoreERTVInh i

i

i, = (9.2)

ScoreER K

TVIng ii ow

i, =

⋅(9.3)

9.3.2.1.1 Inhalation scoring algorithm

Inhalation of compounds emitted from the combustion facility is a potential route of exposure forterrestrial animals. In order to screen compounds based on their potential to present a risk toterrestrial animals via inhalation, an inhalation score was calculated using the equation:where the terms are:

ScoreInh,i the inhalation score for compound i (g-kg-day/mg-s),ERi the emission rate for compound i (g/s), andTVi the terrestrial chronic toxicity value for compound i (mg/kg-day).

The emission rates used to calculate the inhalation score are given in Table 9.1, while thetoxicity values are listed in Table 9.2. Calculated inhalation scores for organic compounds arelisted in Table 9.4. The compounds representing 95 % of the total inhalation score wereincluded in the risk assessment as COECs. These include benzene (90.2 %), iodomethane (2.22%), 2,3,7,8-TCDF (2.36 %), and 2,3,4,7,8-PCDF (1.98 %). These compounds are in boldface onTable 9.4.

9.3.2.1.2 Ingestion Scoring Algorithm

Compounds emitted by the LSI/Greencastle facility could deposit onto soil and plants andbecome incorporated into potential food sources for terrestrial mammals. In order to screencompounds based on their potential to incorporate into food sources and pose ecological risks toterrestrial animals, an ingestion score was calculated using the equation:


ScoreIng,i the ingestion score for compound i (g-kg-day/mg-s),Kow the octanol-water partition coefficient for compound i,

ERi the emission rate for compound i (g/s), andTVi the terrestrial chronic toxicity value for compound i (mg/kg-day).

The toxicity values used for the calculation of the ingestion score are given in Table 9.2. Emission rates and Kow values are given in Table 9.1. Calculated ingestion scores for organic

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LCLC

TEFiTCDD

i50

50 2 3 7 8,

, , , ,= − (9.4)

compounds are listed in Table 9.5. The compounds representing 95 % of the total ingestionscore were included in the risk assessment as COECs. These include 2,3,7,8-TCDD (4.43 % oftotal ingestion score), 1,2,3,7,8-PCDD (3.19 %), 1,2,3,4,7,8-HxCDD (9.78 %), 1,2,3,6,7,8-HxCDD (4.87 %), 1,2,3,7,8,9-HxCDD (4.57 %), 1,2,3,4,6,7,8-HpCDD (33.7 %), 2,3,7,8-TCDF(10.3 %), 2,3,4,7,8-PCDF (21.1 %), and 1,2,3,4,7,8-HxCDF (3.32 %). These compounds are inboldface on Table 9.5.

9.3.2.2 Aquatic Scoring Algorithms

Two aquatic scoring algorithms were used to select organic COECs. The first method was basedon the compound’s bioaccumulation potential, as measured by the octanol-water partitioncoefficient (Kow) for that compound. The second aquatic scoring algorithm was based on thewater solubility of a compound. These scoring algorithms and their results are described below.

Both aquatic scoring algorithms use the toxicity values listed in Table 9.6. As stated in theecological risk assessment work plan (Horizon Environmental, 1998, p. 11), an acute ambientwater quality criterion or the lowest available LC50 value for a freshwater species was used as theaquatic toxicity value in the aquatic scoring algorithms. Federal Ambient Water Quality Criteria(AWQC) for freshwater were used, if available (Federal Register, 1998). If not, Acute AquaticLife Criteria (AALC) obtained from the Indiana Department of Environmental Management(IDEM) were used (IDEM, 2000). If neither was available for a compound, the lowest availableLC50 value for a freshwater species was used as the aquatic toxicity value.

For compounds where an LC50 was not available, values from chemically similar surrogates wereused. For example, for PAHs where no LC50 was available, the LC50 of benzo(a)pyrene was usedas a conservative estimate of their LC50.

For dioxin congeners where no congener-specific LC50 was available, a congener-specific LC50was estimated by the equation (for TEF … 0):


LC50,i the estimated LC50 for dioxin congener i (:g/L),LC50,2,3,7,8-TCDD the lowest available LC50 of 2,3,7,8-TCDD (0.0057 :g/L for high-eyes

medaka), andTEFi the toxicity equivalency factor for dioxin congener i.

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ScoreER K

TVK ii ow

iow , =

⋅(9.5)

The emission rate for coplanar PCBs is calculated on a TEQ basis with 2,3,7,8-TCDD, and thusthe LC50 of 2,3,7,8-TCDD is used for coplanar PCBs.

9.3.2.2.1 Bioconcentration (Kow) based algorithm

Some compounds emitted from the LSI/Greencastle facility may partition into sediments andbioaccumulate in food items, such as aquatic plants, invertebrates, and fish. In order to screencompounds based on their potential to partition to sediments and bioaccumulate in food sources,an aquatic bioaccumulation score was calculated using the equation:


ScoreKow,i the bioconcentration based aquatic score for compound i (g-L/:g-s),Kow the octanol-water partition coefficient for compound i,

ERi the emission rate for compound i (g/s), andTVi the aquatic toxicity value for compound i (:g/L).

Compound emission rates and Kow values are listed in Table 9.1, while the aquatic toxicityvalues used are listed in Table 9.6.

Calculated aquatic bioaccumulation scores for organic compounds are listed in Table 9.7. Thecompounds representing 95 % of the total ingestion score were included in the risk assessment asCOECs. These include total PCB congeners (3.24 % of total ingestion score),benzo(a)anthracene (4.04 %), benzo(g,h,i)perylene (1.85 %), benzo(a)pyrene (2.96 %),phenanthrene (3.12 %), pyrene (0.98 %), 2,3,7,8-TCDD (4.08 %), 1,2,3,6.7.8-HxCDD (4.49 %),1,2,3,7,8,9-HxCDD (4.21 %), 1,2,3,4,6,7,8-HpCDD (31.0 %), 2,3,7,8-TCDF (9.47 %), 1,2,3,7,8-PCDF (0.84 %), 2,3,4,7,8- PCDF (19.5 %), 1,2,3,4,7,8-HxCDF (3.05 %), and 1,2,3,6,7,8-HxCDF (1.39 %). These compounds are in boldface on Table 9.7.

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ScoreS ER

TVSol ii i

i, =

⋅(9.6)

9.3.2.2.2 Solubility based algorithm

Ecological receptors could be exposed to water-soluble compounds emitted by theLSI/Greencastle facility via direct ingestion of surface water. In order to screen compoundsbased on their potential to deposit into water, a solubility based aquatic score was calculatedusing the equation:


ScoreSol,i the water solubility based aquatic score for compound i (g-mg-L/:g-s),Si the water solubility of compound i (mg/L),

ERi the emission rate for compound i (g/s), andTVi the acute aquatic toxicity value for compound i (:g/L).

The aquatic toxicity values presented in Table 9.6 were used as the acute aquatic toxicity valuesin Equation 9.6. Compound emission rates and water solubilities are listed in Table 9.1.

Calculated aquatic solubility scores for organic compounds are listed in Table 9.8. Thecompounds representing 95 % of the total ingestion score were included in the risk assessment asCOECs. These include acetone (37.9 % of the total aquatic solubility score), acrylonitrile (16.9%), m-cresol (1.41 %), iodomethane (20.2 %), methanol (1.89 %) and phenol (17.7 %). Thesecompounds are in boldface on Table 9.8.

9.3.2.3 Selection based on professional judgement

In addition to the organic compounds selected as COECs by the above four scoring algorithms,all 2,3,7,8-dioxin congeners were included in the list of COECs. As a class, dioxins are highlytoxic at small doses, and tend to bioaccumulate in food sources. Thus, all 2,3,7,8-dioxincongeners are assessed for their potential to cause significant ecological effects.

The ecological risk assessment work plan prepared by Horizon Environmental (1998, p. 13)stated that, of the compounds not placed on the COEC list by the above screening algorithms, thecompounds with the five highest soil half-lives would also be selected as COECs. Thiscorresponds to the compounds with the five lowest values for ksg, the first order rate constant ofbiotic and abiotic degradation in soil (see Appendix III). After the compounds alreadyconsidered COECs are removed, the compounds with the five lowest ksg values are carbon

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tetrachloride (0.0703 yr-1), benzo(k)fluoranthene (0.118 yr-1), chrysene (0.253 yr-1),dibenzo(a,h)anthracene (0.269 yr-1), and ideno(1,2,3-cd)pyrene (0.347 yr-1) . Thus, thesecompounds are considered as COECs in the ecological risk assessment. Table 9.9 gives thefinal lists of COECs that are evaluated in the ecological risk assessment.

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9.4 Exposure point concentrations

In order to estimate the potential risks to ecological receptors from COECs emitted by theLSI/Greencastle Facility, exposure point concentrations must be estimated in several media,including air, soil, surface water, sediment, fish tissue, plants tissue, earthworm tissue, mammaltissue, and bird tissue.

As the exposure point locations (i.e., the area of maximum impact for exposure to air, soil, andplants, and Cagle’s Mill Lake for surface water, bed sediment, and fish tissue exposure) are thesame for both the ecological and human health risk assessments, the exposure pointconcentrations calculated in the human health risk assessment for air, soil, surface water, bedsediment, fish tissue, and plants are also valid for the ecological risk assessment, and are usedthroughout. Non-cancer exposure point concentrations were used throughout the ecological riskassessment, as these concentrations are derived assuming that the LSI/Greencastle facility hasbeen operating, and depositing COECs, for a period of 100 years, leading to high-end,conservative estimates of concentrations in soil, surface water, sediment, plants, and fish.

Table 9.10 lists the exposure point concentrations for COECs in air and soil. The listed airconcentrations are the estimated long-term average concentrations of COECs in air at thelocation of maximum impact, and are used to evaluate possible chronic inhalation effects onterrestrial species.

The human health risk assessment lists several exposure point concentrations in soil (see Section2.5). Tilled soil values were used in preference to untilled soil values, because the presence ofearthworms in Indiana soil leads to soil mixing depths of 15 cm to 20 cm , rather than the 1 cmmixing depth assumed in deriving the untilled soil exposure point concentrations. The annualmovements of earthworms give soil an effective mixing depth of about 15 cm to 20 cm (Box andHammond, 1990; Willoughby, 2001). As the derivation of the tilled soil exposure pointconcentrations assumes a soil mixing depth of 20 cm, the tilled exposure concentrations are morerealistic estimates of soil exposure point concentrations for plant exposure, earthworm exposure,and the ingestion of soil by terrestrial animals. For example, much of the soil ingested by birdswould be associated with earthworms. Table 9.10 lists two sets of soil exposure pointconcentrations. The first set gives the estimated soil concentration at the location of maximumimpact, while the second set gives the estimated soil concentration near the watershed.

The estimated exposure point concentrations in surface water are listed in Table 9.11. Four setsof data are given, corresponding to whether the water is near tilled or untilled soil, and whetherthe water is standing or flowing. Similarly, Table 9.12 gives four sets of estimated exposurepoint concentrations in the sediment bed, and Table 9.13 gives four sets of estimated exposure

6 The fish are assumed to be trophic level 4, such as bass, trout, and pike. Smaller fish ofa lower trophic level, , like perch, bluegill, and bloater, would likely have lower concentrationsof COECs in their tissues (E.P.A. Mercury Report to Congress, 1997).

7 This is the equation referenced by the ecological risk assessment work plan, but theform given in the work plan was incorrect. See Section 9.7.

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CC BAF

Fearthwormsoil=

⋅(9.7)

point concentrations in fish, again divided between tilled/untilled soil and standing/flowingwater.6

Table 9.14 gives the estimated exposure point concentrations in plant tissue for five types ofplants: above ground produce (Ag), forage grasses (Forage), fermented, stored forage grasses(Silage), root vegetables (Rootveg), and grains and seeds (Grain), as calculated in the humanhealth risk assessment. The estimation procedure used in the human health risk assessment isslightly different from that presented in the ecological risk assessment work plan (HorizonEnvironmental, 1998), with different limits on the correlations used to estimate root and vaporuptake in plants. The effect of this difference on the ecological risk assessment is discussed inSection 9.8.

The human health risk assessment did not calculate exposure point concentrations in earthworm,mammal or bird tissue, which are needed to estimated the dietary intake of COECs bycarnivores. Exposure point concentrations in earthworm tissue are estimated using the equation:


Cearthworm wet weight earthworm tissue mass fraction (mg/kg),C soil maximum tilled soil exposure point concentration (mg/kg), BAF the compound-specific bioaccumulation factor in earthworm tissue

(unitless), andF dry weight to wet weight tissue conversion factor (equal to 4, based on an

earthworm solids fraction of 25 % (Horizon Environmental, 1998).

Table 9.15 lists the BAF values used for earthworms. Where available, BAF values wereobtained from literature sources. If a BAF was not available for an inorganic compound, a soilto earthworm BAF of 1 was used, as stated in the ecological risk assessment work plan (HorizonEnvironmental, 1988). If a BAF was not available for an organic compound, the BAF wascalculated using the following equation (Markwell & Connell, 1990):7

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BAFf K

xflipid ow

a

oc= (9.8)

C ADD W MF BAFtissue = ⋅ ⋅ ⋅ (9.9)


BAF compound-specific bioaccumulation factor in earthworm tissue (unitless),flipid fraction of lipid content in earthworms (0.0084),Kow octanol-water partition coefficient (unitless),a non-linearity constant (0.08), x proportionality constant (0.66), andfoc fraction of organic carbon in soil (0.01).

For insects, as no bioconcentration data were available, it was assumed that the concentration ofCOECs in insect tissue was the same as the maximum concentration from above-groundproduce, forage plants, grains, soil or earthworms. The impact of this assumption is discussed inSection 9.8.

For mammals and birds, the concentration in the animal tissue was calculated using the formula:where the terms are:

Ctissue wet weight tissue mass fraction (mg/kg),ADD estimated average daily dose of COEC (mg/kg-d),W body weight of indicator species (kg),MF metabolism factor (1),BAF bioaccumulation factor (unitless).

Two mammalian species, the deer mouse and the meadow vole, and two avian species, thenorthern bobwhite and the American woodcock, were used to estimate the exposure pointconcentrations of COECs in animal tissue. These small herbivores are representative of the typeof animals consumed by most terrestrial carnivores. Daily doses of COECs for these species arecalculated in Section 9.7.5 using Equation 9.16, and are listed in Tables 9.27, 9.29, 9.31, and9.33, respectively. Body weights for these species are given in Tables 9.26, 9.28, 9.30, and 9.32,respectively. These average daily doses and body weights are then used in Equation 9.9 tocalculate the exposure point concentrations of COECs in the tissue of herbivores.

For mammals and birds, the BAF values were assumed to be one. If the chicken, pork, or beefBAF values from the human health risk assessment were above one, the more conservativechicken BAF value was used for birds, and the maximum of the beef and pork BAF values wasused for mammals (see Appendix III for beef, pork, and chicken BAF values). The selected

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BAF values are listed in Table 9.15. These BAF values are then used to calculate the animaltissue exposure point concentrations listed in Table 9.16.

9.5 Toxicological data and calculation of Ecological Benchmark Values(EBVs)

In order to estimate the potential for risks to ecological receptors from COECs emitted by theLSI/Greencastle facility, it is necessary to obtain toxicological data on the dose-responsebehavior of COECs in various media and species. Five types of toxicological data were gatheredfor the ecological risk assessment, including:

• Inhalation toxicity data for terrestrial animals (Table 9.17),• Soil toxicity data for plants and soil community organisms (e.g., earthworms)

(Table 9.18),• Surface water toxicity data for the aquatic ecosystem (Table 9.19),• Sediment toxicity data for the aquatic ecosystem (Table 9.20), and• Ingestion toxicity data for birds and mammals (Table 9.18).

Media- and species-specific ecological benchmark values (EBVs) were calculated using thetoxicological data listed in Tables 9.17 through 9.21, following the algorithms from theecological risk assessment work plan (Horizon Environmental, 1998), as described below. Acute toxicological values (such as LC50 values for the aquatic ecosystem) were divided byuncertainty factors of 1000 to extrapolate from acute toxicity data to chronic ecologicalbenchmark values. Subchronic (intermediate) toxicity data were divided by uncertainty factorsof 10 to extrapolate to chronic toxicity data. Similarly, chronic LOAEL values were divided byfactors of 10 to extrapolate to chronic NOAEL values.

However, uncertainty factors were not used for interspecies and intraspecies extrapolations. It isunlikely that other species would be ten times as sensitive as the reported species, as suggestedby the Horizon Environmental work plan. Not only are the toxicological data used to derive theEBVs based on the lowest reported levels, but much of the data are for species that are known tobe especially sensitive to contamination (e.g., mink). In addition, intraspecies variation is likelyto be a minor concern in the ecological risk assessment, as we are interested in maintaining thepopulation of animals near the LSI/Greencastle facility, rather than ensuring that everyindividual animal, no matter how sensitive, is protected from pollution. Since only a smallfraction of a species population is likely to be significantly more sensitive than the norm,intraspecies variation will likely have little to no effect on the population of animals as a whole. Thus, an uncertainty factor of 100 for every ecological benchmark value is likely to be highlyover-protective, and is therefore not included in this ecological risk assessment. The impact ofthe exclusion of this uncertainty factor is discussed in Section 9.8.

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ToxTox WC

Iairingestion= 1 (9.10)

EBVToxUFair

air

total= (9.11)

9.5.1 Calculation of air EBVs

Air EBV’s were calculated from the inhalation toxicological values listed in Table 9.17, whereavailable. If no inhalation toxicological value was available for a COEC, one was estimatedusing the equation:


Toxair estimated inhalation toxicological value (:g/m3),Toxingestion lowest available ingestion toxicological value (mg/kg-day, from Table

9.21),W body weight of meadow vole (0.033 kg),I inhalation rate of meadow vole (0.044 m3/day), andC1 conversion factor (1000 :g/mg).

A meadow vole was used as the indicator species for the calculation of inhalation risk criteriafrom ingestion dose data due to its low body weight to inhalation rate ratio (0.75 kg-d/m3), whichleads to conservative estimates of reference concentrations (U.S. EPA, 1993). The choice of themeadow vole as an indicator species is discussed in Section 9.8.

After inhalation toxicological values were estimated for the remaining COECs, uncertaintyfactors (UFs) were applied to the values for acute to chronic (UF = 1000), subchronic to chronic(UF = 10) and LOAEL to NOAEL extrapolations (UF=10), according to the equation

where the new terms are:

EBVair air ecological benchmark value (:g/m3), andUFtotal the product of all applicable uncertainty factors (unitless).

The resulting air EBVs are listed in Table 9.22. The use of mammal and bird inhalationtoxicological values to derive air EBVs assumes that reptiles, plants, and other birds andmammals are not more sensitive to COECs in air than the species used to determine the

8 Data for Monroe County was used as this county is the closest to the LSI/Greencastlesite of the counties for which data is available.

9 Criteria were calculated using a Tier II methodology, as described in the Great LakesBasin methodologies (IDEM, 2000).

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toxicological values. The impact of this assumption on the ecological risk assessment isdiscussed in Section 8.8.

9.5.2 Calculation of soil EBVs

The soil toxicity criteria for plants and soil community organisms listed in Table 9.18 were usedas soil EBVs, where available. As these criteria were derived as chronic, NOAEL values forplants and soil community organisms, no uncertainty factors were applied to these values. Soiltoxicity values were not available for all COECs, and thus soil EBVs were not calculated for all compounds. The potential ecological risks from COECs for which soil criteria was unavailableare discussed in Section 8.8.

In addition to soil EBVs, soil background data taken from Monroe County, Indiana8, were usedto assess the conservatism of potential ecological risk estimates to plants and soil communityorganisms (Boerngen and Shacklette, 1981). Several soil background levels (e.g., those for totalchromium and copper) greatly exceed the soil EBVs, indicating that the screening-level riskestimates may be overstated, given that EBVs are only a fraction of natural background levels.

9.5.3 Calculation of surface water EBVs

Table 9.19 lists the available aquatic ecosystem toxicological data for surface water. Whereavailable, freshwater Criterion Continuous Concentrations (CCCs) from the federal AmbientWater Quality Standards (AWQC) were used as surface water EBVs (Federal Register, 1998). Ifa federal AWQC was unavailable, chronic aquatic life criteria in fresh water calculated by theIndiana Department of Environmental Management (IDEM) were used as surface water EBVs(IDEM, 2000).9 CCCs and chronic criteria were selected as conservative estimates of protectivelevels in surface water for long-term exposure to contamination, as recommended by theecological risk assessment work plan (Horizon Environmental, 1998). If no federal or statechronic surface water criteria were available, the lowest available fresh water LC50 value,divided by an acute to chronic uncertainty factor of 1000, was used as the surface water EBV. The resulting surface water EBVs are listed in Table 9.24.

10 Assumed value used in the derivation of compound properties in the HHRAP.

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EBV f SQCsediment oc= ⋅ (9.12)

EBV f K FCV Csediment oc oc= ⋅ ⋅ ⋅ 2 (9.13)

9.5.4 Calculation of sediment EBVs

A federal draft Sediment Quality Criterion (SQC) was only available for one COEC:phenanthrene (180 mg/kg of organic carbon in sediment). This was converted to a sedimentEBV by the equation:


EBVsediment sediment ecological benchmark value (mg/kg sediment),foc fraction of organic carbon in sediment (0.04 kg-oc/kg sediment10), andSQC federal sediment quality criterion in freshwater (mg/kg-oc).

Following the ecological risk assessment workplan (Horizon Environmental, 1998), organiccompounds with a log(Kow) value between 2.0 and 5.5 for which Tier II chronic aquatic lifecriteria were available (e.g., benzene and carbon tetrachloride) were given sediment EBVscalculated using the equation:

where the new terms are:

Koc organic carbon partition coefficient (L/kg), FCV final chronic value, or the Tier II chronic water criteria (:g/L), andC2 conversion factor (1 mg/1000 :g).

Koc values for benzene and carbon tetrachloride are given in Appendix III. For othercompounds, Lowest Effects Levels (LELs) in sediment, compiled by the Ontario Ministry ofEnvironment and Energy (OMEE), were used as the sediment EBVs, if available (OMEE, 1996). If not, ER-Ls compiled by the National Oceanic and Atmospheric Administration (NOAA) wereused as sediment EBVs. These ER-L values correspond to a concentration at the low end of therange of concentrations in which adverse effects have been observed (NOAA, 1991).

For several compounds, none of the listed criteria were available. Thus, sediment EBVs werenot calculated for these compounds. The possible effect of the exclusion of these compoundsfrom the calculation of the sediment hazard quotients is discussed in Section 9.8.

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EBV ToxWWIng i Ing test

test

i, ,=

⎛⎝⎜

⎞⎠⎟

14

(9.14)

9.5.5 Calculation of species-specific ingestion EBVs

Ingestion EBVs were calculated on an individual species basis, adjusted for the body weight ofthe species, following the recommendations of the ecological risk assessment work plan(Horizon Environmental, 1998). This was done by, first, dividing the toxicity data given inTable 9.21 by the appropriate uncertainty factors for acute to chronic (UF=1000), subchronic tochronic (UF=10), and LOAEL to NOAEL extrapolations (UF=10). Then, the resultantuncertainty-adjusted toxicity values were converted to species-specific ingestion EBVs by theequation:where the terms are:

EBVIng,i ingestion EBV for species i (mg/kd-d),ToxIng,test uncertainty-adjusted ingestion toxicity value (mg/kg-d)Wtest body weight of tested species, andWi body weight of species i.

The body weights for the tested species are listed in Table 9.21. If the body weight of the testedspecies was not given, the body weight was estimated as either the average of available valuesfor that species (as in the case of rats) or by comparison to a similar or representative species forwhich data were available (as in the case of mice and rabbits, assumed to weigh the same as adeer mouse and an eastern cottontail, respectively). The impact of these assumed weight valueson the ecological risk assessment is discussed in Section 9.8.

Where available, mammalian toxicological data was used to calculate ingestion EBVs formammals, and avian toxicological data was used to calculate ingestion EBVs for birds. ForCOECs where mammal and bird values were not both available, the lowest available value wasused for both mammals and birds. Species-specific ingestion EBVs and body weights forindicator species are listed in Tables 9.26 through 9.43.

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9.6 Selection of indicator species

In order to assess risks to herbivores, earthworm-eaters, piscivores, and carnivores from theingestion of COECs, several indicator species were selected. The selected species are routinelypresent in habitats similar to those found near the LSI/Greencastle facility, and have compileddietary exposure data available (U.S. EPA, 1993). They are also representative of species likelyto be exposed to higher levels of COECs by dint of their dietary habits or are known to besensitive to environmental pollutants.

To assess the risk to mammalian herbivores, the deer mouse and the meadow vole were selected.These small herbivores eat a large percentage of their body weight each day (22% for the deermouse, 35 % for the meadow vole) and are thus likely to have elevated daily doses of COECscompared with larger herbivores. The deer mouse eats a mixture of grasses, grains, produce andinsects, with about 45 % of the diet being plant matter. The meadow vole, in contrast, eatsgrasses and other green shoots almost exclusively, with some root vegetables, grains, andinsects. Given the different types of plants eaten by these two mammalian herbivores, the risks toboth were assessed, to ensure that all types of herbivores are protected.

The northern bobwhite was selected to estimate the risks to an avian herbivore, as this bird eats9 % of its body weight per day, mostly in grains and above ground produce. The Americanwoodcock also eats some plants, but its primary diet is earthworms (68 %) and otherinvertebrates. Thus, the American woodcock was used to assess risks to avian earthworm-eaters.Again, as these species eat a large fraction of their body weight each day, they are assumed to beconservative estimates of the exposure of the average avian herbivore and earthworm-eater.

Three piscivores were selected, two birds and one mammal. The kingfisher was selected torepresent avian piscivores, as this bird eats roughly 50 % of its body weight in fish per day, thehighest fish ingestion rate for a bird for which data is available in the Wildlife Exposure FactorsHandbook (U.S. EPA, 1993). The bald eagle was also included as an indicator species for avianpiscivores, as bald eagles have recently been sighted in the vicinity of Cagle’s Mill Lake. Themink was used as a conservative indicator species for mammalian piscivores, as the mink eats 22 % of its body weight in fish each day , the highest mammalian fish ingestion rate for whichdata is available (U.S. EPA, 1993). Mink are also known to be sensitive to contaminants such asPCBs and mercury.

Finally, two carnivores, one mammal and one bird, were selected. The red fox was selected asthe mammalian carnivore based on the availability of exposure data and its high food ingestionrate (7 % of its body weight per day), leading to conservative estimates of exposure formammals. Similarly, the red-tailed hawk was selected to represent avian carnivores for its highfood intake rate (11 % of its body weight per day) (U.S. EPA, 1993).

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HQEC

EBV=

9.7 Risk characterization

Risks are characterized in the ecological risk assessment by the calculation of hazard quotients(HQs) for the selected media and indicator species. Hazard quotients are calculated using theformula:


HQ hazard quotient,EC estimated exposure point concentration (or exposure dose), andEBV derived ecological benchmark value (See Section 9.5).

The calculation of hazard quotients for the selected media (air, soil, surface water, and sediment)and indicator species (deer mouse, meadow vole, northern bobwhite, American woodcock, mink,bald eagle, kingfisher, red fox and red-tailed hawk) are described below. These media andspecies cover a wide range of habitat and dietary types, and are used to assess the potentialecological risks to the assessment endpoints described in Section 9.1.2.

Hazard quotients below one indicate that there is no significant ecological risk to the media orindicator species from the emission of the COEC from the LSI/Greencastle Facility, and there isno need to further evaluate the effects of this COEC on the given media or indicator species. Hazard quotients above 1 indicate the possibility of significant ecological risks to the media orindicator species. It is important to note that a hazard quotient above one does not mean thatecological harm will occur. Rather, hazard quotients above one simply suggest that thepossibility of future ecological harm cannot be ruled out by a screening-level ecological riskassessment, and further ecological evaluation may be required. In the case of an initial hazardquotient above one, the derivation of the exposure point concentration (or exposure dose) and theEBV is reviewed, taking into account additional site- and species-specific information, and otherconsiderations (such as measured U.S. background levels in soils) are considered.

The COECs acetone, benzene, m-cresol, methanol, and phenol had modeled fugitive emissionsfrom the tank farm and sampling platform in addition to the stack emissions. In order to showthe effect of these modeled fugitive emissions on the estimated hazard quotients, the percentage

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of each hazard quotient that comes from fugitive emissions is listed in the tables in a column tothe right of the estimated hazard quotients.

9.7.1 Calculation of hazard quotients for air

Hazard quotients for air are listed in Table 9.22. The estimated long-term air concentrations atthe locations of maximum impact, as listed in Table 9.10 , were used as the exposureconcentrations, and air EBVs were calculated as described in Section 9.5. As all of the hazardquotients are below one, there is no significant ecological risk to terrestrial mammals and birdsfrom inhalation of COECs that may be emitted by the LSI/Greencastle facility.

As stated earlier, it is assumed that plants and reptiles are less sensitive to COECs in air than thespecies used to derive the air EBV, and that they are also protected by the derived air EBVs, andthus that there is also no significant ecological risk to plants or reptiles from COECs present inair. This assumption is discussed further in Section 9.8.

9.7.2 Calculation of hazard quotients for soil

Calculated hazard quotients for soil are shown in Table 9.23. The maximum listed soilconcentration in Table 9.10 was used as the exposure point concentration, and the soil EBVswere calculated as described in Section 9.5. As all of the soil hazard quotients are below 1, thereare no significant risks to plants or soil community organisms (e.g., earthworms) from COECsthat may emitted by the LSI/Greencastle facility. Ingestion of soil by terrestrial animals isevaluated along with other dietary exposures in Section 9.6.5.

As stated above, soil EBVs were unavailable for several COECs, and so hazard quotients werenot calculated for these compounds. The possible impact of these COECs in soil on plants andsoil community organisms is discussed in Section 9.8.

9.7.3 Calculation of hazard quotients for surface water

Calculated hazard quotients for surface water are listed in Table 9.24. The maximum COECconcentration in surface water (from those listed in Table 9.11) was used as the COEC exposurepoint concentration. Surface water EBVs were calculated as described in Section 9.5. As all ofthe calculated hazard quotients are several orders of magnitude below 1, there is no significantecological risk to the aquatic ecosystem from surface water containing COECs that may beemitted by the LSI/Greencastle facility.

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( )ADD F f EC W EC Cdiet i i water= + ⋅ ⋅∑ , 3 (9.16)

9.7.4 Calculation of hazard quotients for sediment

Calculated hazard quotients for sediment are displayed in Table 9.25. The maximum COECconcentration in sediment (from those listed in Table 9.12) was used as the COEC exposurepoint concentration. Sediment EBVs were calculated as described in Section 9.5. All of thecalculated sediment hazard quotients are well below 1. Thus, there is no significant risk to theaquatic ecosystem from sediment containing COECs that may be emitted by the LSI/Greencastlefacility.

As stated above, sediments EBVs were unavailable for several COECs, and so hazard quotientswere not calculated for these compounds. The possible impact of these COECs in sediment isdiscussed in Section 9.8.

9.7.5 Calculation of species-specific ingestion hazard quotients

In order to assess the risk to animals from the ingestion of food containing COECs that may beemitted by the LSI/Greencastle facility, several indicator species, representing different dietaryand habitat groups in the Greencastle area, were selected. Exposure data for each indicatorspecies was obtained from the Wildlife Exposure Factors Handbook (U.S. EPA, 1993). Toassess the potential ecological risks to mammalian herbivores, two species were selected: thedeer mouse (Tables 9.27 and 9.27) and the meadow vole (Tables 9.29 and 9.29). The potentialecological risks to avian herbivores and earthworm-eaters were assessed using the northernbobwhite (Tables 9.30 and 9.31) and the American woodcock (Tables 9.32 and 9.33). Threepiscivores (fish-eaters) were selected as indicator species: the mink (Tables 9.34 and 9.35), thebald eagle (Tables 9.36 and 9.37), and the kingfisher (Tables 9.38 and 9.39). Finally, potentialrisks to carnivores were assessed using the red fox (Tables 9.40 and 9.41) and the red-tailedhawk (Tables 9.42 and 9.43) as indicator species. It is assumed that as long as these indicatorspecies do not face a significant ecological risk from the LSI/Greencastle facility, all otherherbivores, piscivores, and carnivores are also protected. This assumption is discussed inSection 9.8.

The tables listed above contain weight and dietary data (food and water ingestion rate, % fish indiet, etc.) for each of the selected indicator species, as obtained from studies listed in theWildlife Exposure Factors Handbook (U.S. EPA, 1993). These data were used along with theexposure point concentrations given in Section 9.4 to derive estimates of the average daily doses(ADDs) of COECs ingested by each indicator species. ADDs were calculated using theequation:

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ADD estimated average daily dose (mg/kg-d),F food ingestion rate (kg food/kg-d),fdiet,i fraction of food type i the diet (unitless),ECi exposure point concentration of COEC in food type i (mg/kg food),W water ingestion rate (L/kg-d), ECwater exposure point concentration in surface water (:g/L), andC3 conversion factor (1 mg/1000 :g).

Calculated average daily doses are given in the second table for each species, as listed above. The maximum soil, water, and fish concentrations (Given in Tables 9.10, 9.11, and 9.13,respectively) were used as the exposure point concentrations in these foods. Plant foodconcentrations were obtained from Table 9.14, and earthworm and insect exposure pointconcentrations were obtained from Table 9.16.

Equation 9.16 was used, along with the calculated average daily doses of the deer mouse,meadow vole, northern bobwhite and American woodcock, to estimate the tissue concentrationsof COECs in small mammals and birds, as listed in Table 9.16. The maximum mammal and birdtissue concentration from Table 9.16 was then used as the exposure point concentration formammals and birds, respectively, ingested by carnivores.

Once ADDs were calculated for each indicator species, species-specific ingestion EBVs werecalculated for each indicator species using Equation 9.14. Then hazard quotients were calculatedfor each indicator species by dividing the ADD by the species-specific ingestion EBV. Theresultant hazard quotients are listed in the tables referenced above.

All hazard quotients for the northern bobwhite, mink, red fox, and red-tailed hawk were below 1,indicating that there is no significant ecological risk to these or similar receptors due to ingestionof COECs that may be emitted from the LSI/Greencastle facility. For the remaining fiveindicator species, only lead hazard quotients for the deer mouse (3.9), meadow vole (3.4) andAmerican woodcock (4.0), and only mercury hazard quotients for the bald eagle (1.5) and thekingfisher (3.9) were above a hazard index of one. These estimated hazard quotients, and theconservative assumptions used to calculate them, are discussed below.

9.7.5.1 Lead

Table 9.23 lists the measured background concentration of lead in soil in nearby Monroe County,Indiana (15 mg/kg, as reported in Boerngen and Shacklette, 1981). This value is similar to nineother values (ranging from 15-30 mg/kg) measured in Indiana soils. Thus, the estimatedmaximum impact of the LSI/Greencastle facility on soil lead concentration (0.3 mg/kg) isapproximately 2 % of the current, background lead value. Therefore, the possible ecological

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risks posed by the addition of lead to soil, plants, and earthworms from estimated maximumemissions from the LSI/Greencastle facility are very small when compared with the possiblerisks posed by the background concentrations of lead.

In addition, the estimated lead ADD for the deer mouse, meadow vole, and the Americanbobwhite assume that these species are ingesting only the most highly impacted plants,earthworms, soil, insects, and surface water. Only species living directly at the area of maximumimpact would face these living conditions. Furthermore, the estimated lead ADD varies greatlywith the assumed diet of the species: if the meadow vole eats mainly above ground produce, thehazard index is above one. If it instead eats more seeds or roots, its lead ADD would be muchlower than estimated above.

It should also be noted that a large part of the assumed lead dose for the deer mouse andAmerican woodcock comes from insect ingestion. The exposure point concentrations of COECsin insect tissue were conservatively modeled as the maximum of the concentrations in soils,worms, and above ground plants. Thus, the assumed lead concentration in insect tissue is 0.33mg/kg, equal to the concentration in soil but nearly a factor of 30 higher than the concentrationof lead in earthworms. This may be a significant overprediction of the true concentrations of leadin insect tissue, leading to erroneously elevated lead hazard indices for the deer mouse andAmerican woodcock.

Finally, the above estimates of the hazard index of lead are based on the assumption that theLSI/Greencastle facility is emitting lead at the MACT limit for lead for approximately 100 years. Based on stack testing data (Gossman, 2001a), the amount of lead measured leaving theLSI/Greencastle facility is only 1.3 % of the MACT limit emission rate. Using this emission ratein the above screening risk characterization would reduce the lead ingestion hazard indices forboth the meadow vole and the American woodcock by over a factor of 50, to well below thethreshold hazard quotient value of 1. In addition, the reported emission rate is based on a worst-case measurement of lead emitted from fuel containing high lead levels, and so is a conservativeestimate of the amount of lead emitted by the LSI/Greencastle facility. Thus, we can conclude,with a reasonable degree of confidence, that the current emissions of lead from theLSI/Greencastle facility do not pose a significant ecological risk.

9.7.5.2 Mercury

The measured background concentration of mercury in soil in Monroe County is 0.04 mg/kg,over ten times the 0.0037 mg/kg of mercury in soil estimated as the maximum impact of theLSI/Greencastle facility. Thus, as was the case for lead, the possible ecological risks posed bythe addition of mercury to soil, and thus to fish, from estimated maximum emissions from theLSI/Greencastle facility are very small when compared with the possible risks posed by thebackground concentrations of mercury.

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In addition, the fish concentrations used to calculated the ADD for the bald eagle and kingfisherwere based on the estimated concentrations of methylmercury in trophic level 4 fish, such astrout, pike, and bass. These large fish (a lake trout can be about 60 cm (23 in.) long) may bereasonable estimates of the type of fish a human fisher might eat, but bald eagles (which weigh 3kg) and kingfishers (which weigh 0.15 kg) are likely to have a significant level of lower trophiclevel fish in their diet. According to the Mercury Report to Congress, mercury levels in trophiclevel 3 fish may have only a fifth as much methylmercury in their tissues as trophic level fourfish (U.S. EPA, 1997, Appendix D-13). As the bald eagle and kingfisher are more likely to eatthese trophic level 3 fish than the trophic level 4 fish, their estimated hazard quotients could bereduced by almost a factor of 5 by this consideration alone.

Finally, as for lead, the above estimates of hazard quotients were based on the assumption thatthe LSI/Greencastle facility would be emitting mercury at the MACT limit for at least 100 years. However, based on stack testing, the measured emission rate of mercury compounds is only4.2 % of the MACT emission rate. This lower emission rate would lead to an approximate 20-fold decrease in the estimated mercury hazard quotients for bald eagles and kingfishers, bringingboth values well below the threshold value of one. Thus we can conclude, with a reasonabledegree of confidence, that the current mercury emissions from the LSI/Greencastle facility poseno significant ecological risk.

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9.8 Uncertainties

Many uncertainties are inherent in the type of risk calculations presented here. Most of theseuncertainties have been resolved in a conservative manner to ensure that the risk estimatesoverestimate actual risks to ecological receptors. Several sources of uncertainty in the ecologicalrisk characterization are discussed below.

• Toxicological data and use of uncertainty factors

The lowest available NOAELs, LOAELs, and other toxicological data, derived from availableanimal and ecosystem studies, were used in the risk characterization as described in Section 8.5. As these data are the lowest, and therefore most conservative, of the available values, they areexpected to be overprotective for most compounds and most species.

For a few compounds, the required terrestrial toxicological data was unavailable. Wherepossible, data for surrogate compounds were used to estimate the toxicological values for thesecompounds. While the compound may be more potent than the selected surrogate, there is anequal — and perhaps greater — likelihood that the compound is less toxic than the surrogatecompound. Random chance would suggest an equal likelihood of underestimation oroverestimation, but since toxicologic data are developed selectively for compounds that areknown to exhibit toxic effects, it can be argued (on an overall basis) that the body of availabletoxicologic data likely reflects compounds of greater toxicity than those for which data have notbeen developed. Thus, it seems more likely that the use of surrogate toxicity data is on average aconservative measure.

It is also possible that certain species or ecosystems may be hypersensitive to certaincompounds. The ecological risk assessment work plan (Horizon Environmental, 1998)recommended using an uncertainty factor of 100 to account for interspecies and intraspeciesvariations of sensitivity to COECs. Application of this factor would result in higher hazardquotients that are judged to be unrealistically overpredictive of potential risks. As implemented,the ecological risk algorithms in several cases predicted hazard quotients greater than one eventhough exposure point concentrations were smaller than natural background levels. Moreover,the use of the lowest NOAEL or LOAEL values among all species and studies lessens the needto consider an additional factor to account for interspecies and intraspecies extrapolation. Also,the conservative assumptions used to calculate estimates of exposure (such as the use of themaximum calculated exposure point concentrations, the use of indicator species with large foodintake rates, etc.) add an additional degree of conservatism. Thus, the use of an additionaluncertainty factor to account for interspecies and intraspecies extrapolation was judged bothunnecessary and inappropriate.

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No uncertainty factors were applied to the toxicological values used in the scoring algorithmsused to select COECs, following the recommendations of the ecological risk assessment workplan (Horizon Environmental, 1998). However, uncertainty factors were used to extrapolatefrom acute to chronic values (UF=1000), subchronic to chronic values (UF=10), and LOAEL toNOAEL values (UF=10) in the calculation of EBVs. These uncertainty factors are expected toresult in conservative estimates of chronic NOAEL values. While these uncertainty factorscould lead to an estimated chronic NOAEL value that is larger than the true value in rare cases, itis presumed that the conservative estimates of exposure compensate for the possibility of lessthan conservative chronic NOAEL estimates.

• Estimated body weights of tested species

In order to estimate species-specific ingestion EBVs using Equation 9.14, it is necessary to havean estimate of the weight of the tested species. However, weight data for some mice, rats, andrabbits used to determine the lowest available toxicological value were not given. In these cases,the body weight of the tested species was estimated. Body weights for rats were estimated usingthe average body weight of rats from the studies for which weight data were available. Bodyweights for mice and rabbits were estimated by comparison to a similar or representative speciesfor which data were available, in this case the deer mouse and eastern cottontail, respectively. However, it is possible that the actual body weight of the tested species might be larger orsmaller than these estimated values. In this case, a high estimate of the body weight for thetested species would result in a slightly high (less conservative) estimate of the ingestion EBV. However, as the variations in body weight for rats, mice, and rabbits are expected to be small,and the ingestion EBV varies as the one-quarter power of these values, this slight uncertainty inthe weights of the tested species is expected to result in only a very small uncertainty in theingestion EBV values. It is also equally possible that errors associated with this uncertaintycould follow the opposite sense (i.e., fall on the side of estimating higher potential risks). Giventhe conservative toxicological data and the conservative exposure estimates, this uncertainty isexpected to have a negligible effect on the ecological risk characterization.

• Exclusion of TICs (other than benzaldehyde and benzonitrile) from COEC screening

All tentatively identified compounds (TICs), except for benzaldehyde and benzonitrile, wereexcluded from the selection algorithms for organic COECs. This decision was made in light ofthe lack of adequate toxicological data for nearly all of these TICs, making scoring andassessment impossible. However, the impact of the possible emission of these TICs on theecological risk assessment can be estimated by looking at the results for the organic COECsevaluated in the risk assessment. The largest estimated hazard quotient for an organic COEC is0.2 for dioxin congeners (total) in soil. Thus, as the TICs are expected to be far less toxic thandioxin, and as the emission rates of the TICs are comparable to that of other organic compoundsfrom the stack, it is unlikely that any TICs, even if included in the ecological risk assessment,would have hazard quotients that would affect overall risk values. Many of the TICs weresimple alkane compounds (e.g., methane, propane, etc.) that are of inconsequential toxicity to

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humans (and therefore lack the development of toxicologic data). Hence, potential risks fromTICs are not anticipated to be significant.

• Lack of surrogate data for some compounds in scoring algorithms

In the scoring algorithms used to select COECs, scoring data for a few compounds (e.g., 2-propanol, benzonitrile, butyl acetate, diacetone alcohol, dibenzofuran, ethanol, isobutyl acetate,methyl isoamyl ketone, n-octane, n-propanol, propyl acetate, and tetrahydrofuran) wereunavailable. Thus, inhalation and ingestion scores were not calculated for these compounds, andthey were not selected as COECs. However, the potential impact of these compounds on theecological risk assessment can be estimated from the results for the organic COECs. Again, asthese compounds are expected to be far less toxic than dioxin, and their emission rates areexpected to be comparable to that of other organic emissions from the stack, it is unlikely thatany of these compounds, even if included in the ecological risk assessment, would have acalculated hazard quotient above 1.

• Estimation of inhalation EBVs from oral toxicity data

For COECs where inhalation toxicity data are unavailable, inhalation EBVs were estimatedusing Equation 9.10. This equation converts oral toxicity data (expressed in mg/kg-d) toinhalation toxicity values (in :g/m3) using the body weight and inhalation rate of a meadow voleas conversion factors. The meadow vole was used in this calculation because the low bodyweight to inhalation rate ratio of the meadow vole results in low (and therefore conservative)estimates of inhalation EBVs for most species. In addition, Equation 9.10 assumes that, in theabsence of inhalation data, the potency of a compound via inhalation is equivalent to its potencythrough ingestion. This method will on average tend to overestimate risk values if toxicity issimilar among exposure routes. However, it is possible that a COEC for which inhalationtoxicity data are unavailable is more potent through inhalation through ingestion. However,given the conservative estimates of long-term air concentration, and that the highest estimatedinhalation hazard quotient for a COEC for which inhalation toxicity data is unavailable is 9 ×10!5 (for lead), it is likely that further inhalation toxicity data would still lead to a conclusion thatCOECs in air do not pose a significant ecological risk to terrestrial mammals and birds.

• Risks to plants and reptiles from COECs in air

The inhalation hazard quotients for terrestrial animals exposed to COECs in air are calculated inSection 8.7.1. The inhalation EBVs used in calculating these hazard quotients are based on themost conservative toxicity data available for birds and mammals. It is assumed that if mammalsand birds face no significant ecological risk from COECs in air, that reptiles and plants presentnear the LSI/Greencastle facility are also protected. However, it is possible that plants, reptiles,or even mammals or birds other than those tested may be more sensitive to COECs in air thanthe species used to derive the inhalation EBVs. The results of the inhalation hazard quotient

9–37

calculation can be used to determine how much more sensitive another species would have to beto receive an estimated hazard quotient of 1. The highest estimated inhalation hazard quotient is 1.3 × 10!2 for zinc (based on acute exposure in humans), followed by 2.1 × 10!4 for carbondisulfide. Thus, unless a species near the LSI/Greencastle facility is about 76 times moresensitive to zinc, or about 4,700 times more sensitive to other COECs in air than the testedspecies, COECs in air from the LSI/Greencastle facility will pose no significant ecological risk.

• Lack of soil and sediment toxicological data for some COECs

For some COECs, soil and sediment EBVs could not be calculated, due to the lack of soil andsediment toxicological data for these compounds. It is possible that one of the COECs for whichsoil and /or sediment data were unavailable could present a significant ecological risk to plants,soil community organisms, or the aquatic ecosystem. However, given that none of the assessedCOECs potentially in soil or sediment pose significant ecological risks, it is unlikely that theother COECs would indicate the possibility of significant ecological risks. However, ifadditional soil or sediment toxicological data became available, it would be advisable tocalculate the hazard quotients in soil and/or sediment for the additional COECs.

• Differences between exposure equations in HHRAP and in the approved work plan(Horizon Environmental, 1998).

A few differences exist between Equation 9.8, used to calculate earthworm BAFs, and theformula given on page 22 of the ecological risk assessment work plan (Horizon Environmental,1998). The equation given in the work plan is not used because it does not match the originalequation given by Connell and Markwell (1990), does not give a dimensionless value for theBAF, and uses an incorrect estimate of earthworm lipid content (84%, instead of the moreaccurate 0.84%; Connell and Markwell, 1990). Thus, it appears that the equation as given in theecological risk assessment workplan is incorrect, and that Equation 9.8, from Connell andMarkwell (1990) (the apparent primary reference) is a more accurate estimate of the BAF fororganic compounds in earthworms.

In addition, the equations for plant tissue concentration due to direct deposition, vapor phaseuptake, and root uptake given in the HHRAP differ somewhat from those given in the ecologicalrisk assessment workplan. Generally, the differences have little or no impact on the estimatedplant tissue concentration. However, in a few cases the impact may be significant. For example,in estimating plant tissue concentration due to vapor phase uptake, the HHRAP uses the equationgiven in Chapter 5, where VGag = 0.01 if log (Kow) > 4. This is equivalent to the equation givenin the ecological risk assessment workplan (Horizon Environmental, 1998). However, forcompounds where log Kow < 4, like acetone and acetonitrile, the HHRAP states that VGag = 1,while the protocol from Horizon Environmental (1998) would continue to use a value of 0.01,resulting in an underestimate of the vapor phase uptake of these contaminants. Thus, where theHHRAP and the ecological risk assessment work plan equations for estimating exposure

9–38

concentrations disagree, the HHRAP equations were used as the more reliable (since based onlater guidance) and/or conservative of the two.

• Weight and dietary data for indicator species

Indicator species were selected to estimate the high-end ingestion dose and risk to herbivores,earthworm eaters, piscivores and carnivores. The selected indicator species were those whichare known to inhabit the types of habitats near the LSI/Greencastle facility, for which dietary andweight data were available, and which have high food and water ingestion rates, relative to theirbody weights. Thus, it is presumed that these species represent the upper end of the doses towhich an herbivore, earthworm eater, piscivore, or carnivore may be exposed.

Weight and dietary data for indicator species were taken from the Wildlife Exposure FactorsHandbook (U.S. EPA, 1993). Where a range of food and water ingestion rates were given, thehigh-end estimate was used to arrive at conservative dose estimates. Dietary composition datawere taken from studies performed as close to the site as possible — either in Indiana or nearbystates. It is possible that dietary compositions may differ for species near the LSI/Greencastlefacility, and that differences could result in higher doses than the assumed diet. The oppositecase, however, is equally possible, and no information exists to indicate a likely bias in eitherdirection. Also, it is likely that the conservative estimates of oral dose (using the maximumestimated food, soil, and water concentrations) compensate for any uncertainties in dietarycomposition.

Concentrations of COECs in insects were estimated in the ecological risk assessment as beingequal to the maximum concentration in above ground produce, forage grasses, grains, soil orearthworms. For species with large percentages of insects in their diet, such as the deer mouse(44%), northern bobwhite (13%) and American woodcock (20%), this assumption givessignificant uncertainty in the calculated hazard quotients. However, given the highlyconservative estimates of COEC concentrations in insect tissue, the calculated hazard quotientsare more likely to overpredict risks than to underpredict them. For example, the concentration oflead in insects is calculated as 0.33 mg/kg, equal to the maximum concentration estimated forsoil, but about 30 times less that the concentration estimated in earthworms.

Ingestion EBVs were scaled by Equation 9.14, using average body weight estimates. It ispossible that some individual animals or species may weigh more than the average weight of theindicator species, giving them a lower ingestion EBV value. However, larger species are alsoexpected to eat a lower percentage of their body weight per day than the indicator species, and sothe doses of COECs are expected to decrease along with ingestion EBVs for larger animals.

9–39

• Bioaccumulation estimates

The ecological risk assessment uses the bioaccumulation factors for beef and pork from theHHRAP for all mammals, the bioaccumulation factors for chicken from the HHRAP for allbirds, and uses an equation from Connell and Markwell (1990) to estimate earthworm BAFs fororganic compounds for which data are unavailable. While these BAFs are designed to beconservative, upper-end estimates of the bioaccumulation of COECs in animals, it is possiblethat they may underestimate the BAFs of some terrestrial species. However, it is unlikely thatthe estimates of COEC concentrations in mammal and bird flesh are underestimates, given thattheir high ingestion rates lead to conservative estimates of oral doses of COECs relative to thegeneral population of species, leading to conservative estimates of tissue concentration. Similarly, as all earthworms are assumed to be in equilibrium with the most highly impacted soil,the estimated earthworm BAFs would lead to conservative estimated of concentration of COECsin earthworm tissue, even if the BAFs themselves were slightly underestimated.

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9.9 Conclusions

Potential risks to ecological receptors from the operation of the LSI/Greencastle facility havebeen evaluated following the ecological risk assessment work plan (Horizon Environmental,1998). Exposure of ecological receptors to compounds of ecological concern (COECs) in air,soil, surface water, sediment, and food have been evaluated using conservative fate-and-transportmodeling and the most appropriate available ecotoxicological data.

Conclusions of the ecological risk assessment are:

• The potential presence of COECs from the LSI/Greencastle facility in air does not pose asignificant ecological risk to terrestrial receptors, as determined using available chronicinhalation toxicity data for mammals and birds.

• There is no significant ecological risk to plants or soil community organisms (e.g.,earthworms) from the potential presence of COECs from the LSI/Greencastle facility insoils, based on available soil ecotoxicological criteria.

• Surface water potentially contaminated with COECs from the LSI./Greencastle facilitydoes not pose a significant ecological risk to the aquatic ecosystem, as determined usingavailable federal and state ambient water quality criteria.

• The potential presence of COECs from the LSI/Greencastle facility in sediments does notpose a significant ecological risk to the aquatic ecosystem, based on available sedimentquality criteria.

• Based on MACT emission limits, all COECs other than mercury and lead do not presenta significant ecological risk to receptors that encounter these contaminants through theirdiet.

• Measured emissions of mercury and lead from the LSI/Greencastle facility are only4.3 % and 1.3 %, respectively, of the MACT emission limit for these compounds, and theMACT emission limits of these compounds result in estimated maximum soil impactsthat are only 10 % and 2 %, respectively, of background soil concentrations. Thus, webelieve, with a fair degree of confidence, that emissions of mercury and lead from theLSI/Greencastle facility do not pose a significant ecological risk.

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Table 9.1 Possible organic compound emissions from the LSI/Greencastle facilityA

Compound StackEmission

RateB

(g/s)

TankFugitiveEmission

RateB

(g/s)

SamplingPlatformFugitiveEmission

RateB

(g/s)

CombinedEmission

RateB

(g/s)

KowC SolubilityD

(mg/L)

acenaphthene 1.19e-04 NF NF 1.19e-04 9.22e+03 4.13e+00acenaphthalene 4.10e-04 NF NF 4.10e-04 8.71e+03 3.93e+00acetone 3.74e-02 2.29e-03 1.16e-03 4.09e-02 6.00e-01 6.04e+05acetonitrile 1.27e-02 1.71e-04 4.91e-05 1.29e-02 4.57e-01 7.50e+04acetophenone 2.98e-03 NF NF 2.98e-03 4.37e+01 6.10e+03acrylonitrile 5.57e-03 NF NF 5.57e-03 1.78e+00 7.50e+04anthracene 1.71e-04 NF NF 1.71e-04 2.95e+04 5.37e-02benzaldehyde 4.19e-03 NF NF 4.19e-03 3.00e+01 3.30e+03benzene 2.25e-02 2.64e-04 4.09e-05 2.29e-02 1.37e+02 1.80e-03benzo(a)anthracene 4.08e-06 NF NF 4.08e-06 4.77e+05 1.28e-02benzo(ghi)perylene 1.14e-06 NF NF 1.14e-06 1.70e+07 3.00e-04benzo(a)pyrene 5.06e-07 NF NF 5.06e-07 1.35e+06 1.94e-03benzo(e)pyrene 1.39e-06 NF NF 1.39e-06 2.75e+06 6.30e-03benzo(b)fluoranthene 2.11e-06 NF NF 2.11e-06 1.59e+06 4.33e-03benzo(k)fluoranthene 1.61e-06 NF NF 1.61e-06 1.56e+06 8.00e-04benzonitrile 1.92e-03 NF NF 1.92e-03 3.63e+01 2.00e+03benzyl alcohol 1.29e-04 NF NF 1.29e-04 1.26e+01 4.00e+04bis(2-ethylhexyl)phthalate 1.53e-03 NF NF 1.53e-03 2.00e+05 4.00e-01bromomethane 1.60e-03 NF NF 1.60e-03 1.26e+01 9.00e+02butanol, n- 5.06e-03 1.23e-03 1.04e-05 6.30e-03 6.76e+00 7.70e+04butyl acetate 6.32e-03 1.54e-03 2.91e-05 7.89e-03 6.61e+01 1.40e+04carbon disulfide 1.02e-02 NF NF 1.02e-02 1.00e+02 2.67e-03carbon tetrachloride 3.59e-05 NF NF 3.59e-05 5.21e+02 7.92e+02chlorobenzene 8.89e-04 NF NF 8.89e-04 6.16e+02 4.09e+02chloroform 1.62e-04 NF NF 1.62e-04 8.90e+01 7.98e+03chrysene 6.35e-06 NF NF 6.35e-06 5.48e+05 1.94e-03cresol, m- (methylphenol,3-)

1.08e-03 1.99e-04 3.30e-08 1.28e-03 9.10e+01 2.30e+04

cresol, o- (methylphenol,2-)

5.53e-04 1.99e-04 7.20e-08 7.52e-04 1.05e+02 2.77e+04

cresol, p- (methylphenol,4-)

1.08e-03 1.99e-04 2.96e-08 1.28e-03 8.70e+01 2.30e+04



RateB

(g/s)


RateB

(g/s)


RateB

(g/s)

CombinedEmission

RateB

(g/s)

KowC SolubilityD

(mg/L)

9–42

cumene (isopropylbenzene) 1.28e-04 1.38e-02 6.94e-05 1.40e-02 4.10e+03 5.60e+01cyclohexanone 3.23e-04 7.87e-05 4.70e-07 4.02e-04 6.46e+00 2.30e+04diacetone alcohol 2.26e-04 5.51e-05 6.77e-08 2.81e-04 1.25e+00 1.00e+06dibenz(ah)anthracene 1.86e-06 NF NF 1.86e-06 3.53e+06 6.70e-04dibenzofuran 7.27e-04 NF NF 7.27e-04 1.32e+04 3.70e+00dichloroethane, 1,2- 4.99e-05 2.25e-05 2.15e-06 7.46e-05 2.90e+01 8.31e+02dichloroethylene, 1,1- 1.54e-04 NF NF 1.54e-04 1.32e+02 3.00e+03dimethylphenol, 2,4- 2.16e-04 NF NF 2.16e-04 2.29e+02 6.25e+03di-n-butylphthalate 6.67e-05 NF NF 6.67e-05 5.25e+04 1.08e+01ethanol 5.74e-03 1.40e-03 1.39e-04 7.28e-03 4.79e-01 1.00e+05ethyl acetate 3.87e-03 9.44e-04 1.13e-04 4.93e-03 5.37e+00 6.40e+04ethylbenzene 1.08e-03 2.44e-03 2.87e-05 3.55e-03 1.33e+03 1.73e+02ethyl ether 4.20e-04 1.02e-04 6.86e-05 5.91e-04 7.76e+00 6.99e+04fluoranthene 1.02e-04 NF NF 1.02e-04 1.21e+05 2.32e-01fluorene 1.15e-04 NF NF 1.15e-04 1.47e+04 1.86e+00glycol ethers (diethyleneglycol)

4.24e-03 1.03e-03 7.76e-06 5.28e-03 7.94e-01 1.22e+01

hexane (for aliphatics) 6.00e-02 1.46e-02 5.11e-03 7.97e-02 5.00e+03 2.22e+01hexanone, 2- 1.62e-03 NF NF 1.62e-03 2.40e+01 1.40e+04indeno(1,2,3-cd)pyrene 3.17e-07 NF NF 3.17e-07 8.22e+06 1.07e-02iodomethane 4.40e-02 NF NF 4.40e-02 4.90e+01 1.40e+04isobutyl acetate 2.03e-04 4.95e-05 1.12e-06 2.54e-04 3.98e+01 6.70e+03methanol 6.35e-03 1.55e-03 6.19e-04 8.52e-03 1.95e-01 2.90e+04methyl tert-butyl ether 3.23e-04 7.87e-05 2.19e-05 4.24e-04 7.94e+01 3.66e+04methyl ethyl ketone 5.98e-03 3.73e-03 6.19e-04 1.03e-02 1.91e+00 2.40e-05methyl isoamyl ketone 9.24e-05 2.25e-05 6.09e-04 7.24e-04 7.59e+01 5.40e+03methyl isobutyl ketone 1.41e-04 2.15e-03 1.30e-07 2.29e-03 1.55e+01 2.00e+04methylene chloride 1.80e-03 4.25e-04 5.42e-05 2.28e-03 1.80e+01 1.74e+04methylnaphthalene, 2- 2.02e-03 NF NF 2.02e-03 7.24e+03 2.46e+01naphthalene 2.43e-03 1.12e-06 2.10e-04 2.64e-03 2.36e+03 3.11e+01octane, n- 2.17e-03 NF NF 2.17e-03 3.98e-03 6.60e-01perylene 1.07e-07 NF NF 1.07e-07 6.61e+05 4.00e-04



RateB

(g/s)


RateB

(g/s)


RateB

(g/s)

CombinedEmission

RateB

(g/s)

KowC SolubilityD

(mg/L)

9–43

phenanthrene 1.55e-03 NF NF 1.55e-03 3.55e+04 1.28e+00phenol 2.41e-03 6.45e-04 9.56e-11 3.06e-03 3.00e+01 9.08e+04propanol, 2- (isopropylalcohol)

1.25e-02 3.04e-03 3.63e-07 1.55e-02 6.92e-01 1.00e+05

propanol, n- 1.80e-03 4.39e-04 1.88e-04 2.43e-03 1.78e+00 1.00e+06propyl acetate 7.80e-04 1.90e-04 1.56e-05 9.86e-04 1.70e+01 1.60e+04pyrene 1.03e-04 NF NF 1.03e-04 1.00e+05 1.37e-01pyridine 3.82e-04 1.12e-05 8.90e-07 3.94e-04 4.68e+00 3.00e+02styrene 4.39e-03 1.48e-03 3.48e-07 5.87e-03 8.49e+02 2.57e+02tetrachloroethylene 3.38e-04 1.60e-04 1.14e-05 5.09e-04 3.51e+02 2.32e+02tetrahydrofuran 3.34e-03 8.13e-04 3.46e-06 4.16e-03 2.80e+00 1.00e+06toluene 9.13e-03 1.16e-02 2.32e-04 2.09e-02 4.65e+02 5.58e+02trichloroethane, 1,1,1- 3.69e-05 3.46e-04 4.70e-04 8.53e-04 2.64e+02 1.17e+03trichloroethylene 7.80e-05 2.26e-04 3.79e-05 3.42e-04 2.71e+02 1.18e+03trimethylbenzene, 1,2,4- 5.62e-04 NF NF 5.62e-04 4.27e+03 5.70e+01trimethylbenzene, 1,3,5- 2.69e-04 NF NF 2.69e-04 2.63e+03 2.00e+01xylene, m- 3.76e-03 3.73e-03 1.43e-05 7.51e-03 1.59e+03 1.86e+02xylene, o- 1.10e-03 3.73e-03 3.70e-05 4.87e-03 1.35e+03 1.86e+02xylene, p- 3.76e-03 3.73e-03 3.70e-05 7.53e-03 1.48e+03 1.86e+022,3,7,8-TCDD 1.12e-08 NF NF 1.12e-08 4.37e+06 1.93e-051,2,3,7,8-PCDD 8.04e-09 NF NF 8.04e-09 4.37e+06 1.20e-041,2,3,4,7,8-HxCDD 1.75e-08 NF NF 1.75e-08 6.17e+07 4.40e-061,2,3,6,7,8-HxCDD 3.02e-08 NF NF 3.02e-08 1.78e+07 4.40e-061,2,3,7,8,9-HxCDD 2.83e-08 NF NF 2.83e-08 1.78e+07 4.40e-061,2,3,4,6,7,8-HpCDD 2.35e-07 NF NF 2.35e-07 1.58e+08 2.40e-06OCDD 6.24e-08 NF NF 6.24e-08 3.89e+07 7.40e-082,3,7,8-TCDF 3.34e-08 NF NF 3.34e-08 3.39e+06 4.19e-041,2,3,7,8-PCDF 1.62e-08 NF NF 1.62e-08 6.17e+06 2.40e-042,3,4,7,8-PCDF 2.80e-08 NF NF 2.80e-08 8.32e+06 2.36e-041,2,3,4,7,8-HxCDF 2.05e-08 NF NF 2.05e-08 1.78e+07 8.25e-061,2,3,6,7,8-HxCDF 9.31e-09 NF NF 9.31e-09 1.78e+07 1.77e-052,3,4,6,7,8-HxCDF 1.63e-09 NF NF 1.63e-09 1.78e+07 1.30e-05



RateB

(g/s)


RateB

(g/s)


RateB

(g/s)

CombinedEmission

RateB

(g/s)

KowC SolubilityD

(mg/L)

9–44

1,2,3,7,8,9-HxCDF 2.10e-09 NF NF 2.10e-09 1.78e+07 1.30e-051,2,3,4,6,7,8-HpCDF 2.03e-08 NF NF 2.03e-08 8.32e+07 1.35e-061,2,3,4,7,8,9-HpCDF 1.63e-09 NF NF 1.63e-09 8.32e+07 1.40e-06OCDF 1.63e-09 NF NF 1.63e-09 6.03e+08 1.20e-06coplanar PCBs TEQ 7.21e-12 NF NF 7.21e-12 1.61e+06 5.15e-02Total PCB Cogener 5.91e-08 NF NF 5.91e-08 1.61e+06 5.15e-02NF - Fugitive emissions are not calculated for this compound. See Section 2.5.A In keeping with the human health risk assessment, only two tentatively identified compounds (benzaldehydeand benzonitrile) are included as possible organic emissions. See Section 2.3.B Emission rates were calculated according to the methodology outlined in Section 2.5.C Octanol-water partition coefficient. See Appendix III for sources.D Solubility in water. See Appendix III for sources.

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Table 9.2 Terrestrial chronic toxicity data

Compound NOAELA

(mg/kg-d)LOAELB

(mg/kg-d) Species Source

acenaphthene 1.75e+02 NR mice IRIS, 2001acenaphthalene 7.10e+01 NR naphthalene Surrogateacetone 1.00e+02 NR rats IRIS, 2001acetonitrile 4.30e+01 NR mice HEAST, 1997acetophenone 4.23e+02 NR rats IRIS, 2001acrylonitrile 1.00e+00 NR mice HEAST, 1997anthracene 1.00e+03 NR mice IRIS, 2001benzaldehyde 1.43e+02 NR rats IRIS, 2001benzene NA 1.79e-01 mice ATSDR, 1997benzo(a)anthracene 7.10e+01 NR naphthalene Surrogatebenzo(ghi)perylene 7.10e+01 NR naphthalene Surrogatebenzo(a)pyrene 7.10e+01 NR naphthalene Surrogatebenzo(e)pyrene 7.10e+01 NR naphthalene Surrogatebenzo(b)fluoranthene 7.10e+01 NR naphthalene Surrogatebenzo(k)fluoranthene 7.10e+01 NR naphthalene Surrogatebenzonitrile NA NA - -benzyl alcohol NA 2.86e+02 rats HEAST,1997bis(2-ethylhexyl)phthalate NA 1.90e+01 guinea pigs IRIS, 2001bromomethane 1.40e+00 NR rats IRIS, 2001butanol, n- 1.25e+02 NR rats IRIS, 2001butyl acetate NA NA - -carbon disulfide 1.10e+01 NR rabbits IRIS, 2001carbon tetrachloride 7.10e-01 NR rats IRIS, 2001chlorobenzene 1.90e+01 NR beagle dogs IRIS, 2001chloroform NA 1.29e+01 dogs IRIS, 2001chrysene 7.10e+01 NR naphthalene Surrogatecresol, m- (methylphenol, 3-) 5.00e+01 NR rats HEAST, 1997cresol, o- (methylphenol, 2-) 5.00e+01 NR rats HEAST, 1997cresol, p- (methylphenol, 4-) 5.00e+00 NR rabbits HEAST, 1997cumene (isopropylbenzene) 1.10e+02 NR rats IRIS, 2001cyclohexanone 4.62e+02 NR rats IRIS, 2001diacetone alcohol NA NA - -dibenz(ah)anthracene 7.10e+01 NR naphthalene Surrogatedibenzofuran NA NA - -


Compound NOAELA

(mg/kg-d)LOAELB


9–46

dichloroethane, 1,2- NA 5.80e+01 female rats ATSDR, 1999dichloroethylene, 1,1- NA 9.00e+00 rats IRIS, 2001dimethylphenol, 2,4- 5.00e+01 NR albino mice IRIS, 2001di-n-butylphthalate 1.25e+02 NR rats IRIS, 2001ethanol NA NA - -ethyl acetate 9.00e+02 NR rats IRIS, 2001ethylbenzene 9.71e+01 NR rats IRIS, 2001ethyl ether 5.00e+02 NR rats IRIS, 2001fluoranthene 1.25e+02 NR mice IRIS, 2001fluorene 1.25e+02 NR mice IRIS, 2001glycol ethers (diethylene glycol) NA 3.57e+02 rat HEAST,1997hexane (for aliphatics) 5.70e+02 NR rats HEAST, 1997hexanone, 2- NA 1.00e+02 hen ATSDR, 1992indeno(1,2,3-cd)pyrene 7.10e+01 NR naphthalene surrogateiodomethane 1.40e+00 NR bromomethane surrogateisobutyl acetate NA NA - -methanol 5.00e+02 NR rats IRIS, 2001methyl tert-butyl ether NA 1.00e+02 rats ATSDR, 1996methyl ethyl ketone 1.77e+03 NR rats IRIS, 2001methyl isoamyl ketone NA NA - -methyl isobutyl ketone 2.50e+02 NR rats HEAST, 1997methylene chloride 5.85e+00 NR male rats IRIS, 2001methylnaphthalene, 2- 7.10e+01 NR naphthalene surrogatenaphthalene 7.10e+01 NR rat IRIS, 2001octane, n- NA NA - -perylene 7.10e+01 NR naphthalene surrogatephenanthrene 7.10e+01 NR naphthalene surrogatephenol 6.00e+01 NR rats IRIS, 2001propanol, 2- (isopropyl alcohol) NA NA - -propanol, n- NA NA - -propyl acetate NA NA - -pyrene 7.50e+01 NR mice IRIS, 2001pyridine 1.00e+00 NR rats IRIS, 2001styrene 2.00e+02 NR dogs IRIS, 2001


Compound NOAELA

(mg/kg-d)LOAELB


9–47

tetrachloroethylene 1.40e+01 NR mice IRIS, 2001tetrahydrofuran NA NA - -toluene 2.23e+02 NR rats IRIS, 2001trichloroethane, 1,1,1- 9.00e+01 NR guinea pig HEAST, 1992trichloroethylene NA 1.26e+01 rats ATSDR, 1997trimethylbenzene, 1,2,4- 9.71e+01 NR ethylbenzene surrogatetrimethylbenzene, 1,3,5- 9.71e+01 NR ethylbenzene surrogatexylene, m- 1.79e+02 NR rats IRIS, 2001xylene, o- 1.79e+02 NR rats IRIS, 2001xylene, p- 1.79e+02 NR rats IRIS, 20012,3,7,8-TCDD 1.00e-06 NR rat RTI, 19991,2,3,7,8-PCDD 1.00e-06 NR mammals calculated1,2,3,4,7,8-HxCDD 1.00e-05 NR mammals calculated1,2,3,6,7,8-HxCDD 1.00e-05 NR mammals calculated1,2,3,7,8,9-HxCDD 1.00e-05 NR mammals calculated1,2,3,4,6,7,8-HpCDD 1.00e-04 NR mammals calculatedOCDD 1.00e-02 NR mammals calculated2,3,7,8-TCDF 1.00e-06 NR bird calculated1,2,3,7,8-PCDF 1.00e-05 NR bird calculated2,3,4,7,8-PCDF 1.00e-06 NR bird calculated1,2,3,4,7,8-HxCDF 1.00e-05 NR mammals calculated1,2,3,6,7,8-HxCDF 1.00e-05 NR mammals calculated2,3,4,6,7,8-HxCDF 1.00e-05 NR mammals calculated1,2,3,7,8,9-HxCDF 1.00e-05 NR mammals calculated1,2,3,4,6,7,8-HpCDF 1.00e-04 NR mammals calculated1,2,3,4,7,8,9-HpCDF 1.00e-04 NR mammals calculatedOCDF 1.00e-02 NR mammals calculatedcoplanar PCBs TEQ 1.00e-06 NR rat RTI, 1999Total PCB Cogener NA 7.00e-02 rat HEAST,1997NA - Not available. NR - LOAEL not required as NOAEL is available.Surrogate - As no NOAEL or LOAEL was available for this compound, a surrogate compound was used. Thesurrogate compound used is listed under the column “Species”.Calculated - These NOAELs were calculated using Equation 9.0 and the toxicity equivalency factors (TEFs)listed in Table 9.3.A NOAEL - No Observed Adverse Effects Level B LOAEL - Lowest Observed Adverse Effects Level

9–48

Table 9.3 Toxicity equivalency factors (TEFs) for dioxin congeners

Congener Mammals Birds

2,3,7,8-TCDD 1 1

1,2,3,7,8-PCDD 1 1

1,2,3,4,7,8-HxCDD 0.1 0.05

1,2,3,6,7,8-HxCDD 0.1 0.01

1,2,3,7,8,9-HxCDD 0.1 0.1

1,2,3,4,6,7,8-HpCDD 0.01 < 0.001

OCDD 0.0001 0.0001

2,3,7,8-TCDF 0.1 1

1,2,3,7,8-PCDF 0.05 0.1

2,3,4,7,8-PCDF 0.5 1

1,2,3,4,7,8-HxCDF 0.1 0.05

1,2,3,6,7,8-HxCDF 0.1 0.1

2,3,4,6,7,8-HxCDF 0.1 0.1

1,2,3,7,8,9-HxCDF 0.1 0.1

1,2,3,4,6,7,8-HpCDF 0.01 0.01

1,2,3,4,7,8,9-HpCDF 0.01 0.01

OCDF 0.0001 0.0001

Source: RTI, 1999

9–49

Table 9.4 Inhalation scores for organic compounds

Compound Stack Inhalation

Score(g-kg-

day/mg-s)

TankFarm

InhalationScore(g-kg-

day/mg-s)

SamplingPlatform


day/mg-s)

CombinedInhalation

Score(g-kg-

day/mg-s)

Percent ofTotal

InhalationScore

Rank

acenaphthene 6.81e-07 NF NF 6.81e-07 4.81e-07 72acenaphthalene 5.78e-06 NF NF 5.78e-06 4.08e-06 62acetone 3.74e-04 2.29e-05 1.16e-05 4.09e-04 2.89e-04 18acetonitrile 2.95e-04 3.98e-06 1.14e-06 3.00e-04 2.12e-04 21acetophenone 7.05e-06 NF NF 7.05e-06 4.98e-06 57acrylonitrile 5.57e-03 NF NF 5.57e-03 3.93e-03 7anthracene 1.71e-07 NF NF 1.71e-07 1.21e-07 74benzaldehyde 2.93e-05 NF NF 2.93e-05 2.07e-05 43benzene 1.26e+00 1.48e-02 2.29e-03 1.28e+00 9.02e-01 1benzo(a)anthracene 5.75e-08 NF NF 5.75e-08 4.06e-08 77benzo(ghi)perylene 1.61e-08 NF NF 1.61e-08 1.13e-08 82benzo(a)pyrene 7.13e-09 NF NF 7.13e-09 5.03e-09 83benzo(e)pyrene 1.96e-08 NF NF 1.96e-08 1.38e-08 81benzo(b)fluoranthene 2.97e-08 NF NF 2.97e-08 2.10e-08 78benzo(k)fluoranthene 2.27e-08 NF NF 2.27e-08 1.60e-08 80benzonitrile NA NA NA NA 0.00e+00 86benzyl alcohol 4.52e-06 NF NF 4.52e-06 3.19e-06 64bis(2-ethylhexyl)phthalate 8.03e-04 NF NF 8.03e-04 5.67e-04 17bromomethane 1.14e-03 NF NF 1.14e-03 8.05e-04 14butanol, n- 4.05e-05 9.87e-06 8.30e-08 5.04e-05 3.56e-05 36butyl acetate NA NA NA NA 0.00e+00 86carbon disulfide 9.28e-04 NF NF 9.28e-04 6.55e-04 16carbon tetrachloride 5.06e-05 NF NF 5.06e-05 3.57e-05 35chlorobenzene 4.68e-05 NF NF 4.68e-05 3.30e-05 37chloroform 1.25e-04 NF NF 1.25e-04 8.86e-05 32chrysene 8.95e-08 NF NF 8.95e-08 6.32e-08 76cresol, m- (methylphenol, 3-) 2.16e-05 3.98e-06 6.61e-10 2.56e-05 1.81e-05 45cresol, o- (methylphenol, 2-) 1.11e-05 3.98e-06 1.44e-09 1.50e-05 1.06e-05 51cresol, p- (methylphenol, 4-) 2.16e-04 3.98e-05 5.91e-09 2.56e-04 1.81e-04 23cumene (isopropylbenzene) 1.16e-06 1.26e-04 6.31e-07 1.27e-04 9.00e-05 31cyclohexanone 6.99e-07 1.70e-07 1.02e-09 8.71e-07 6.15e-07 70



Score(g-kg-

day/mg-s)

TankFarm


day/mg-s)

SamplingPlatform


day/mg-s)

CombinedInhalation

Score(g-kg-

day/mg-s)

Percent ofTotal

InhalationScore

Rank

9–50

diacetone alcohol NA NA NA NA 0.00e+00 86dibenz(ah)anthracene 2.61e-08 NF NF 2.61e-08 1.85e-08 79dibenzofuran NA NA NA NA 0.00e+00 86dichloroethane, 1,2- 8.61e-06 3.88e-06 3.71e-07 1.29e-05 9.08e-06 52dichloroethylene, 1,1- 1.71e-04 NF NF 1.71e-04 1.21e-04 26dimethylphenol, 2,4- 4.33e-06 NF NF 4.33e-06 3.06e-06 65di-n-butylphthalate 5.33e-07 NF NF 5.33e-07 3.77e-07 73ethanol NA NA NA NA 0.00e+00 86ethyl acetate 4.30e-06 1.05e-06 1.25e-07 5.47e-06 3.87e-06 63ethylbenzene 1.11e-05 2.51e-05 2.95e-07 3.66e-05 2.58e-05 40ethyl ether 8.40e-07 2.05e-07 1.37e-07 1.18e-06 8.35e-07 68fluoranthene 8.18e-07 NF NF 8.18e-07 5.77e-07 71fluorene 9.17e-07 NF NF 9.17e-07 6.48e-07 69glycol ethers (diethylene glycol)

1.19e-04 2.89e-05 2.17e-07 1.48e-04 1.04e-04 29

hexane (for aliphatics) 1.05e-04 2.57e-05 8.97e-06 1.40e-04 9.88e-05 30hexanone, 2- 1.62e-04 NF NF 1.62e-04 1.14e-04 28indeno(1,2,3-cd)pyrene 4.47e-09 NF NF 4.47e-09 3.15e-09 84iodomethane 3.14e-02 NF NF 3.14e-02 2.22e-02 3isobutyl acetate NA NA NA NA 0.00e+00 86methanol 1.27e-05 3.10e-06 1.24e-06 1.70e-05 1.20e-05 49methyl tert-butyl ether 3.23e-05 7.87e-06 2.19e-06 4.24e-05 2.99e-05 38methyl ethyl ketone 3.38e-06 2.11e-06 3.49e-07 5.83e-06 4.12e-06 60methyl isoamyl ketone NA NA NA NA 0.00e+00 86methyl isobutyl ketone 5.66e-07 8.61e-06 5.19e-10 9.18e-06 6.48e-06 54methylene chloride 3.08e-04 7.27e-05 9.27e-06 3.90e-04 2.75e-04 20methylnaphthalene, 2- 2.85e-05 NF NF 2.85e-05 2.01e-05 44naphthalene 3.42e-05 1.58e-08 2.96e-06 3.72e-05 2.63e-05 39octane, n- NA NA NA NA 0.00e+00 86perylene 1.51e-09 NF NF 1.51e-09 1.07e-09 85phenanthrene 2.19e-05 NF NF 2.19e-05 1.54e-05 46



Score(g-kg-

day/mg-s)

TankFarm


day/mg-s)

SamplingPlatform


day/mg-s)

CombinedInhalation

Score(g-kg-

day/mg-s)

Percent ofTotal

InhalationScore

Rank

9–51

phenol 4.02e-05 1.07e-05 1.59e-12 5.09e-05 3.60e-05 34propanol, 2- (isopropyl alcohol) NA NA NA NA 0.00e+00 86propanol, n- NA NA NA NA 0.00e+00 86propyl acetate NA NA NA NA 0.00e+00 86pyrene 1.37e-06 NF NF 1.37e-06 9.66e-07 67pyridine 3.82e-04 1.12e-05 8.90e-07 3.94e-04 2.78e-04 19styrene 2.20e-05 7.41e-06 1.74e-09 2.94e-05 2.07e-05 42tetrachloroethylene 2.41e-05 1.14e-05 8.17e-07 3.63e-05 2.57e-05 41tetrahydrofuran NA NA NA NA 0.00e+00 86toluene 4.10e-05 5.19e-05 1.04e-06 9.39e-05 6.63e-05 33trichloroethane, 1,1,1- 4.10e-07 3.85e-06 5.22e-06 9.48e-06 6.69e-06 53trichloroethylene 6.19e-05 1.79e-04 3.00e-05 2.71e-04 1.92e-04 22trimethylbenzene, 1,2,4- 5.79e-06 NF NF 5.79e-06 4.09e-06 61trimethylbenzene, 1,3,5- 2.77e-06 NF NF 2.77e-06 1.95e-06 66xylene, m- 1.05e-05 1.04e-05 4.02e-08 2.10e-05 1.49e-05 47xylene, o- 1.39e-06 4.71e-06 4.68e-08 6.15e-06 4.34e-06 59xylene, p- 1.05e-05 1.04e-05 1.03e-07 2.10e-05 1.49e-05 472,3,7,8-TCDD 1.12e-02 NF NF 1.12e-02 7.89e-03 51,2,3,7,8-PCDD 8.04e-03 NF NF 8.04e-03 5.68e-03 61,2,3,4,7,8-HxCDD 1.75e-03 NF NF 1.75e-03 1.23e-03 121,2,3,6,7,8-HxCDD 3.02e-03 NF NF 3.02e-03 2.13e-03 81,2,3,7,8,9-HxCDD 2.83e-03 NF NF 2.83e-03 2.00e-03 91,2,3,4,6,7,8-HpCDD 2.35e-03 NF NF 2.35e-03 1.66e-03 10OCDD 6.24e-06 NF NF 6.24e-06 4.40e-06 582,3,7,8-TCDF 3.34e-02 NF NF 3.34e-02 2.36e-02 21,2,3,7,8-PCDF 1.62e-03 NF NF 1.62e-03 1.15e-03 132,3,4,7,8-PCDF 2.80e-02 NF NF 2.80e-02 1.98e-02 41,2,3,4,7,8-HxCDF 2.05e-03 NF NF 2.05e-03 1.45e-03 111,2,3,6,7,8-HxCDF 9.31e-04 NF NF 9.31e-04 6.58e-04 152,3,4,6,7,8-HxCDF 1.63e-04 NF NF 1.63e-04 1.15e-04 271,2,3,7,8,9-HxCDF 2.10e-04 NF NF 2.10e-04 1.48e-04 24



Score(g-kg-

day/mg-s)

TankFarm


day/mg-s)

SamplingPlatform


day/mg-s)

CombinedInhalation

Score(g-kg-

day/mg-s)

Percent ofTotal

InhalationScore

Rank

9–52

1,2,3,4,6,7,8-HpCDF 2.03e-04 NF NF 2.03e-04 1.43e-04 251,2,3,4,7,8,9-HpCDF 1.63e-05 NF NF 1.63e-05 1.15e-05 50OCDF 1.63e-07 NF NF 1.63e-07 1.15e-07 75coplanar PCBs TEQ 7.21e-06 NF NF 7.21e-06 5.09e-06 56

Total PCB Cogener 8.44e-06 NF NF 8.44e-06 5.96e-06 55Total Inhalation Score - - - 1.42e+00 - -

NA - An inhalation score cannot be calculated for this compound, as there is no terrestrial toxicity valueavailable.Compounds in boldface contribute to 95 % of the total inhalation score.

9–53

Table 9.5 Ingestion scores of organic compoundsCompound Stack

IngestionScore(g-kg-

day/mg-s)

Tank FarmIngestion

Score(g-kg-

day/mg-s)

SamplingPlatformIngestion

Score(g-kg-

day/mg-s)

CombinedIngestion

Score(g-kg-

day/mg-s)

Percent ofTotal

IngestionScore

Rank

acenaphthene 6.28e-03 NF NF 6.28e-03 5.70e-09 61acenaphthalene 5.03e-02 NF NF 5.03e-02 4.57e-08 35acetone 2.25e-04 1.37e-05 6.95e-06 2.45e-04 2.23e-10 76

acetonitrile 1.35e-04 1.82e-06 5.21e-07 1.37e-04 1.24e-10 78

acetophenone 3.08e-04 NF NF 3.08e-04 2.79e-10 75acrylonitrile 9.92e-03 NF NF 9.92e-03 9.00e-09 56anthracene 5.05e-03 NF NF 5.05e-03 4.58e-09 62benzaldehyde 8.79e-04 NF NF 8.79e-04 7.98e-10 72benzene 1.73e+02 2.02e+00 3.13e-01 1.75e+02 1.59e-04 17benzo(a)anthracene 2.74e-02 NF NF 2.74e-02 2.49e-08 46benzo(ghi)perylene 2.73e-01 NF NF 2.73e-01 2.48e-07 26benzo(a)pyrene 9.62e-03 NF NF 9.62e-03 8.73e-09 57benzo(e)pyrene 5.39e-02 NF NF 5.39e-02 4.89e-08 34benzo(b)fluoranthene 4.72e-02 NF NF 4.72e-02 4.28e-08 38benzo(k)fluoranthene 3.54e-02 NF NF 3.54e-02 3.21e-08 41benzonitrile NA NA NA NA 0.00e+00 86benzyl alcohol 5.69e-05 NF NF 5.69e-05 5.17e-11 80bis(2-ethylhexyl)phthalate 1.61e+02 NF NF 1.61e+02 1.46e-04 18bromomethane 1.44e-02 NF NF 1.44e-02 1.30e-08 52butanol, n- 2.74e-04 6.67e-05 5.61e-07 3.41e-04 3.09e-10 74butyl acetate NA NA NA NA 0.00e+00 86carbon disulfide 9.28e-02 NF NF 9.28e-02 8.42e-08 30carbon tetrachloride 2.64e-02 NF NF 2.64e-02 2.39e-08 47chlorobenzene 2.88e-02 NF NF 2.88e-02 2.62e-08 44chloroform 1.12e-02 NF NF 1.12e-02 1.01e-08 55chrysene 4.90e-02 NF NF 4.90e-02 4.45e-08 36cresol, m- (methylphenol,3-)

1.97e-03 3.62e-04 6.01e-08 2.33e-03 2.11e-09 66


1.16e-03 4.18e-04 1.51e-07 1.58e-03 1.43e-09 68


1.88e-02 3.46e-03 5.14e-07 2.23e-02 2.02e-08 51



day/mg-s)

Tank FarmIngestion

Score(g-kg-

day/mg-s)


Score(g-kg-

day/mg-s)

CombinedIngestion

Score(g-kg-

day/mg-s)

Percent ofTotal

IngestionScore

Rank

9–54

cumene (isopropylbenzene) 4.77e-03 5.15e-01 2.59e-03 5.23e-01 4.74e-07 25cyclohexanone 4.52e-06 1.10e-06 6.57e-09 5.62e-06 5.10e-12 84diacetone alcohol NA NA NA NA 0.00e+00 86dibenz(ah)anthracene 9.23e-02 NF NF 9.23e-02 8.37e-08 31dibenzofuran NA NA NA NA 0.00e+00 86dichloroethane, 1,2- 2.50e-04 1.12e-04 1.08e-05 3.73e-04 3.38e-10 73dichloroethylene, 1,1- 2.25e-02 NF NF 2.25e-02 2.04e-08 50

dimethylphenol, 2,4- 9.91e-04 NF NF 9.91e-04 8.99e-10 71di-n-butylphthalate 2.80e-02 NF NF 2.80e-02 2.54e-08 45ethanol NA NA NA NA 0.00e+00 86ethyl acetate 2.31e-05 5.63e-06 6.73e-07 2.94e-05 2.67e-11 81ethylbenzene 1.48e-02 3.34e-02 3.93e-04 4.86e-02 4.41e-08 37ethyl ether 6.52e-06 1.59e-06 1.06e-06 9.17e-06 8.32e-12 83fluoranthene 9.89e-02 NF NF 9.89e-02 8.98e-08 29fluorene 1.35e-02 NF NF 1.35e-02 1.22e-08 53glycol ethers (diethyleneglycol)

9.43e-05 2.30e-05 1.73e-07 1.17e-04 1.07e-10 79

hexane (for aliphatics) 5.26e-01 1.28e-01 4.48e-02 7.00e-01 6.35e-07 24hexanone, 2- 3.88e-03 NF NF 3.88e-03 3.52e-09 63indeno(1,2,3-cd)pyrene 3.67e-02 NF NF 3.67e-02 3.33e-08 40iodomethane 1.54e+00 NF NF 1.54e+00 1.40e-06 22isobutyl acetate NA NA NA NA 0.00e+00 86methanol 2.48e-06 6.04e-07 2.41e-07 3.32e-06 3.01e-12 85methyl tert-butyl ether 2.56e-03 6.25e-04 1.74e-04 3.36e-03 3.05e-09 64methyl ethyl ketone 6.45e-06 4.02e-06 6.67e-07 1.11e-05 1.01e-11 82methyl isoamyl ketone NA NA NA NA 0.00e+00 86methyl isobutyl ketone 8.77e-06 1.33e-04 8.04e-09 1.42e-04 1.29e-10 77methylene chloride 5.54e-03 1.31e-03 1.67e-04 7.02e-03 6.37e-09 60methylnaphthalene, 2- 2.06e-01 NF NF 2.06e-01 1.87e-07 27naphthalene 8.08e-02 3.74e-05 6.99e-03 8.78e-02 7.97e-08 32octane, n- NA NA NA NA 0.00e+00 86perylene 9.98e-04 NF NF 9.98e-04 9.05e-10 70



day/mg-s)

Tank FarmIngestion

Score(g-kg-

day/mg-s)


Score(g-kg-

day/mg-s)

CombinedIngestion

Score(g-kg-

day/mg-s)

Percent ofTotal

IngestionScore

Rank

9–55

phenanthrene 7.76e-01 NF NF 7.76e-01 7.04e-07 23phenol 1.21e-03 3.22e-04 4.78e-11 1.53e-03 1.39e-09 69propanol, 2- (isopropylalcohol)

NA NA NA NA 0.00e+00 86

propanol, n- NA NA NA NA 0.00e+00 86propyl acetate NA NA NA NA 0.00e+00 86pyrene 1.37e-01 NF NF 1.37e-01 1.24e-07 28pyridine 1.79e-03 5.26e-05 4.17e-06 1.84e-03 1.67e-09 67styrene 1.86e-02 6.29e-03 1.48e-06 2.49e-02 2.26e-08 48tetrachloroethylene 8.47e-03 4.00e-03 2.87e-04 1.28e-02 1.16e-08 54tetrahydrofuran NA NA NA NA 0.00e+00 86toluene 1.90e-02 2.41e-02 4.85e-04 4.37e-02 3.96e-08 39trichloroethane, 1,1,1- 1.08e-04 1.02e-03 1.38e-03 2.50e-03 2.27e-09 65trichloroethylene 1.68e-02 4.86e-02 8.14e-03 7.35e-02 6.67e-08 33trimethylbenzene, 1,2,4- 2.47e-02 NF NF 2.47e-02 2.24e-08 49trimethylbenzene, 1,3,5- 7.28e-03 NF NF 7.28e-03 6.61e-09 59xylene, m- 1.68e-02 1.66e-02 6.39e-05 3.34e-02 3.03e-08 42xylene, o- 1.88e-03 6.36e-03 6.31e-05 8.31e-03 7.54e-09 58xylene, p- 1.56e-02 1.54e-02 1.53e-04 3.11e-02 2.82e-08 432,3,7,8-TCDD 4.88e+04 NF NF 4.88e+04 4.43e-02 71,2,3,7,8-PCDD 3.51e+04 NF NF 3.51e+04 3.19e-02 91,2,3,4,7,8-HxCDD 1.08e+05 NF NF 1.08e+05 9.78e-02 41,2,3,6,7,8-HxCDD 5.37e+04 NF NF 5.37e+04 4.87e-02 51,2,3,7,8,9-HxCDD 5.04e+04 NF NF 5.04e+04 4.57e-02 61,2,3,4,6,7,8-HpCDD 3.71e+05 NF NF 3.71e+05 3.37e-01 1OCDD 2.43e+02 NF NF 2.43e+02 2.20e-04 162,3,7,8-TCDF 1.13e+05 NF NF 1.13e+05 1.03e-01 31,2,3,7,8-PCDF 1.00e+04 NF NF 1.00e+04 9.09e-03 122,3,4,7,8-PCDF 2.33e+05 NF NF 2.33e+05 2.11e-01 21,2,3,4,7,8-HxCDF 3.66e+04 NF NF 3.66e+04 3.32e-02 81,2,3,6,7,8-HxCDF 1.66e+04 NF NF 1.66e+04 1.50e-02 112,3,4,6,7,8-HxCDF 2.89e+03 NF NF 2.89e+03 2.63e-03 14



day/mg-s)

Tank FarmIngestion

Score(g-kg-

day/mg-s)


Score(g-kg-

day/mg-s)

CombinedIngestion

Score(g-kg-

day/mg-s)

Percent ofTotal

IngestionScore

Rank

9–56

1,2,3,7,8,9-HxCDF 3.73e+03 NF NF 3.73e+03 3.39e-03 131,2,3,4,6,7,8-HpCDF 1.69e+04 NF NF 1.69e+04 1.53e-02 101,2,3,4,7,8,9-HpCDF 1.35e+03 NF NF 1.35e+03 1.23e-03 15OCDF 9.81e+01 NF NF 9.81e+01 8.90e-05 19coplanar PCBs TEQ 1.16e+01 NF NF 1.16e+01 1.05e-05 21Total PCB Cogener 1.36e+01 NF NF 1.36e+01 1.23e-05 20Total Ingestion Score - - - 1.10e+06 - -NA - An ingestion score cannot be calculated for this compound, as there is no terrestrial toxicity value available.Compounds in boldface contribute to 95 % of the total ingestion score.

9–57

Table 9.6 Aquatic toxicity data

Compound AWQCA

(:g/L)AALCB

(ug/L)LC50

C

(:g/L) Species Source

acenaphthene NA 1.40e+02 NA - -acenaphthalene NA 7.70e+00 NA - -acetone NA 1.50e+04 1.21e+07 water flea ECOTOX, 2001acetonitrile NA NA 1.00e+05 water flea ECOTOX, 2001acetophenone NA NA 1.55e+05 fathead minnow ECOTOX, 2001acrylonitrile NA 5.70e+02 2.60e+03 fathead minnow ECOTOX, 2001anthracene NA 6.10e+00 5.00e+00 benzo(a)pyrene Surrogatebenzaldehyde NA NA 8.00e+02 bluegill ECOTOX, 2001benzene NA 8.80e+02 1.54e+04 water fles ECOTOX, 2001benzo(a)anthracene NA 2.30e-01 1.00e+01 water flea ECOTOX, 2001benzo(ghi)perylene NA NA 5.00e+00 benzo(a)pyrene Surrogatebenzo(a)pyrene NA 1.10e-01 5.00e+00 water flea ECOTOX, 2001benzo(e)pyrene NA NA 5.00e+00 benzo(a)pyrene Surrogatebenzo(b)fluoranthene NA NA 5.00e+00 benzo(a)pyrene Surrogatebenzo(k)fluoranthene NA NA 5.00e+00 benzo(a)pyrene Surrogatebenzonitrile NA NA 1.50e+04 medaka, high-eyes ECOTOX, 2001benzyl alcohol NA NA 1.00e+04 bluegill sunfish HSDB, 2001bis(2-ethylhexyl)phthalate NA NA 1.00e+03 water flea HSDB, 2001bromomethane NA NA 7.00e+02 coleoptera HSDB, 2001butanol, n- NA NA 1.51e+06 fathead minnow HSDB, 2001butyl acetate NA NA 1.00e+05 bluegill HSDB, 2001carbon disulfide NA NA 1.90e+03 water flea ECOTOX, 2001carbon tetrachloride NA 3.60e+02 2.00e+02 flatworm ECOTOX, 2001chlorobenzene NA NA 6.70e+02 goldfish ECOTOX, 2001chloroform NA 1.30e+03 1.80e+03 rotifer ECOTOX, 2001chrysene NA NA 1.00e+03 polycheate worm ECOTOX, 2001cresol, m- (methylphenol,3-)

NA 4.80e+02 7.00e+03 gammarus fasciatus HSDB, 2001

cresol, o- (methylphenol, 2-) NA 6.00e+02 7.00e+03 gammarus fasciatus HSDB, 2001cresol, p- (methylphenol, 4-) NA 4.80e+02 7.00e+03 gammarus fasciatus HSDB, 2001cumene (isopropylbenzene) NA NA 2.70e+03 rainbow trout ECOTOX, 2001cyclohexanone NA NA 4.81e+05 fathead minnow ECOTOX, 2001diacetone alcohol NA NA 4.20e+05 menidia beryllina HSDB, 2001

dibenz(ah)anthracene NA NA 1.00e+03 neanthesarenaceodentata HSDB, 2001


Compound AWQCA

(:g/L)AALCB

(ug/L)LC50

C


9–58

dibenzofuran NA 6.50e+01 1.00e+03 water flea ECOTOX, 2001

dichloroethane, 1,2- NA 7.30e+03 3.88e+05 northern pike (100%lethal)

ECOTOX, 2001

dichloroethylene, 1,1- NA NA 9.00e+03 water flea ECOTOX, 2001

dimethylphenol, 2,4- NA NA 2.60e+03 water flea ECOTOX, 2001

di-n-butylphthalate NA NA 2.10e+02 scud HSDB, 2001

ethanol NA NA 2.32e+05 water flea ECOTOX, 2001

ethyl acetate NA NA 2.30e+05 fathead minnow HSDB, 2001

ethylbenzene NA 1.00e+03 1.02e+04 grass shrimp larvae HSDB, 2001

ethyl ether NA NA 2.56e+06 fathead minnow HSDB, 2001

fluoranthene NA 1.50e+02 NA - -

fluorene NA 2.20e+01 NA - -

glycol ethers (diethyleneglycol)

NA NA 5.00e+06 goldfish ECOTOX, 2001

hexane (for aliphatics) NA NA 2.10e+03 fathead minnow ECOTOX, 2001

hexanone, 2- NA NA 4.28e+05 fathead minnow ECOTOX, 2001

indeno(1,2,3-cd)pyrene NA NA 5.00e+00 benzo(a)pyrene Surrogate

iodomethane NA NA 7.00e+02 bromomethane surrogate

isobutyl acetate NA NA 2.50e+05 water flea ECOTOX, 2001

methanol NA 3.00e+03 3.70e+04 mussel ECOTOX, 2001

methyl tert-butyl ether NA 6.50e+03 6.72e+05 fathead minnow ECOTOX, 2001

methyl ethyl ketone NA 1.20e+05 4.00e+05 sheepshead minnow ECOTOX, 2001

methyl isoamyl ketone NA NA 1.59e+05 fathead minnow HSDB, 2001

methyl isobutyl ketone NA NA 4.92e+05 fathead minnow ECOTOX, 2001

methylene chloride NA 1.40e+04 1.40e+05 water flea ECOTOX, 2001

methylnaphthalene, 2- NA NA 1.30e+03 Dungeness Crab larvae HSDB, 2001

naphthalene NA 2.00e+02 6.08e+03 fathead minnow HSDB, 2001

octane, n- NA NA 4.00e+02 brine shrimp ECOTOX, 2001

perylene NA NA 5.00e+00 benzo(a)pyrene Surrogate

phenanthrene NA 8.40e+00 6.00e+02 Neanhesarenaceodentata

HSDB, 2001

phenol NA 3.60e+02 3.60e+04 water flea ECOTOX, 2001

propanol, 2- (isopropyl alcohol) NA NA 7.50e+05 sand shrimp ECOTOX, 2001

propanol, n- NA NA 5.00e+05 creek chub, LD100 HSDB, 2001

propyl acetate NA NA 6.00e+04 fathead minnow HSDB, 2001

pyrene NA NA 5.00e+00 benzo(a)pyrene Surrogate

pyridine NA NA 1.10e+03 pink salmon ECOTOX, 2001

styrene NA NA 5.10e+03 sheepshead minnow ECOTOX, 2001


Compound AWQCA

(:g/L)AALCB

(ug/L)LC50

C


9–59

tetrachloroethylene NA 4.80e+02 1.40e+03 flatworm ECOTOX, 2001

tetrahydrofuran NA NA 1.97e+06 fathead minnow ECOTOX, 2001

toluene NA 8.40e+02 4.30e+03 shrimp HSDB, 2001

trichloroethane, 1,1,1- NA 3.70e+03 3.70e+03 water flea ECOTOX, 2001

trichloroethylene NA 2.30e+03 1.70e+03 flatworm ECOTOX, 2001

trimethylbenzene, 1,2,4- NA NA 3.87e+03 scud ECOTOX, 2001

trimethylbenzene, 1,3,5- NA NA 3.87e+03 1,2,4-trimethylbenzene surrogate

xylene, m- NA 3.10e+02 7.40e+03 daggerblade grassshrimp

ECOTOX, 2001

xylene, o- NA 3.10e+02 7.40e+03 daggerblade grassshrimp

ECOTOX, 2001

xylene, p- NA 3.10e+02 7.40e+03 daggerblade grassshrimp

ECOTOX, 2001

2,3,7,8-TCDD NA NA 5.70e-03 medaka, high-eyes ECOTOX, 2001

1,2,3,7,8-PCDD NA NA 2.30e-02 medaka, high-eyes ECOTOX, 2001

1,2,3,4,7,8-HxCDD NA NA 7.18e-01 medaka, high-eyes ECOTOX, 2001

1,2,3,6,7,8-HxCDD NA NA 5.70e-02 - calculated

1,2,3,7,8,9-HxCDD NA NA 5.70e-02 - calculated

1,2,3,4,6,7,8-HpCDD NA NA 5.70e-01 - calculated

OCDD NA NA 5.70e+01 - calculated

2,3,7,8-TCDF NA NA 5.70e-03 - calculated

1,2,3,7,8-PCDF NA NA 5.70e-02 - calculated

2,3,4,7,8-PCDF NA NA 5.70e-03 - calculated

1,2,3,4,7,8-HxCDF NA NA 5.70e-02 - calculated




1,2,3,4,6,7,8-HpCDF NA NA 5.70e-01 - calculated

1,2,3,4,7,8,9-HpCDF NA NA 5.70e-01 - calculated

OCDF NA NA 5.70e+01 - calculated

coplanar PCBs TEQ NA NA 5.70e-03 medaka, high-eyes ECOTOX, 2001

Total PCB Cogener 1.40e-02 NA NA - -

NA - Not available.Calculated - Calculated using Equation 9.0 And the toxicity equivalency factors (TEFs) from Table 9.3. A Criterion Continuous Concentration (CCC) from the Federal Ambient Water Quality Criteria (AWQC) (Federal Register,1998).B Acute Aquatic Life Criteria (AALC) calculated using the Great Lakes Basin Methodologies (IDEM, 2000).C Water concentration at which 50 % of the tested population dies. D Species and Source for LC50 values.

9–60

Table 9.7 Aquatic bioconcentration (BC) scores of organic compoundsCompound Stack BC

Score(g-L/:g-s)

TankFarm BC

Score(g-L/:g-s)

SamplingPlatformBC Score(g-L/:g-s)

CombinedBC Score(g-L/:g-s)

Percent ofTotal

BC Score

Rank

acenaphthene 7.85e-03 NF NF 7.85e-03 3.74e-05 43acenaphthalene 4.64e-01 NF NF 4.64e-01 2.21e-03 26acetone 1.50e-06 9.16e-08 4.63e-08 1.63e-06 7.79e-09 75

acetonitrile 5.79e-08 7.81e-10 2.24e-10 5.89e-08 2.80e-10 86acetophenone 8.40e-07 NF NF 8.40e-07 4.00e-09 76acrylonitrile 1.74e-05 NF NF 1.74e-05 8.29e-08 67anthracene 8.28e-01 NF NF 8.28e-01 3.94e-03 19benzaldehyde 1.57e-04 NF NF 1.57e-04 7.49e-07 60benzene 3.51e-03 4.12e-05 6.37e-06 3.56e-03 1.69e-05 47benzo(a)anthracene 8.47e+00 NF NF 8.47e+00 4.04e-02 7benzo(ghi)perylene 3.88e+00 NF NF 3.88e+00 1.85e-02 12benzo(a)pyrene 6.21e+00 NF NF 6.21e+00 2.96e-02 11benzo(e)pyrene 7.65e-01 NF NF 7.65e-01 3.64e-03 20benzo(b)fluoranthene 6.70e-01 NF NF 6.70e-01 3.19e-03 21benzo(k)fluoranthene 5.02e-01 NF NF 5.02e-01 2.39e-03 25benzonitrile 4.64e-06 NF NF 4.64e-06 2.21e-08 71benzyl alcohol 1.63e-07 NF NF 1.63e-07 7.76e-10 82bis(2-ethylhexyl)phthalate 3.05e-01 NF NF 3.05e-01 1.45e-03 27bromomethane 2.87e-05 NF NF 2.87e-05 1.37e-07 65butanol, n- 2.27e-08 5.52e-09 4.65e-11 2.82e-08 1.34e-10 88butyl acetate 4.18e-06 1.02e-06 1.93e-08 5.22e-06 2.48e-08 69carbon disulfide 5.37e-04 NF NF 5.37e-04 2.56e-06 54carbon tetrachloride 5.20e-05 NF NF 5.20e-05 2.48e-07 63chlorobenzene 8.17e-04 NF NF 8.17e-04 3.89e-06 52chloroform 1.11e-05 NF NF 1.11e-05 5.28e-08 68chrysene 3.48e-03 NF NF 3.48e-03 1.66e-05 48cresol, m- (methylphenol, 3-) 2.05e-04 3.77e-05 6.26e-09 2.43e-04 1.16e-06 57cresol, o- (methylphenol, 2-) 9.67e-05 3.48e-05 1.26e-08 1.32e-04 6.27e-07 61cresol, p- (methylphenol, 4-) 1.96e-04 3.61e-05 5.36e-09 2.32e-04 1.11e-06 58cumene (isopropylbenzene) 1.94e-04 2.10e-02 1.05e-04 2.13e-02 1.01e-04 35cyclohexanone 4.34e-09 1.06e-09 6.32e-12 5.40e-09 2.57e-11 94diacetone alcohol 6.73e-10 1.64e-10 2.01e-13 8.37e-10 3.99e-12 97dibenz(ah)anthracene 6.55e-03 NF NF 6.55e-03 3.12e-05 44


Score(g-L/:g-s)

TankFarm BC

Score(g-L/:g-s)



Percent ofTotal

BC Score

Rank

9–61

dibenzofuran 1.48e-01 NF NF 1.48e-01 7.04e-04 30dichloroethane, 1,2- 1.98e-07 8.94e-08 8.56e-09 2.96e-07 1.41e-09 79dichloroethylene, 1,1- 2.25e-06 NF NF 2.25e-06 1.07e-08 73dimethylphenol, 2,4- 1.91e-05 NF NF 1.91e-05 9.08e-08 66di-n-butylphthalate 1.67e-02 NF NF 1.67e-02 7.94e-05 39ethanol 1.19e-08 2.89e-09 2.87e-10 1.50e-08 7.16e-11 90ethyl acetate 9.04e-08 2.20e-08 2.63e-09 1.15e-07 5.48e-10 83ethylbenzene 1.44e-03 3.25e-03 3.82e-05 4.72e-03 2.25e-05 46ethyl ether 1.27e-09 3.10e-10 2.08e-10 1.79e-09 8.53e-12 95fluoranthene 8.24e-02 NF NF 8.24e-02 3.93e-04 31fluorene 7.66e-02 NF NF 7.66e-02 3.65e-04 32glycol ethers (diethylene glycol)

6.73e-10 1.64e-10 1.23e-12 8.39e-10 3.99e-12 96

hexane (for aliphatics) 1.43e-01 3.48e-02 1.22e-02 1.90e-01 9.04e-04 29hexanone, 2- 9.07e-08 NF NF 9.07e-08 4.32e-10 84indeno(1,2,3-cd)pyrene 5.21e-01 NF NF 5.21e-01 2.48e-03 23iodomethane 3.08e-03 NF NF 3.08e-03 1.47e-05 49isobutyl acetate 3.23e-08 7.88e-09 1.78e-10 4.04e-08 1.92e-10 87methanol 4.13e-07 1.01e-07 4.02e-08 5.54e-07 2.64e-09 77methyl tert-butyl ether 3.95e-06 9.62e-07 2.67e-07 5.17e-06 2.46e-08 70methyl ethyl ketone 9.52e-08 5.93e-08 9.85e-09 1.64e-07 7.83e-10 81methyl isoamyl ketone 4.41e-08 1.07e-08 2.91e-07 3.46e-07 1.65e-09 78methyl isobutyl ketone 4.46e-09 6.78e-08 4.08e-12 7.23e-08 3.44e-10 85methylene chloride 2.32e-06 5.47e-07 6.97e-08 2.93e-06 1.40e-08 72methylnaphthalene, 2- 1.13e-02 NF NF 1.13e-02 5.37e-05 42naphthalene 2.87e-02 1.33e-05 2.48e-03 3.12e-02 1.48e-04 34octane, n- 2.16e-08 NF NF 2.16e-08 1.03e-10 89perylene 1.42e-02 NF NF 1.42e-02 6.75e-05 40phenanthrene 6.56e+00 NF NF 6.56e+00 3.12e-02 9phenol 2.01e-04 5.37e-05 7.97e-12 2.55e-04 1.21e-06 56propanol, 2- (isopropyl alcohol)

1.15e-08 2.80e-09 3.35e-13 1.43e-08 6.83e-11 91

propanol, n- 6.41e-09 1.56e-09 6.70e-10 8.64e-09 4.12e-11 92propyl acetate 2.21e-07 5.38e-08 4.41e-09 2.79e-07 1.33e-09 80


Score(g-L/:g-s)

TankFarm BC

Score(g-L/:g-s)



Percent ofTotal

BC Score

Rank

9–62

pyrene 2.05e+00 NF NF 2.05e+00 9.77e-03 15pyridine 1.63e-06 4.79e-08 3.79e-09 1.68e-06 7.99e-09 74styrene 7.31e-04 2.47e-04 5.79e-08 9.78e-04 4.66e-06 51tetrachloroethylene 2.47e-04 1.17e-04 8.36e-06 3.72e-04 1.77e-06 55tetrahydrofuran 4.75e-09 1.16e-09 4.92e-12 5.91e-09 2.81e-11 93toluene 5.06e-03 6.41e-03 1.29e-04 1.16e-02 5.52e-05 41trichloroethane, 1,1,1- 2.63e-06 2.47e-05 3.35e-05 6.09e-05 2.90e-07 62trichloroethylene 9.19e-06 2.66e-05 4.46e-06 4.03e-05 1.92e-07 64trimethylbenzene, 1,2,4- 6.20e-04 NF NF 6.20e-04 2.95e-06 53trimethylbenzene, 1,3,5- 1.83e-04 NF NF 1.83e-04 8.70e-07 59xylene, m- 9.68e-03 9.59e-03 3.69e-05 1.93e-02 9.20e-05 36xylene, o- 1.09e-03 3.67e-03 3.65e-05 4.80e-03 2.28e-05 45xylene, p- 8.99e-03 8.90e-03 8.83e-05 1.80e-02 8.56e-05 372,3,7,8-TCDD 8.56e+00 NF NF 8.56e+00 4.08e-02 61,2,3,7,8-PCDD 1.53e+00 NF NF 1.53e+00 7.28e-03 171,2,3,4,7,8-HxCDD 1.50e+00 NF NF 1.50e+00 7.15e-03 181,2,3,6,7,8-HxCDD 9.42e+00 NF NF 9.42e+00 4.49e-02 41,2,3,7,8,9-HxCDD 8.84e+00 NF NF 8.84e+00 4.21e-02 51,2,3,4,6,7,8-HpCDD 6.51e+01 NF NF 6.51e+01 3.10e-01 1OCDD 4.26e-02 NF NF 4.26e-02 2.03e-04 332,3,7,8-TCDF 1.99e+01 NF NF 1.99e+01 9.47e-02 31,2,3,7,8-PCDF 1.76e+00 NF NF 1.76e+00 8.37e-03 162,3,4,7,8-PCDF 4.09e+01 NF NF 4.09e+01 1.95e-01 21,2,3,4,7,8-HxCDF 6.41e+00 NF NF 6.41e+00 3.05e-02 101,2,3,6,7,8-HxCDF 2.91e+00 NF NF 2.91e+00 1.39e-02 142,3,4,6,7,8-HxCDF 5.08e-01 NF NF 5.08e-01 2.42e-03 241,2,3,7,8,9-HxCDF 6.55e-01 NF NF 6.55e-01 3.12e-03 221,2,3,4,6,7,8-HpCDF 2.96e+00 NF NF 2.96e+00 1.41e-02 131,2,3,4,7,8,9-HpCDF 2.37e-01 NF NF 2.37e-01 1.13e-03 28OCDF 1.72e-02 NF NF 1.72e-02 8.20e-05 38coplanar PCBs TEQ 2.04e-03 NF NF 2.04e-03 9.70e-06 50Total PCB Cogener 6.80e+00 NF NF 6.80e+00 3.24e-02 8Total Bioconcentration Score 2.10e+02


Score(g-L/:g-s)

TankFarm BC

Score(g-L/:g-s)



Percent ofTotal

BC Score

Rank

9–63

Compounds in boldface represent 95 % of the total aquatic bioconcentration score.

9–64

Table 9.8 Aquatic solubility score for organic compounds

Compound

StackSolubility

Score(g-mg-L/:g-s)

Tank FarmSolubility

Score(g-mg-L/:g-s)

SamplingPlatformSolubility

Score(g-mg-L/:g-s)

SolubilityScore(g-mg-L/:g-s)

Percent ofTotal

SolubilityScore(%)

Rank

acenaphthene 3.52e-06 NF NF 3.52e-06 8.09e-07 58acenaphthalene 2.09e-04 NF NF 2.09e-04 4.82e-05 40acetone 1.51e+00 9.22e-02 4.66e-02 1.65e+00 3.79e-01 1acetonitrile 9.50e-03 1.28e-04 3.68e-05 9.66e-03 2.22e-03 11acetophenone 1.17e-04 NF NF 1.17e-04 2.70e-05 42acrylonitrile 7.33e-01 NF NF 7.33e-01 1.69e-01 4anthracene 1.51e-06 NF NF 1.51e-06 3.47e-07 61benzaldehyde 1.73e-02 NF NF 1.73e-02 3.98e-03 9benzene 4.61e-08 5.41e-10 8.37e-11 4.67e-08 1.08e-08 67benzo(a)anthracene 2.27e-07 NF NF 2.27e-07 5.23e-08 64benzo(ghi)perylene 6.84e-11 NF NF 6.84e-11 1.58e-11 77benzo(a)pyrene 8.92e-09 NF NF 8.92e-09 2.05e-09 70benzo(e)pyrene 1.75e-09 NF NF 1.75e-09 4.03e-10 73benzo(b)fluoranthene 1.83e-09 NF NF 1.83e-09 4.20e-10 72benzo(k)fluoranthene 2.58e-10 NF NF 2.58e-10 5.93e-11 76benzonitrile 2.56e-04 NF NF 2.56e-04 5.88e-05 37benzyl alcohol 5.17e-04 NF NF 5.17e-04 1.19e-04 30bis(2-ethylhexyl)phthalate

6.10e-07 NF NF 6.10e-07 1.40e-07 63

bromomethane 2.05e-03 NF NF 2.05e-03 4.72e-04 20butanol, n- 2.58e-04 6.29e-05 5.29e-07 3.21e-04 7.40e-05 32butyl acetate 8.85e-04 2.16e-04 4.08e-06 1.10e-03 2.54e-04 22carbon disulfide 1.43e-08 NF NF 1.43e-08 3.30e-09 68carbon tetrachloride 7.91e-05 NF NF 7.91e-05 1.82e-05 45chlorobenzene 5.43e-04 NF NF 5.43e-04 1.25e-04 28chloroform 9.93e-04 NF NF 9.93e-04 2.29e-04 23chrysene 1.23e-11 NF NF 1.23e-11 2.84e-12 82cresol, m-(methylphenol, 3-)

5.18e-02 9.54e-03 1.58e-06 6.13e-02 1.41e-02 6


2.55e-02 9.19e-03 3.32e-06 3.47e-02 7.99e-03 8


5.18e-02 9.54e-03 1.42e-06 6.13e-02 1.41e-02 7


Compound

StackSolubility

Score(g-mg-L/:g-s)

Tank FarmSolubility

Score(g-mg-L/:g-s)


Score(g-mg-L/:g-s)


Percent ofTotal

SolubilityScore(%)

Rank

9–65

cumene(isopropylbenzene)

2.65e-06 2.87e-04 1.44e-06 2.91e-04 6.69e-05 34

cyclohexanone 1.54e-05 3.76e-06 2.25e-08 1.92e-05 4.43e-06 51diacetone alcohol 5.38e-04 1.31e-04 1.61e-07 6.69e-04 1.54e-04 25dibenz(ah)anthracene 1.24e-12 NF NF 1.24e-12 2.86e-13 89dibenzofuran 4.14e-05 NF NF 4.14e-05 9.53e-06 48dichloroethane, 1,2- 5.68e-06 2.56e-06 2.45e-07 8.49e-06 1.95e-06 54dichloroethylene, 1,1- 5.12e-05 NF NF 5.12e-05 1.18e-05 47dimethylphenol, 2,4- 5.20e-04 NF NF 5.20e-04 1.20e-04 29di-n-butylphthalate 3.43e-06 NF NF 3.43e-06 7.89e-07 59ethanol 2.47e-03 6.03e-04 5.99e-05 3.14e-03 7.22e-04 13ethyl acetate 1.08e-03 2.63e-04 3.14e-05 1.37e-03 3.15e-04 21ethylbenzene 1.87e-04 4.22e-04 4.96e-06 6.14e-04 1.41e-04 27ethyl ether 1.15e-05 2.79e-06 1.87e-06 1.61e-05 3.71e-06 52fluoranthene 1.58e-07 NF NF 1.58e-07 3.64e-08 66fluorene 9.69e-06 NF NF 9.69e-06 2.23e-06 53glycol ethers (diethyleneglycol)

1.04e-08 2.53e-09 1.90e-11 1.29e-08 2.98e-09 69

hexane (for aliphatics) 6.33e-04 1.54e-04 5.39e-05 8.41e-04 1.94e-04 24hexanone, 2- 5.29e-05 NF NF 5.29e-05 1.22e-05 46indeno(1,2,3-cd)pyrene 6.78e-10 NF NF 6.78e-10 1.56e-10 75iodomethane 8.79e-01 NF NF 8.79e-01 2.02e-01 2isobutyl acetate 5.44e-06 1.33e-06 3.00e-08 6.80e-06 1.56e-06 56methanol 6.14e-02 1.50e-02 5.98e-03 8.23e-02 1.89e-02 5methyl tert-butyl ether 1.82e-03 4.44e-04 1.23e-04 2.39e-03 5.49e-04 15methyl ethyl ketone 1.20e-12 7.46e-13 1.24e-13 2.07e-12 4.75e-13 88methyl isoamyl ketone 3.14e-06 7.64e-07 2.07e-05 2.46e-05 5.66e-06 50methyl isobutyl ketone 5.75e-06 8.75e-05 5.27e-09 9.33e-05 2.15e-05 44methylene chloride 2.24e-03 5.28e-04 6.74e-05 2.83e-03 6.52e-04 14methylnaphthalene, 2- 3.83e-05 NF NF 3.83e-05 8.82e-06 49naphthalene 3.78e-04 1.75e-07 3.27e-05 4.11e-04 9.45e-05 31octane, n- 3.58e-06 NF NF 3.58e-06 8.25e-07 57


Compound

StackSolubility

Score(g-mg-L/:g-s)

Tank FarmSolubility

Score(g-mg-L/:g-s)


Score(g-mg-L/:g-s)


Percent ofTotal

SolubilityScore(%)

Rank

9–66

perylene 8.57e-12 NF NF 8.57e-12 1.97e-12 83phenanthrene 2.36e-04 NF NF 2.36e-04 5.44e-05 39phenol 6.08e-01 1.63e-01 2.41e-08 7.71e-01 1.77e-01 3propanol, 2- (isopropylalcohol)

1.67e-03 4.05e-04 4.85e-08 2.07e-03 4.77e-04 19

propanol, n- 3.60e-03 8.77e-04 3.77e-04 4.85e-03 1.12e-03 12propyl acetate 2.08e-04 5.07e-05 4.15e-06 2.63e-04 6.05e-05 36pyrene 2.81e-06 NF NF 2.81e-06 6.47e-07 60pyridine 1.04e-04 3.07e-06 2.43e-07 1.07e-04 2.47e-05 43styrene 2.21e-04 7.47e-05 1.75e-08 2.96e-04 6.81e-05 33tetrachloroethylene 1.63e-04 7.72e-05 5.53e-06 2.46e-04 5.66e-05 38tetrahydrofuran 1.70e-03 4.13e-04 1.76e-06 2.11e-03 4.86e-04 18toluene 6.07e-03 7.69e-03 1.54e-04 1.39e-02 3.20e-03 10trichloroethane, 1,1,1- 1.17e-05 1.10e-04 1.49e-04 2.70e-04 6.21e-05 35trichloroethylene 4.00e-05 1.16e-04 1.94e-05 1.75e-04 4.04e-05 41trimethylbenzene, 1,2,4- 8.28e-06 NF NF 8.28e-06 1.90e-06 55trimethylbenzene, 1,3,5- 1.39e-06 NF NF 1.39e-06 3.20e-07 62xylene, m- 1.13e-03 1.12e-03 4.32e-06 2.26e-03 5.20e-04 16xylene, o- 1.50e-04 5.06e-04 5.02e-06 6.61e-04 1.52e-04 26xylene, p- 1.13e-03 1.12e-03 1.11e-05 2.26e-03 5.20e-04 162,3,7,8-TCDD 3.78e-11 NF NF 3.78e-11 8.70e-12 811,2,3,7,8-PCDD 4.19e-11 NF NF 4.19e-11 9.65e-12 801,2,3,4,7,8-HxCDD 1.07e-13 NF NF 1.07e-13 2.46e-14 931,2,3,6,7,8-HxCDD 2.33e-12 NF NF 2.33e-12 5.36e-13 861,2,3,7,8,9-HxCDD 2.18e-12 NF NF 2.18e-12 5.03e-13 871,2,3,4,6,7,8-HpCDD 9.89e-13 NF NF 9.89e-13 2.28e-13 90OCDD 8.09e-17 NF NF 8.09e-17 1.86e-17 962,3,7,8-TCDF 2.46e-09 NF NF 2.46e-09 5.66e-10 711,2,3,7,8-PCDF 6.83e-11 NF NF 6.83e-11 1.57e-11 782,3,4,7,8-PCDF 1.16e-09 NF NF 1.16e-09 2.67e-10 741,2,3,4,7,8-HxCDF 2.97e-12 NF NF 2.97e-12 6.84e-13 841,2,3,6,7,8-HxCDF 2.89e-12 NF NF 2.89e-12 6.65e-13 85


Compound

StackSolubility

Score(g-mg-L/:g-s)

Tank FarmSolubility

Score(g-mg-L/:g-s)


Score(g-mg-L/:g-s)


Percent ofTotal

SolubilityScore(%)

Rank

9–67

2,3,4,6,7,8-HxCDF 3.71e-13 NF NF 3.71e-13 8.54e-14 921,2,3,7,8,9-HxCDF 4.78e-13 NF NF 4.78e-13 1.10e-13 911,2,3,4,6,7,8-HpCDF 4.80e-14 NF NF 4.80e-14 1.11e-14 941,2,3,4,7,8,9-HpCDF 3.99e-15 NF NF 3.99e-15 9.19e-16 95OCDF 3.42e-17 NF NF 3.42e-17 7.88e-18 97coplanar PCBs TEQ 6.51e-11 NF NF 6.51e-11 1.50e-11 79Total PCB Cogener 2.17e-07 NF NF 2.17e-07 5.00e-08 65Total Solubility Score 4.35e+00Compounds in boldface represent 95 % of the total solubility score.

9–68

Table 9.9 Selected compounds of ecological concern (COECs)A

CompoundTerrestrial Aquatic Soil

Half-LifeInhalation Ingestion Bioconcentration SolubilityAcetone No No No Yes NoAcrylonitrile No No No Yes NoBenzene Yes No No No NoBenzo(a)anthracene No No Yes No NoBenzo(g,h,i)perylene No No Yes No NoBenzo(a)pyrene No No Yes No NoBenzo(k)fluoranthene No No No No YesCarbon Tetrachloride No No No No YesChrysene No No No No YesCresol, -m (methylphenol, 3-) No No No Yes NoDibenzo(a,h)anthracene No No No No YesIodomethane Yes No No Yes NoMethanol No No No Yes NoPhenanthrene No No Yes No NoPhenol No No No Yes NoPyrene No No Yes No NoIdeno(1,2,3-cd)pyrene No No No No Yes

Coplanar PCB TEQ No No No No NoTotal PCB Cogener No No Yes No No

2,3,7,8-TCDD No Yes Yes No No1,2,3,7,8-PCDD No Yes No No No1,2,3,4,7,8-HxCDD No Yes No No No1,2,3,6,7,8-HxCDD No Yes Yes No No1,2,3,7,8,9-HxCDD No Yes Yes No No1,2,3,4,6,7,8-HpCDD No Yes Yes No NoOCDD No No No No No2,3,7,8-TCDF Yes Yes Yes No No1,2,3,7,8-PCDF No No Yes No No2,3,4,7,8-PCDF Yes Yes Yes No No1,2,3,4,7,8-HxCDF No Yes Yes No No1,2,3,6,7,8-HxCDF No No Yes No No2,3,4,6,7,8-HxCDF No No No No No

Table 9.9 Selected compounds of ecological concern (COECs)A

CompoundTerrestrial Aquatic Soil

Half-LifeInhalation Ingestion Bioconcentration Solubility

9–69

1,2,3,7,8,9-HxCDF No No No No No1,2,3,4,6,7,8-HpCDF No No Yes No No1,2,3,4,7,8,9-HpCDF No No No No NoOCDF No No No No No

Aluminum NA NA NA NA NAAntimony NA NA NA NA NAArsenic NA NA NA NA NABarium NA NA NA NA NABeryllium NA NA NA NA NACadmium NA NA NA NA NAChromium (total) NA NA NA NA NAChromium (hexavalent) NA NA NA NA NACobalt NA NA NA NA NACopper NA NA NA NA NALead NA NA NA NA NAManganese NA NA NA NA NAMercuric chloride (particle) NA NA NA NA NAMercuric chloride (vapor) NA NA NA NA NAMercury NA NA NA NA NAMethyl mercury NA NA NA NA NANickel NA NA NA NA NASelenium NA NA NA NA NASilver NA NA NA NA NAThallium NA NA NA NA NAVanadium NA NA NA NA NAZinc NA NA NA NA NA

NA - Not applicable. Compound is inorganic.A Chemicals included because of a given scoring algorithm have “Yes” under the appropriate column.

9–70

Table 9.10 Estimated exposure point concentrations in air and soil

CompoundAirA

Long-term(:g/m3)

SoilB

Maximum(mg/kg)

Watershed(mg/kg)

Acetone 1.39e-02 1.28e-04 1.27e-06Acrylonitrile 8.04e-05 5.13e-16 7.87e-17Benzene 1.45e-03 8.80e-06 3.32e-07Benzo(a)anthracene 5.90e-08 5.31e-07 6.82e-08Benzo(g,h,i)perylene 1.65e-08 1.75e-07 2.13e-09Benzo(a)pyrene 7.30e-09 5.98e-08 2.52e-09Benzo(k)fluoranthene 2.32e-08 7.88e-07 2.22e-08Carbon Tetrachloride 5.19e-07 5.66e-09 8.68e-10Chrysene 9.17e-08 1.25e-06 1.37e-07Cresol, -m (methylphenol, 3-) 7.23e-04 2.07e-04 1.56e-06Dibenzo(a,h)anthracene 2.67e-08 4.17e-07 5.47e-09Iodomethane 6.35e-04 5.51e-06 8.45e-07Methanol 8.38e-03 3.00e-06 1.75e-08Phenanthrene 2.24e-05 4.15e-06 6.37e-07Phenol 2.33e-03 2.49e-04 1.62e-06Pyrene 1.48e-06 3.55e-05 5.19e-06Ideno(1,2,3-cd)pyrene 4.57e-09 5.50e-08 7.02e-10

Coplanar PCB TEQ 1.04e-13 6.61e-14 9.88e-15Total PCB Cogener 8.53e-10 5.42e-10 8.10e-11

2,3,7,8-TCDD 1.60e-10 8.60e-09 5.94e-101,2,3,7,8-PCDD 1.14e-10 6.60e-09 2.36e-101,2,3,4,7,8-HxCDD 2.48e-10 1.49e-08 2.69e-101,2,3,6,7,8-HxCDD 4.28e-10 2.58e-08 3.83e-101,2,3,7,8,9-HxCDD 4.01e-10 2.43e-08 3.26e-101,2,3,4,6,7,8-HpCDD 3.33e-09 2.02e-07 2.72e-09OCDD 8.84e-10 5.38e-08 6.44e-102,3,7,8-TCDF 4.80e-10 2.47e-08 2.29e-091,2,3,7,8-PCDF 2.32e-10 1.29e-08 6.83e-102,3,4,7,8-PCDF 3.99e-10 2.28e-08 9.31e-101,2,3,4,7,8-HxCDF 2.91e-10 1.75e-08 2.96e-101,2,3,6,7,8-HxCDF 1.32e-10 7.93e-09 1.37e-10

Table 9.10 Estimated exposure point concentrations in air and soil

CompoundAirA

Long-term(:g/m3)

SoilB

Maximum(mg/kg)

Watershed(mg/kg)

9–71

2,3,4,6,7,8-HxCDF 2.31e-11 1.38e-09 2.43e-111,2,3,7,8,9-HxCDF 2.97e-11 1.78e-09 3.19e-111,2,3,4,6,7,8-HpCDF 2.88e-10 1.73e-08 2.68e-101,2,3,4,7,8,9-HpCDF 2.31e-11 1.40e-09 1.94e-11OCDF 2.31e-11 1.40e-09 1.68e-11

Aluminum 4.12e-03 1.85e-01 3.29e-03Antimony 3.93e-06 1.35e-03 2.35e-05Arsenic 3.88e-06 8.56e-04 1.51e-05Barium 5.23e-05 1.30e-02 2.29e-04Beryllium 4.31e-07 4.17e-04 7.19e-06Cadmium 3.82e-05 1.56e-02 2.72e-04Chromium (total) 8.11e-05 8.86e-02 1.52e-03Chromium (hexavalent) 2.98e-06 5.44e-04 9.59e-06Cobalt 3.17e-06 1.28e-03 2.23e-05Copper 2.37e-05 2.57e-02 4.42e-04Lead 3.28e-04 3.32e-01 5.72e-03Manganese 1.22e-04 8.77e-02 1.52e-03Mercuric chloride (particle) 2.00e-04 4.08e-04 4.79e-06Mercuric chloride (vapor) 2.02e-04 3.17e-03 9.02e-05Mercury 2.03e-04 0.00e+00 0.00e+00Methyl mercury 0.00e+00 7.23e-05 1.92e-06Nickel 9.27e-06 3.44e-03 6.00e-05Selenium 1.90e-06 1.40e-04 2.49e-06Silver 5.95e-06 2.77e-04 4.93e-06Thallium 2.17e-05 9.61e-03 1.67e-04Vanadium 8.35e-06 8.52e-03 1.47e-04Zinc 4.72e-05 2.08e-02 3.62e-04A Obtained from the human health risk assessment, Appendix IV.B Non-cancer, tilled soil values obtained from the human health risk assessment, Appendix IV.

9–72

Table 9.11 Estimated exposure point concentrations in surface waterA

CompoundTilled Untilled

Standing(mg/L)

Flowing(mg/L)

Standing(mg/L)

Flowing(mg/L)

Acetone 1.90e-06 4.92e-06 1.95e-07 3.28e-07Acrylonitrile 1.58e-12 2.98e-12 1.58e-12 2.98e-12Benzene 7.97e-08 1.45e-07 4.21e-09 7.46e-09Benzo(a)anthracene 3.19e-11 2.92e-11 4.45e-10 5.11e-10Benzo(g,h,i)perylene 1.04e-12 1.04e-12 5.56e-12 6.08e-12Benzo(a)pyrene 1.11e-12 9.94e-13 1.05e-11 1.13e-11Benzo(k)fluoranthene 6.31e-12 6.11e-12 6.79e-11 9.00e-11Carbon Tetrachloride 8.43e-11 1.51e-10 4.28e-12 7.63e-12Chrysene 5.99e-11 5.41e-11 8.17e-10 9.42e-10Cresol, -m (methylphenol, 3-) 1.66e-06 2.04e-06 4.47e-06 5.55e-06Dibenzo(a,h)anthracene 2.40e-12 2.39e-12 1.63e-11 1.85e-11Iodomethane 4.21e-07 7.28e-07 2.24e-08 3.81e-08Methanol 2.62e-08 5.31e-08 8.16e-09 8.16e-09Phenanthrene 8.58e-10 1.35e-09 4.71e-11 7.41e-11Phenol 3.38e-06 3.91e-06 1.23e-05 1.45e-05Pyrene 5.54e-09 7.13e-09 4.75e-08 6.81e-08Ideno(1,2,3-cd)pyrene 3.23e-13 3.21e-13 1.90e-12 2.10e-12

Coplanar PCB TEQ 9.70e-18 1.43e-17 7.67e-17 1.16e-16Total PCB Cogener 7.95e-14 1.18e-13 6.28e-13 9.49e-13

2,3,7,8-TCDD 9.16e-14 9.15e-14 1.04e-12 1.66e-121,2,3,7,8-PCDD 4.01e-14 3.96e-14 4.26e-13 6.80e-131,2,3,4,7,8-HxCDD 4.34e-14 4.32e-14 4.12e-13 6.60e-131,2,3,6,7,8-HxCDD 6.77e-14 6.77e-14 6.10e-13 9.74e-131,2,3,7,8,9-HxCDD 5.94e-14 5.94e-14 5.20e-13 8.30e-131,2,3,4,6,7,8-HpCDD 4.74e-13 4.74e-13 4.17e-12 6.67e-12OCDD 1.19e-13 1.19e-13 1.01e-12 1.61e-122,3,7,8-TCDF 3.68e-13 3.65e-13 4.22e-12 6.74e-121,2,3,7,8-PCDF 1.04e-13 1.03e-13 1.16e-12 1.86e-122,3,4,7,8-PCDF 1.42e-13 1.40e-13 1.53e-12 2.46e-121,2,3,4,7,8-HxCDF 5.03e-14 5.03e-14 4.68e-13 7.49e-13

Table 9.11 Estimated exposure point concentrations in surface waterA


Standing(mg/L)

Flowing(mg/L)

Standing(mg/L)

Flowing(mg/L)

9–73

1,2,3,6,7,8-HxCDF 2.32e-14 2.31e-14 2.17e-13 3.47e-132,3,4,6,7,8-HxCDF 4.10e-15 4.09e-15 3.85e-14 6.16e-141,2,3,7,8,9-HxCDF 5.35e-15 5.33e-15 5.04e-14 8.07e-141,2,3,4,6,7,8-HpCDF 4.49e-14 4.49e-14 4.10e-13 6.56e-131,2,3,4,7,8,9-HpCDF 3.36e-15 3.36e-15 2.98e-14 4.76e-14OCDF 3.03e-15 3.03e-15 2.57e-14 4.10e-14

Aluminum 4.87e-04 4.87e-04 4.87e-04 4.87e-04Antimony 4.37e-07 4.37e-07 4.57e-07 4.57e-07Arsenic 4.51e-07 4.51e-07 4.54e-07 4.54e-07Barium 6.04e-06 6.04e-06 6.11e-06 6.11e-06Beryllium 1.22e-08 1.22e-08 4.18e-08 4.47e-08Cadmium 4.07e-06 4.07e-06 4.42e-06 4.42e-06Chromium (total) 4.28e-08 4.28e-08 3.78e-07 7.06e-07Chromium (hexavalent) 3.49e-07 3.49e-07 3.50e-07 3.50e-07Cobalt 3.39e-07 3.39e-07 3.67e-07 3.67e-07Copper 8.58e-08 8.58e-08 6.87e-07 1.12e-06Lead 6.21e-06 6.21e-06 2.83e-05 3.23e-05Manganese 8.67e-06 8.67e-06 1.37e-05 1.37e-05Mercuric chloride (particle) 3.06e-10 3.06e-10 2.66e-09 4.89e-09Mercuric chloride (vapor) 4.95e-09 4.79e-09 4.93e-08 9.10e-08Mercury 0.00e+00 0.00e+00 0.00e+00 0.00e+00Methyl mercury 6.10e-09 6.08e-09 5.96e-08 1.11e-07Nickel 1.01e-06 1.01e-06 1.07e-06 1.08e-06Selenium 2.24e-07 2.24e-07 2.24e-07 2.24e-07Silver 7.02e-07 7.02e-07 7.02e-07 7.02e-07Thallium 2.25e-06 2.25e-06 2.50e-06 2.50e-06Vanadium 1.45e-07 1.45e-07 6.97e-07 8.12e-07Zinc 4.90e-06 4.90e-06 5.45e-06 5.45e-06A Non-cancer values obtained from Appendix IV.

9–74

Table 9.12 Estimated exposure point concentrations in sediment bedA


Standing(mg/kg)

Flowing(mg/kg)

Standing(mg/kg)

Flowing(mg/kg)



2,3,7,8-TCDD 1.85e-09 1.85e-09 2.10e-08 3.36e-081,2,3,7,8-PCDD 8.10e-10 8.01e-10 8.62e-09 1.37e-081,2,3,4,7,8-HxCDD 1.06e-09 1.05e-09 1.00e-08 1.61e-081,2,3,6,7,8-HxCDD 1.59e-09 1.59e-09 1.43e-08 2.29e-081,2,3,7,8,9-HxCDD 1.40e-09 1.40e-09 1.22e-08 1.95e-081,2,3,4,6,7,8-HpCDD 1.17e-08 1.17e-08 1.03e-07 1.64e-07OCDD 2.88e-09 2.88e-09 2.44e-08 3.89e-082,3,7,8-TCDF 7.03e-09 6.97e-09 8.06e-08 1.29e-071,2,3,7,8-PCDF 2.23e-09 2.19e-09 2.47e-08 3.96e-082,3,4,7,8-PCDF 3.13e-09 3.09e-09 3.39e-08 5.44e-081,2,3,4,7,8-HxCDF 1.18e-09 1.18e-09 1.10e-08 1.76e-081,2,3,6,7,8-HxCDF 5.46e-10 5.43e-10 5.10e-09 8.16e-092,3,4,6,7,8-HxCDF 9.64e-11 9.61e-11 9.05e-10 1.45e-09

Table 9.12 Estimated exposure point concentrations in sediment bedA


Standing(mg/kg)

Flowing(mg/kg)

Standing(mg/kg)

Flowing(mg/kg)

9–75

1,2,3,7,8,9-HxCDF 1.26e-10 1.25e-10 1.19e-09 1.90e-091,2,3,4,6,7,8-HpCDF 1.10e-09 1.10e-09 1.00e-08 1.60e-081,2,3,4,7,8,9-HpCDF 8.23e-11 8.23e-11 7.29e-10 1.16e-09OCDF 7.50e-11 7.50e-11 6.37e-10 1.02e-09

Aluminum 2.68e-03 2.68e-03 2.68e-03 2.68e-03Antimony 1.96e-05 1.96e-05 2.05e-05 2.05e-05Arsenic 1.25e-05 1.25e-05 1.26e-05 1.26e-05Barium 1.90e-04 1.90e-04 1.93e-04 1.93e-04Beryllium 6.59e-06 6.59e-06 2.26e-05 2.42e-05Cadmium 2.28e-04 2.28e-04 2.47e-04 2.48e-04Chromium (total) 1.92e-03 1.92e-03 1.69e-02 3.16e-02Chromium (hexavalent) 7.95e-06 7.95e-06 7.97e-06 7.97e-06Cobalt 1.86e-05 1.86e-05 2.01e-05 2.02e-05Copper 5.13e-04 5.13e-04 4.10e-03 6.70e-03Lead 5.48e-03 5.48e-03 2.50e-02 2.86e-02Manganese 1.30e-03 1.30e-03 2.04e-03 2.06e-03Mercuric chloride (particle) 4.86e-06 4.86e-06 4.23e-05 7.76e-05Mercuric chloride (vapor) 7.85e-05 7.60e-05 7.83e-04 1.44e-03Mercury 0.00e+00 0.00e+00 0.00e+00 0.00e+00Methyl mercury 5.80e-06 5.79e-06 5.68e-05 1.06e-04Nickel 5.01e-05 5.01e-05 5.32e-05 5.32e-05Selenium 2.04e-06 2.04e-06 2.04e-06 2.04e-06Silver 4.01e-06 4.01e-06 4.01e-06 4.01e-06Thallium 1.40e-04 1.40e-04 1.56e-04 1.56e-04Vanadium 1.42e-04 1.42e-04 6.82e-04 7.95e-04Zinc 3.03e-04 3.03e-04 3.37e-04 3.38e-04A Non-cancer values obtained from Appendix IV.

9–76

Table 9.13 Estimated exposure point concentrations in fish tissueA


Flowing(mg/kg)

Standing(mg/kg)

Flowing(mg/kg)

Standing(mg/kg)



2,3,7,8-TCDD 2.91e-10 2.92e-10 5.29e-09 5.23e-091,2,3,7,8-PCDD 1.26e-10 1.28e-10 2.16e-09 2.16e-091,2,3,4,7,8-HxCDD 7.38e-11 7.41e-11 1.13e-09 1.13e-091,2,3,6,7,8-HxCDD 1.11e-10 1.11e-10 1.60e-09 1.60e-091,2,3,7,8,9-HxCDD 9.78e-11 9.77e-11 1.37e-09 1.36e-091,2,3,4,6,7,8-HpCDD 1.02e-10 1.02e-10 1.44e-09 1.44e-09OCDD 5.03e-13 5.04e-13 6.81e-12 6.81e-122,3,7,8-TCDF 1.10e-09 1.11e-09 2.03e-08 2.00e-081,2,3,7,8-PCDF 3.46e-10 3.51e-10 6.24e-09 6.21e-092,3,4,7,8-PCDF 4.87e-10 4.93e-10 8.57e-09 8.54e-091,2,3,4,7,8-HxCDF 8.28e-11 8.29e-11 1.23e-09 1.23e-091,2,3,6,7,8-HxCDF 3.80e-11 3.82e-11 5.71e-10 5.70e-102,3,4,6,7,8-HxCDF 6.73e-12 6.75e-12 1.01e-10 1.01e-10

Table 9.13 Estimated exposure point concentrations in fish tissueA


Flowing(mg/kg)

Standing(mg/kg)

Flowing(mg/kg)

Standing(mg/kg)

9–77

1,2,3,7,8,9-HxCDF 8.77e-12 8.80e-12 1.33e-10 1.33e-101,2,3,4,6,7,8-HpCDF 9.62e-12 9.62e-12 1.40e-10 1.40e-101,2,3,4,7,8,9-HpCDF 7.20e-13 7.20e-13 1.02e-11 1.02e-11OCDF 1.31e-14 1.31e-14 1.78e-13 1.78e-13

Aluminum 0.00e+00 0.00e+00 0.00e+00 0.00e+00Antimony 1.75e-05 1.75e-05 1.83e-05 1.83e-05Arsenic 9.01e-06 9.01e-06 9.07e-06 9.07e-06Barium 3.82e-03 3.82e-03 3.87e-03 3.87e-03Beryllium 7.46e-07 7.46e-07 2.74e-06 2.74e-06Cadmium 1.02e-03 1.02e-03 1.10e-03 1.10e-03Chromium (total) 2.96e-07 2.96e-07 4.88e-06 4.88e-06Chromium (hexavalent) 1.05e-06 1.05e-06 1.05e-06 1.05e-06Cobalt 0.00e+00 0.00e+00 0.00e+00 0.00e+00Copper 0.00e+00 0.00e+00 0.00e+00 0.00e+00Lead 4.87e-05 4.87e-05 2.54e-04 2.22e-04Manganese 0.00e+00 0.00e+00 0.00e+00 0.00e+00Mercuric chloride (particle) 0.00e+00 0.00e+00 0.00e+00 0.00e+00Mercuric chloride (vapor) 0.00e+00 0.00e+00 0.00e+00 0.00e+00Mercury 0.00e+00 0.00e+00 0.00e+00 0.00e+00Methyl mercury 5.41e-03 5.50e-03 1.00e-01 5.41e-02Nickel 7.89e-05 7.89e-05 8.38e-05 8.38e-05Selenium 2.89e-05 2.89e-05 2.89e-05 2.89e-05Silver 1.43e-04 1.43e-04 1.43e-04 1.43e-04Thallium 2.24e-06 2.24e-06 2.50e-06 2.50e-06Vanadium 0.00e+00 0.00e+00 0.00e+00 0.00e+00Zinc 1.01e-02 1.01e-02 1.12e-02 1.12e-02A Non-cancer values obtained from Appendix IV.

9–78

Table 9.14 Estimated exposure point concentrations in plantsA

Compound Ag(mg/kg)

Forage(mg/kg)

Silage(mg/kg)

Rootveg(mg/kg)

Grain(mg/kg)

Acetone 6.64e-03 6.64e-03 6.64e-03 8.68e-04 6.64e-03Acrylonitrile 7.11e-13 6.97e-11 3.49e-11 1.54e-15 1.42e-14Benzene 1.98e-05 1.98e-05 1.98e-05 2.22e-06 1.98e-05Benzo(a)anthracene 8.06e-07 1.32e-06 5.50e-07 1.12e-06 1.07e-08Benzo(g,h,i)perylene 1.82e-07 1.39e-06 4.23e-07 2.35e-08 4.49e-10Benzo(a)pyrene 4.02e-07 7.97e-07 3.10e-07 1.02e-07 6.63e-10Benzo(k)fluoranthene 1.71e-06 3.16e-06 1.26e-06 1.33e-06 7.96e-09Carbon Tetrachloride 5.89e-09 5.89e-09 5.89e-09 1.06e-09 5.89e-09Chrysene 3.65e-06 5.27e-06 2.28e-06 2.57e-06 2.34e-08Cresol, -m (methylphenol, 3-) 5.92e-04 5.97e-04 5.94e-04 5.98e-05 5.92e-04Dibenzo(a,h)anthracene 1.17e-05 1.36e-05 6.37e-06 5.91e-07 2.65e-09Iodomethane 2.25e-05 2.25e-05 2.25e-05 2.66e-07 2.25e-05Methanol 2.99e-04 2.99e-04 2.99e-04 4.83e-05 2.99e-04Phenanthrene 3.77e-07 3.77e-07 3.77e-07 1.48e-05 3.77e-07Phenol 1.35e-03 1.35e-03 1.35e-03 1.17e-04 1.35e-03Pyrene 3.59e-06 4.18e-06 2.84e-06 8.28e-05 1.77e-06Ideno(1,2,3-cd)pyrene 7.15e-06 7.48e-06 3.67e-06 6.58e-08 2.15e-10

Coplanar PCB TEQ 2.73e-14 2.73e-14 1.40e-14 9.41e-13 6.61e-16Total PCB Cogener 2.24e-10 2.24e-10 1.14e-10 7.72e-09 5.42e-12

2,3,7,8-TCDD 4.96e-09 1.10e-08 4.16e-09 9.62e-09 4.83e-111,2,3,7,8-PCDD 5.76e-09 1.24e-08 4.72e-09 7.38e-09 3.71e-111,2,3,4,7,8-HxCDD 8.24e-09 2.57e-08 8.91e-09 9.03e-09 1.81e-111,2,3,6,7,8-HxCDD 8.58e-09 3.97e-08 1.29e-08 2.09e-08 6.46e-111,2,3,7,8,9-HxCDD 5.68e-09 3.53e-08 1.10e-08 1.96e-08 6.08e-111,2,3,4,6,7,8-HpCDD 6.59e-08 3.11e-07 1.00e-07 9.89e-08 1.42e-10OCDD 9.58e-09 7.57e-08 2.30e-08 3.63e-08 8.56e-112,3,7,8-TCDF 1.35e-08 2.55e-08 1.01e-08 2.93e-08 1.61e-101,2,3,7,8-PCDF 8.07e-09 1.90e-08 7.07e-09 1.33e-08 5.94e-112,3,4,7,8-PCDF 1.09e-08 3.28e-08 1.15e-08 2.20e-08 8.80e-111,2,3,4,7,8-HxCDF 4.03e-09 2.48e-08 7.72e-09 1.41e-08 4.38e-111,2,3,6,7,8-HxCDF 1.88e-09 1.13e-08 3.52e-09 6.40e-09 1.98e-112,3,4,6,7,8-HxCDF 3.37e-10 1.97e-09 6.18e-10 1.12e-09 3.46e-121,2,3,7,8,9-HxCDF 4.46e-10 2.54e-09 8.00e-10 1.44e-09 4.46e-12

Table 9.14 Estimated exposure point concentrations in plantsA

Compound Ag(mg/kg)

Forage(mg/kg)

Silage(mg/kg)

Rootveg(mg/kg)

Grain(mg/kg)

9–79

1,2,3,4,6,7,8-HpCDF 9.09e-09 2.99e-08 1.03e-08 9.84e-09 1.77e-111,2,3,4,7,8,9-HpCDF 4.94e-10 2.19e-09 7.12e-10 7.91e-10 1.42e-12OCDF 2.44e-10 1.97e-09 5.95e-10 5.05e-10 4.57e-13

Aluminum 8.44e-02 9.41e-01 2.77e-01 1.20e-04 1.20e-04Antimony 1.23e-04 1.17e-03 5.33e-04 4.04e-05 2.69e-04Arsenic 8.47e-05 9.16e-04 2.91e-04 6.84e-06 3.42e-06Barium 1.49e-03 1.39e-02 5.47e-03 1.96e-04 1.96e-04Beryllium 9.89e-06 1.03e-04 3.32e-05 6.25e-07 6.25e-07Cadmium 2.73e-03 1.44e-02 8.25e-03 1.00e-03 9.68e-04Chromium (total) 2.09e-03 1.92e-02 6.11e-03 3.99e-04 3.99e-04Chromium (hexavalent) 6.36e-05 6.85e-04 2.05e-04 2.45e-06 2.45e-06Cobalt 7.37e-05 7.32e-04 2.22e-04 8.94e-06 8.94e-06Copper 6.90e-03 1.18e-02 8.01e-03 6.42e-03 6.42e-03Lead 1.12e-02 8.97e-02 3.70e-02 2.99e-03 2.99e-03Manganese 2.44e-02 4.98e-02 3.01e-02 4.38e-03 2.19e-02Mercuric chloride (particle) 1.16e-05 6.34e-05 1.87e-05 1.47e-07 0.00e+00Mercuric chloride (vapor) 4.59e-05 2.22e-06 1.11e-06 1.14e-06 0.00e+00Mercury 0.00e+00 0.00e+00 0.00e+00 0.00e+00 0.00e+00Methyl mercury 3.74e-06 1.85e-05 5.58e-06 7.16e-06 0.00e+00Nickel 2.21e-04 2.22e-03 7.33e-04 2.75e-05 2.06e-05Selenium 4.16e-05 4.37e-04 1.30e-04 3.09e-06 2.81e-07Silver 1.60e-04 1.47e-03 5.11e-04 2.77e-05 2.77e-05Thallium 4.51e-04 4.98e-03 1.49e-03 3.84e-06 3.84e-06Vanadium 1.96e-04 1.93e-03 5.87e-04 2.56e-05 2.56e-05Zinc 2.46e-03 1.60e-02 8.37e-03 9.15e-04 1.12e-03A Non-cancer values obtained from Appendix IV.

9–80

Table 9.15 Bioaccumulation factors for selected animalsCompound EarthwormA Mammals BirdsAcetone 1.22e+00 1.00e+00 1.00e+00Acrylonitrile 1.33e+00 1.00e+00 1.00e+00Benzene 1.89e+00 1.00e+00 1.00e+00Benzo(a)anthracene 3.62e+00 1.00e+00 1.00e+00Benzo(g,h,i)perylene 4.82e+00 1.00e+00 1.00e+00Benzo(a)pyrene 3.94e+00 1.00e+00 1.00e+00Benzo(k)fluoranthene 3.98e+00 1.00e+00 1.00e+00Carbon Tetrachloride 2.10e+00 1.00e+00 1.00e+00Chrysene 3.66e+00 1.00e+00 1.00e+00Cresol, -m (methylphenol, 3-) 1.83e+00 1.00e+00 1.00e+00Dibenzo(a,h)anthracene 4.25e+00 1.00e+00 1.00e+00Iodomethane 1.74e+00 1.00e+00 1.00e+00Methanol 1.12e+00 1.00e+00 1.00e+00Phenanthrene 2.94e+00 1.00e+00 1.00e+00Phenol 1.67e+00 1.00e+00 1.00e+00Pyrene 3.20e+00 1.00e+00 1.00e+00Ideno(1,2,3-cd)pyrene 4.55e+00 1.00e+00 1.00e+00

Coplanar PCB TEQ 9.10e+00B 1.00e+00 1.00e+00Total PCB Cogener 3.99e+00 1.00e+00 1.00e+00

2,3,7,8-TCDD 9.10e+00B 1.00e+00 1.51e+011,2,3,7,8-PCDD 9.10e+00B 1.00e+00 1.14e+011,2,3,4,7,8-HxCDD 9.10e+00B 1.00e+00 8.32e+001,2,3,6,7,8-HxCDD 9.10e+00B 1.00e+00 5.32e+001,2,3,7,8,9-HxCDD 9.10e+00B 1.00e+00 2.86e+001,2,3,4,6,7,8-HpCDD 9.10e+00B 1.00e+00 1.77e+00OCDD 9.10e+00B 1.00e+00 1.00e+002,3,7,8-TCDF 9.10e+00B 1.00e+00 1.16e+011,2,3,7,8-PCDF 9.10e+00B 1.00e+00 1.49e+012,3,4,7,8-PCDF 9.10e+00B 1.00e+00 1.49e+011,2,3,4,7,8-HxCDF 9.10e+00B 1.00e+00 7.18e+001,2,3,6,7,8-HxCDF 9.10e+00B 1.00e+00 7.36e+002,3,4,6,7,8-HxCDF 9.10e+00B 1.00e+00 3.59e+001,2,3,7,8,9-HxCDF 9.10e+00B 1.00e+00 5.75e+00

Table 9.15 Bioaccumulation factors for selected animalsCompound EarthwormA Mammals Birds

9–81

1,2,3,4,6,7,8-HpCDF 9.10e+00B 1.00e+00 1.45e+001,2,3,4,7,8,9-HpCDF 9.10e+00B 1.00e+00 2.18e+00OCDF 9.10e+00B 1.00e+00 1.00e+00

Aluminum 1.00e+00 1.00e+00 1.00e+00Antimony 1.00e+00 1.00e+00 1.00e+00Arsenic 1.00e+00 1.00e+00 1.00e+00Barium 1.00e+00 1.00e+00 1.00e+00Beryllium 1.00e+00 1.00e+00 1.00e+00Cadmium 2.30e+00B 1.00e+00 1.00e+00Chromium (total) 1.40e+00C 1.00e+00 1.00e+00Chromium (hexavalent) 1.40e+00C 1.00e+00 1.00e+00Cobalt 1.00e+00 1.00e+00 1.00e+00Copper 1.55e+00C 1.00e+00 1.00e+00Lead 3.50e-02B 1.00e+00 1.00e+00Manganese 4.10e-01C 1.00e+00 1.00e+00Mercuric chloride (particle) 6.40e-01C 1.00e+00 1.00e+00Mercuric chloride (vapor) 6.40e-01C 1.00e+00 1.00e+00Mercury 2.70e+01B NA NAMethyl mercury 1.00e+00 1.00e+00 1.00e+00Nickel 3.20e-02B 1.00e+00 1.00e+00Selenium 2.20e+02C 1.00e+00 1.13e+00Silver 1.00e+00 1.00e+00 1.00e+00Thallium 1.00e+00 1.00e+00 1.00e+00Vanadium 1.00e+00 1.00e+00 1.00e+00Zinc 2.00e+01C 1.00e+00 1.00e+00NA - Not applicable. All mercury exposure for birds and mammals is assumed to be in the forms or mercuricchloride and methyl mercury, rather than elemental mercury.A Unless otherwise noted, organic BAF values were calculated using Equation 9.8, and inorganic BAF valueswere assumed to be 1 (Horizon Environmental, 1998).B Source: RTI, 1999.C Source: ECOTOX, 2001

9–82

Table 9.16 Estimated exposure concentrations in animal tissue

Compound Earthworm(mg/kg)

Insect(mg/kg)

DeerMouse(mg/kg)

MeadowVole

(mg/kg)

NorthernBobwhite(mg/kg)

AmericanWoodcock

(mg/kg)Acetone 3.90e-05 6.64e-03 2.58e-05 6.81e-05 1.04e-04 2.61e-04Acrylonitrile 1.71e-16 6.97e-11 1.75e-13 6.13e-13 1.95e-13 1.76e-12Benzene 4.15e-06 1.98e-05 7.74e-08 2.05e-07 3.22e-07 1.23e-06Benzo(a)anthracene 4.81e-07 1.32e-06 3.85e-09 1.31e-08 7.01e-09 8.18e-08Benzo(g,h,i)perylene 2.11e-07 1.39e-06 3.61e-09 1.23e-08 4.66e-09 5.56e-08Benzo(a)pyrene 5.88e-08 7.97e-07 2.24e-09 7.14e-09 3.53e-09 2.60e-08Benzo(k)fluoranthene 7.85e-07 3.16e-06 9.02e-09 2.96e-08 1.52e-08 1.58e-07Carbon Tetrachloride 2.97e-09 5.89e-09 2.33e-11 6.24e-11 1.00e-10 5.56e-10Chrysene 1.15e-06 5.27e-06 1.55e-08 4.97e-08 2.78e-08 2.48e-07Cresol, -m (methylphenol, 3-) 9.45e-05 5.97e-04 2.32e-06 6.15e-06 9.55e-06 3.37e-05Dibenzo(a,h)anthracene 4.44e-07 1.36e-05 4.11e-08 1.21e-07 7.40e-08 3.88e-07Iodomethane 2.39e-06 2.25e-05 8.76e-08 2.29e-07 3.59e-07 1.14e-06Methanol 8.38e-07 2.99e-04 1.16e-06 3.07e-06 4.67e-06 1.16e-05Phenanthrene 3.05e-06 4.15e-06 8.92e-09 2.30e-08 1.97e-08 4.27e-07Phenol 1.04e-04 1.35e-03 5.26e-06 1.39e-05 2.14e-05 6.42e-05Pyrene 2.84e-05 3.55e-05 7.60e-08 1.53e-07 1.56e-07 3.82e-06Ideno(1,2,3-cd)pyrene 6.26e-08 7.48e-06 2.30e-08 6.59e-08 4.27e-08 1.95e-07

Coplanar PCB TEQ 1.50e-13 1.50e-13 3.23e-16 1.37e-15 5.16e-16 1.76e-14Total PCB Cogener 5.41e-10 5.42e-10 1.34e-12 1.11e-11 2.81e-12 6.73e-11

2,3,7,8-TCDD 1.96e-08 1.96e-08 4.74e-11 1.13e-10 1.15e-09 3.45e-081,2,3,7,8-PCDD 1.50e-08 1.50e-08 4.00e-11 1.20e-10 7.67e-10 2.00e-081,2,3,4,7,8-HxCDD 3.38e-08 3.38e-08 8.58e-11 2.43e-10 1.12e-09 3.29e-081,2,3,6,7,8-HxCDD 5.88e-08 5.88e-08 1.43e-10 3.85e-10 1.14e-09 3.65e-081,2,3,7,8,9-HxCDD 5.53e-08 5.53e-08 1.32e-10 3.45e-10 5.50e-10 1.85e-081,2,3,4,6,7,8-HpCDD 4.59e-07 4.59e-07 1.12e-09 2.95e-09 2.94e-09 9.50e-08OCDD 1.22e-07 1.22e-07 2.88e-10 7.35e-10 4.14e-10 1.43e-082,3,7,8-TCDF 5.61e-08 5.61e-08 1.32e-10 2.73e-10 2.47e-09 7.61e-081,2,3,7,8-PCDF 2.93e-08 2.93e-08 7.30e-11 1.89e-10 1.76e-09 5.10e-082,3,4,7,8-PCDF 5.18e-08 5.18e-08 1.26e-10 3.25e-10 2.94e-09 9.02e-081,2,3,4,7,8-HxCDF 3.98e-08 3.98e-08 9.44e-11 2.43e-10 9.90e-10 3.34e-081,2,3,6,7,8-HxCDF 1.80e-08 1.80e-08 4.28e-11 1.10e-10 4.61e-10 1.55e-082,3,4,6,7,8-HxCDF 3.15e-09 3.15e-09 7.48e-12 1.93e-11 3.94e-11 1.32e-09

Table 9.16 Estimated exposure concentrations in animal tissue

Compound Earthworm(mg/kg)

Insect(mg/kg)

DeerMouse(mg/kg)

MeadowVole

(mg/kg)

NorthernBobwhite(mg/kg)

AmericanWoodcock

(mg/kg)

9–83

1,2,3,7,8,9-HxCDF 4.06e-09 4.06e-09 9.65e-12 2.49e-11 8.14e-11 2.73e-091,2,3,4,6,7,8-HpCDF 3.95e-08 3.95e-08 9.98e-11 2.82e-10 2.26e-10 6.69e-091,2,3,4,7,8,9-HpCDF 3.17e-09 3.17e-09 7.75e-12 2.08e-11 2.54e-11 8.09e-10OCDF 3.19e-09 3.19e-09 7.50e-12 1.86e-11 1.07e-11 3.73e-10

Aluminum 4.63e-02 9.41e-01 2.42e-03 8.33e-03 3.13e-03 3.02e-02Antimony 3.36e-04 1.35e-03 3.65e-06 1.11e-05 8.57e-06 8.41e-05Arsenic 2.14e-04 9.16e-04 2.42e-06 8.32e-06 4.08e-06 5.28e-05Barium 3.26e-03 1.39e-02 3.69e-05 1.27e-04 6.40e-05 8.05e-04Beryllium 1.04e-04 4.17e-04 8.91e-07 1.11e-06 1.58e-06 2.50e-05Cadmium 8.98e-03 1.56e-02 4.20e-05 1.34e-04 8.30e-05 1.38e-03Chromium (total) 3.10e-02 8.86e-02 1.88e-04 2.13e-04 3.36e-04 6.07e-03Chromium (hexavalent) 1.90e-04 6.85e-04 1.80e-06 6.19e-06 2.91e-06 4.08e-05Cobalt 3.19e-04 1.28e-03 3.02e-06 6.97e-06 5.33e-06 7.65e-05Copper 9.95e-03 2.57e-02 6.69e-05 1.31e-04 1.83e-04 1.92e-03Lead 2.91e-03 3.32e-01 7.18e-04 9.56e-04 1.30e-03 1.30e-02Manganese 8.99e-03 8.77e-02 2.35e-04 5.07e-04 6.33e-04 4.43e-03Mercuric chloride (particle) 6.53e-05 4.08e-04 8.50e-07 7.65e-07 1.52e-06 2.13e-05Mercuric chloride (vapor) 5.07e-04 3.17e-03 6.27e-06 1.75e-06 1.13e-05 1.65e-04Mercury 0.00e+00 0.00e+00 0.00e+00 0.00e+00 0.00e+00 0.00e+00Methyl mercury 1.81e-05 7.23e-05 1.56e-07 2.06e-07 2.80e-07 4.33e-06Nickel 2.75e-05 3.44e-03 8.28e-06 2.09e-05 1.46e-05 1.35e-04Selenium 7.71e-03 7.71e-03 1.49e-05 5.69e-06 1.86e-05 9.71e-04Silver 6.93e-05 1.47e-03 3.82e-06 1.31e-05 5.22e-06 4.70e-05Thallium 2.40e-03 9.61e-03 2.23e-05 4.78e-05 3.88e-05 5.75e-04Vanadium 2.13e-03 8.52e-03 1.81e-05 2.12e-05 3.23e-05 5.10e-04Zinc 1.04e-01 1.04e-01 2.10e-04 1.71e-04 2.74e-04 1.18e-02

9–84

Table 9.17 Inhalation toxicity data

Compound NOAELA

(:g/m3)LOAELB

(:g/m3) Species Source

Acetone NA NA - -Acrylonitrile NA 7.70e+03 Rat IRIS, 2001BenzeneE NA 2.49e+03 Mouse ATSDR, 1997Benzo(a)anthracene NA NA - -Benzo(g,h,i)perylene NA NA - -Benzo(a)pyrene NA NA - -Benzo(k)fluoranthene NA NA - -Carbon Tetrachloride NA NA - -Chrysene NA NA - -Cresol, m- (methylphenol, 3-) NA NA - -Dibenzo(a,h)anthracene NA NA - -Iodomethane NA 2.08e+03 - surrogateC

Methanol NA NA - -Phenanthrene NA NA - -PhenolE 1.92e+04 NR Rat ATSDR, 1998Pyrene NA NA - -Ideno(1,2,3-cd)pyrene NA NA - -

Coplanar PCB TEQ NA NA - -Total PCB Cogener NA NA - -

2,3,7,8-TCDD NA NA - -1,2,3,7,8-PCDD NA NA - -1,2,3,4,7,8-HxCDD NA NA - -1,2,3,6,7,8-HxCDD NA NA - -1,2,3,7,8,9-HxCDD NA NA - -1,2,3,4,6,7,8-HpCDD NA NA - -OCDD NA NA - -2,3,7,8-TCDF NA NA - -1,2,3,7,8-PCDF NA NA - -2,3,4,7,8-PCDF NA NA - -1,2,3,4,7,8-HxCDF NA NA - -1,2,3,6,7,8-HxCDF NA NA - -2,3,4,6,7,8-HxCDF NA NA - -1,2,3,7,8,9-HxCDF NA NA - -

Table 9.17 Inhalation toxicity data

Compound NOAELA

(:g/m3)LOAELB

(:g/m3) Species Source

9–85

1,2,3,4,6,7,8-HpCDF NA NA - -1,2,3,4,7,8,9-HpCDF NA NA - -OCDF NA NA - -

Aluminum NA NA - -Antimony NA 1.60e+03 Rat ATSDR, 1992Arsenic NA 1.00e+01 Human ATSDR, 1998bBarium 1.15e+03 NR Rat IRIS, 2001Beryllium 2.00e-02 NR Human IRIS, 2001Cadmium NA NA - -Chromium (total) 1.00e+00 NR Human ATSDR, 1998cChromium (hexavalent)D 1.00e+00 NR Human ATSDR, 1998cCobaltE NA 1.00e+02 Pig ATSDR, 1992bCopperE 6.00e+02 NR Rabbit ATSDR,1990Lead NA NA - -Manganese 5.00e+01 NR Human IRIS, 2001Mercuric chloride (particle) NA NA - -Mercuric chloride (vapor) NA NA - -Mercury 9.00e+00 NR Human IRIS, 2001Methyl mercury NA NA - -Nickel 3.00e+01 NR Rat ATSDR, 1997bSeleniumF NA 1.00e+03 Guinea Pig ATSDR, 1996Silver NA NA - -Thallium NA NA - -Vanadium NA 8.00e+02 Rabbit ATSDR, 1992cZincF 3.60e+00 NR Human ATSDR, 1994NA- Not available. NR - LOAEL not required as NOAEL is available.A No Observed Adverse Effects Level for inhalation toxicity.B Lowest Observed Adverse Effects Level for inhalation toxicity.C Bromomethane data was used as a surrogate value for iodomethane.D Uses same value as total chromium.E Sub-chronic value.F Acute value.

9–86

Table 9.18 Soil background and toxicity data

CompoundSoil

Background LevelsA

(mg/kg)

Soil CriteriaB

(mg/kg)

Acetone NA NAAcrylonitrile NA NABenzene NA NABenzo(a)anthracene NA NABenzo(g,h,i)perylene NA NABenzo(a)pyrene NA NABenzo(k)fluoranthene NA NACarbon Tetrachloride NA NAChrysene NA NACresol, m- (methylphenol, 3-) NA NADibenzo(a,h)anthracene NA NAIodomethane NA NAMethanol NA NAPhenanthrene NA NAPhenol NA NAPyrene NA NAIdeno(1,2,3-cd)pyrene NA NA

Coplanar PCB TEQC NA 2.60e-07Total PCB Cogener NA NA

2,3,7,8-TCDD NA 2.60e-071,2,3,7,8-PCDDC NA 2.60e-071,2,3,4,7,8-HxCDDC NA 5.20e-061,2,3,6,7,8-HxCDDC NA 2.60e-051,2,3,7,8,9-HxCDDC NA 2.60e-061,2,3,4,6,7,8-HpCDDC NA 2.60e-04OCDDC NA 2.60e-032,3,7,8-TCDFC NA 2.60e-071,2,3,7,8-PCDFC NA 2.60e-062,3,4,7,8-PCDFC NA 2.60e-071,2,3,4,7,8-HxCDFC NA 5.20e-061,2,3,6,7,8-HxCDFC NA 2.60e-062,3,4,6,7,8-HxCDFC NA 2.60e-06

Table 9.18 Soil background and toxicity data

CompoundSoil

Background LevelsA

(mg/kg)

Soil CriteriaB

(mg/kg)

9–87

1,2,3,7,8,9-HxCDFC NA 2.60e-061,2,3,4,6,7,8-HpCDFC NA 2.60e-051,2,3,4,7,8,9-HpCDFC NA 2.60e-05OCDFC NA 2.60e-04

Aluminum 7.00e+04 NAAntimony NA NAArsenic 8.00e+00 1.00e+01Barium 7.00e+02 5.00e+02Beryllium NA NACadmium NA 1.00e+00Chromium (total) 5.00e+01 1.00e+00Chromium (hexavalent) NA 1.00e+00Cobalt 7.00e+00 NACopper 7.00e+01 2.10e+01Lead 1.50e+01 2.80e+01Manganese 5.00e+02 5.00e+02Mercuric chloride (particle) NA 1.00e-01Mercuric chloride (vapor) NA 1.00e-01Mercury 4.00e-02 1.00e-01Methyl mercury NA 1.00e-01Nickel 1.00e+01 3.00e+01Selenium 4.00e-01 1.00e+00Silver NA NAThallium NA NAVanadium 7.00e+01 NAZinc 4.50e+05 NANA - Not available.A Data for Monroe County, Indiana. Source: Boerngen and Shacklette, 1981.B Source: RTI, 1999.C Calculated from the criteria for 2,3,7,8-TCDD and the TEF values given in Table 9.3.

9–88

Table 9.19 Surface water toxicity data

Compound

AWQC(CCC)A

(:g/L)

ChronicAquatic

LifeCriteriaB

(:g/L)

LC50(:g/L) Species Source

Acetone NA 1.70e+03 NA - -Acrylonitrile NA 6.30e+01 NA - -Benzene NA 9.80e+01 NA - -Benzo(a)anthracene NA 2.30e-01 1.00e+01 water flea ECOTOX, 2001Benzo(g,h,i)perylene NA NA 5.00e+00 - surrogateC

Benzo(a)pyrene NA 1.10e-01 5.00e+00 water flea ECOTOX, 2001Benzo(k)fluoranthene NA NA 5.00e+00 - surrogateC

Carbon Tetrachloride NA 4.00e+01 NA - -

Chrysene NA NA 1.00e+03 polycheateworm ECOTOX, 2001

Cresol, m- (methylphenol, 3-) NA 4.80e+02 7.00e+03 gammarusfasciatus HSDB, 2001

Dibenzo(a,h)anthracene NA NA 1.00e+03 neanthesarenaceodentata HSDB, 2001

Iodomethane NA NA 4.51e+03 - surrogateD

Methanol NA 3.00e+03 3.70e+04 mussel ECOTOX, 2001Phenanthrene NA 9.30e-01 NA - -Phenol NA NA 3.60e+04 water flea ECOTOX, 2001Pyrene NA NA 5.00e+00 - surrogateC

Ideno(1,2,3-cd)pyrene NA NA 5.00e+00 - surrogateC

Coplanar PCB TEQ NA NA 5.70e-03 medaka,high-eyes ECOTOX, 2001

Total PCB Cogener 1.40e-02 NA NA - -

2,3,7,8-TCDD NA NA 5.70e-03 medaka,high-eyes ECOTOX, 2001

1,2,3,7,8-PCDD NA NA 2.30e-02 medaka,high-eyes ECOTOX, 2001

1,2,3,4,7,8-HxCDD NA NA 7.18e-01 medaka,high-eyes ECOTOX, 2001

1,2,3,6,7,8-HxCDD NA NA 5.70e-02 - calculatedE

1,2,3,7,8,9-HxCDD NA NA 5.70e-02 - calculatedE

1,2,3,4,6,7,8-HpCDD NA NA 5.70e-01 - calculatedE


Compound

AWQC(CCC)A

(:g/L)

ChronicAquatic

LifeCriteriaB

(:g/L)


9–89

OCDD NA NA 5.70e+01 - calculatedE

2,3,7,8-TCDF NA NA 5.70e-03 - calculatedE

1,2,3,7,8-PCDF NA NA 5.70e-02 - calculatedE

2,3,4,7,8-PCDF NA NA 5.70e-03 - calculatedE

1,2,3,4,7,8-HxCDF NA NA 5.70e-02 - calculatedE




1,2,3,4,6,7,8-HpCDF NA NA 5.70e-01 - calculatedE

1,2,3,4,7,8,9-HpCDF NA NA 5.70e-01 - calculatedE

OCDF NA NA 5.70e+01 - calculatedE

Aluminum 8.70e+01 NA NA - -

Antimony NA NA 3.00e+02 toad ECOTOX, 2001

Arsenic 1.50e+02 NA NA - -

Barium NA 1.40e+02 NA - -

BerylliumG NA 5.10e+00 NA - -

Cadmium 2.20e+00 NA NA - -

Chromium (total) 7.40e+01 NA NA - -

Chromium (hexavalent) 1.10e+01 NA NA - -

Cobalt NA 4.30e+01 NA - -

Copper 9.00e+00 NA NA - -

Lead 2.50e+00 NA NA - -

Manganese NA 9.00e+01 NA - -

Mercuric chloride (particle) 7.70e-01 NA NA - -

Mercuric chloride (vapor) 7.70e-01 NA NA - -

Mercury 7.70e-01 NA NA - -

Methyl mercury 7.70e-01 NA NA - -

Nickel 5.20e+01 NA NA - -

Selenium 5.00e+00 NA NA - -

Silver 3.40e+00 NA NA - -

Thallium NA NA 1.70e+02 rainbow trout ECOTOX, 2001

Vanadium NA 1.20e+01 NA - -

ZincF 1.20e+02 NA NA - -


Compound

AWQC(CCC)A

(:g/L)

ChronicAquatic

LifeCriteriaB

(:g/L)


9–90

NA - Not available or not applicableA Ambient Water Quality Criteria - Criterion Continuous Concentration in fresh water. Source: Federal Register, 1998.B Calculated using Tier II methodology from the Great Lakes Basin methodologies. Source: IDEM, 2000.C The LC50 value for benzo(a)pyrene (for a water flea (ECOTOX, 2001)) was used as a surrogate LC50 value for PAHs withno available LC50 values. D The LC50 value for bromomethane was used as the LC50 value of iodomethane.E LC50 values for dioxin congeners were calculated from the LC50 value of 2,3,7,8-TCDD and the TEF values given in Table9.3. F Value for Zinc is the Criterion Maximum Concentration for Zinc.G Beryllium value from ECO Update (U.S. EPA, 1996.)

9–91

Table 9.20 Sediment toxicity data

CompoundSQCA

(mg/kg-oc)

Tier IIWater CriteriaB

(:g/L)

SQBC

(mg/kg)LELD

(mg/kg)ER-LE

(mg/kg)

Acetone NA 1.70e+03 NA NA NAAcrylonitrile NA 6.30e+01 NA NA NABenzene NA 9.80e+01 2.43e-01 NA NABenzo(a)anthracene NA 2.50e-02 NA 3.20e-01 2.30e-01Benzo(g,h,i)perylene NA NA NA 1.70e-01 NABenzo(a)pyrene NA 1.30e-02 NA 3.70e-01 4.00e-01Benzo(k)fluoranthene NA NA NA 2.40e-01 NACarbon Tetrachloride NA 4.00e+01 2.43e-01 NA NAChrysene NA NA NA 3.40e-01 4.00e-01Cresol, m- (methylphenol, 3-) NA NA NA NA NADibenzo(a,h)anthracene NA NA NA 6.00e-02 6.00e-02Iodomethane NA NA NA NA NAMethanol NA 3.30e+02 NA NA NAPhenanthrene 1.80e+02 NA NA 5.60e-01 2.25e-01Phenol NA 5.00e+01 NA NA NAPyrene NA NA NA 4.90e-01 3.50e-01Ideno(1,2,3-cd)pyrene NA NA NA 2.00e-01 NA

Coplanar PCB TEQ NA NA NA NA NATotal PCB Cogener NA NA NA 7.00e-02 5.00e-02

2,3,7,8-TCDD NA NA NA NA NA1,2,3,7,8-PCDD NA NA NA NA NA1,2,3,4,7,8-HxCDD NA NA NA NA NA1,2,3,6,7,8-HxCDD NA NA NA NA NA1,2,3,7,8,9-HxCDD NA NA NA NA NA1,2,3,4,6,7,8-HpCDD NA NA NA NA NAOCDD NA NA NA NA NA2,3,7,8-TCDF NA NA NA NA NA1,2,3,7,8-PCDF NA NA NA NA NA2,3,4,7,8-PCDF NA NA NA NA NA1,2,3,4,7,8-HxCDF NA NA NA NA NA1,2,3,6,7,8-HxCDF NA NA NA NA NA2,3,4,6,7,8-HxCDF NA NA NA NA NA

Table 9.20 Sediment toxicity data

CompoundSQCA

(mg/kg-oc)

Tier IIWater CriteriaB

(:g/L)

SQBC

(mg/kg)LELD

(mg/kg)ER-LE

(mg/kg)

9–92

1,2,3,7,8,9-HxCDF NA NA NA NA NA1,2,3,4,6,7,8-HpCDF NA NA NA NA NA1,2,3,4,7,8,9-HpCDF NA NA NA NA NAOCDF NA NA NA NA NAAluminum NA NA NA NA NAAntimony NA NA NA NA 2.00e+00Arsenic NA NA NA 6.00e+00 3.30e+01Barium NA NA NA NA NABeryllium NA NA NA NA NACadmium NA NA NA 6.00e-01 5.00e+00Chromium (total) NA NA NA 2.60e+01 8.00e+01Chromium (hexavalent) NA NA NA NA NACobalt NA NA NA 5.00e+01 NACopper NA NA NA 1.60e+01 7.00e+01Lead NA NA NA 3.10e+01 3.50e+01Manganese NA NA NA NA NAMercuric chloride (particle)F NA NA NA 2.00e-01 1.50e-01Mercuric chloride (vapor)F NA NA NA 2.00e-01 1.50e-01MercuryF NA NA NA 2.00e-01 1.50e-01Methyl mercuryF NA NA NA 2.00e-01 1.50e-01Nickel NA NA NA 1.60e+01 3.00e+01Selenium NA NA NA NA NASilver NA NA NA 5.00e-01 1.00e+00Thallium NA NA NA NA NAVanadium NA NA NA NA NAZinc NA NA NA 1.20e+02 1.20e+02NA - Not available or not applicable.A Sediment Quality Criteria, in units of milligrams per kilograms of organic carbon. Source: U.S. EPA, 1993.B Tier II water quality criteria calculated using the Great Lakes methodologies. Source: IDEM, 2000.C Sediment Quality Benchmark. Values calculated from Tier II water criteria and physical properties ofcompounds. D Lowest Effect Level in sediment. Source: OMEE, 1996.E Concentration at the low end of the range in which effects had been observed. Source: NOAA, 1991.F Values for mercury were used for all forms of mercury.

9–93

Table 9.21 Toxicity values for terrestrial animalsCompound NOAELA

(mg/kg-d)LOAELB

(mg/kg-d)Species Weight

(kg)Source

Acetone 1.00e+02 NR rat 0.282C IRIS, 2001Acrylonitrile 1.00e+00 NR mouse 0.019D HEAST, 1997BenzeneF,L NA 1.79e-01 mouse 0.019D ATSDR, 1997Benzo(a)anthraceneE 7.10e+01 NR rat 0.282C IRIS, 2001Benzo(g,h,i)peryleneE 7.10e+01 NR rat 0.282C IRIS, 2001Benzo(a)pyreneE 7.10e+01 NR rat 0.282C IRIS, 2001Benzo(k)fluorantheneE 7.10e+01 NR rat 0.282C IRIS, 2001Carbon Tetrachloride 7.10e-01 NR rat 0.282C IRIS, 2001ChryseneE 7.10e+01 NR rat 0.282C IRIS, 2001Cresol, m-(methylphenol, 3-)

5.00e+01 NR rat 0.282C HEAST, 1997

Dibenzo(a,h)anthraceneE 7.10e+01 NR rat 0.282C IRIS, 2001IodomethaneH 1.40e+00 NR rat 0.282C IRIS, 2001Methanol 5.00e+02 NR rat 0.282C IRIS, 2001PhenanthreneE 7.10e+01 NR rat 0.282C IRIS, 2001Phenol 6.00e+01 NR rat 0.282C IRIS, 2001Pyrene 7.50e+01 NR mouse 0.019D IRIS, 2001Ideno(1,2,3-cd)pyreneE 7.10e+01 NR rat 0.282C IRIS, 2001

Coplanar PCB TEQ 1.00e-061.40e-05

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

Total PCB Cogener NA 7.00e-02 rat 0.282C HEAST, 1997

2,3,7,8-TCDD 1.00e-061.40e-05

NRNR

ratpheasant

0.2551.1

RTI, 1999RTI, 1999

1,2,3,7,8-PCDD 1.00e-061.40e-05

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

1,2,3,4,7,8-HxCDD 1.00e-052.80e-04

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

1,2,3,6,7,8-HxCDD 1.00e-051.40e-03

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

1,2,3,7,8,9-HxCDD 1.00e-051.40e-04

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

1,2,3,4,6,7,8-HpCDD 1.00e-041.40e-02

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

OCDD 1.00e-021.40e-01

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

2,3,7,8-TCDF 1.00e-051.40e-05

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999


(mg/kg-d)LOAELB


(kg)Source

9–94

1,2,3,7,8-PCDF 2.00e-051.40e-04

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

2,3,4,7,8-PCDF 2.00e-061.40e-05

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

1,2,3,4,7,8-HxCDF 1.00e-051.40e-04

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

1,2,3,6,7,8-HxCDF 1.00e-051.40e-04

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

2,3,4,6,7,8-HxCDF 1.00e-051.40e-04

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

1,2,3,7,8,9-HxCDF 1.00e-051.40e-04

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

1,2,3,4,6,7,8-HpCDF 1.00e-041.40e-03

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

1,2,3,4,7,8,9-HpCDF 1.00e-041.40e-03

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

OCDF 1.00e-021.40e-01

NRNR

ratI

pheasantI0.255

1.1RTI, 1999RTI, 1999

AluminumJ 4.30e-01 NR rat 0.282C HEAST, 1997Antimony 1.43e-01 NR rat 0.255 RTI, 1999

Arsenic 4.63e+006.00e-03

NRNR

ratmallard

0.4391.043

RTI, 1999RTI, 1999

Barium 2.10e+01 NR chick 0.121 RTI, 1999Beryllium 5.40e-01 NR rat 0.282C HEAST, 1997

Cadmium 1.00e+001.44e+00

NRNR

ratmallard

0.3211.53

RTI, 1999RTI, 1999

Chromium (total) 1.00e+00 NR duck 1.25 RTI, 1999Chromium (hexavalent) 3.30e+00 NR mouse 0.023 RTI, 1999CobaltL 5.00e-02 NR rat 0.282C ATSDR, 1992

Copper 6.20e+004.70e+01

NRNR

minkchick

0.7450.534

RTI, 1999RTI, 1999

Lead 5.00e-032.07e-02

NRNR

ratquail

0.2350.15

RTI, 1999RTI, 1999

Manganese 1.40e-01 NR human 70 IRIS, 2001Mercuric chloride NA 2.26e-01 rat 0.282C IRIS, 2001

Mercury 5.50e-02NA

NR7.80e-02

minkmallard

0.81.162

RTI, 1999RTI, 1999

Methyl mercury 5.50e-02NA

NR7.80e-02

minkmallard

0.81.162

RTI, 1999RTI, 1999


(mg/kg-d)LOAELB


(kg)Source

9–95

Nickel 5.35e+017.74e+01

NRNR

ratmallard

0.1480.782

RTI, 1999RTI, 1999

Selenium 2.02e-015.00e-01

NRNR

ratmallard

0.321.055

RTI, 1999RTI, 1999

Silver NA 1.40e-02 human 70 IRIS, 2001ThalliumK 2.30e-01 NR rat 0.282C HEAST, 1997Vanadium 7.00e-01 NR rat 0.282C HEAST, 1997Zinc NA 1.00e+00 human 70 IRIS, 2001NA - Not available. NR - LOAEL not required, as NOAEL is available.A NOAEL - No Observed Adverse Effects LevelB LOAEL - Lowest Observed Adverse Effects Level C Estimated weight of a rat, calculated as average of reported weights for rats.D Estimated weight of a mouse, based average wight of deer mouse (RTI, 1999).E Toxicity data is for surrogate compound, naphthalene.F Value is based on inhalation tests, not oral ingestion.G Estimated weight of a rabbit, based on the average weight of eastern cottontails (RTI, 1999). H Toxicity data is for surrogate compound, bromomethane.I Toxicity values are calculated from the NOAEL of 2,3,7,8-TCDD and the TEF values given in Table 9.3. J Based on aluminum phosphide.K Based on thallium chloride.L Intermediate (sub-chronic) value.

9–96

Table 9.22 Estimated hazard quotients for inhalation exposure to terrestrial animals

Compound

Long-term AirConcentration

Cair(:g/m3)

Air EcologicalBenchmark

ValueEBVair

(:g/m3)

Hazard QuotientHQ

Percent of HQfrom Fugitive

Emissions

Acetone 1.39e-02 7.50e+04 1.85e-07 96%Acrylonitrile 8.04e-05 7.70e+02 1.04e-07 NFBenzene 1.45e-03 2.49e+01 5.82e-05 78%Benzo(a)anthracene 5.90e-08 5.33e+04 1.11e-12 NFBenzo(g,h,i)perylene 1.65e-08 5.33e+04 3.09e-13 NFBenzo(a)pyrene 7.30e-09 5.33e+04 1.37e-13 NFBenzo(k)fluoranthene 2.32e-08 5.33e+04 4.36e-13 NFCarbon Tetrachloride 5.19e-07 5.33e+02 9.74e-10 NFChrysene 9.17e-08 5.33e+04 1.72e-12 NFCresol, -m (methylphenol, 3-) 7.23e-04 3.75e+04 1.93e-08 98%Dibenzo(a,h)anthracene 2.67e-08 5.33e+04 5.02e-13 NFIodomethane 6.35e-04 2.08e+02 3.05e-06 NFMethanol 8.38e-03 3.75e+05 2.23e-08 99%Phenanthrene 2.24e-05 5.33e+04 4.21e-10 NFPhenol 2.33e-03 1.92e+03 1.21e-06 99%Pyrene 1.48e-06 5.62e+04 2.63e-11 NFIdeno(1,2,3-cd)pyrene 4.57e-09 5.33e+04 8.58e-14 NF

Coplanar PCB TEQ 1.04e-13 7.50e-04 1.39e-10 NFTotal PCB Cogener 8.53e-10 5.25e+00 1.62e-10 NF

2,3,7,8-TCDD 1.60e-10 7.50e-04 2.13e-07 NF1,2,3,7,8-PCDD 1.14e-10 7.50e-04 1.53e-07 NF1,2,3,4,7,8-HxCDD 2.48e-10 7.50e-03 3.30e-08 NF1,2,3,6,7,8-HxCDD 4.28e-10 7.50e-03 5.70e-08 NF1,2,3,7,8,9-HxCDD 4.01e-10 7.50e-03 5.35e-08 NF1,2,3,4,6,7,8-HpCDD 3.33e-09 7.50e-02 4.44e-08 NFOCDD 8.84e-10 7.50e+00 1.18e-10 NF2,3,7,8-TCDF 4.80e-10 7.50e-03 6.40e-08 NF1,2,3,7,8-PCDF 2.32e-10 1.50e-02 1.54e-08 NF2,3,4,7,8-PCDF 3.99e-10 1.50e-03 2.66e-07 NF1,2,3,4,7,8-HxCDF 2.91e-10 7.50e-03 3.88e-08 NF

Table 9.22 Estimated hazard quotients for inhalation exposure to terrestrial animals

Compound

Long-term AirConcentration

Cair(:g/m3)

Air EcologicalBenchmark

ValueEBVair

(:g/m3)

Hazard QuotientHQ

Percent of HQfrom Fugitive

Emissions

9–97

1,2,3,6,7,8-HxCDF 1.32e-10 7.50e-03 1.76e-08 NF2,3,4,6,7,8-HxCDF 2.31e-11 7.50e-03 0.00e+00 NF1,2,3,7,8,9-HxCDF 2.97e-11 7.50e-03 3.97e-09 NF1,2,3,4,6,7,8-HpCDF 2.88e-10 7.50e-02 3.84e-09 NF1,2,3,4,7,8,9-HpCDF 2.31e-11 7.50e-02 3.07e-10 NFOCDF 2.31e-11 7.50e+00 0.00e+00 NF

Aluminum 4.12e-03 3.23e+02 1.28e-05 NFAntimony 3.93e-06 1.60e+02 2.46e-08 NFArsenic 3.88e-06 1.00e+00 3.88e-06 NFBarium 5.23e-05 1.15e+03 4.55e-08 NFBeryllium 4.31e-07 2.00e-02 2.16e-05 NFCadmium 3.82e-05 7.50e+02 5.09e-08 NFChromium (total) 8.11e-05 1.00e+00 8.11e-05 NFChromium (hexavalent) 2.98e-06 1.00e+00 2.98e-06 NFCobalt 3.17e-06 1.00e+00 3.17e-06 NFCopper 2.37e-05 6.00e+01 3.96e-07 NFLead 3.28e-04 3.75e+00 8.74e-05 NFManganese 1.22e-04 5.00e+01 2.45e-06 NFMercuric chloride (particle) 2.00e-04 1.70e+01 1.18e-05 NFMercuric chloride (vapor) 2.02e-04 1.70e+01 1.19e-05 NFMercury 2.03e-04 9.00e+00 2.26e-05 NFMethyl mercury 0.00e+00 5.85e+00 0.00e+00 NFNickel 9.27e-06 3.00e+01 3.09e-07 NFSelenium 1.90e-06 1.00e-01 1.90e-05 NFSilver 5.95e-06 1.05e+00 5.67e-06 NFThallium 2.17e-05 1.72e+02 1.26e-07 NFVanadium 8.35e-06 8.00e+00 1.04e-06 NFZinc 4.72e-05 3.60e-03 1.31e-02 NF

NF - Fugitive emissions are not modeled for this compound.

9–98

Table 9.23 Estimated hazard quotients for plants and soil community

CompoundSoil

Concentration(mg/kg)

SoilBackground

LevelsA

(mg/kg)

SoilBenchmark

Value (mg/kg)

HazardQuotient

Percent ofHQ fromFugitive

EmissionsAcetone 1.28e-04 NA NA - 96%Acrylonitrile 5.13e-16 NA NA - NFBenzene 8.80e-06 NA NA - 78%Benzo(a)anthracene 5.31e-07 NA NA - NFBenzo(g,h,i)perylene 1.75e-07 NA NA - NFBenzo(a)pyrene 5.98e-08 NA NA - NFBenzo(k)fluoranthene 7.88e-07 NA NA - NFCarbon Tetrachloride 5.66e-09 NA NA - NFChrysene 1.25e-06 NA NA - NFCresol, m- (methylphenol, 3-) 2.07e-04 NA NA - 98%Dibenzo(a,h)anthracene 4.17e-07 NA NA - NFIodomethane 5.51e-06 NA NA - NFMethanol 3.00e-06 NA NA - 99%Phenanthrene 4.15e-06 NA NA - NFPhenol 2.49e-04 NA NA - 99%Pyrene 3.55e-05 NA NA - NFIdeno(1,2,3-cd)pyrene 5.50e-08 NA NA - NF

Coplanar PCB TEQ 6.61e-14 NA 2.60e-07 2.54e-07 NFTotal PCB Cogener 5.42e-10 NA NA - NF

2,3,7,8-TCDD 8.60e-09 NA 2.60e-07 3.31e-02 NF1,2,3,7,8-PCDD 6.60e-09 NA 2.60e-07 2.54e-02 NF1,2,3,4,7,8-HxCDD 1.49e-08 NA 5.20e-06 2.86e-03 NF1,2,3,6,7,8-HxCDD 2.58e-08 NA 2.60e-05 9.93e-04 NF1,2,3,7,8,9-HxCDD 2.43e-08 NA 2.60e-06 9.35e-03 NF1,2,3,4,6,7,8-HpCDD 2.02e-07 NA 2.60e-04 7.76e-04 NFOCDD 5.38e-08 NA 2.60e-03 2.07e-05 NF2,3,7,8-TCDF 2.47e-08 NA 2.60e-07 9.48e-02 NF1,2,3,7,8-PCDF 1.29e-08 NA 2.60e-06 4.95e-03 NF2,3,4,7,8-PCDF 2.28e-08 NA 2.60e-07 8.75e-02 NF1,2,3,4,7,8-HxCDF 1.75e-08 NA 5.20e-06 3.37e-03 NF1,2,3,6,7,8-HxCDF 7.93e-09 NA 2.60e-06 3.05e-03 NF

Table 9.23 Estimated hazard quotients for plants and soil community

CompoundSoil


SoilBackground

LevelsA

(mg/kg)

SoilBenchmark

Value (mg/kg)

HazardQuotient

Percent ofHQ fromFugitive

Emissions

9–99

2,3,4,6,7,8-HxCDF 1.38e-09 NA 2.60e-06 5.33e-04 NF1,2,3,7,8,9-HxCDF 1.78e-09 NA 2.60e-06 6.86e-04 NF1,2,3,4,6,7,8-HpCDF 1.73e-08 NA 2.60e-05 6.67e-04 NF1,2,3,4,7,8,9-HpCDF 1.40e-09 NA 2.60e-05 5.37e-05 NFOCDF 1.40e-09 NA 2.60e-03 5.39e-07 NF

Aluminum 1.85e-01 7.00e+04 NA - NFAntimony 1.35e-03 NA NA - NFArsenic 8.56e-04 8.00e+00 1.00e+01 8.56e-05 NFBarium 1.30e-02 7.00e+02 5.00e+02 2.61e-05 NFBeryllium 4.17e-04 NA NA - NFCadmium 1.56e-02 NA 1.00e+00 1.56e-02 NFChromium (total) 8.86e-02 5.00e+01 1.00e+00 8.86e-02 NFChromium (hexavalent) 5.44e-04 NA 1.00e+00 5.44e-04 NFCobalt 1.28e-03 7.00e+00 NA - NFCopper 2.57e-02 7.00e+01 2.10e+01 1.22e-03 NFLead 3.32e-01 1.50e+01 2.80e+01 1.19e-02 NFManganese 8.77e-02 5.00e+02 5.00e+02 1.75e-04 NFMercuric chloride (particle) 4.08e-04 NA 1.00e-01 4.08e-03 NFMercuric chloride (vapor) 3.17e-03 NA 1.00e-01 3.17e-02 NFMercury 0.00e+00 4.00e-02 1.00e-01 0.00e+00 NFMethyl mercury 7.23e-05 NA 1.00e-01 7.23e-04 NFNickel 3.44e-03 1.00e+01 3.00e+01 1.15e-04 NFSelenium 1.40e-04 4.00e-01 1.00e+00 1.40e-04 NFSilver 2.77e-04 NA NA - NFThallium 9.61e-03 NA NA - NFVanadium 8.52e-03 7.00e+01 NA - NFZinc 2.08e-02 4.50e+05 NA - NFNA - Not available. NF- Fugitive emissions not modeled for this compound.A Source: Boerngen and Shacklette, 1981.

9–100

Table 9.24 Estimated hazard quotients for surface waterCompound Surface Water

Concentration(:g/L)

Surface WaterBenchmark

Value(:g/L)

Hazard Quotient Percent of HQfrom Fugitive

Emissions

Acetone 4.92e-06 1.70e+03 2.89e-09 40%Acrylonitrile 2.98e-12 6.30e+01 4.73e-14 NFBenzene 1.45e-07 9.80e+01 1.48e-09 9%Benzo(a)anthracene 5.11e-10 2.30e-01 2.22e-09 NFBenzo(g,h,i)perylene 6.08e-12 5.00e-03 1.22e-09 NFBenzo(a)pyrene 1.13e-11 1.10e-01 1.03e-10 NFBenzo(k)fluoranthene 9.00e-11 5.00e-03 1.80e-08 NFCarbon Tetrachloride 1.51e-10 4.00e+01 3.78e-12 NFChrysene 9.42e-10 1.00e+00 9.42e-10 NFCresol, -m (methylphenol, 3-) 5.55e-06 4.80e+02 1.16e-08 56%Dibenzo(a,h)anthracene 1.85e-11 1.00e+00 1.85e-11 NFIodomethane 7.28e-07 4.51e+00 1.62e-07 NFMethanol 5.31e-08 3.00e+03 1.77e-11 70%Phenanthrene 1.35e-09 9.30e-01 1.45e-09 NFPhenol 1.45e-05 3.60e+01 4.04e-07 65%Pyrene 6.81e-08 5.00e-03 1.36e-05 NFIdeno(1,2,3-cd)pyrene 2.10e-12 5.00e-03 4.20e-10 NF

Coplanar PCB TEQ 1.16e-16 5.70e-06 2.03e-11 NFTotal PCB Cogener 9.49e-13 1.40e-02 6.78e-11 NF

2,3,7,8-TCDD 1.66e-12 5.70e-06 2.92e-07 NF1,2,3,7,8-PCDD 6.80e-13 2.30e-05 2.96e-08 NF1,2,3,4,7,8-HxCDD 6.60e-13 7.18e-04 9.19e-10 NF1,2,3,6,7,8-HxCDD 9.74e-13 5.70e-05 1.71e-08 NF1,2,3,7,8,9-HxCDD 8.30e-13 5.70e-05 1.46e-08 NF1,2,3,4,6,7,8-HpCDD 6.67e-12 5.70e-04 1.17e-08 NFOCDD 1.61e-12 5.70e-02 2.82e-11 NF2,3,7,8-TCDF 6.74e-12 5.70e-06 1.18e-06 NF1,2,3,7,8-PCDF 1.86e-12 5.70e-05 3.26e-08 NF2,3,4,7,8-PCDF 2.46e-12 5.70e-06 4.32e-07 NF1,2,3,4,7,8-HxCDF 7.49e-13 5.70e-05 1.31e-08 NF1,2,3,6,7,8-HxCDF 3.47e-13 5.70e-05 6.09e-09 NF

Table 9.24 Estimated hazard quotients for surface waterCompound Surface Water

Concentration(:g/L)

Surface WaterBenchmark

Value(:g/L)

Hazard Quotient Percent of HQfrom Fugitive

Emissions

9–101

2,3,4,6,7,8-HxCDF 6.16e-14 5.70e-05 1.08e-09 NF1,2,3,7,8,9-HxCDF 8.07e-14 5.70e-05 1.42e-09 NF1,2,3,4,6,7,8-HpCDF 6.56e-13 5.70e-04 1.15e-09 NF1,2,3,4,7,8,9-HpCDF 4.76e-14 5.70e-04 8.35e-11 NFOCDF 4.10e-14 5.70e-02 7.19e-13 NF

Aluminum 4.87e-04 8.70e+01 5.59e-06 NFAntimony 4.57e-07 3.00e-01 1.52e-06 NFArsenic 4.54e-07 1.50e+02 3.03e-09 NFBarium 6.11e-06 1.40e+02 4.37e-08 NFBeryllium 4.47e-08 5.10e+00 8.76e-09 NFCadmium 4.42e-06 2.20e+00 2.01e-06 NFChromium (total) 7.06e-07 7.40e+01 9.54e-09 NFChromium (hexavalent) 3.50e-07 1.10e+01 3.18e-08 NFCobalt 3.67e-07 4.30e+01 8.54e-09 NFCopper 1.12e-06 9.00e+00 1.25e-07 NFLead 3.23e-05 2.50e+00 1.29e-05 NFManganese 1.37e-05 9.00e+01 1.53e-07 NFMercuric chloride (particle) 4.89e-09 7.70e-01 6.35e-09 NFMercuric chloride (vapor) 9.10e-08 7.70e-01 1.18e-07 NFMercury 0.00e+00 7.70e-01 0.00e+00 NFMethyl mercury 1.11e-07 7.70e-01 1.44e-07 NFNickel 1.08e-06 5.20e+01 2.07e-08 NFSelenium 2.24e-07 5.00e+00 4.49e-08 NFSilver 7.02e-07 3.40e+00 2.06e-07 NFThallium 2.50e-06 1.70e-01 1.47e-05 NFVanadium 8.12e-07 1.20e+01 6.77e-08 NFZinc 5.45e-06 1.20e+02 4.54e-08 NF

NF - Fugitive emission not modeled for this compound.

9–102

Table 9.25 Estimated hazard quotients for sediment exposure

CompoundSediment


SedimentEcologicalBenchmark

Value(mg/kg)

Hazard QuotientPercent of HQfrom Fugitive

Emissions

Acetone 1.87e-07 NA - 40%Acrylonitrile 2.65e-13 NA - NFBenzene 3.80e-07 2.43e-01 1.56e-06 9%Benzo(a)anthracene 3.74e-06 3.20e-01 1.17e-05 NFBenzo(g,h,i)perylene 1.40e-07 1.70e-01 8.26e-07 NFBenzo(a)pyrene 1.50e-07 3.70e-01 4.06e-07 NFBenzo(k)fluoranthene 1.27e-06 2.40e-01 5.29e-06 NF

Carbon Tetrachloride 1.13e-09 2.43e-01 4.63e-09 NFChrysene 7.56e-06 3.40e-01 2.22e-05 NFCresol, -m (methylphenol, 3-) 1.06e-05 NA - 56%Dibenzo(a,h)anthracene 3.42e-07 6.00e-02 5.70e-06 NFIodomethane 8.58e-07 NA - NFMethanol 8.40e-10 NA - 70%Phenanthrene 1.09e-06 7.20e+00 1.52e-07 NFPhenol 1.17e-05 NA - 65%Pyrene 1.42e-04 4.90e-01 2.90e-04 NFIdeno(1,2,3-cd)pyrene 4.53e-08 2.00e-01 2.27e-07 NF

Coplanar PCB TEQ 6.94e-17 NA - NFTotal PCB Cogener 5.69e-13 7.00e-02 8.13e-12 NF

2,3,7,8-TCDD 3.36e-08 NA - NF1,2,3,7,8-PCDD 1.37e-08 NA - NF1,2,3,4,7,8-HxCDD 1.61e-08 NA - NF1,2,3,6,7,8-HxCDD 2.29e-08 NA - NF1,2,3,7,8,9-HxCDD 1.95e-08 NA - NF1,2,3,4,6,7,8-HpCDD 1.64e-07 NA - NFOCDD 3.89e-08 NA - NF2,3,7,8-TCDF 1.29e-07 NA - NF1,2,3,7,8-PCDF 3.96e-08 NA - NF2,3,4,7,8-PCDF 5.44e-08 NA - NF1,2,3,4,7,8-HxCDF 1.76e-08 NA - NF

Table 9.25 Estimated hazard quotients for sediment exposure

CompoundSediment


SedimentEcologicalBenchmark

Value(mg/kg)

Hazard QuotientPercent of HQfrom Fugitive

Emissions

9–103

1,2,3,6,7,8-HxCDF 8.16e-09 NA - NF2,3,4,6,7,8-HxCDF 1.45e-09 NA - NF1,2,3,7,8,9-HxCDF 1.90e-09 NA - NF1,2,3,4,6,7,8-HpCDF 1.60e-08 NA - NF1,2,3,4,7,8,9-HpCDF 1.16e-09 NA - NFOCDF 1.02e-09 NA - NF

Aluminum 2.68e-03 NA - NFAntimony 2.05e-05 2.00e+00 1.03e-05 NFArsenic 1.26e-05 6.00e+00 2.10e-06 NFBarium 1.93e-04 NA - NFBeryllium 2.42e-05 NA - NFCadmium 2.48e-04 6.00e-01 4.13e-04 NFChromium (total) 3.16e-02 2.60e+01 1.22e-03 NFChromium (hexavalent) 7.97e-06 NA - NFCobalt 2.02e-05 5.00e+01 4.03e-07 NFCopper 6.70e-03 1.60e+01 4.19e-04 NFLead 2.86e-02 3.10e+01 9.21e-04 NFManganese 2.06e-03 NA - NFMercuric chloride (particle) 7.76e-05 2.00e-01 3.88e-04 NFMercuric chloride (vapor) 1.44e-03 2.00e-01 7.22e-03 NFMercury 0.00e+00 2.00e-01 0.00e+00 NFMethyl mercury 1.06e-04 2.00e-01 5.30e-04 NFNickel 5.32e-05 1.60e+01 3.33e-06 NFSelenium 2.04e-06 NA - NFSilver 4.01e-06 5.00e-01 8.02e-06 NFThallium 1.56e-04 NA - NFVanadium 7.95e-04 NA - NFZinc 3.38e-04 1.20e+02 2.81e-06 NFNA - Not available.NF - Fugitive emissions not modeled for this compound.

9–104

Table 9.26 Weight and diet data for a deer mouse

Parameter Value Source

Weight 0.02 kg Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Food Ingestion Rate 0.22 kg/kg-d Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Soil Ingestion Rate 0.0039 kg/kg-d RTI, 1999

Water Ingestion Rate 0.19 L/kg-d Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Diet percentages

Ag plants 13.6 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Forage plants 14.0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Silage plants 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Rootveg plants 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Grain plants 17.5 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Earthworms 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Insects 43 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Fish 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Birds 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Mammals 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

9–105

Table 9.27 Estimated hazard quotients for a deer mouseCompound Dose

(mg/kg-d)Ingestion EBV

(mg/kg-d)Hazard Quotient Percent of HQ

from FugitiveEmissions

Acetone 1.29e-03 1.94e+02 6.64e-06 96%Acrylonitrile 8.76e-12 9.87e-01 8.88e-12 NFBenzene 3.87e-06 1.76e-03 2.20e-03 88%Benzo(a)anthracene 1.92e-07 1.38e+02 1.40e-09 NFBenzo(g,h,i)perylene 1.81e-07 1.38e+02 1.31e-09 NFBenzo(a)pyrene 1.12e-07 1.38e+02 8.16e-10 NFBenzo(k)fluoranthene 4.51e-07 1.38e+02 3.28e-09 NFCarbon Tetrachloride 1.16e-09 1.38e+00 8.45e-10 NFChrysene 7.75e-07 1.38e+02 5.63e-09 NFCresol, m- (methylphenol, 3-) 1.16e-04 9.69e+01 1.20e-06 99%Dibenzo(a,h)anthracene 2.06e-06 1.38e+02 1.50e-08 NFIodomethane 4.38e-06 2.71e+00 1.61e-06 NFMethanol 5.79e-05 9.69e+02 5.98e-08 99%Phenanthrene 4.46e-07 1.38e+02 3.24e-09 NFPhenol 2.63e-04 1.16e+02 2.26e-06 99%Pyrene 3.80e-06 7.40e+01 5.13e-08 NFIdeno(1,2,3-cd)pyrene 1.15e-06 1.38e+02 8.37e-09 NF


2,3,7,8-TCDD 2.37e-09 1.89e-06 1.26e-03 NF1,2,3,7,8-PCDD 2.00e-09 1.89e-06 1.06e-03 NF1,2,3,4,7,8-HxCDD 4.29e-09 1.89e-05 2.27e-04 NF1,2,3,6,7,8-HxCDD 7.14e-09 1.89e-05 3.78e-04 NF1,2,3,7,8,9-HxCDD 6.58e-09 1.89e-05 3.48e-04 NF1,2,3,4,6,7,8-HpCDD 5.58e-08 1.89e-04 2.95e-04 NFOCDD 1.44e-08 1.89e-02 7.63e-07 NF2,3,7,8-TCDF 6.60e-09 1.89e-05 3.49e-04 NF1,2,3,7,8-PCDF 3.65e-09 3.78e-05 9.66e-05 NF2,3,4,7,8-PCDF 6.32e-09 3.78e-06 1.67e-03 NF1,2,3,4,7,8-HxCDF 4.72e-09 1.89e-05 2.50e-04 NF1,2,3,6,7,8-HxCDF 2.14e-09 1.89e-05 1.13e-04 NF2,3,4,6,7,8-HxCDF 3.74e-10 1.89e-05 1.98e-05 NF

Table 9.27 Estimated hazard quotients for a deer mouseCompound Dose




9–106

1,2,3,7,8,9-HxCDF 4.82e-10 1.89e-05 2.55e-05 NF1,2,3,4,6,7,8-HpCDF 4.99e-09 1.89e-04 2.64e-05 NF1,2,3,4,7,8,9-HpCDF 3.88e-10 1.89e-04 2.05e-06 NFOCDF 3.75e-10 1.89e-02 1.98e-08 NF

Aluminum 1.21e-01 8.33e-01 1.45e-01 NFAntimony 1.82e-04 2.70e-01 6.75e-04 NFArsenic 1.21e-04 1.00e+01 1.21e-05 NFBarium 1.84e-03 3.29e+01 5.60e-05 NFBeryllium 4.45e-05 1.05e+00 4.26e-05 NFCadmium 2.10e-03 2.00e+00 1.05e-03 NFChromium (total) 9.39e-03 2.81e+00 3.34e-03 NFChromium (hexavalent) 9.00e-05 3.42e+00 2.63e-05 NFCobalt 1.51e-04 9.69e-03 1.56e-02 NFCopper 3.35e-03 1.53e+01 2.18e-04 NFLead 3.59e-02 9.26e-03 3.88e+00 NFManganese 1.17e-02 1.08e+00 1.09e-02 NFMercuric chloride (particle) 4.25e-05 4.38e-02 9.70e-04 NFMercuric chloride (vapor) 3.13e-04 4.38e-02 7.16e-03 NFMercury 0.00e+00 1.38e-01 0.00e+00 NFMethyl mercury 7.81e-06 1.38e-01 5.64e-05 NFNickel 4.14e-04 8.83e+01 4.69e-06 NFSelenium 7.45e-04 4.04e-01 1.84e-03 NFSilver 1.91e-04 1.08e-02 1.77e-02 NFThallium 1.11e-03 4.46e-01 2.50e-03 NFVanadium 9.06e-04 1.36e+00 6.68e-04 NFZinc 1.05e-02 7.69e-01 1.37e-02 NF

Hazard quotients greater than 1 are in boldface.NF - Fugitive emission not modeled for this compound.

9–107

Table 9.28 Weight and diet data for a meadow vole






Diet percentages

Ag plants 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)



Rootveg plants 9.3 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)







9–108

Table 9.29 Estimated hazard quotients for a meadow voleCompound Dose




Acetone 1.92e-03 1.68e+02 1.14e-05 96%Acrylonitrile 1.73e-11 8.55e-01 2.02e-11 NFBenzene 5.78e-06 1.53e-03 3.78e-03 78%Benzo(a)anthracene 3.69e-07 1.19e+02 3.09e-09 NFBenzo(g,h,i)perylene 3.47e-07 1.19e+02 2.91e-09 NFBenzo(a)pyrene 2.01e-07 1.19e+02 1.69e-09 NFBenzo(k)fluoranthene 8.33e-07 1.19e+02 6.99e-09 NFCarbon Tetrachloride 1.76e-09 1.19e+00 1.47e-09 NFChrysene 1.40e-06 1.19e+02 1.17e-08 NFCresol, m- (methylphenol, 3-) 1.73e-04 8.39e+01 2.06e-06 98%Dibenzo(a,h)anthracene 3.39e-06 1.19e+02 2.85e-08 NFIodomethane 6.45e-06 2.35e+00 2.75e-06 NFMethanol 8.66e-05 8.39e+02 1.03e-07 99%Phenanthrene 6.49e-07 1.19e+02 5.45e-09 NFPhenol 3.91e-04 1.01e+02 3.88e-06 98%Pyrene 4.30e-06 6.41e+01 6.70e-08 NFIdeno(1,2,3-cd)pyrene 1.86e-06 1.19e+02 1.56e-08 NF



Table 9.29 Estimated hazard quotients for a meadow voleCompound Dose




9–109


Aluminum 2.35e-01 7.22e-01 3.25e-01 NFAntimony 3.12e-04 2.34e-01 1.33e-03 NFArsenic 2.34e-04 8.68e+00 2.70e-05 NFBarium 3.56e-03 2.85e+01 1.25e-04 NFBeryllium 3.12e-05 9.07e-01 3.44e-05 NFCadmium 3.77e-03 1.73e+00 2.18e-03 NFChromium (total) 6.00e-03 2.44e+00 2.46e-03 NFChromium (hexavalent) 1.74e-04 2.96e+00 5.89e-05 NFCobalt 1.96e-04 8.39e-03 2.34e-02 NFCopper 3.69e-03 1.33e+01 2.78e-04 NFLead 2.69e-02 8.02e-03 3.36e+00 NFManganese 1.43e-02 9.33e-01 1.53e-02 NFMercuric chloride (particle) 2.16e-05 3.79e-02 5.68e-04 NFMercuric chloride (vapor) 4.93e-05 3.79e-02 1.30e-03 NFMercury 0.00e+00 1.20e-01 0.00e+00 NFMethyl mercury 5.80e-06 1.20e-01 4.84e-05 NFNickel 5.90e-04 7.65e+01 7.71e-06 NFSelenium 1.60e-04 3.50e-01 4.58e-04 NFSilver 3.68e-04 9.33e-03 3.94e-02 NFThallium 1.35e-03 3.86e-01 3.49e-03 NFVanadium 5.98e-04 1.18e+00 5.09e-04 NFZinc 4.82e-03 6.66e-01 7.23e-03 NFHazard quotients above 1 are in boldface.NF - Fugitive emissions were not modeled for this compound.

9–110

Table 9.30 Weight and diet data for a northern bobwhite






Diet percentages











9–111

Table 9.31 Estimated hazard quotients for a northern bobwhiteCompound Dose




Acetone 6.10e-04 1.13e+02 5.38e-06 96%Acrylonitrile 1.15e-12 5.78e-01 1.98e-12 NFBenzene 1.89e-06 1.03e-03 1.83e-03 80%Benzo(a)anthracene 4.12e-08 8.06e+01 5.12e-10 NFBenzo(g,h,i)perylene 2.74e-08 8.06e+01 3.41e-10 NFBenzo(a)pyrene 2.08e-08 8.06e+01 2.58e-10 NFBenzo(k)fluoranthene 8.95e-08 8.06e+01 1.11e-09 NFCarbon Tetrachloride 5.89e-10 8.06e-01 7.31e-10 NFChrysene 1.64e-07 8.06e+01 2.03e-09 NFCresol, m- (methylphenol, 3-) 5.62e-05 5.67e+01 9.90e-07 98%Dibenzo(a,h)anthracene 4.36e-07 8.06e+01 5.41e-09 NFIodomethane 2.11e-06 1.59e+00 1.33e-06 NFMethanol 2.74e-05 5.67e+02 4.84e-08 99%Phenanthrene 1.16e-07 8.06e+01 1.44e-09 NFPhenol 1.26e-04 6.81e+01 1.85e-06 99%Pyrene 9.20e-07 4.34e+01 2.12e-08 NFIdeno(1,2,3-cd)pyrene 2.51e-07 8.06e+01 3.12e-09 NF



Table 9.31 Estimated hazard quotients for a northern bobwhiteCompound Dose




9–112


Aluminum 1.84e-02 4.88e-01 3.77e-02 NFAntimony 5.04e-05 1.58e-01 3.19e-04 NFArsenic 2.40e-05 9.44e-03 2.54e-03 NFBarium 3.76e-04 1.93e+01 1.95e-05 NFBeryllium 9.28e-06 6.13e-01 1.52e-05 NFCadmium 4.88e-04 2.49e+00 1.96e-04 NFChromium (total) 1.98e-03 1.65e+00 1.20e-03 NFChromium (hexavalent) 1.71e-05 2.00e+00 8.55e-06 NFCobalt 3.13e-05 5.67e-03 5.52e-03 NFCopper 1.07e-03 6.26e+01 1.72e-05 NFLead 7.63e-03 2.01e-02 3.80e-01 NFManganese 3.72e-03 6.31e-01 5.90e-03 NFMercuric chloride (particle) 8.94e-06 2.56e-02 3.48e-04 NFMercuric chloride (vapor) 6.65e-05 2.56e-02 2.59e-03 NFMercury 0.00e+00 1.26e-02 0.00e+00 NFMethyl mercury 1.64e-06 1.26e-02 1.30e-04 NFNickel 8.56e-05 1.13e+02 7.55e-07 NFSelenium 9.71e-05 7.89e-01 1.23e-04 NFSilver 3.07e-05 6.31e-03 4.87e-03 NFThallium 2.28e-04 2.61e-01 8.74e-04 NFVanadium 1.90e-04 7.94e-01 2.39e-04 NFZinc 1.61e-03 4.50e-01 3.58e-03 NFHazard quotients above 1 are in boldface.NF - Fugitive emission are not modeled for this compound.

9–113

Table 9.32 Weight and diet data for an American woodcock






Diet percentages


Forage plants 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)




Earthworms 68.0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)





9–114

Table 9.33 Estimated hazard quotients for an American woodcockCompound Dose







Table 9.33 Estimated hazard quotients for an American woodcockCompound Dose




9–115


Aluminum 1.84e-01 4.92e-01 3.74e-01 NFAntimony 5.13e-04 1.60e-01 3.21e-03 NFArsenic 3.22e-04 9.53e-03 3.38e-02 NFBarium 4.91e-03 1.95e+01 2.52e-04 NFBeryllium 1.52e-04 6.18e-01 2.46e-04 NFCadmium 8.44e-03 2.51e+00 3.36e-03 NFChromium (total) 3.70e-02 1.66e+00 2.23e-02 NFChromium (hexavalent) 2.49e-04 2.02e+00 1.23e-04 NFCobalt 4.67e-04 5.73e-03 8.15e-02 NFCopper 1.17e-02 6.31e+01 1.86e-04 NFLead 7.95e-02 2.02e-02 3.93e+00 NFManganese 2.70e-02 6.36e-01 4.24e-02 NFMercuric chloride (particle) 1.30e-04 2.59e-02 5.01e-03 NFMercuric chloride (vapor) 1.01e-03 2.59e-02 3.89e-02 NFMercury 0.00e+00 1.27e-02 0.00e+00 NFMethyl mercury 2.64e-05 1.27e-02 2.07e-03 NFNickel 8.20e-04 1.14e+02 7.17e-06 NFSelenium 5.24e-03 7.96e-01 6.58e-03 NFSilver 2.87e-04 6.36e-03 4.51e-02 NFThallium 3.51e-03 2.63e-01 1.33e-02 NFVanadium 3.11e-03 8.02e-01 3.88e-03 NFZinc 7.22e-02 4.55e-01 1.59e-01 NFHazard quotients above 1 are in boldface.NF- Fugitive emissions are not modeled for this compound.

9–116

Table 9.34 Weight and diet data for a mink



Food Ingestion Rate 0.22 kg/kg-day Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Soil Ingestion Rate 0 kg/kg-d RTI, 1999

Water Ingestion Rate 0.11 L/kg-day Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Diet percentages





Grain plants 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)






9–117

Table 9.35 Estimated hazard quotients for a minkCompound Dose







Table 9.35 Estimated hazard quotients for a minkCompound Dose




9–118


Aluminum 2.54e-04 3.10e-01 8.19e-04 NFAntimony 4.32e-06 1.01e-01 4.30e-05 NFArsenic 2.24e-06 3.73e+00 6.01e-07 NFBarium 7.89e-04 1.23e+01 6.43e-05 NFBeryllium 7.26e-07 3.90e-01 1.86e-06 NFCadmium 2.34e-04 7.45e-01 3.13e-04 NFChromium (total) 4.24e-05 1.05e+00 4.05e-05 NFChromium (hexavalent) 5.23e-07 1.27e+00 4.11e-07 NFCobalt 5.51e-07 3.61e-03 1.53e-04 NFCopper 1.36e-05 5.70e+00 2.38e-06 NFLead 1.44e-04 3.45e-03 4.17e-02 NFManganese 3.26e-05 4.01e-01 8.12e-05 NFMercuric chloride (particle) 1.46e-07 1.63e-02 8.95e-06 NFMercuric chloride (vapor) 1.13e-06 1.63e-02 6.94e-05 NFMercury 0.00e+00 5.15e-02 0.00e+00 NFMethyl mercury 2.03e-02 5.15e-02 3.94e-01 NFNickel 1.80e-05 3.29e+01 5.47e-07 NFSelenium 1.24e-05 1.50e-01 8.22e-05 NFSilver 2.94e-05 4.01e-02 7.33e-04 NFThallium 4.62e-06 1.66e-01 2.78e-05 NFVanadium 3.51e-06 5.05e-01 6.95e-06 NFZinc 2.35e-03 2.86e+00 8.20e-04 NFHazard quotients above 1 are in boldface.NF - Fugitive emissions are not modeled for this compound.

9–119

Table 9.36 Weight and diet data for a bald eagle


Weight 3.00 kg Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Food Ingestion Rate 0.12 kg/kg-d Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Soil Ingestion Rate 0 kg/kg-d RTI, 1999.

Water Ingestion Rate 0.037 L/kg-d Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Diet percentages

Ag plants 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Forage plants 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Silage plants 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Rootveg plants 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Grain plants 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Earthworms 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)


Fish 76.7 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Birds 16.5 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Mammals 6.8 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

9–120

Table 9.37 Estimated hazard quotients for a bald eagleCompound Dose




Acetone 5.77e-06 5.54e+01 1.04e-07 96%Acrylonitrile 1.32e-11 2.82e-01 4.68e-11 NFBenzene 3.56e-07 5.04e-04 7.07e-04 15%Benzo(a)anthracene 1.71e-07 3.93e+01 4.35e-09 NFBenzo(g,h,i)perylene 1.65e-07 3.93e+01 4.19e-09 NFBenzo(a)pyrene 5.40e-09 3.93e+01 1.37e-10 NFBenzo(k)fluoranthene 3.89e-08 3.93e+01 9.89e-10 NFCarbon Tetrachloride 4.29e-10 3.93e-01 1.09e-09 NFChrysene 3.59e-07 3.93e+01 9.13e-09 NFCresol, m- (methylphenol, 3-) 9.96e-06 2.77e+01 3.60e-07 59%Dibenzo(a,h)anthracene 1.42e-08 3.93e+01 3.62e-10 NFIodomethane 7.84e-07 7.75e-01 1.01e-06 NFMethanol 2.56e-07 2.77e+02 9.25e-10 99%Phenanthrene 4.06e-07 3.93e+01 1.03e-08 NFPhenol 1.18e-05 3.32e+01 3.56e-07 69%Pyrene 6.84e-05 2.12e+01 3.23e-06 NFIdeno(1,2,3-cd)pyrene 4.73e-09 3.93e+01 1.20e-10 NF



Table 9.37 Estimated hazard quotients for a bald eagleCompound Dose




9–121


Aluminum 6.66e-04 2.38e-01 2.80e-03 NFAntimony 3.44e-06 7.72e-02 4.45e-05 NFArsenic 1.95e-06 4.61e-03 4.23e-04 NFBarium 3.73e-04 9.41e+00 3.96e-05 NFBeryllium 7.55e-07 2.99e-01 2.53e-06 NFCadmium 1.30e-04 1.22e+00 1.07e-04 NFChromium (total) 1.22e-04 8.03e-01 1.52e-04 NFChromium (hexavalent) 9.55e-07 9.76e-01 9.78e-07 NFCobalt 1.57e-06 2.77e-03 5.68e-04 NFCopper 3.92e-05 3.05e+01 1.28e-06 NFLead 2.89e-04 9.79e-03 2.96e-02 NFManganese 9.18e-05 3.08e-01 2.98e-04 NFMercuric chloride (particle) 4.28e-07 1.25e-02 3.42e-05 NFMercuric chloride (vapor) 3.32e-06 1.25e-02 2.65e-04 NFMercury 0.00e+00 6.15e-03 0.00e+00 NFMethyl mercury 9.23e-03 6.15e-03 1.50e+00 NFNickel 1.05e-05 5.53e+01 1.91e-07 NFSelenium 2.20e-05 3.85e-01 5.72e-05 NFSilver 1.42e-05 3.08e-02 4.62e-04 NFThallium 1.20e-05 1.27e-01 9.43e-05 NFVanadium 1.03e-05 3.88e-01 2.65e-05 NFZinc 1.27e-03 2.20e+00 5.77e-04 NFHazard quotients above 1 are in boldface.NF - Fugitive emissions are not modeled for this compound.

9–122

Table 9.38 Weight and diet data for a kingfisher




Soil Ingestion Rate 0 kg/kg-d RTI, 1999


Diet percentages








Fish 100 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Birds 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Mammals 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

9–123

Table 9.39 Estimated hazard quotients for a kingfisherCompound Dose







Table 9.39 Estimated hazard quotients for a kingfisherCompound Dose




9–124


Aluminum 5.35e-08 5.04e-01 1.06e-07 NFAntimony 9.13e-06 1.63e-01 5.59e-05 NFArsenic 4.54e-06 9.74e-03 4.66e-04 NFBarium 1.93e-03 1.99e+01 9.72e-05 NFBeryllium 1.37e-06 6.32e-01 2.17e-06 NFCadmium 5.52e-04 2.57e+00 2.15e-04 NFChromium (total) 2.44e-06 1.70e+00 1.44e-06 NFChromium (hexavalent) 5.25e-07 2.07e+00 2.54e-07 NFCobalt 4.04e-11 5.85e-03 6.90e-09 NFCopper 1.23e-10 6.46e+01 1.91e-12 NFLead 1.27e-04 2.07e-02 6.13e-03 NFManganese 1.51e-09 6.51e-01 2.32e-09 NFMercuric chloride (particle) 5.37e-13 2.65e-02 2.03e-11 NFMercuric chloride (vapor) 1.00e-11 2.65e-02 3.78e-10 NFMercury 0.00e+00 1.30e-02 0.00e+00 NFMethyl mercury 5.01e-02 1.30e-02 3.85e+00 NFNickel 4.19e-05 1.17e+02 3.58e-07 NFSelenium 1.45e-05 8.14e-01 1.78e-05 NFSilver 7.16e-05 6.51e-02 1.10e-03 NFThallium 1.25e-06 2.69e-01 4.64e-06 NFVanadium 8.94e-11 8.20e-01 1.09e-10 NFZinc 5.61e-03 4.65e+00 1.21e-03 NFHazard quotients above 1 are in boldface.NF - Fugitive emissions are not modeled for this compound.

9–125

Table 9.40 Weight and diet data for a red fox






Diet percentages





Grain plants 0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)




Birds 13.6 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

Mammals 64.0 % Wildlife Exposure Factors Handbook (U.S. EPA, 1993)

9–126

Table 9.41 Estimated hazard quotients for a red foxCompound Dose


(mg/kg-d)Hazard

QuotientPercent of HQfrom Fugitive

EmissionsAcetone 8.37e-05 4.99e+01 1.68e-06 96%Acrylonitrile 5.22e-14 2.54e-01 2.05e-13 NFBenzene 2.70e-07 4.54e-04 5.95e-04 78%Benzo(a)anthracene 1.18e-08 3.54e+01 3.34e-10 NFBenzo(g,h,i)perylene 3.55e-09 3.54e+01 1.00e-10 NFBenzo(a)pyrene 5.40e-09 3.54e+01 1.52e-10 NFBenzo(k)fluoranthene 2.44e-08 3.54e+01 6.88e-10 NFCarbon Tetrachloride 8.81e-11 3.54e-01 2.49e-10 NFChrysene 4.99e-08 3.54e+01 1.41e-09 NFCresol, m- (methylphenol, 3-) 7.94e-06 2.50e+01 3.18e-07 98%Dibenzo(a,h)anthracene 1.47e-07 3.54e+01 4.14e-09 NFIodomethane 2.96e-07 6.99e-01 4.23e-07 NFMethanol 3.76e-06 2.50e+02 1.51e-08 99%Phenanthrene 1.75e-08 3.54e+01 4.93e-10 NFPhenol 1.75e-05 3.00e+01 5.85e-07 98%Pyrene 1.53e-07 1.91e+01 8.04e-09 NFIdeno(1,2,3-cd)pyrene 8.88e-08 3.54e+01 2.51e-09 NF



Table 9.41 Estimated hazard quotients for a red foxCompound Dose


(mg/kg-d)Hazard

QuotientPercent of HQfrom Fugitive

Emissions

9–127


Aluminum 2.00e-03 2.15e-01 9.32e-03 NFAntimony 5.33e-06 6.96e-02 7.65e-05 NFArsenic 3.51e-06 2.58e+00 1.36e-06 NFBarium 5.58e-05 8.48e+00 6.58e-06 NFBeryllium 1.20e-06 2.70e-01 4.47e-06 NFCadmium 8.12e-05 5.16e-01 1.57e-04 NFChromium (total) 2.62e-04 7.24e-01 3.62e-04 NFChromium (hexavalent) 2.45e-06 8.80e-01 2.79e-06 NFCobalt 4.36e-06 2.50e-03 1.75e-03 NFCopper 1.54e-04 3.95e+00 3.91e-05 NFLead 9.38e-04 2.38e-03 3.93e-01 NFManganese 5.20e-04 2.77e-01 1.88e-03 NFMercuric chloride (particle) 1.16e-06 1.13e-02 1.03e-04 NFMercuric chloride (vapor) 8.49e-06 1.13e-02 7.52e-04 NFMercury 0.00e+00 3.56e-02 0.00e+00 NFMethyl mercury 2.33e-07 3.56e-02 6.55e-06 NFNickel 1.14e-05 2.27e+01 5.02e-07 NFSelenium 1.05e-05 1.04e-01 1.01e-04 NFSilver 3.43e-06 2.77e-02 1.24e-04 NFThallium 3.14e-05 1.15e-01 2.73e-04 NFVanadium 2.45e-05 3.49e-01 7.01e-05 NFZinc 1.90e-04 1.98e+00 9.56e-05 NFHazard quotients above 1 are in boldface.NF - Fugitive emissions are not modeled for this compound.

9–128

Table 9.42 Weight and diet data for a red-tailed hawk






Diet percentages







Insects 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Fish 0 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Birds 26.3 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

Mammals 73.7 % Wildlife Exposure Factor’s Handbook (U.S. EPA, 1993)

9–129

Table 9.43 Estimated hazard quotients for a red-tailed hawkCompound Dose




Acetone 1.33e-05 7.07e+01 1.88e-07 96%Acrylonitrile 1.01e-13 3.60e-01 2.81e-13 NFBenzene 6.24e-08 6.43e-04 9.70e-05 87%Benzo(a)anthracene 4.03e-09 5.02e+01 8.04e-11 NFBenzo(g,h,i)perylene 2.82e-09 5.02e+01 5.61e-11 NFBenzo(a)pyrene 1.40e-09 5.02e+01 2.80e-11 NFBenzo(k)fluoranthene 7.87e-09 5.02e+01 1.57e-10 NFCarbon Tetrachloride 2.75e-11 5.02e-01 5.49e-11 NFChrysene 1.27e-08 5.02e+01 2.52e-10 NFCresol, m- (methylphenol, 3-) 1.71e-06 3.53e+01 4.84e-08 99%Dibenzo(a,h)anthracene 2.15e-08 5.02e+01 4.29e-10 NFIodomethane 5.81e-08 9.90e-01 5.87e-08 NFMethanol 5.92e-07 3.53e+02 1.67e-09 99%Phenanthrene 1.89e-08 5.02e+01 3.77e-10 NFPhenol 3.27e-06 4.24e+01 7.72e-08 99%Pyrene 1.63e-07 2.70e+01 6.05e-09 NFIdeno(1,2,3-cd)pyrene 1.11e-08 5.02e+01 2.21e-10 NF



Table 9.43 Estimated hazard quotients for a red-tailed hawkCompound Dose




9–130


Aluminum 1.76e-03 3.04e-01 5.79e-03 NFAntimony 4.84e-06 9.86e-02 4.91e-05 NFArsenic 3.16e-06 5.88e-03 5.37e-04 NFBarium 4.81e-05 1.20e+01 4.00e-06 NFBeryllium 1.28e-06 3.82e-01 3.35e-06 NFCadmium 6.85e-05 1.55e+00 4.41e-05 NFChromium (total) 2.92e-04 1.03e+00 2.85e-04 NFChromium (hexavalent) 2.29e-06 1.25e+00 1.84e-06 NFCobalt 4.21e-06 3.53e-03 1.19e-03 NFCopper 9.51e-05 3.90e+01 2.44e-06 NFLead 8.24e-04 1.25e-02 6.59e-02 NFManganese 2.67e-04 3.93e-01 6.80e-04 NFMercuric chloride (particle) 1.14e-06 1.60e-02 7.14e-05 NFMercuric chloride (vapor) 8.82e-06 1.60e-02 5.52e-04 NFMercury 0.00e+00 7.85e-03 0.00e+00 NFMethyl mercury 2.23e-07 7.85e-03 2.84e-05 NFNickel 9.41e-06 7.06e+01 1.33e-07 NFSelenium 2.98e-05 4.91e-01 6.06e-05 NFSilver 2.74e-06 3.93e-02 6.96e-05 NFThallium 3.13e-05 1.63e-01 1.92e-04 NFVanadium 2.60e-05 4.95e-01 5.26e-05 NFZinc 3.86e-04 2.81e+00 1.38e-04 NFHazard quotients above 1 are in boldface.NF- Fugitive emissions are not modeled for this compound.

10–1

10 ConclusionsLone Star Industries operates a cement kiln near Greencastle, Indiana which, as part of it’s operation,disposes of hazardous wastes generated by various other industries and manufacturers by combustingthis material within the kiln. The facility is subject to a number of different regulations andrequirements designed to ensure that any pollutants are released in small enough quantities such thatthey do not adversely affect the health of nearby residents or harm the environment. Most of thechemicals emitted from the LSI/Greencastle plant originate from the limestone feedstock and theplant’s primary fuel (coal), and they are typical of cement kiln emissions. However, because thefacility burns combustible liquids that qualify as hazardous wastes, the U.S. EPA requires that anextensive and conservative multi-pathway risk assessment be performed to estimate the potentialhazards the emissions may pose on the nearby population and environment.

Using average measured, maximum measured, and maximum permissable emission rates forchemicals released from the LSI/Greencastle facility, several series of fate and transport models wereemployed to predict the resulting concentrations and distribution of the chemicals throughout thenearby environment. The estimated concentrations of these chemicals are then used to evaluate theirpotential to impact the health of three hypothetical groups of people that could encounter higher-than-average exposure to chemicals released by the LSI/Greencastle facility: nearby residents, subsistencefarmers, and subsistence fishers. The final step of the risk assessment per se is the calculation ofexcess lifetime cancer risks and non-cancer health hazards for each of the chemicals and exposurescenarios. To insure that the models do not underestimate the risks and hazards associated with theplant’s emissions, most uncertainties in the modeling are resolved in a manner that over predicts theconcentrations and effects that are likely to occur. The modeling is thus designed to make high-endestimates of the degree to which people’s health may be impacted to chemicals released by theLSI/Greencastle facility.

Similar to the human health assessment, risks to the environment were examined using two genericscenarios to evaluate general risks, and nine specific scenarios were examined to focus on animalsthat are known to be sensitive to pollutants due to the animals’ high dietary intake rates.

The highest estimated incremental cancer risk associated with average measured emissions from theLSI/Greencastle facility is 1 in 1,000,000 for subsistence farmers. This risk is an order of magnitudelower than the regulatory benchmark of 1 in 100,000, and represents an increase of only 0.0002 –0.0003% above the background, overall risk of getting cancer (i.e.,1 in 2 for men and 1 in 3 forwomen). The total likelihood that chemicals emitted from the facility may cause adverse, non-cancerhealth effects is similarly low. The highest hazard index (the sum of the ratios of predicted exposuresto safe reference levels) is 0.02 for subsistence fishers—well below the value of one at which healtheffects might possibly occur. The hazard indices for the environmental scenarios are alsosubstantially smaller than one, so chemicals released from the LSI/Greencastle facility are notexpected to harm the environment.

10–2

These risk estimates correspond to the emissions from the LSI/Greencastle facility that weremeasured when it was operating under stressed conditions, and at full capacity. Since normalemission rates are probably lower than those measured and the facility does not always operate at fullcapacity (e.g., it is shut down for periods of maintenance each year), the long-term emission rates,and hence risk estimates, are likely lower. A series of risk estimates based on the highest emissionrates measured during facility testing are only about twice as large as the average values. This factorof two would not alter conclusions relative to typical regulatory risk criteria, as incremental cancerrisks would remain well below 1 in 100,000, and hazard indices well below one. Thus, even basingestimates on the highest measured emission rates would not lead to a prediction of risk levels ofsignificant concern.

The LSI/Greencastle facility is, however, legally permitted to release chemicals at emission ratesmuch higher than those measured. While it is not anticipated that emissions will ever approach orexceed the levels allowed by U.S. EPA and IDEM regulations, the risk assessment report actuallyfocuses on these limits, since they are of regulatory concern to the U.S. EPA. Tables 7-1 through 7-4of the risk assessment report, as well as all of Chapter 9 (the ecological risk assessment), reflect riskestimates based upon hypothetical, legally permitted emission levels. Specifically, the riskassessment evaluates risks based on emissions at the Maximum Achievable Control Technology(MACT) limits promulgated by the U.S. EPA under the provisions of the Clean Air Act. Among thecompounds subject to MACT emission limits, those that lead to the highest estimated risks whenevaluated at their MACT-based emission rates are also those whose actual emission rates are thefarthest below the MACT limits. Measured emission rates of mercury compounds are 4.2% of theMACT limit, semi-volatile metals (i.e., cadmium and lead), and hydrogen chloride/chlorine areemitted at 1.3% of the MACT limit, and measured emissions of dioxins and furans are only 0.38% oftheir MACT limit.

Some of the risk estimates based on these MACT-based emission rates exceed typical target risklevels by small margins. (1) The incremental cancer risk to the susbsistence farmer is a little less thanthree times the target of 1 in 100,000 (which itself is only a small increment above background cancerincidence levels), and (2) a few of the environmental hazard indices based on the MACT emissionlimits exceed one (reflecting the point where potential exposure levels exceed those gauged to be safewith a fair degree of certainty). The fact that these target risk levels are exceeded does not, however,indicate that the facility would present significant risks if it released chemicals at levels as high asthose of the MACT limits. As discussed in various places in the report, the risk assessmentcalculations are designed in a biased manner to overestimate actual risks in an attempt to compensatefor various uncertainties. Thus, considering numerous site-specific factors, even if the facility’semissions reached the MACT-based limits, they would not be likely to lead to risks in excess ofregulatory target levels.

The predicted incremental cancer risk for the subsistence farmer is dominated by exposure topolychlorinated dibenzo(p)dioxins and furans (PCDD/PCDFs) through ingestion of locally producedpoultry and eggs. In addition to the large uncertainties and likely overestimates inherent in thecalculation of PCDD and PCDF levels in chickens and eggs discussed in Section 8.3.3, the estimatedexposure level experienced by such a subsistence farmer is only 10 – 20% of the typical U.S. adult’sbackground exposure to PCDD/PCDFs (from the general environment and dietary intake —see Table

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7-13). This demonstrates the combined overall conservatism of the exposure estimates, cancerpotency factors, and the cancer risk benchmark of 1 in 100,000. When viewed from the perspectiveof the measured PCDD/PCDF emission rate corresponding to only 0.38% of the MACT-based limit,the additional PCDD/PCDF exposure due to LSI/Greencastle facility emissions is a small incrementrelative to the background exposure experienced by the general U.S. population.

A similar situation exists for the ecological risks predicted for two MACT chemicals — mercury andlead — that exceed the target hazard criterion of one. The exposure estimates for these twochemicals depend most strongly on the predicted levels that will accumulate in soil. The predictedconcentrations in soil, however, are in each case only a small portion of the natural background level(see Table 9.18). The implication from this finding is, as above, not that natural backgroundcorresponds to a large (and possibly unacceptable) risk, but rather that the risk assessment methodsoverestimate the risks—as expected.

Overall, it has been found that the LSI/Greencastle facility is expected to have no significant impacton the health of the local population or the local environment.

• Emissions of a wide range of chemicals from the LSI/Greencastle cement kiln havebeen measured and, even under stressed operating conditions, they are well below theU.S. EPA’s applicable emisssions’ limits.

• The highest expected personal exposures to these chemicals by direct and indirectpathways are estimated to produce less than a 0.0003% increase in the risk of cancer,and are well below the U.S. EPA’s reference dose and concentration levels fornoncancer effects.

• If the facility were to emit the chemicals of concern at the much higher emission ratespermitted under MACT regulations, a few estimated risk and hazard levels would exceede regulatory bechmarks. However, these predicted exceedences are derivedfrom fate and transport calculations that are likely to significantly overestimate boththe chemical’s exposure levels, and their associated risk-to-exposure ratios.

• In balance, even if the facility’s emissions reached the MACT-based limits, theywould not be likely to lead to risks in excess of regulatory target levels, and theimpacts from the LSI/Greencastle facility would still be indistinguishable from background.

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risk assessment for the evaluation of kiln stack emissions

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