Supplemental Risk Assessment
of Potential Air Emissions
from the Confined Disposal Facility
for the Indiana Harbor and Shipping Canal
Sediment Dredging and Disposal Project
December 2006
Prepared by
United States Environmental Protection Agency
Region 5
77 W. Jackson Blvd.
Chicago, Illinois
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AUTHORS AND CONTRIBUTORS
Waste Pesticides and Toxics Division
• Christopher Lambesis, Environmental Scientist
• Laura Lodisio, Project Manager
• Mario Mangino, Toxicologist
• Dave Petrovski, Environmental Scientist
• Todd Ramaly, Environmental Scientist
Air and Radiation Division
• George Bollweg, Environmental Health Scientist
• Phuong Nguyen, Environmental Scientist / Meteorologist
Office of Science, Ecosystems and Communities
• Carmen Maso, GIS Specialist
Office of Regional Counsel
• Rick Nagle, Associate Regional Counsel
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TABLE OF CONTENTS
EXECUTIVE SUMMARY 1
1 INTRODUCTION 1-1
1.1 Background 1-1
1.2 Purpose 1-2
1.3 Scope 1-3
2 CDF DESCRIPTION 2-1
2.1 Facility Setting 2-1
2.2 Facility Description 2-1
3 GENERAL STUDY DESIGN AND METHODOLOGY 3-1
3.1 Contaminant Releases and Contaminant Emission Rates 3-1
3.2 Air Dispersion and Deposition Modeling of Contaminants 3-1
3.3 Contaminant Toxicity Assessment and Toxicity Factor Selection 3-4
3.4 Exposure Pathways and Exposure Scenarios 3-5
3.5 Estimation of Environmental Media Concentrations and Receptor Exposure Doses..3-8
3.6 Conceptual Models 3-9
3.7 Risk Characterization 3-15
4 CONTAMINANTS OF POTENTIAL CONCERN AND CONTAMINANT EMISSION RATES ....4-1
4.1 Contaminant Identification and Contaminant Levels in Buried Sediments 4-1
4.2 Sediment Contaminant Identification and Contaminant Levels in the CDF 4-4
4.3 CDF Operating Parameters Needed as Modeling Inputs for the SRA 4-7
4.4 Chemical Contaminant Emission Rates as Modeling Inputs for the SRA 4-8
"4.4.1 Volatile Emissions from Submerged Sediments and Drying Sediments: 4-8
4.4.2 Particulate Emissions from Exposed Sediments 4-9
4.4.3 Volatile and Particulate Emission Rates Based on Regulatory Limits 4-11
4.4.3.1 Regulatory Limit-Based Volatile Emissions 4-12
4.4.3.2 Regulatory Limit-Based Particulate Emissions 4-13
4.5 Mercury Emissions 4-13
4.6 Uncertainties 4-15
5 ATMOSPHERIC DISPERSION AND DEPOSITION MODELING OF EMISSIONS 5-1
5.1 Dispersion Model 5-1
5.2 Source Information 5-2
5.3 Meteorological Data 5-5
5.4 Source Characterization Inputs 5-8
5.5 Terrain Heights 5-11
5.6 Receptor Grid 5-11
5.7 Output 5-11
5.7.1 Long-Term Average (Annual) 5-11
5.7.2 Short-Term (One-Hour) Averages 5-12
5.7.3 PM10 (24-hour Average) 5-12
5.7.4 Mercuric Chloride Vapor (Annual Average) ...5-12
5.8 Uncertainties 5-13
6 HUMAN HEALTH RISK ASSESSMENT 6-1
6.1 Toxicity Assessment 6-1
6.1.1 Toxicity Associated with Chronic Exposure 6-1
6.1.2 Carcinogenic Effects 6-1
6.1.3 Noncarcinogenic Effects 6-2
6.1.4 Special Substances or Groups of Compounds 6-3
6.1.4.1 Chlorinated Dioxins and Furans (Dioxins) 6-3
6.1.4.2 Polycyclic Aromatic Hydrocarbons (PAHs) 6-6
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6.1.4.3 Polychlorinated Biphenyls (PCBs) 6-7
6.1.4.4 Lead 6-8
6.1.4.5 Mercury 6-9
6.1.4.6 Chromium 6-10
6.1.4.7 Particulate Matter 6-10
6.1.5 Selection of Chronic Toxicity Factors 6-11
6.1.6 Toxicity Associated with Short-Term Exposure 6-16
6.1.7 Acute Inhalation Exposure Criteria Values for Potential Chemicals of Concern
from CDF Emissions 6-18
6.1.8 Toxicology Uncertainties and Limitations 6-22
6.1.8.1 Uncertainties in the Characterization of Carcinogenic Effects 6-22
6.1.8.2 Uncertainties in the Characterization of Noncancer Effects 6-23
6.1.8.3 Uncertainties Associated with Route-to-Route Extrapolation 6-24
6.1.8.4 Uncertainties Associated With Substances Without Toxicity Factor Values 6-25
6.2 Selection of Contaminants of Concern for the SRA 6-25
6.3 Exposure Assessment 6-27
6.3.1 Study Area 6-27
6.3.2 Exposure Scenarios 6-28
6.3.2.1 Local Area Resident 6-28
6.3.2.2 Local Area Student 6-28
6.3.2.3 Local Area Fisher 6-29
6.3.3 Exposure Pathways 6-30
6.3.3.1 Air Exposure 6-30
6.3.3.2 Soil Exposure 6-30
6.3.3.3 Home Garden Food Chain Exposure 6-30
6.3.3.4 Fish Consumption Exposure 6-31
6.3.3.5 Breast Milk Exposure 6-31
6.3.3.6 Surface Water Exposure 6-31
6.3.3.7 Groundwater Exposure 6-31
6.3.4 Estimation of Contaminant Concentrations in Environmental Media 6-32
6.3.4.1 Estimation of Contaminant Concentrations in Soil 6-32
6.3.4.2 Estimation of Concentrations in Vegetation 6-34
6.3.4.3 Estimation of Contaminant Concentrations in a Water Body 6-36
6.3.4.4 Estimation of Contaminant Concentrations in Fish •> 6-39
6.3.4.5 Estimation of Contaminant Concentrations in Breast Milk 6-41
6.3.5 Estimation of Contaminant Exposure Doses 6-42
6.3.5.1 Generic Intake Dose Equation 6-42
6.3.5.2 Air Exposure 6-46
6.3.5.3 Soil Contaminant Ingestion 6-47
6.3.5.4 Food Consumption 6-47
6.3.5.5 Exposure Frequency 6-49
6.3.5.6 Exposure Duration 6-49
6.3.5.7 Dermal Exposure to Soil 6-50
6.3.5.8 Breast Milk Consumption 6-57
6.3.5.9 Intake of Lead: IEUBK Model for Lead 6-58
6.4 Risk Characterization and Results 6-61
6.4.1 Modeling Methodology 6-61
6.4.2 Methodology for Estimating Cancer Risk 6-61
6.4.3 Methodology for Estimating Noncancer Health Risk - Hazard Quotient 6-62
6.4.4 Estimates of Cancer Risk and Hazard Index using IRAP-h 6-64
6.4.4.1 Local Resident Scenario 6-66
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6.4.4.2 Local Fisher Scenario 6-68
6.4.4.3 Local Area Student Scenario 6-72
6.4.5 Intake of Lead: Uptake-Biokinetic Model for Lead 6-73
6.4.6 Margin of Exposure Evaluation for Dioxin Intake 6-76
6.4.6.1 Breast-Feeding Infant 6-77
6.4.6.2 Local Adult Resident 6-78
6.4.7 Early Lifestage Exposure and Effects 6-80
6.4.7.1 Purpose, Scope, and Limitations 6-80
6.4.7.2 Children's Health Considerations: General USEPA Approach 6-80
6.4.7.3 Toxicity: Agents with Carcinogenic Effects 6-81
6.4.7.4 Toxicity: Agents with Noncarcinogenic Effects 6-85
6.4.7.5 Toxicity: Approach for SRA Chemicals 6-86
6.4.7.6 Toxicity: Limitations and Uncertainties Related to "Children's Health" 6-86
6.4.7.7 Toxicity: Limitations and Uncertainties Related to Noncancer Effects of PCBs.
.: 6-86
6.4.7.8 Exposure Assessment for Early Lifestages: Child and Student Exposure
Scenarios 6-87
6.4.7.9 Summary: Early Lifestage Exposure and Effects 6-87
6.4.8 Short-Term Inhalation Exposure 6-87
6.4.8.1 Chemical Contaminants 6-88
6.4.8.2 Particulate Matter (as PM-10) 6-92
7 SUMMARY AND CONCLUSIONS 7-1
7.1 Introduction 7-1
7.2 Expression of Chronic Health Risks 7-2
7.3 Criteria for Determining the Significance of Chronic Health Risks 7-3
7.4 Summary and Significance of Estimated Cancer Risks 7-4
7.4.1 Local Area Resident 7-4
7.4.1.1 Inhalation 7-5
7.4.1.2 Soil Ingestion 7-5
7.4.1.3 Home Garden Consumption 7-6
7.4.1.4 Fish Consumption 7-7
7.4.1.5 Dermal Absorption 7-8
7.4.2 Local Student 7-8
7.5 Summary and Significance of Estimated Hazard Index Results 7-8
7.5.1 Local Area Resident 7-8
7.5.1.1 Inhalation 7-9
7.5.1.2 Home Garden Consumption 7-9
7.5.1.3 Fish Consumption 7-10
7.5.2 Local Student 7-10
7.6 Early Lifestage Differences in Contaminant Exposure and Toxicity 7-10
7.7 Criteria for Determining the Significance of Lead Emissions 7-11
7.8 Summary and Significance of Estimated Lead Emissions 7-11
7.9 Margin of Exposure Evaluation for Dioxin Intake 7-13
7.9.1 Breast-Feeding Infant 7-14
7.9.2 Local Adult Resident 7-15
7.10 Summary and Significance of Short-Term Inhalation Exposure to CDF Emissions..7-16
7.10.1 Chemical Contaminants 7-16
7.10.1.1 Particulate Matter 7-18
7.11 Conclusions 7-19
8 REFERENCES 8-1
9 LIST OF ACRONYMS AND ABBREVIATIONS 9-1
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LIST OF FIGURES
Figure 2-1
Figure 3-1
Figure 3-2
Figure 3-3
Figure 3-4
Figure 3-5
Figure 4-1
Figure 4-2
Figure 4-3
Figure 4-4
Figure 5-1
Figure 5-2
Figure 5-3
Figure 6-1
LIST OF TABLES
Table 4-1
Table 4-2
Table 4-3
Table 5-1
Table 5-2
Table 5-3
Table 5-4
Table 5-5
Table 5-6
Table 6-1
Table 6-2
Table 6-3
Table 6-4A
Table 6-4B
Table 6-5
Table 6-6
CDF Facility Layout Plan
Indiana Harbor CDF Supplemental Risk Analysis Receptor Grid
Nodes and Receptor Neighborhoods
Generic Conceptual Model of How Air Toxics Releases May
Result in Injury or Disease
Conceptual Model for Local Area Resident
Conceptual Model for Local School Student
Conceptual Model for Local Area Fisher
Sediment Sampling Locations in Indiana Harbor Canal Used to
Obtain Chemical Contaminant Data
Two-Year Operating Cycle and Emissions
Difference in Total Particle Deposition in for Constant Versus Variable
Emission Rates
Difference in Particle Air Concentration for Constant Versus Variable
Emission Rates
Wind Rose Plot for Five Years (1987-1991) of On-Site Meteorological
Data, AMOCO TOWER Monitoring Site, IN
Wind Rose Plot for Five Years (1987-1991), NWS Data,
Chicago/O'Hare INT'L ARPT, IL
Percentages of Land Use Within 3 km of the CDF
Supplemental Risk Assessment Study Area
Summary of Chemical Constituent Data from Buried Sediments -
Indiana Harbor and Canal
Identification and Summary of Analytical Data on PCOCs in Buried
Sediments
Modeling Approach for Mercury Species
Selected Characteristics of Particle Size Categories
Wet Scavenging Coefficients by Particle Size
Details of Model Runs for Scenarios One and Two
Surface Characteristics at the CDF Site
Land Use Within 3 km of the CDF (1992 Data)
Source Input Data
Toxicity Factors for the PCOCs Identified in the SRA
Acute Inhalation Exposure Criteria Values for PCOCs in the SRA
Hydrologic Parameters for the Water Bodies Selected for Evaluation
in the SRA
Exposure Factors and Intake/Contact Rates for Environmental Media
- Local Area Resident and Local Area Fisher Scenarios
Exposure Factors and Intake/Contact Rates for Environmental Media
- Local Area Student Scenario
Dermal Absorption Fraction (ABS) from Soil for the COCs in the SRA
Summary of Gastrointestinal Absorption Efficiency and
Recommendations for Adjustments of Toxicity Factors for Specific
Chemicals
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Table 6-7
Table 6-8
Table 6-9
Table 6-10
Table 6-11
Table 6-12
Table 6-13
Table 6-14
Table 6-15
Table 6-16
Table 6-17
Table 6-18
Table 6-19
Table 6-20
Table 6-21
Table 6-22
Table 6-23
Table 6-24
Table 6-25
Table 6-26
Table 6-27
Table 6-28
Table 6-29
Input Values for the IEUBK Lead Model
Local Adult Resident Cancer Risk - Exposure Pathway Estimates
Local Child Resident Cancer Risk - Exposure Pathway Estimates
Local Adult Resident Hazard Index - Exposure Pathway Estimates
Local Child Resident Hazard Index - Exposure Pathway Estimates
Estimated Cancer Risk and Hazard Index from Local Fish
Consumption
Estimated Cancer Risk and Hazard Index from Local Fish
Consumption
Child Resident Fisher Cancer Risk - Exposure Pathway Estimates
(Fish Obtained from Lake George)
Adult Resident Fisher Hazard Index - Exposure Pathway Estimates
(Fish Obtained from Lake George)
Child Resident Fisher Hazard Index - Exposure Pathway Estimates
(Fish Obtained from Lake George)
Adult Resident Fisher Cancer Risk - Exposure Pathway Estimates
(Fish Obtained from Powderhom Lake)
Child Resident Fisher Cancer Risk - Exposure Pathway Estimates
(Fish Obtained from Powderhom Lake)
Adult Resident Fisher Hazard Index - Exposure Pathway Estimates
(Fish Obtained from Powderhom Lake)
Child Resident Fisher Hazard Index - Exposure Pathway Estimates
(Fish Obtained from Powderhom Lake)
Local Area Student Cancer Risk and Hazard Index - Exposure
Pathway Estimates
Estimated Incremental Increases in Soil and Air Lead Concentrations
Due to Particulate Lead Emissions from the Confined Disposal Facility
Summary of IEUBK Model Results for Child Exposure to Lead
Margin of Exposure Estimate for Average Daily Dose of Dioxin in
Breast-Feeding Infant
Margin of Exposure Estimate for Average Daily Dose of Dioxin in
Resident Adult
Highest Predicted One-Hour Air Concentrations and Acute Inhalation
Hazard Quotients for Naphthalene
Contaminant-Specific Hazard Quotients for Highest One-Hour Air
Concentrations at the School Zone
Short-Term Acute Inhalation Hazard Index Values for Each Area
of Interest
Maximum Short-term Air Concentration of PM10 for Each Area of
Interest
LIST OF APPENDICES
Appendix 1-1 Peer Review Members and Biographies
Appendix 1-2 Charge to the Peer Reviewers
Appendix 1-3 Response to Peer Review Comments
Appendix 4-1 Particle Emission Model Report
Appendix 4-2 Regulatory Emission Limits
Appendix 4-3 Regulatory Emission Limit Approach to Model
Appendix 4-4 Operations USACE Information, Including Drawings
Appendix 4-5 Particle Simulated Hourly Emissions
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Appendix 4-6
Appendix 4-7
Appendix 4-8
Appendix 4-9
Appendix 4-10
Appendix 4-11
Appendix 4-12
Appendix 4-13
Appendix 4-14
Appendix 4-15
Appendix 5-1
Appendix 5-2
Appendix 5-3
Appendix 5-4
Appendix 5-5
Appendix 5-6
Appendix 5-7
Appendix 5-8
Appendix 5-9
Appendix 5-10
Appendix 5-11
Appendix 5-12
Appendix 5-13
Appendix 5-14
Appendix 6-1
Appendix 6-2
Appendix 6-3
Appendix 6-4
Appendix 6-5
Appendix 6-6
Appendix 6-7
Appendix 6-8
Appendix 6-9
Appendix 6-10
Appendix 6-11
Appendix 7-1
Particle Simulated Emissions Scaled to 25 TPY
Particle Simulated Emissions with Mitigation Techniques
Volatile Correspondence and Emission Spreadsheet
Volatile Divalent Mercury Vapor Flux Calculation
Particle Emission Model Peer Review References
Operations Model Sensitivity to Release Height
Operations Model Sensitivity to Remote Operations versus CDF
Particle Emission Model Sensitivity Analysis
Particle Double Check of Simulated Emissions
Operations'Cell Dimensions, Area, and Capacity Calculations
Particle Hourly Emission Rate File
Volatile Hourly Emission Rate File
Missing Meteorological Data
Five Years of Meteorological Data
MPRM Input
ISCST3 Receptor Grid
ISCST3 Annual Input Files
ISCST3 Annual Plotfiles
ISCST3 One-Hour Average Input Files
ISCST3 One-Hour Average Plotfiles
ISCST3 24-Hour PM-10 Input Files
ISCST3 24-Hour PM-10 Plotfiles
ISCST3 Divalent Mercury Vapor Input
ISCST3 Divalent Mercury Vapor Plotfiles
Media Concentration Algorithms
Soil and Garden Parameters
COPC-Specific Parameters
Exposure Dose Algorithms
IEUBK Lead Metal Output
Dioxin TEQ Infant ADD (All Zones)
Dioxin TEQ Adult ADD (All Zones)
Application of ADAFs: Six-Year PAH Exposure (Child)
Application of ADAFs: 30-Year PAH Exposure
IRAP Output Files
I RAP Project Archive
COPC Cancer Risk and Hazard Quotient by Pathway
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EXECUTIVE SUMMARY
In order to maintain channel depths in the Indiana Harbor and Shipping Canal (IHSC), the
United States Army Corps of Engineers (USACE) must periodically dredge the bottom
sediment. The harbor was last dredged in 1972. Because the sediment contains a variety of
pollutants, it must be handled and disposed of properly. USACE is currently constructing a
confined disposal facility (CDF) for the sediment in East Chicago, Indiana. The site consists of
about 168 acres of land and was formerly operated as an oil refinery for many years. Dredging
is expected to begin in 2009 and continue for 30 years.
In September 1998, USACE submitted a Comprehensive Management Plan for the proposed
construction of a CDF in East Chicago, Indiana for disposal of dredged sediments from the
IHSC. This included a Feasibility Study (FS) and Environmental Impact Statement (EIS). Due
to the concern of risks posed by construction and operation of a CDF, the United States
Environmental Protection Agency (USEPA) conducted a risk assessment for USACE that was
finalized in 1995 and included in the EIS. The 1995 risk assessment reported that the total
cancer and noncancer hazard risks due to inhalation of potential emissions from the CDF are
within the risk range that USEPA considers acceptable.
Because the public raised concerns about the 1995 health risk assessment and because risk
assessment methods have evolved and advanced since 1995, USEPA agreed to perform
additional risk study and calculations to provide additional information regarding potential
exposures from the CDF. USEPA met'with concerned residents and the public on several
occasions to discuss the supplemental risk assessment and describe the approach that was
used.
The purpose of the supplemental risk assessment (SRA) is to estimate potential health risks
from the incremental emissions from the CDF. It does not attempt to estimate cumulative health
risks from other existing background exposures. The methodology of the study generally
followed the 2005 EPA Human Health Risk Assessment Protocol for Hazardous Waste
Combustion Facilities. As described in detail in the report, the SRA approach included several
components, in the following general sequence:
• Estimation of sediment contaminant concentrations
• Estimation of contaminant releases (emission rates)
• Air dispersion and deposition modeling of contaminants
• Contaminant toxicity assessment and toxicity factor selection
• Selection of exposure pathways and exposure scenarios
• Estimation of environmental media concentrations and human exposures
• Quantified risk and hazard.
Information utilized in the study included:
• 53 chemicals of potential concern
• Site-specific CDF operating parameters and schedules
• Five years of meteorological data from three nearby meteorological towers, including
hourly wind speed, wind direction, and temperature to account for seasonal and climatic
changes
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• Compliance limits on emissions that the facility will be required to meet (25 tons per year
volatiles and 25 tons per year particulate matter), which were not in effect at the time of
the 1995 study.
•
The following exposure scenarios were considered for cancer and noncancer health effects:
• Adult residents in six nearby neighborhoods
• Child residents in six nearby neighborhoods
• Students at local schools
• Local fishers (adults and children)
• Nursing infants.
Specifically, the SRA evaluated the following:
• Chronic inhalation exposures
• Acute inhalation exposures
• Chronic home-grown produce ingestion exposures
• Chronic incidental soil ingestion exposures
• Chronic fish consumption exposures
• Chronic dermal absorption exposures
• Early life stage differences.
Conclusions
The results of the SRA provide an estimate of cancer risks, noncancer hazard index results,
early life-stage differences in exposure and toxicity, lead exposure, dioxin exposures and acute
inhalation risks.
The risk of developing cancer is expressed as the chance or probability that an individual will
develop cancer sometime during their lifetime from exposure to pollutants from the CDF. Using
high-end exposure scenarios, the risk of developing cancer for an individual adult or child
resident living near the CDF is estimated not to exceed 1.4 people in 100,000 people
(expressed mathematically as 1.4 x 10"5). The high-end cancer health risk found in the SRA is
considered relatively low and below EPA's established risk level (less than 1.0 x 10"4).
For non-cancer health effects, the study's results show that no individual chemical displays a
"hazard quotient" above a level of 1.0. A hazard quotient indicates the extent to which an
estimated level of chemical exposure is expected to cause adverse health effects. The hazard
quotient is a ratio obtained by comparing the estimated chemical exposure level to a safe or "no
effect" exposure level that should not cause serious illness even over the long term. A hazard
quotient is determined for each chemical through each exposure pathway. The hazard quotients
for all chemicals are then added, and the combined hazard quotients are called the "hazard
index" for that exposure pathway.
For an estimated hazard index of less than 1.0, EPA will generally recommend no further action;
for an estimated hazard index greater than 1.0, EPA will generally recommend some sort of
action to cut down on the possible exposure to pollutants and reduce health risk. The total
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hazard index for all the CDF chemicals combined is below 1.0 (highest HI Scenario, Adult
Fisher HI = 0.265).
EPA evaluated possible lead exposure from the CDF. Lead can act as a developmental
neurotoxin; therefore, lead exposure in young children is a significant health concern. Potential
exposure to lead releases from the CDF could occur as the result of wind-blown particles
landing on soil in the vicinity of the site. Exposure to lead emissions cannot be evaluated the
same way that cancer and non-cancer risks are estimated. Instead, EPA uses a computer
model that estimates possible increases in blood lead levels for children living near a lead
source. The model showed that potential lead releases from the CDF will not cause significant
increases in child blood lead levels.
EPA evaluated dioxin exposure from the CDF. For local adult and child residents, dioxin
exposure is assumed to occur from consumption of locally caught fish, consumption of garden
vegetables, incidental soil ingestion and dermal absorption. For infants up to 1 year of age,
dioxin exposure is assumed to occur through breast milk consumption. The dioxin exposure
estimates from the CDF were compared with expected U.S. average background exposure
levels for adults and breast-feeding infants. The dioxin exposures estimated to occur from CDF
emissions are much lower than the national background averages. Therefore, the estimated
dioxin emission released from the CDF is not expected to significantly increase health risks
compared to the existing background situation. In addition, potential cancer risk from dioxin
exposure was also evaluated for adult and child residents.
EPA conducted a limited evaluation of potential early lifestage exposure and effects.- This study
attempts to quantify how much more sensitive exposed children are to pollutants than exposed
adults. The study presents one exposure pathway (soil ingestion) to give a quantitative
illustration showing the extent to which estimated cancer risk could increase under assumptions
of increased childhood susceptibility to a particular type of carcinogenic agent. The study used
age-dependent adjustment factors for sediment contaminants that have a mutagenic mode of
carcinogenicity action. The early lifestage exposure study results show estimated cancer risk
for exposure to these chemicals during ages zero to six years through the soil ingestion
pathway produces approximately a three-fold increased cancer risk (from 1.6 x 10"6 to
5.2 x 10"6).
Finally, the SRA examined acute inhalation exposure from CDF contaminants. When compared
with levels of pollutants that can cause illness, the study shows the health risks from breathing
short-term concentrations of contaminated dust and vapor from the CDF are relatively low.
The Indiana Department of Environmental Management has set limits on the amount of air
pollution that can be released from the site. The Army Corps of Engineers will conduct modeling
in order to show that CDF emissions conform to these limits. The Corps will also operate
monitors around the site to measure contaminants coming from the CDF. If the site does not
exceed these air pollution limits, the health risks should not increase.
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1 INTRODUCTION
1.1 Background
The United States Army Corps of Engineers (USACE) is authorized to operate and maintain a
navigation project at Indiana Harbor in East Chicago, Lake County, Indiana, to allow for
passage of ship traffic in the harbor and shipping canal. Northwest Indiana is part of a highly
industrialized urban area, which is one of the nation's foremost locations for integrated steel
production and a wide range of other manufacturing and petroleum refining activities.
Sediments, many of which are contaminated from previous industrial discharges, have entered
the Grand Calumet River/Indiana Harbor and Shipping Canal (GCR/IHSC) waterway and have
been deposited in the channel, reducing depth and restricting the movements of navigational
traffic. In order to maintain authorized channel depths, these sediments must be dredged
periodically. Because these sediments are contaminated with a variety of pollutants, they must
be disposed of properly. Local residents and others in the area have expressed concern about
air pollutant emissions and potential health consequences from the USACE-operated disposal
site that is under construction.
Indiana Harbor - View from Lake Michigan
In September 1998, USACE submitted a Comprehensive Management Plan for the proposed
construction of a confined disposal facility (CDF) in East Chicago, Indiana for disposal of
dredged sedments from the IHSC. This included a Feasibility Study (FS) and Environmental
Impact Statement (EIS). Due to the concern of risks posed by construction and operation of a
CDF, the United States Environmental Protection Agency (USEPA) conducted a risk
assessment :"or USACE that was finalized in 1995 and included in the EIS. This report, titled
Inhalation Risk Analysis for Potential Air Emissions from the Proposed Confined Disposal
Facility in the Recommended Alternative for the Indiana Harbor and Canal Sediment Dredging
and Disposal Project (USEPA 1995b), was finalized on September 1, 1995.
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The study had three objectives:
1) To compare the proposed CDF particulate and volatile toxic air contaminant emissions
to emissions reported in the Toxics Release Inventory (TRI) and reported in two previous
air pollution studies in Northwest Indiana.
2) To compare the expected particulate and volatile air contaminant emissions from the
CDF to those expected from the site in the absence of the CDF.
3) To assess the human health risks posed by the inhalation of potential airborne
contaminants released from the proposed CDF.
The following is a summary of results from the 1995 study.
1) In comparison to air contaminant emissions reported in the TRI and in two previous air
pollution studies conducted by USEPA Region 5 for the area, the projected emissions
from the CDF are small—less than one percent of those reported in the inventory and
from both of the air pollution studies.
2) Exposing dredged material to air following disposal in the CDF results in emissions of air
toxics to the atmosphere that are greater than those that would occur with no activity at
the site. However, some volatile and particulate emissions from the soil at the site will
be eliminated by the construction of the CDF, because the CDF will cover a portion of
the site and prevent emission of existing soil contaminants. It was not possible to
determine if the CDF air emissions are significantly different from those posed by the
existing site.
3) The cancer risk assessment reported that, using conservative input parameters, the total
cancer risk due to inhalation of emissions from the CDF are smaller than the risks
attributable to inhalation of existing air pollutants. The cancer risk due to inhalation
exposure to CDF emissions is estimated to be 2.3 x 10"6 (2.3 in 1,000,000). Based on
air monitoring data, the total estimated cancer risk due to air toxics inhalation exposure
from other sources in the area (i.e., without including CDF emissions) for 30 years is
estimated to be 3.1 x lO"4^ in 10,000 or 310 in 1,000,000). The noncancer
assessment showed that adverse health effects from lifetime exposure to noncancer
compounds emitted from the proposed CDF are unlikely.
1.2 Purpose
USEPA completed the risk assessment (described above) for the proposed CDF for dredged
sediments from the IHSC in March 1994 and revised it in 1995. Most assumptions used in the
1995 risk assessment were attempts to err on the side of overestimating, rather than
underestimating, pollutant concentrations and resulting risk from the CDF. However, to respond
to public concerns, USEPA agreed in 2001 to perform additional risk assessment work to
supplement the existing study. This Supplemental Risk Assessment (SRA) is intended to:
1) Provide additional information regarding potential exposures from the CDF
2) Be used as a predictive tool to help evaluate potential risks from proposed future CDF
operations
3) Serve as a basis for recommending additional CDF emission controls and mitigation
measures, if necessary.
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Partly due to these limited objectives and scope (see below), SRA results are likely to be most
informative when used in conjunction with other important information, such as CDF air
monitoring data, future USACE sediment sampling and analysis; and controls and contingency
plans to mitigate CDF emissions
1.3 Scope
The SRA will estimate incremental human health risks from CDF air contaminant exposure
under certain emission, transport and exposure assumptions. There are uncertainties
associated with those assumptions, as discussed in the report. The SRA will not evaluate
"background" air pollution, nor is it designed to provide a prediction of cumulative human health
risk associated with CDF air emissions and background air contamination from other local
sources.
In keeping with the purpose and intent described in Section 1.2 above, the SRA will address the
following:
• Inhalation, ingestion and dermal exposures. In addition to inhalation, the SRA
addresses the concern that airborne particles could be deposited on the ground and
absorbed through the skin or ingested from consuming locally grown produce.
• Potential exposures and potential health effects to children. The SRA addresses the
concern that'children are more sensitive to chemical exposures than adults.
• Additional contaminants. USEPA agreed to re-evaluate the list of chemicals of concern
to assess whether additional chemicals of concern should be included.
• Potential exposures from dredging and transport of sediments. There was concern that
contaminants could be released from the dredging and transport operations, as well as,
the operation of the CDF. However, USACE has modified its dredging and
transportation operations since the time that these concerns were raised. It was
originally proposed that sediments be dredged, loaded into vehicles, and transported
over road surfaces to the CDF. It is currently proposed that the dredged sediments be
slurried and hydraulically placed directly into the CDF from a barge on the canal
adjacent to the facility. This eliminates the concern of emissions from vehicular
transportation. In addition, the surface area of the canal affected by dredging is very
small relative to the surface area of the CDF, and therefore, relatively insignificant in
terms of emissions.
• Use of more site-specific information. The SRA uses site-specific operational,
meteorological and geographic information, to the extent that it is available.
Peer Review
In accordance with the USEPA Peer Review Handbook (USEPA 2005g), this SRA report and
supporting documents have been subjected to an internal peer review by individual independent
experts from within the Agency. Appendix 1-1 identifies the peer review panel members and
provides copies of their credentials, Appendix 1-2 provides the charge to the peer review panel,
and Appendix 1-3 provides the response to peer review comments report.
1-3
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2 CDF DESCRIPTION
2.1 Facility Setting
The CDF site consists of about 168 acres of land in East Chicago (Lake County) formerly
occupied by an oil refinery, which was owned and operated by Sinclair Oil Corporation and
subsequently acquired by Energy Cooperative Industries (ECI). Sinclair Oil Corporation was
later purchased by Atlantic Richfield Company (ARCO). ECI operated for approximately 20
years at the site, which is located just north of the Lake George Canal. The site is bordered on
the east by Indianapolis Boulevard, on the north by the Cline Avenue extension, and to the west
by the former Baltimore and Ohio (now CSX) railroad. ECI filed for Chapter 11 bankruptcy
reorganization in 1987 and went into liquidation in 1989. In response to a bankruptcy court
order in 1990, operations ceased at the site and the refinery, including oil tanks, pipelines,
hazardous waste storage areas, a hazardous waste incinerator, and buildings, were completely
demolished above ground. The site was leveled, cleared of debris, covered with topsoil and
seeded; however, there was no remediation of sub-surface on-site contamination.
2.2 Facility Description
The CDF, when constructed, will cover about 95 percent of the site north of the Lake George
Canal. It will be constructed of earthen dikes using material brought in from off site. Dikes will
be constructed to a final height of approximately 33 feet above the existing ground surface. The
entire dike will be constructed of compacted clay. A soil bentonite slurry wall has been
constructed beyond the outside toe of the dike to a clay strata approximately 33 feet below
ground surface. See Figure 2-1.
A groundwater collection system will be constructed on the inside of the bentonite slurry wall.
This groundwater collection system, composed of perforated drain pipes along three sides of
the CDF site, will be connected to sump pits and an on-site wastewater treatment system.
Approximately 4.8 million cubic yards of sediment will be dredged using a mechanical
(clamshell) dredge with modifications to the bucket to minimize resuspension of contaminated
sediments into the water column. The dredged material will be lowered into barges or scows
and transported to a location near the CDF site, where water will be added to create a desired
consistency that will enable it to be slurried into the CDF disposal cells. The CDF facility will be
divided into two disposal cells and a smaller water equalization basin.
Dredged sediment slurry deposited in the CDF will be offloaded at the north side of the CDF and
gravitationally flow toward the south. Trenches will be dug in the dredged material along the
dikes to facilitate dewatering. An adjustable weir will be installed in each cell to control the
distribution of water. A pump in each decant structure will pump the water from the decant
structure to the equalization basin. The effluent from the equalization basin will also be treated
at the on-site wastewater treatment system.
The wastewater treatment system effluent will be discharged to the Lake George Branch of the
IHSC, pursuant to a National Pollutant Discharge Elimination System (NPDES) permit issued by
the Indiana Department of Environmental Management (IDEM). After the CDF is filled (i.e., in
approximately 30 years), it will be capped with three feet of clay, six inches of sand drainage
layer, and two feet of clean fill; overlain by six inches of topsoil; and seeded. Post-closure
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groundwater monitoring will be conducted to ensure that the integrity of the CDF is maintained
to prevent releases to the environment.
View from the South of the CDF Site (North of Canal) Prior to Construction;
Lake Michigan in Background
2-2
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3 GENERAL STUDY DESIGN AND METHODOLOGY
The SRA consists of a combination of several procedural steps and methodologies to derive
quantitative estimates of health risks from potential exposure to contaminants released from the
CDF. The following sections provide a preview and summary of the key steps, methodologies,
and assumptions used in the SRA.
3.1 Contaminant Releases and Contaminant Emission Rates
Chemical contaminants available for release after dredging and disposal to the CDF are
currently located in the IHSC (referred to as the "project area") in the form of buried sediments.
Since the dredging project has not yet been initiated, data on contaminant identification and
concentration levels in buried sediments were used as the starting point for predicting the
contaminant concentration levels in the CDF sediments after the project starts. USEPA
reviewed the available data record (i.e., "historical data") on sediments in the project area to
select data sets that were judged to most appropriately represent the chemical identity, location,
and characteristics of sediments planned for dredging and placement in the CDF.
After sediments are placed in the CDF, contaminant releases could occur in the form of volatile
emissions and particulate emissions. Published theoretical models (supported by limited
empirical data) indicate that volatilization occurs primarily from submerged sediments and wet
exposed sediments, and that volatilization becomes negligible as the sediments become fully
dry. By contrast, particulate emissions from soils/sediments are known to be practically
negligible from wet sediments and to be maximized from dry sediments.
For development of the SRA, available published models for predicting volatile and particulate
emission rates from sediments were reviewed. USEPA, USACE, and independent scientists
who have developed and published the models, reviewed and discussed the major advantages,
disadvantages, and uncertainties inherent in the theoretical models. During these discussions,
it was determined that, as part of the operating requirements of the CDF, the emission levels for
both volatile and particulate emissions would need to comply with a specific total annual limit
designated by a State of Indiana air emission regulation. Based on this regulation, emission
rates of contaminants were derived by setting the annual emissions of volatile contaminants and
particulate matter to 25 tons for each category. In this way, the most advantageous aspects of
emission rate models and regulatory emission limits were combined to devise strategies for
modeling the emission rates of volatiles and particulates for use in the SRA.
3.2 Air Dispersion and Deposition Modeling of Contaminants
Chemical contaminants that become airborne from the surface of the CDF after release as
volatiles or particulate matter will disperse in the ambient air and become available for
deposition to the ground surface through a number of processes including dry deposition, wet
deposition, and vapor deposition. At any given time, the direction and distance of contaminant
transport will be governed by several meteorological factors including wind speed, wind
direction, air temperature, solar radiation level, and precipitation events. Since disposal of
sediments to the CDF has not started, direct monitoring (i.e., trapping and measurement) of
contaminants cannot be performed. Instead, the air dispersion, transport, and deposition of
contaminants must be predicted by a model system that accounts for the meteorological factors
described above, and also incorporates local (i.e., site-specific) meteorological data and local
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data on terrain elevations (i.e., land heights and land shape) to the extent possible. Air
dispersion models are mathematical constructs that simulate the physical processes occurring
in the atmosphere that directly influence the dispersion of vapor phase and particulate
emissions from a point source or an area source. These mathematical simulations are coded
into computer programs to facilitate the computational process.
The USEPA peer-reviewed Industrial Source Complex Short-Term 3 (ISCST3) Model ("Model")
was employed for this project. This computerized software model estimates air concentration
levels of contaminants and the rates of contaminant deposition onto local soil and local water
bodies. ISCST3 was originally designed for estimating air dispersion and transport from point
sources such as stack emissions from waste combustion facilities, area sources, and line and
volume sources. For this application, the Model was adapted to treat the CDF as an "area
source" containing two distinct sections, or "cells," with the actual dimensions planned for the
CDF. In the basic Model configuration, the CDF was placed at the center of ten kilometer by ten
kilometer square grid space, which serves as the study area within the Model software program.
The Model then used the available data on contaminant emission rates, local meteorology, and
local terrain as input data to predict the contaminant air concentrations and deposition rates at
each receptor grid point for a large array of grid points spaced at specific intervals within the
study area. The Model output data, in the form of digitized (numerical) air concentration and
deposition rates at each grid point, were stored as a set of computer files that were utilized in
the exposure pathway analysis procedure of the SRA.
The guidance for evaluating risk from combustion sources recommends using an array of
receptor grid nodes covering the area within ten kilometers of the facility, with the origin at the
centroid of a polygon formed by the stack emission sources (USEPA 2005c). The guidance
gives an example wherein a Cartesian grid with nodes spaced 100 meters apart extends three
kilometers from the origin, and grid nodes spaced 500 meters apart extend from three
kilometers to ten kilometers from the origin. Consistent with this guidance, the centroid of the
two CDF sediment cells was set as the origin, and a Cartesian receptor grid was extended from
the origin. However, there was concern about the variability of the dispersion modeling in close
proximity to the CDF, due to the large size of the cells and the presence of several critical
receptor areas. Thus, a more densely spaced inner tier of receptors was generated with 50-
meter spacing. After obtaining confirmation that the grid was sufficient to capture all critical
receptor areas, the inner tier was limited to two kilometers from the origin and the outer tier was
limited to five kilometers from the origin to compensate for the computational increase
associated with the denser inner grid. See Figure 3-1 for an illustration of the receptor grid.
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Figure 3-1: Indiana Harbor CDF Supplemental Risk Analysis Receptor Grid Nodes and
Receptor Neighborhoods
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3-3
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Another feature of the Model is that it can be set up to make multiple runs that utilize different
time durations of the local meteorological data. For example, to simulate the long-term average
air concentrations of volatile and particulate contaminants, five years were modeled and annual
average air concentrations were calculated from dispersion results of this entire period. To
simulate short-term air concentrations of contaminants, the Model utilized meteorological data
associated with short-term (e.g., hours, days) weather conditions and estimated the highest
expected one-hour or one-day average. These results are useful for evaluating long-term and
short-term concentrations of air contaminants and the corresponding potential inhalation health
risks due to chronic (i.e., long-term) and acute (i.e., short-term) duration periods.
To enhance the utility of the ISCST3 Model output results for risk analysis, the SRA employed
Geographic Information System (GIS) technology to aid in visualizing the relationship between
the Model output and actual local features of concern in the vicinity of the CDF. For example,
since the exact latitude-longitude coordinates of the CDF boundaries are known, the study
area's computerized grid was placed ("overlaid") onto maps and/or photographs which also
have verified latitude-longitude coordinates. The maps and photographs can display many local
features of interest, in particular, land use designations^-residential, industrial, and agricultural
zoning; school locations; parkland locations; and water body boundaries.
3.3 Contaminant Toxicity Assessment and Toxicity Factor Selection
The toxicity assessment portion of a risk assessment combines the chemical contaminant
identification with a dose-response assessment. The primary objectives of this step of the risk
assessment process are to identify the types of toxic effects associated with each contaminant
of potential concern (COPC), characterize the conditions (e.g., route, duration) of exposure
under which these effects might occur, and assign a quantitative relationship between the
amount of exposure and the magnitude of adverse health effects. The quantitative relationship
is represented through the use of toxicity values, usually referred to in USEPA risk assessments
as "toxicity factors." Toxicity factors are developed for individual chemicals and represent the
quantitative relationship between an exposure level and a specific adverse health effect.
USEPA derives toxicity factors for two categories of health effects—cancer and noncancer
endpoints.
USEPA develops toxicity factors for specific chemical constituents after conducting reviews of
the available toxicological and health effects information contained in the scientific literature or
found in appropriate government and non-govemment studies. The preferred information
sources are verifiable reports on human health effects (e.g., epidemiological studies of workers)
from which adverse health effects can be correlated to dose levels and routes of exposure. If
verifiable human studies are not available, then dose-response studies of chemical
administration to experimental animals are used when the adverse effects observed in animals
are determined to be relevant to potential human health effects.
USEPA has already conducted and published toxicity assessments on many of the most
frequently occurring environmental chemicals and has developed toxicity factors for general use
in risk assessment. Cancer and noncancer toxicity factors for chemical substances are
published by USEPA and appear in an Internet database called the Integrated Risk Information
System (IRIS), which is maintained by USEPA (USEPA 2005d). IRIS contains chemical profiles
that summarize USEPA's assessment on the critical toxic effects of a chemical and explain the
basis for deriving toxicity factors. IRIS profiles receive both internal and external peer review
before publication. In addition, for several chemical substances with wide environmental
distribution and/or complex toxicity assessments, USEPA also publishes internally and
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externally peer-reviewed documents known as "Toxicological Reviews." When a Toxicological
Review exists for a chemical, the IRIS profile will be developed from this document. The toxicity
factors published in IRIS are routinely applied in USEPA risk assessments to promote
consistency and transparency across the various USEPA programs, and because they
represent a source of scientifically peer-reviewed information.
For certain substances or group of chemicals, the methodology that USEPA uses to assess
toxicity or derive toxicity factors is somewhat different from that described above for the IRIS
database. USEPA has adopted alternative procedures for addressing the cancer and/or
noncancer dose-response assessment for the following chemicals and chemical groups
addressed in the SRA: (1) polychlorinated dioxins and furans (dioxins), (2) polycyclic aromatic
hydrocarbons (PAHs), (3) Lead, and (4) Particulate Matter.
The SRA provides an explanation of the alternative toxicity assessment and toxicity factor
procedures that USEPA has developed for these chemicals and how the procedures were
applied.
The toxicity factors described above apply under the assumption that long-term (i.e., chronic)
exposure will be the primary scenario contributing to potential exposure for a given contaminant.
For a risk assessment, this assumption is valid when the potential site-specific exposure is
expected to occur over multiple years. This assumption is valid for the SRA since potential
releases from the CDF could occur over many years of operation. The situation is evaluated in
the SRA by using annual average air concentrations and deposition rates calculated from the
entire modeled period as inputs to the risk assessment.
However, it is recognized that fluctuations (i.e., peaks and valleys) in the actual air
concentration of a given contaminant could occur over shorter time frames within the annual
average due to variations in meteorological conditions (e.g., wind speed, temperature, cloud
cover, precipitation rates). As explained in Section 3.2, the ISCST3 Model utilized
meteorological data corresponding to short-term (e.g., hours, days) variations in weather to
estimate the highest expected one-hour or one-day average. These results are useful for
evaluating the predicted range in short-term air concentration levels, and the corresponding
potential inhalation health risks attributable to acute (short-term) duration periods. To evaluate
the potential for adverse health effects due to short-term air concentration levels of
contaminants, USEPA and other organizations have developed air concentration levels
intended to provide protection for the general population from the acute effects of many
commonly encountered air contaminants. These air concentration levels are commonly referred
to as "acute inhalation exposure criteria" or "emergency response planning guidelines." The
SRA uses these air concentration guidelines for comparison to the short-term air concentration
levels predicted by the ISCST3 Model.
3.4 Exposure Pathways and Exposure Scenarios
Chemical contaminants that are emitted from the surface of the CDF, become airborne, and
disperse beyond the boundaries of the CDF could subsequently be found in three environmental
media of primary interest: (1) ambient air as airborne vapors and airborne particulates; (2) local
soil due to wet deposition of vapor, and wet and dry deposition of particle and particle-bound
contaminants; and (3) local surface water bodies due to direct deposition of contaminants from
air and runoff of contaminants from land to surface water (see Figure 3-2 in Section 3.6).
Human contact with one or several of these environmental media could be a potential source of
exposure and intake of contaminants.
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In keeping with typical USEPA risk assessment methodology, complete exposure pathways for
potential CDF contaminants are assumed to exist for some individuals in the vicinity of the CDF.
In some USEPA risk assessments, including this one, an individual who could be exposed to
contaminants is called a receptor. A complete exposure pathway exists if the receptor has
contact with a contaminated medium and an exposure route is present that results in
contaminant intake. These receptors are assumed to have exposure to contaminants through
one or several exposure pathways that constitute an exposure scenario.
Depending on the number of contaminated media and the expected receptor behaviors in the
vicinity of the contaminant source, there could be a number of exposure scenarios selected for a
risk assessment. The following exposure scenarios were selected for the SRA after USEPA
evaluated the potential contaminant exposures expected in the vicinity of the CDF, conducted
site visits to the CDF locale, and held discussions with local citizens:
• Local Area Resident - An adult or child who lives within a known residential area in the
vicinity of the CDF. Residential areas are verified by evaluating zoning maps, United
States Geological Survey (USGS) Quadrant maps, local land use maps, and site visits.
The applicable exposure pathways are:
Inhalation of volatile contaminants and particulate contaminants
- Incidental ingestion of soil containing deposited contaminants
- Dermal contact with soil containing deposited contaminants
Ingestion of contaminants incorporated into produce from a typical home garden.
See Figure 3-3 (in Section 3.6) for a conceptual model.
• Local Area Student - A school-age child or teenager who attends school in the vicinity
of the CDF. Specific schools were selected by evaluating local maps and through site
visits. The applicable exposure pathways are:
- Inhalation of volatile contaminants and particulate contaminants during routine
school attendance
Incidental ingestion of soil during routine school attendance or as a student-
athlete
- Dermal contact with soil during routine school attendance or as a student-athlete.
See Figure 3-4 in Section 3.6 for a conceptual model.
• Local Area Fisher - An adult or child who consumes fish obtained from a local water
body and is also a local area resident. A candidate local water body is one that is
located partially or completely within the air model study area and is known to support
the habits of a recreational fisher or the nutritional needs of a subsistence fisher (high-
end fish consumer). The applicable exposure pathways are:
- High-end or subsistence consumption of fish fillets harvested from a local water
body
Exposure pathways expected for a Local Area Resident (as described above).
See Figure 3-5 in Section 3.6 for a conceptual model.
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After the exposure scenarios and applicable exposure pathways are selected, several numerical
values are assigned to quantify the level or magnitude of the receptor's exposure to
contaminants through a specific exposure pathway. These values are commonly known as
exposure factors or exposure parameters. Examples of exposure factors include rates of soil
ingestion (e.g., amount/day), frequency of soil ingestion (e.g., days/year), exposure duration
(e.g., years), and body weight. For any given exposure pathway, the applicable exposure
factors are combined with the estimated concentration of the chemical in a specific medium
(e.g., air, soil) to construct an intake equation. The equation is used to calculate an intake dose
of the chemical contaminant, and the calculation is repeated until an intake dose is calculated
for each applicable chemical in the medium.
For the SRA, exposure factors and intake equations were selected from guidance documents
that USEPA routinely applies for risk assessments. These guidance documents have
undergone both internal and external peer review, and have become the standard sources that
USEPA risk assessors employ for developing risk assessments. In many cases, the guidance
documents recommend specific default exposure factor values and intake equations that should
be applied when evaluating a specific exposure pathway. The following documents comprise
the primary USEPA guidance on exposure factors and intake equations:
1) Exposure Factors Handbook (USEPA 1997a)
2) Child-Specific Exposure Factors Handbook (USEPA 2002a)
3) Risk Assessment Guidance for Superfund, Volume I: Human Health Evaluation Manual
(Part A) (USEPA 1989)
4) Risk Assessment Guidance for Superfund, Volume I: Human Health Evaluation Manual
(Part E: Supplemental Guidance for Dermal Risk Assessment) (USEPA 2004a)
5) Human Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities
(USEPA 1998b, 2005c)
Another important concept inherent to the SRA is that it is a prospective or screening-level risk
assessment. Namely, it is an evaluation of potential health risk from exposures to contaminants
that have not been released and to exposure intakes that have not yet occurred. For
contaminant releases that actually occur from the CDF, a wide range or distribution of actual
contaminant exposure/intake levels would be possible within the entire population in the vicinity
of the CDF. The distribution of exposure will be due mainly to variability in the contaminant
concentrations (i.e., contaminant variability by location) and the variability in human exposure
factors and behaviors (e.g., variability in body weight, ingestion rate, exposure duration).
An analysis of the full range of exposure distribution in the vicinity of the CDF is beyond the
scope of the SRA. Consequently, the SRA adopted a simplified approach to modeling or
estimating contaminant exposure, which is realistic and also protective in nature. The approach
is the application of the concept that USEPA calls reasonable maximum exposure (RME). The
RME is the highest exposure that is reasonably expected to occur under the exposure scenario
that applies to a given situation. The concept of the RME was developed within the USEPA
Superfund remediation program, where the goal is to protect an individual at the high-end level
of exposure, but not at the highest possible level of exposure that could be envisioned (USEPA
2004b). Thus, the RME is intended to represent an exposure level at the high end but within the
realistic range of exposure. The high end is usually defined as that part of the exposure
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distribution that is at or above the 90th percentile, but below the 99.9th percentile. In practice, the
RME estimate for a specific scenario is constructed by setting one or more sensitive exposure
factors to their near-maximum values and employing other factors at their known or expected
mean (i.e., average) values (USEPA 1992a).
The SRA contains detailed lists and tables of exposure factors and intake equations that were
used in this risk assessment; guidance documents from which they were derived; and
justifications for factor selection, such as whether a factor is set at a high-end or mean value, in
a limited number of situations, a recommended numerical value for a specific exposure factor
was not available from published USEPA guidance. For those cases, professional judgment
was applied to select a value considered reasonable and appropriately conservative for the
exposure scenario in question.
3.5 Estimation of Environmental Media Concentrations and Receptor Exposure Doses
Individuals residing in the vicinity of the CDF facility may be exposed to chemical substances
released from the CDF through two primary mechanisms—direct and indirect exposure. The
direct exposure pathway occurs through inhalation of vapors and particles that are released to,
and remain in, ambient air. Indirect ingestion and dermal exposure pathways occur as a result
of dry and wet deposition of particles and vapor onto soil and vegetation, and subsequent
migration of these chemicals into other environmental media. For example, chemical
constituents released from the CDF that are deposited onto soil can be incorporated into
vegetation, which can then contribute to human exposure through ingestion of vegetables grown
in home gardens. Additionally, deposition of CDF chemical constituents on local water bodies
and runoff from watershed soils will result in concentrations of contaminants in surface water in
the vicinity of the facility. Deposition and runoff of chemicals to surface water could result in
uptake by fish and contribute to human exposure through ingestion of fish.
In order to assess the risk of exposure to chemical constituents emitted from the CDF, an
estimate of the concentrations of chemicals of concern in air, soil, vegetables, surface water,
and fish is necessary. The modeling of contaminant transport in air is determined through the
air dispersion and transport model (ISCST3) described earlier. For other environmental media,
USEPA risk assessments estimate media concentrations using chemical "fate and transport
models" designed to simulate the transport of substances in the environment over time. USEPA
has issued several guidance documents that cover various aspects of environmental fate and
transport processes. The SRA employs the fate and transport modeling presented in the
guidance document titled Human Health Risk Assessment Protocol for Hazardous Waste
Combustion Facilities (USEPA 2005c) ("HHRAP guidance"). USEPA Region 5 believes that this
peer-reviewed guidance provides the current and comprehensive modeling procedures.
Although originally developed for evaluating the fate and transport of chemical substances
deposited from stack gas and fugitive emissions from combustion facilities, the procedures are
applicable to a variety of situations in which chemical constituents could be released to the
environment. The HHRAP guidance provides a detailed presentation of the fate and transport
models, recommended default input values used in the models, and the basis for selecting
default values. Whenever possible, the SRA applied site-specific data rather than relying only
on conservative default values. In particular, site-specific parameters describing the hydrologic
characteristics of local water bodies were used to model the deposition and transport of
chemical contaminants into local water bodies in the vicinity of the CDF.
After the environmental media concentration estimates were completed for all the applicable
chemicals of concern, the SRA estimated contaminant doses for receptors in each exposure
3-8
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describing the hydrologic characteristics of local water bodies were used to model the
deposition and transport of chemical contaminants into local water bodies in the vicinity of the
CDF.
After the environmental media concentration estimates were completed for all the applicable
chemicals of concern, the SRA estimated contaminant doses for receptors in each exposure
scenario and through each applicable exposure pathway. This is the step in the SRA where
environmental media concentrations are combined with exposure factors and intake
equations.
3.6 Conceptual Models
The following conceptual models represent the SRA study design and methodology.
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Figure 3-2: Generic Conceptual Model of How Air Toxics Releases May Result in Injury or Disease
)
IP I!JJ
WIND DIRECTION
TRANSPORT
DISPERSION of vapors
and particulate matter
DRY DEPOSITION
WET DEPOSITION
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REENTRAINMENT
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IN FOOD
CANCER
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ESTIMATE
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INHALATION
ORGANS
NON-CANCER
HAZARD ESTIMATE
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Adults, children, and
students
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Summary of Figure 3-2
Starting at the upper left hand side of this diagram, air toxics are released from the source
(CDF) to the air and begin to disperse by the wind away from the point of release. Once
released, the chemicals may remain airborne; convert into a different substance; and/or
deposit out of the air onto soils, water, or plants. People may be exposed to air toxics by
breathing contaminated air (inhalation) or through ingestion of chemicals that can accumulate
in soils, sediments, and foods (the latter process is called bioaccumulation). People also can
be exposed to deposited chemicals via skin (dermal) contact; however, this tends to be a less
important risk factor than ingestion or inhalation. Inhalation, ingestion, and dermal absorption
are called the routes of exposure.
This description of what happens to an air pollutant once it is released into the air is called fate
and transport analysis. "Transport" evaluates how a toxic air pollutant physically moves (i.e., is
transported) through the environment. "Fate" describes what ultimately happens to the
chemical after it is released to the air (i.e., what is the "fate" of the chemical in the
environment). The results of a fate and transport analysis is an estimate of the concentration
of the air pollutant in the air, soil, water, and/or food at the point where it is contacted by a
person. The exposure assessment is the process of evaluating how human contact with the
contaminated media occurs.
In the case of an air pathway analysis, the metric representing the inhalation exposure is
called the exposure concentration (EC). For example, if benzene is released from the source
and all of this blows into a nearby neighborhood where people breathe it, the EC is the
concentration of benzene in the air that they breathe.
Once an exposure occurs, air pollutants can enter the body and exert an effect at the point of
entry (the "portal of entry") or move via the bloodstream to other target organs or tissues. The
action of a pollutant on a target organ can result in no adverse effect or a variety of harmful
effects, including cancer, respiratory effects, birth defects, and reproductive and neurological
disorders. An overall risk assessment process evaluates what people are exposed to, how the
exposure occurs, and, when combined with information about the toxic properties of the
chemicals in question, estimates the likelihood that the exposure will result in injury or disease.
Modified from Air Toxics Reference Library, Vol. 3, Community Scale Assessment
Exhibit 3-1, p. 3-2;
http://www.epa.gov/ttn/fera/data/risk/vol_3/Chapter_03_April_2006.pdf
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Figure 3-3: Conceptual Model for Local Area Resident
CDF
WET
SEDIMENTS
VOLATILIZATION
AMBIENT AIR
VOLATILES
CDF
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I
CONCEPTUAL MODEL FOR LOCAL AREA RESIDENT
"Mercuric Chloride vapor was modeled for wet and dry vapor deposition
3-12
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Figure 3-4: Conceptual Model for Local School Student
VOLATILIZATION
AIR DISPERSION
AND WIND
TRANSPORT
CDF
DRY
SEDIMENTS
WIND
EROS ON
AIRBORNE
VOLATILES
AIRBORNE
PARTICULATE
MATTER
~\
INHALATION
~sr
_/
SUBSURFACE
SOIL
DIRECT
CONTACT
DERMAL
ADSORPTION
INGESTION
4
ft
CONCEPTUAL MODEL FOR LOCAL SCHOOL STUDENT
' Mercuric Chloride vapor was modeled for wet and dry vapor deposition
3-13
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Figure 3-5: Conceptual Model for Local Area Fisher
CDF
WET
SEDIMENTS
VOLATILIZATION
CDF
DRY
SEDIMENTS
WIND
EROSION
SEDIMENTS
€
»
CONCEPTUAL MODEL FOR LOCAL AREA FISHER
' Mercuric Chloride vapor was modeled for wet and dry vapor deposition
3-14
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3.7 Risk Characterization
The risk characterization integrates information from the preceding risk assessment
components. In the risk characterization step of a risk assessment, the chemical toxicity factors
are combined with dose estimates for each of the defined exposure scenarios and
corresponding exposure pathways to make quantitative estimates of both potential carcinogenic
risks and the potential for noncarcinogenic health effects.
Beyond the quantitative aspects of the risk assessment and the tabulation of risk results, the
risk characterization is also intended to place the estimated risks in context through a discussion
of the qualitative elements of the risk assessment, including a discussion of the major factors
influencing the risk estimates, the underlying assumptions, and the rationale for these
assumptions. In addition, the risk characterization generally includes a qualitative discussion of
the uncertainty and variability associated with the quantitative results.
Because the evaluation of multiple chemicals, multiple exposure pathways, and multiple fate
and transport processes is a very challenging computational exercise, the SRA utilized a
computer software program to run the contaminant dispersion, exposure and risk modeling. For
this project, the software system called Industrial Risk Assessment Protocol - Human Health
(IRAP-h View™; abbreviated IRAP) was used. This is a commercial software package
developed by Lakes Environmental Software (Waterloo, Ontario, Canada). IRAP was expressly
designed to closely follow the recommendations, chemical-specific parameters, and fate and
transport algorithms given in the 1998 and 2005 HHRAP guidance. IRAP is a Microsoft
Windows application that can be run in the Windows 3.1, Windows 3.11, Windows 95, Windows
98, and Windows NT operating systems.1
The major features of the IRAP system that make it advantageous for conducting a risk
assessment are its capability to perform the following tasks:
• Recognize and import ISCST3 plot files containing the output from the ISCST3 air
dispersion/deposition model runs, and provide a graphical display of the ISCST3
receptor grid node locations
• Recognize and import GIS-generated land use/land cover data (e.g., residential,
farming, and water body locations)
• Define the perimeter of important exposure assessment landmark areas (e.g., residential
zones, water bodies, watersheds) using a polygon drawing tool, and identify all the
ISCST3 receptor grid nodes that fall within a selected polygon
• Eliminate the need to perform hand calculations and write multiple interconnected
computational spreadsheets
• Simultaneously calculate intake doses and risk values (i.e., cancer risks and hazard
quotients) for multiple chemicals and multiple exposure pathways.
1 USEPA does not endorse or require the use of the IRAP-h View™ computer software, but recognizes that the
developers of IRAP-h View™ made a concerted effort to design a program that would closely follow the
recommendations of the 1998 and 2005 HHRAP guidance documents.
3-15
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Whether a COPC is emitted as a vapor, particle, or particle-bound contaminant is a primary
input to dispersion modeling and deposition calculations. For stack emissions, many studies
have concluded that stack sampling techniques can be unreliable for determining the
partitioning of contaminant emissions among the three phases. Faced with a need for this
information, USEPA turned to a growing body of research focused on the partitioning of certain
contaminants in ambient aerosols and compared it to proposed partitioning models in literature.
The analytical data from this area of study is based primarily on analysis of air samples
collected from areas of similar land use (urban versus rural). Ultimately, USEPA recognized
that significant uncertainty is still associated with both approaches. Partition coefficients,
expressed as a fraction of the airborne contaminant in the vapor phase, have been developed
from this research and adopted by the Agency for partitioning stack contaminants. An integral
part of this approach is to run the dispersion model at the unit emission rate (1 gram per second
[g/s] or 1 gram per second per square meter [g/s-m2]) for all emission phases so that the
partitioning can be assigned to the node values after dispersion modeling using these partition
coefficients (Fv). Accordingly, I RAP has been developed with this feature integrated in the
calculation.
The nature of emissions from the Indiana Harbor CDF is expected to be episodic, such that the
different emission phases (vapor, particle, and particle bound) may not occur at similar
magnitudes or even simultaneously throughout the project. Thus, we believe it is
computationally inaccurate to re-partition the emissions in the same manner as suggested in the
guidance for stack emissions modeled with unit emission rates. Further investigation into the
theoretical origins of the atmospheric partitioning revealed additional reasons why the Fv
coefficients might not be applicable to CDF sediment emissions. The air sampling programs for
partitioning estimates were not designed for the evaluation of any specific source of air
contamination, but rather to assess overall conditions in areas of similar land use (usually
urban). Furthermore, the theoretical basis for the partitioning always refers to an
inexchangeable fraction of particle or particle-bound contaminants that are not available for
conversion into the vapor phase. Unfortunately, very little research has been conducted into
techniques for estimating these phenomena. Sediment contaminants weathered over many
decades could very well have a significant amount of inexchangeable contaminant mass that is
not accounted for at all in the Fv partitioning values. Moreover, key parameters used for the
theoretical development of the partitioning coefficients are representative of particles that are a
lot smaller in diameter than much of those expected to be released from the CDF.
Although some amount of Indiana Harbor sediment contaminants probably do partition after
release, the current approach in IRAP likely overestimates the partitioning because of the
uncertainty regarding inexchangeable contaminant fractions. This disparity between the sizes
of particles considered and the independent nature of how the vapors and particles are emitted
from the CDF leads us to disable the contaminant partitioning in IRAP in order to obtain the
most appropriate results. Accordingly, we defined the Fv value of contaminants primarily
emitted as vapors as 1.0 and that of contaminants emitted primarily as particles or particle
bound as 0.
Risk characterization also serves as the starting point for evaluating the significance of the risk
results. There are a variety of different benchmarks or health risk criteria that USEPA uses
when determining the significance of a cancer risk or a noncancer hazard index, depending on
the context and purpose of the risk assessment and potential risk management decisions that
may need to be made. This section discusses several criteria that may be helpful in interpreting
the results of the SRA. The SRA does not specify any single set of health risk criteria that
should be regarded as conclusive or absolute for determining the significance of the identified
3-16
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risks. This is because each set of criteria was developed in a different USEPA statutory or
programmatic context that may not exactly match with the regulatory requirements or
compliance limits that apply to operation of the CDF.
3-17
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4 CONTAMINANTS OF POTENTIAL CONCERN AND CONTAMINANT EMISSION
RATES
4.1 Contaminant Identification and Contaminant Levels in Buried Sediments
Since the dredging project has not yet been initiated, existing data on contaminant identification
and concentration levels in buried sediments were regarded as the logical starting point for
predicting the contaminant concentration levels that would be expected in the CDF sediments.
Because a number of factors are related to the operation plan for the CDF, the use of data on
chemical contaminants in buried sediments should be regarded as an approximation of the
contaminant concentrations that will exist when the CDF dredging/disposal is under way. For
example, the dredging/disposal operation will actually occur in various stages based on
geographic locations, channel geometry, and water depth within the project area.
Concentrations of chemical contaminants disposed to the CDF at any given time may vary by
the location in the IHSC where dredging occurs and the depth profile of the sediments removed.
Consequently, the SRA uses data on chemical contaminants in buried sediment to provide an
estimation of reasonable long-term average concentrations of contaminant levels that could be
expected within the CDF over the life of the project.
USEPA reviewed the available data record on chemical contaminant identification and
concentration levels in IHSC sediments. The data record contains many reports and
compilations on chemical analysis of harbor sediments collected over a span of decades based
on work by USACE, USEPA, and other organizations. The analytical reports vary in regard to
the range of selected chemical contaminants, the geographic location of sampling points within
the project area and the type of sample collected. A summary of the data record is presented in
Table 4-1. The summary provides general descriptive information on the date of the sampling
project, the type of samples, and the identity/class of targeted chemical contaminants.
The goal of the review was to identify the available sediment data reports that were best able to
partially or fully meet the following criteria:
1) Data reports on chemical contaminants that would be expected to result from sources
such as industrial discharges, combined sewer overflows, and urban runoff.
2) Data reports on chemical contaminants that would serve as potential contaminants of
concern (PCOCs) for evaluation in a risk assessment. Examples include known toxic or
hazardous chemical contaminants from the following classes: volatile organic
compounds (VOCs), semi-volatile organic compounds (SVOCs), and metals.
3) Data reports that include sampling locations providing comprehensive coverage of the
geographic areas of the Harbor and Canal that are targeted for inclusion in the
dredging/disposal project area for the CDF.
4) Data reports that include adequate descriptions of sampling locations, sample collection
methodology, and quality assurance/quality control (QA/QC) parameters (e.g., analytical
method procedures, constituent detection limits).
Based on the review, four data reports were identified that reasonably met at least three of the
four criteria set out above.
4-1
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Table 4-1: Summary of Chemical Constituent Data from Buried Sediments -
Indiana Harbor and Canal
Year
Collected
Agency
or Entity
Sample Number /
Type
Chemical
Constituents/Groups
Comments on Usability for SRA
1966
USEPA
7 / Surface grab
Organic nitrogen, total
nitrogen, phenol, sulfide, iron
Surface samples only, not
constituents for SRA, QA/QC
unknown or outdated; not useful
1971
Unknown
3 / Surface grab
9 metals, phosphorus
Surface samples only, QA/QC
unknown or outdated; not useful
1977
USEPA
13/Surface grab
11 metals, total PCBs
Surface samples only, QA/QC
unknown or outdated; not useful
1979
USACE
13 / Core
11 metals, total PCBs
QA/QC unknown or outdated; not
useful
1980
USACE
7 / Surface grab
22 metals
Surface samples only, QA/QC
unknown or outdated; not useful
1983
USACE
5 / Core
Total PCBs
QA/QC unknown or outdated; not
useful
1984
USACE
6 / Core
11 metals, total PCBs
QA/QC unknown or outdated; not
useful
1987
USACE
22 / Surface grab
7 metals, total PCBs
Surface samples only, QA/QC
unknown or outdated; not useful
1988
USACE
9 / Core
8 metals
QA/QC unknown or outdated; not
useful
1988
USACE
9 / Core
20 metals, PCBs
QA/QC unknown or outdated; not
useful
1989
USEPA-
ARCS
7 / Surface grab
Metals, PAHs, PCBs,
pesticides, dioxins
Surface samples only, known
locations, QA/QC is well documented,
important constituents for SRA;
potentially useful
1990
USEPA-
ARCS
37 / Core
7 metals
Samples not collected by water depth
measurement, known locations,
QA/QC is well documented, sample
locations relevant to dredging plan for
CDF; potentially useful
1992
USEPA
14/Core
Metals, PAHs, pesticides,
VOCs
Samples collected by water depth
measurement, known locations,
QA/QC is well documented, important
constituents for SRA, sample
locations relevant to dredging plan for
CDF; potentially useful
1993
USACE
4 / Core
PCBs, metals, PAHs
QA/QC is well documented, most
relevant data on PCBs, sample
locations relevant to dredging plan for
CDF; potentially useful
2003
USACE
5 / Surface grab
Dioxins, pesticides, metals
Composite grab sample from five
locations, QA/QC is well documented,
sample locations relevant to dredging
plan for CDF; potentially useful
ARCS - Assessment and Remediation of Contaminated Sediments
PCB - Polychlorinated biphenyl
1992 USEPA "Sediment Core Study"
In this study, USEPA conducted targeted sampling across the IHSC project area for the purpose
of characterizing chemical contaminants in sediments. A sampling methodology was designed
through the use of IHSC bathymetry (water depth) maps of the project area. Bathymetry data
indicated that the greatest accumulations of sediment within the project area occur along the
boundaries of the navigation channel and at the near-shore portions of the outer harbor.
4-2
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Greater accumulations of sediment occur in the more quiescent areas of the channel and harbor
that are the most distant from the turbulence caused by surface water flow, outfalls and ship
traffic. In addition, the quiescent areas with the most sediment accumulation will also
accumulate the finer-grained sediment material. The finer-grained material will generally
contain higher concentrations of chemical contaminants than coarse-grained material for a
variety of reasons, including: higher percentage of clay/silt sized materials; a higher fraction of
organic carbon to retain organic contaminants; and higher surface area-to-mass ratios (ratios of
particle sample surface area to particle sample mass). Consequently, sediments from
accumulation zones were assumed to be associated with higher concentrations of chemical
contaminants than elsewhere in the IHSC.
Bathymetry maps were used to select 14 sampling locations that represented local maximum
levels of sediment accumulation thickness. These samples were well distributed geographically
across the project area. At each sample location, a sediment core sample was collected, and a
five-foot length of core was homogenized for chemical constituent analysis. The chemical
constituent list included chemicals from the following classes: eight metals, 16 PAHs, six
pesticides/herbicides, and six volatile hydrocarbons. The sampling methodology was
subsequently published (Petrovski 1995). A diagram depicting the approximate sampling
locations in the IHSC project area is shown in Figure 4-1.
1993 USACE "Sediment Core Study"
In 1993, USACE performed a small characterization study of sediment samples from a limited
geographic zone of the IHSC. In this study-, sediment core samples were collected and
analyzed from four locations within the "Calumet River Branch" of the project area. (Bathymetry
data apparently were not used to select sampling locations). The primary chemical constituent
targeted in this sampling was PCBs. Additional target constituents included heavy metals and
PAHs. A diagram depicting the approximate sampling locations in the IHSC project area is
shown in Figure 4-1.
1989/1990 USEPA ARCS Study
In 1989 and 1990, USEPA conducted two sediment characterization surveys of IHSC sediments
under the Agency's ARCS Program (USEPA 1996a). The purpose of the program was to
characterize sediment quality and chemical contamination at five areas of concern around the
Great Lakes region.
In the 1989 sampling survey, only surface grab samples of sediments were obtained. The
samples were collected at seven locations (called Master Stations) distributed geographically
over the entire length of the IHSC, including the inner Harbor, the main channel, the Calumet
River Branch, and the Lake George Branch. The chemical constituent list included chemicals
from the following classes: metals, PAHs, PCBs, pesticides/herbicides, and polychlorinated
dioxins/furan congeners. A diagram depicting the approximate sampling survey locations in the
IHSC project area is shown in Figure 4-1.
In the 1990 sampling survey, sediment core samples of approximately 14 feet in length were
collected at 37 locations that were distributed over the entire length of the IHSC. The sample
locations were well distributed geographically but did not represent areas associated with known
sediment accumulation, as in the 1992 bathymetry study. The sediment cores were each
divided into four depth segments on which chemical analysis was performed. However, seven
4-3
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metals (i.e., cadmium, chromium, copper, iron, lead, nickel, and zinc) were the only constituents
analyzed in these sediment core samples; no organic constituents were analyzed.
2003 USACE "Surface Sediment Samples"
In 2003, USACE performed a small characterization study of sediment samples from a limited
geographic zone of the IHSC. In this study, sediment surface grab samples were collected from
five locations in the project area and homogenized into a single sample for analysis. The
primary chemical constituents targeted in this sampling were polychlorinated dioxins/furan
congeners. Additional target constituents included heavy metals, pesticides, and PAHs.
4.2 Sediment Contaminant Identification and Contaminant Levels in the CDF
The sediment data reports described above contain information on sample collection and
chemical constituent identity that were determined to meet a set of basic criteria for potential
use in the SRA project. However, these data reports exhibit variation in their capacity to
appropriately represent the distribution of contaminant levels geographically across the project
area and by the depth of sediments to be dredged.
PCOCs selected for the SRA are chemicals that display the following criteria: (1) expected
byproducts of industrial/commercial/urban discharges to waterways; (2) potentially toxic or
hazardous to humans; and (3) persistent in the environment, and therefore a concern for long-
term exposure and for uptake or bioaccumulation in the food chain.
Consequently, a rationale was developed to prioritize and select chemical constituent data from
the above reports to serve as an appropriate representation of chemical constituent identity and
concentration levels in the sediments after disposal of buried sediments in the CDF. The
following rationale was adopted;
1) The 1992 USEPA "Sediment Core Study" provides the most appropriate data set on
buried sediments to use for representing the long-term sediment profile in the CDF after
disposal. The data from this study on the following classes of chemical constituents
should be used to represent the identity and concentration levels of constituents in the
CDF: metals, PAHs, pesticides/herbicides, and volatile hydrocarbons.
2) The 1993 USACE "Sediment Core Study" and the 2003 USACE "Surface Sediment
Samples" provide the most appropriate source for data on PCBs in buried sediments,
and seven additional pesticides/herbicides not available from rationale number 1 above.
3) The detection of dioxins (i.e., polychlorinated dioxins/furan congeners) in sediments is
considered potentially significant for the SRA, even though they were verified only as a
surface sediment contaminant. The 1989 USEPA ARCS Study and the 2003 COE
"Surface Sediment Samples" of surface sediments should be utilized for this constituent.
The list of constituents and summary data on sediment concentration levels in buried sediments
is shown in Table 4-2. This table presents the PCOCs for the SRA, which will be discussed
further in Section 6.
4-4
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Table 4-2: Identification and Summary of Analytical Data on PCOCs in Buried Sediments
Constituents
Data Seta
Frequency
of Detection
(# Detects/
#Samples)
Arithmetic
Mean
(mg/kg)
Standard
Deviation
Comments
Metals
Antimony
1993 CORE
18/18
23.5
8.4
Arsenic
1992 CORE
16/16
75.4
40.1
Barium
1992 CORE
14/16°
159
75.6
Cadmium
1992 CORE
16/16
13.6
5.39
Chromium (total)
1992 CORE
16/16
705
369
Copper
1993 CORE
18/18
336
81.3
Lead
1992 CORE
16/16
1022
470
Manganese
1993 CORE
18/18
3374
939
Mercury
Mercury (Total)
1992 CORE
16/16
1.06
0.70
Methylmercury
1989
SURFACE
3/7°
6.0E-04
7.8E-04
Nickel
1993 CORE
18/18
165
102
Selenium
1992 CORE
16/16
3.7
1.2
Silver
1992 CORE
0/16°
<6.5
[2.7]
Not detected in any
sample
Zinc
1993 CORE
18/18
6973
2021
PAHs
Acenaphthene
1992 CORE
10/16°
21.6
36.0
Acenaphthylene
1992 CORE
5/16°
54.9
158
Anthracene
1992 CORE
10/16°
' 35.0
77.5
Benzo[a]anthracene
1992 CORE
16/16
44.1
65.7
Benzo[a]pyrene
1992 CORE
16/16
35.3
50.6
Benzo[b]fluoranthene
1992 CORE
15/16°
35.4
52.9
Benzo[k]fluoranthene
1992 CORE
15/16°
18.5
24.1
Benzo[g,h,i]perylene
1992 CORE
6/16°
25.3
48.5
Chrysene
1992 CORE
16/16
60.7
102
Dibenz[a,h]anthracene
1992 CORE
0/16C
10.6
[23.1]
Not detected in any
sample
Fluoranthene
1992 CORE
16/16
88.1
160
Fluorene
1992 CORE
13/16°
42.7
94.5
lndeno[1,2,3-cd]pyrene
1992 CORE
1/16°
94.6
228
Naphthalene
1992 CORE
16/16
478
1467
Phenanthrene
1992 CORE
16/16
171
346
Pyrene
1992 CORE
16/16
93.4
145
PCBs (total)
1993 CORE
16/16
35.6
25.3
Dioxin/Furan
Congeners'1
2,3,7,8-TetraCDD
1989/2003
SURFACE
1/8°
4.7E-05
4.0E-05
1,2,3,7,8-PentaCDD
1989/2003
SURFACE
4/8°
4.8E-05
1.9E-05
1,2,3,4,7,8-HexaCDD
1989/2003
SURFACE
O
00
8.6E-05
1.3E-04
4-5
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Constituents
Data Seta
Frequency
of Detection
(# Detects/
#Samples)
Arithmetic
Mean
(mg/kg)
Standard
Deviation
Comments
1,2,3,6,7,8-HexaCDD
1989/2003
SURFACE
8/8
1.4E-04
1.7E-04
1,2,3,7,8,9-HexaCDD
1989/2003
SURFACE
8/8
2.0E-04
1.9E-04
1,2,3,4,6,7,8-
HeptaCDD
1989/2003
SURFACE
8/8
3.1E-03
3.6E-03
OctaCDD
1989/2003
SURFACE
8/8
1.7E-02
1.8E-02
2,3,7,8-TetraCDF
1989/2003
SURFACE
8/8
2.7E-04
2.4E-04
1,2,3,7,8-PentaCDF
1989/2003
SURFACE
8/8
2.4E-05
1.6E-05
2,3,4,7,8-PentaCDF
1989/2003
SURFACE
8/8
5.7E-05
4.5E-05
1,2,3,4,7,8-HexaCDF
1989/2003
SURFACE
8/8
7.8E-05
7.3E-05
1,2,3,6,7,8-HexaCDF
1989/2003
SURFACE
O
00
CD
4.5E-05
3.4E-05
1,2,3,7,8,9-HexaCDF
1989/2003
SURFACE
8/8
2.8E-05
2.1E-05
2,3,4,6,7,8-HexaCDF
1989/2003
SURFACE
3/8°
1.9E-05
2.7E-05
1,2,3,4,6,7,8-
HeptaCDF
1989/2003
SURFACE
a
CO
8.2E-04
1.1E-03
1,2,3,4,7,8,9-
HeptaCDF
1989/2003
SURFACE
CO
o
2.0E-04
3.0E-04
OctaCDF
1989/2003
SURFACE
8/8
5.1E-03
6.4E-03
Pesticides and
Phenols
Aldrin
1993 CORE
1/1
0.045
NA
Reported detection is
from a single sample;
therefore, this is only
value that can be used
for SRA
d-BHC
1993 CORE
2/2
0.004
0.004
Apparently this
constituent is "delta-
lindane", one of several
isomers of lindane
Dieldrin
1993 CORE
16/16
0.019
0.006
DDD (dichlorodiphenyl-
dichloroethane)
1993 CORE
18/18
0.103
0.073
DDE (dichlorodiphenyl
dichloroethylene)
1993 CORE
16/16
0.038
0.013
DDT (dichlorodiphenyl-
trichloroethane)
1989/2003
SURFACE
4/8°
0.068
0.031
Endosulfan II
1993 CORE
2/2
0.038
0.004
Isomer of endosulfan;
could be evaluated in
SRA using the
chemical-physical
4-6
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Constituents
Data Seta
Frequency
of Detection
(# Detects/
#Samples)
Arithmetic
Mean
(mg/kg)
Standard
Deviation
Comments
parameters and toxicity
factors for endosulfan
Endrin
1992 CORE
0/16C
<0.05
NA
Not detected in any
sample
Heptachlor
1992 CORE
0/16C
<0.05
NA
Not detected in any
sample
Heptachlor Epoxide
1992 CORE
0/16°
<0.05
NA
Not detected in any
sample
Lindane
1992 CORE
0/16°
<0.25
NA
Not detected in any
sample
Phenol
1992 CORE
0/16C
<28.1
[61.7]
Not detected in any
sample
Toxaphene
1992 CORE
0/16C
<0.5
NA
Not detected in any
sample
VOCs
Benzene
1992 CORE
16/16
3.09
7.11
Ethylbenzene
1992 CORE
7/16°
0.74
0.96
Tetrachloroethene
(PCE)
1992 CORE
0/16°
<0.17
[0.04]
Not detected in any
sample
Toluene
1992 CORE
9/16°
4.95
14.1
Trichloroethene (TCE)
1992 CORE
0/16C
<0.25
[0.06]
Not detected in any
sample
Xylene (meta-para)
1992 CORE
9/16°
6.65
15.4
Xylene (ortho)
1992 CORE
10/16°
2.18
4.39
Footnotes:
a 1993 CORE - Data from sediment core samples collected from 4 locations by the USACE in
November 1993.
1992 CORE - Data from sediment core samples collected from 16 locations by USEPA in June 1992.
1989 SURFACE - Data from sediment surface grab samples collected by USEPA in 1989.
1989/2003 SURFACE - Combined data from sediment surface grab samples collected by USEPA and
USACE in 1989 and 2003.
b If the constituent was detected in at least one sample, the non-detects were included in the calculation
at the fuH reported detection limit.
c If the constituent was not detected in any sample, the non-detects were included in the calculation at
one-half of the reported detection limit.
d CDD - Chlorinated dibenzo-para-dioxin
CDF - Chlorinated dibenzoftjran
NA - Not applicable because the constituent was not detected in any sample and the detection limit was
identical for each sample.
[ ] - Apparent Standard Deviation calculated when the constituent was a "non-detect" in every sample
and the detection limits were not identical for each sample.
4.3 CDF Operating Parameters Needed as Modeling Inputs for the SRA
According to USACE, the CDF will comprise two sediment dewatering and containment cells
and an equalization basin to facilitate dewatering and water treatment (Thai 2005a, 2005b).
Dredged sediments will arrive at the CDF by barge and be slurried into one of the two disposal
cells, which will each be as small as 36 acres when empty and 47 acres in size when full (due to
4-7
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the sloping design of the cell walls). The cells were each modeled as 41-acre emission sources
for the SRA. The CDF cell walls will be constructed and operated in two phases. During the
first phase, the cell walls will have a constructed height of 20 feet above grade (approximately 6
meters), which will be raised to 30 feet (approximately 9 meters) for the second phase of
dredging. The 6-meter release height was used for SRA emission modeling.
The cells will be operated on a two-year cycle, receiving sediments every other year. Figure 4-2
presents a schematic of the two-year operating cycle of the CDF. According to USACE, a cell
would receive dredged sediments starting in May of a given year and it would remain or be kept
wet through August 1 of the following year, at which point it would become dry enough to emit
particles. Particle emissions would then be possible until May 1 of the third year when active
placement of dredged sediment resumes in that cell. Volatile emissions were assumed to occur
primarily during the saturated or wet periods, when the cell is receiving dredged sediment as a
slurry and when sediments dewater and dry.
Note that the period selected for Figure 4-2 is from the middle of the CDF operating cycle, such
that there would be sediments and potential emissions from both cells. This is also the way the
cells were modeled for air dispersion, except that the five years of dispersion modeling began at
the start of the calendar year.
4.4 Chemical Contaminant Emission Rates as Modeling Inputs for the SRA
During and after sediment placement in the CDF, the release of chemical contaminants can be
described by essentially two mechanisms: release of volatile contaminants into ambient air as
vapor phase contaminants, and release of low volatility and non-volatile contaminants into
ambient air as particles (i.e., "particulate matter"). Contaminants could be released as
particulate matter because the contaminants themselves are expected to be particles (e.g.,
metals), or because the contaminants are low volatility organic chemicals (e.g., PAHs,
pesticides, PCBs) that will primarily be adsorbed onto the surface of particulate matter.
To proceed with the SRA, release rates of contaminants must be defined as inputs for the air
dispersion model. Because the dredging/disposal operation for the CDF has not yet started,
release rates of volatile and particulate contaminants were assigned based on a modeling
procedure combined with applicable information regarding state regulatory emission limits, the
CDF operating parameters and climatic conditions.
4.4.1 Volatile Emissions from Submerged Sediments and Drying Sediments
The current operating scenario calls for the dredged sediments to be placed in the CDF in the
form of a slurry. The sediments will likely be submerged in water during periods of active
dredging and exposed as wet sediments during inactive periods. Mechanisms that govern
volatile emissions include desorption of contaminants from sediment to water and air, diffusion
of dissolved contaminants through sediment pores and free water, diffusion of contaminant
vapor through sediment pores, and mass transfer through evaporation at the air/water interface.
The mechanistic and quantitative aspects of the available volatilization model for sediments
have been described in detail by Dr. L.J. Thibodeaux and co-workers (Thibodeaux et al. 2004,
Thibodeaux 2005). After a review of the available models (including discussions with
4-8
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developers of published models2), it was determined that application of the full volatilization
model to operation of the CDF would be exceedingly complex. The mechanisms for
volatilization described above are dependent on time, weather, chemicals, and operations.
These consequences create significant difficulty in defining a reasonable set of conditions for
estimating volatilization rates of Indiana Harbor sediment constituents. USEPA did not possess
a ready means to simultaneously evaluate all of these variables in a way that would allow
detailed volatile emission estimates. Furthermore, while the application of these theoretical
mechanisms to actual pilot laboratory observations of sediment emissions was successful in
predicting volatilization trends, the predicted volatile chemical emission rates did not match the
actual laboratory measured rates (Thibodeaux et al. 2004, Thibodeaux 2005). Due to these
challenges, complexities and uncertainties, a basic understanding of these models was
combined with a regulatory compliance limit of 25 tons per year (TPY) in preparing the volatile
emissions estimate for the SRA (discussed further below).
4.4.2 Particulate Emissions from Exposed Sediments
Particulate emissions from the surface of the CDF can be regarded as a variant of the typical
process for wind erosion of soils. Soil erosion by wind is initiated when the local wind exceeds a
"threshold" speed that allows soil particles to become airborne and be carried to a new location.
The properties of the soil (Indiana Harbor sediment in this case), local weather, and operational
factors could all influence what the "threshold wind speed" will be for the CDF. After initiation,
the severity of an erosion event depends primarily on the wind speed duration and magnitude.
The threshold wind speed, severity, and duration of an erosion event can be altered by
modifying the roughness of the terrain, deploying different types of vegetative cover, and other
forms of mitigation to reduce or eliminate windblown particle emissions.
From a historical standpoint, the evaluation of soil erosion has been considered to be a major
challenge in the context of food crop production, land management, and soil conservation. The
U.S. Department of Agriculture - Agricultural Research Service (USDA-ARS) has been involved
in direct measurement and modeling studies of the soil erosion process for many years. USDA-
ARS developed an empirical model called the Wind Erosion Equation to predict soil erosion in
simple situations, such as a single soil type and a fixed wind speed and direction (Woodruff and
Siddoway 1965). To supplement the empirical model and to address the fact that soil erosion is
a more complex non-linear process over space and time, USDA-ARS developed a more robust
model known as the Wind Erosion Prediction System (WEPS) (Hagen et al. 1995). WEPS is a
continuous, daily time-step computer model that simulates the basic wind erosion process and
also accounts for parameters that modify a soil's susceptibility to wind erosion such as
vegetation type, surface roughness, surface crust, and soil water content. In addition, WEPS
has the ability to incorporate important site-specific information such as the basic size/shape of
the erodible source area, local meteorological data (i.e., precipitation rate, wind speed, wind
direction, humidity, solar radiation), and the addition of mitigation controls (e.g., vegetative
cover, hedgerows, fences).
2 The developers of this SRA in cooperation with USACE, held a number of discussions with Dr. Louis Thibodeaux
and co-workers at Louisiana State University on the application of models to simulate the volatilization of chemical
contaminants from sediments. For example, in March 2005, Dr. Thibodeaux led a two-day workshop in Chicago at
which a detailed analysis of the mechanistic and quantitative aspects of the volatilization model for sediments was
provided. In addition, the workshop explored the problems, complexities, and uncertainties expected if the complete
model were to be applied to the SRA project. (Dr. Thibodeaux and co-workers provide consultation on the IHSC
dredging-disposal project through a contract issued by the USACE).
4-9
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After a review of the available models for soil erosion (including discussions with developers of
the WEPS Model), it was determined that application of the WEPS Model for soil erosion would
be valid for simulating sediment erosion within the CDF. USEPA began by reviewing annual
particle emissions as estimated by USDA-ARS for USACE as the basis for the emissions
estimate for dispersion modeling (Hagen 2005a). Dr. Lawrence Hagen of ARS recommended
against using a constant particle emission rate derived from the annual average because
windblown erosion events at the CDF were expected to be limited to only a few days per year.
If the wind direction during those few days is different than the average wind direction over time,
the location of impacted receptors based on dispersion modeling using a constant emission rate
will be incorrect.
The WEPS Model was modified to use hourly meteorological data to generate hourly particle
emission estimates. In order to increase confidence in the proper use of WEPS,
representatives of USDA-ARS collaborated with USEPA on the application of WEPS to the SRA
project, including defining the project area, the sediment surface characteristics, and the
incorporation of the site-specific meteorological data. USEPA tested whether the additional
sophistication of an hourly variable particle emission was necessary by comparing particle
concentration and deposition results from dispersion modeling trials using constant emission
rate inputs and preliminary variable rates from USDA-ARS. The constant year-long emission
rate was scaled so that total annual emissions equaled the losses predicted by the hourly
variable modeling from USDA. Air concentrations and deposition rates from the constant
emission flux were subtracted at each receptor node from the air concentrations and deposition
rates from the hourly variable emission estimate from USDA-ARS. These differences between
modeling results are graphed in Figures 4-3 and 4-4. The pink areas show where the air
concentration or deposition values would be underestimated by annualizing the particle
emission and the green areas show where they would be overestimated. Thus, ignoring the
episodic nature of the particle emissions as predicted by the modified WEPS would have
significantly underestimated impacts south of the CDF and overestimated them elsewhere.
Strong winds combined with favorable soil conditions for erosion were usually associated with
winds from the north. Due to the advanced development of the modified WEPS model and the
fact that some of the most critical receptor locations (i.e., schools and residences) are located
directly south of the CDF, USEPA decided to incorporate the modified WEPS predicted variable
emissions to the greatest extent possible.3
Five years of local meteorological data, including hourly records of wind speed/wind direction
and other significant weather data, were compiled and processed as a computer input file to the
WEPS Model to determine which hours possessed the required combination of wind speed and
surface conditions to cause the release of particulate matter from the CDF. USDA-ARS
provided USEPA with hourly particle emission estimates for the five-year period using a worst
case emission scenario for the CDF (Hagen 2004a, 2004b). To generate a conservative
particle emission estimate, the following conditions were used:
3 The developers of the SRA collaborated with USDA-ARS to apply the WEPS Model to simulate erosion and
particulate matter release from sediment disposal in the CDF. The developers of the WEPS Model (Dr. Lawrence
Hagen and co-workers of USDA-ARS, Manhattan, KS) were provided with site-specific information on the CDF (e.g.,
geographic location, area dimensions, local meteorological data) that was used to run the WEPS Model. USDA-ARS
developed a written report that summarizes the application of the WEPS Model to the IHSC CDF project (Appendix 4-
1). (USDA-ARS provides consultation on the IHSC dredging-disposal project through a contract issued by USACE.)
4-10
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1) A single large containment cell comprising the entirety of the CDF was assumed to be
filled to capacity (minimizing the height of the potentially wind-blocking cell wall above
the sediment surface)
2) Sediments were assumed to be placed hydraulically to dry in a smooth, flat configuration
(the worst case for windblown emissions)
3) The single large cell was modeled for WEPS in its second year of drying, after a season
of freeze/thaw cycles had already served to break up the dried sediment to enhance
erodibility.
Particle emissions were not estimated from the equalization basin, barges, or dredging areas
because these are wet operations. The resulting hourly particle emissions estimate was placed
into a large text file with lines of data corresponding to each hour of the five-year meteorological
data used for the dispersion model (see Appendix 4-5). The file was prepared in the format
required by the dispersion model for the hourly variable emission option.
4.4.3 Volatile and Particulate Emission Rates Based on Regulatory Limits
In the course of developing the SRA, it was determined that the CDF operation would be subject
to specific regulatory compliance limits on allowable emissions from the CDF. The compliance
limits are spelled out in a June 2002 New Source Registration issued by the Indiana Department
of Environmental Management (IDEM) to the East Chicago Waterway Management District
(Appendix 4-2).4 The basic annual emission limits of the Registration may be summarized as
follows: total volatile organic compounds and total particulate matter during construction and
operation of the CDF may each not exceed 25 tons; a single hazardous air pollutant (HAP) may
not exceed 10 tons; and combined HAPs may not exceed 25 tons. The Registration also
outlines requirements for on-site sediment analysis and air monitoring to provide
demonstrations that the emissions limits would not be exceeded during the actual operation of
the CDF.5
The application of regulatory-based emission compliance limits offered a reasonable and
practical approach for setting emission rate inputs for the SRA. This approach uses essentially
maximized emission rates allowed by regulation in lieu of complex, theoretical and time-
dependent emission models. The use of compliance limits as inputs for the SRA also allows the
results of SRA to. serve as a check on the range of potential health risks associated with
operation of the CDF at the compliance limits. This should be important information for the
operators of the CDF and the public.
4 The regulatory authority for requiring a New Source Registration is found in the Indiana Administrative Code (IAC)
at 326 IAC 2-5.1-2; this citation stands for Title 326: "Air Pollution Control Board"; Article 2: "Permit Review Rules";
Rule 5.1: "Construction of New Sources"; Part 2: "Registrations."
5 USEPA interpreted the emission limits in the Registration to apply to the entire operation of the CDF, including the
dredging and transport of project sediments to the CDF. Consequently, a separate analysis of contaminant
emissions from the dredging/transport operation was not performed for the SRA. This is considered justified for the
following additional reasons: 1) The time required for dredging and transport is a small fraction of the total time that
sediments will spend in the CDF where volatile emissions could occur over several months during any dredging
season; 2) the surface area of the transport barge (< 0.5 acre) is minimal compared to the total surface area from
which volatile contaminants could be released in the CDF (82 acres); and 3) particulate matter release during
dredging/transport is predicted to be negligible because sediments will remain saturated with water and no dry
sediments will be generated that could be subjected to wind erosion.
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The regulatory compliance limit approach to the SRA was proposed to USACE in May of 2005
(USEPA 2005e; Appendix 4-3) and incorporated into the CDF emissions estimate as described
in the following Sections.
4.4.3.1 Regulatory Limit-Based Volatile Emissions
Since a mixture of volatile contaminants is found in the sediment, a mixture of volatile
contaminants would likely be emitted after placement in the CDF. The SRA uses naphthalene
as a surrogate volatile organic pollutant to represent all volatile PCOCs. The toxicity
characteristics of naphthalene represent the highest Cancer Slope Factor (CSF) and lowest
reference concentration compared to all other volatile PCOCs selected for this study. This
approach presumes that all of the allowable 25 TPY of volatile emissions from the CDF would
be composed of naphthalene. Although the compliance limit does not allow an emission of
greater than 10 TPY (TPY) of a single HAP, for analysis purposes we took this conservative
approach and assessed the risk of a single HAP (naphthalene) at the higher limit of 25 TPY for
combined volatile HAPs. This is a simpler method to implement than the multiple chemical, full
volatilization emission model, and is conservative. In reality, the 25 TPY volatile maximum will
include other less toxic compounds, thereby the actual risk and hazard levels will be below the
estimated naphthalene level. The annual 25 tons of naphthalene emissions were uniformly
apportioned throughout the CDF operating cycle based on operating parameters provided by
USACE, basic knowledge derived from the extensive modeling efforts of Thibodeaux et al., and
the available climatological information.
The volatile organic emissions estimate of 25 TPY is based on the knowledge that volatile
emissions are likely to be continuous, at least when the sediment is wet. Thus the 25 TPY was
divided between the two cells based on the wet or saturated periods of the cell cycle and did not
include winter months when declining temperatures, a frozen surface, and/or snow cover could
significantly inhibit volatilization. The result is a period between May 1 and July 31 when both
cells are sources of volatile emissions coinciding with the active dredging season. One cell
actively receives dredged sediments as a slurry while the other cell, containing the previous
year's dredged sediment, continues to dry. After July 31, the inactive cell is assumed to be too
dry to continue emitting significant volatiles, while the cell with the fresh sediment continues to
emit volatiles as it begins to dewater. This continues until November 30 when the surface of the
sediment is assumed to be effectively frozen over. This assumption is consistent with the latest
first soil freeze reported as December 2 for the top 2.5 centimeters of soil in West Lafayette,
Indiana (approximately 85 miles south of East Chicago) measured between 1965 and 1980
(Dale et al. 1981).
The 25-ton annual volatile emission limit was divided into these active periods and a constant
emission rate flux (emissions per unit area) was calculated uniformly for each cell. Thus the
site-wide hourly volatile emissions are twice as high during the active dredging period from May
1 through July 30 as they are during the single dewatering cell period from August 1 through
November 30. Volatile emissions from the dredge and barges were considered as part of the
25 TPY limited emission from the CDF. USEPA decided to prepare the volatile emission as an
hourly variable emission file for the dispersion model, even though the volatile flux rate did not
vary from hour to hour when a cell was assumed to be emitting volatiles. Rather, preparing
hourly emission files was deemed the most appropriate way to incorporate the cyclic nature
assumed to govern volatile emissions as well as the alternating year operation of each cell.
Hourly volatile emission rates for the dispersion modeling period were developed as a text file
for each cell and can be found in Appendix 5-2 of this report.
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4.4.3.2 Regulatory Limit-Based Particulate Emissions
The regulatory limit approach sets the total allowable loss of particulate matter from the CDF
due to wind erosion to 25 TPY.6 USEPA modified the original hourly variable conservative
particle emission estimate from USDA-ARS in order to evaluate the impact of particle emissions
at the 25 TPY limit. Based on recommendations from USDA-ARS and USACE, the particle
emission estimate was restricted to August 1 of a given year through May 1 of the following year
(since the cells will be wet or kept wet during the dredging season) and individual hourly
emissions from the modified WEPS model were scaled proportionally such that the annual total
for each year studied was exactly 25 tons. USACE estimated that a cell operated within a two-
year cycle would be dry enough to emit particles approximately one year after sediments had
last been placed in the cell (late summer of the second year). Particle emissions would
terminate the following spring (the third year) when new wet sediments were placed in the cell.
One of the findings of the initial conservative particle emissions estimate from WEPS was that
the 25 TPY limit may be exceeded. USACE subsequently tasked USDA-ARS to recommend
particle emission mitigation techniques and to use WEPS to evaluate their potential
effectiveness. USDA-ARS ultimately provided updated hourly particle emission data, applying
the revised two-cell operation scheme as well as various emission mitigation techniques (Hagen
2005b). The newly estimated particle emissions were generally lower, reflective of the
mitigation techniques added to the simulation. The average annual emission for the five-year
period with mitigation techniques was 11 TPY, with one year exceeding the 25-ton annual limit.
Since USEPA does not presently know how USACE will actually modify operations to prevent
exceeding the annual emission limit, USEPA decided to continue using the modified particle
emission data for the SRA wherein the annual emissions were proportionally set equal to the
annual emission limit of 25 tons. This approach is more conservative and is in keeping with the
intention to evaluate exposure and risks at the compliance limit. Hourly particle emission rates
for the dispersion modeling period were developed as a text file for each cell with a line for each
hour's particle emission flux corresponding to each hour of the five-years of meteorological data.
The hourly particle emission file can be found in Appendix 5-1 of this report.
The particle emission estimate coupled with the subsequent air dispersion modeling is used to
predict the impact of bulk particle emissions within the air model receptor grid. The impact of
specific Indiana Harbor chemical contaminants that migrate as part of the particle emission will
be taken into account in the SRA based on their chemical-specific concentrations in the bulk
CDF sediments.
4.5 Mercury Emissions
While the concentration of mercury in the sediments is relatively low in comparison to other
Indiana Harbor sediment contaminants, mercury has a high potential to bioaccumulate in the
environment and the type of mercury present (i.e., elemental, divalent, or methylated) has a
large impact on the fate and transport of mercury from the CDF to potential receptors. Due to
the Agency's ongoing focus on the speciation, fate, and transport of mercury from a variety of
6 Particulate matter derived from sediments should be composed predominantly of naturally occurring or inert
materials (e.g., sand, clays, organic detritus) with relatively small concentrations of chemical contaminants adsorbed
to the particulates. Contaminants on airborne particulate matter could be available for direct inhalation exposure or
for indirect exposure after deposition to soil. Therefore, it was not appropriate to model the allowable 25 tons of
particulate matter as a single "most toxic" contaminant for cancer risk and noncancer hazard as was done for the
volatile emission modeling. The concentrations of chemical contaminants on airborne particles and deposited
particles were assigned based on the data reports on chemical contaminant concentrations in the project sediments.
4-13
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sources, we have the ability to evaluate different chemical species of mercury (this level of detail
is generally not available for other contaminants). However, actual speciation data for mercury
in Indiana Harbor sediments is minimal.
In order to evaluate possible risks from the different possible species of mercury, a number of
scenarios were run with different mercury species in a manner that likely exceeded the mass
balance of mercury present while maximizing the pathway specific health threats of mercury.
For example, the greatest risk from a vapor emission of elemental mercury is from direct
inhalation. To evaluate direct inhalation, elemental mercury vapor was emitted based on all
available mercury in the sediment dredged within a single year. However, other mercury
species were evaluated simultaneously (with different pathway outcomes) so that the amount of
mercury emitted was greater than the amount of mercury actually available.
Table 4-3 summarizes the modeling approach for the different species of mercury possible from
the CDF. Elemental mercury was run as a vapor emission by taking the vapor emission scaled
to 25 tons (originally run for naphthalene) and using the emission rate entry in the risk
assessment program to scale the emission to the total tons of mercury present in a heavy
dredging year. At a maximum dredge removal rate of 240,000 cubic yards per year of wet in-
situ sediment, a dry sediment in wet in-situ volume density of 0.67 tons per cubic yard, and an
average concentration of 1.1 mg/kg mercury in Indiana Harbor sediments, USEPA estimates
that 0.18 tons of mercury could be placed in the CDF annually. Assuming that all 0.18 tons emit
from the CDF each year, the 25-ton vapor emission must be adjusted by a factor of 0.007 (the
ratio of 25 tons to 0.18 tons).
Elemental, divalent (as mercuric chloride), and methylmercury potentially emitted as particle
contaminants were run by applying the average concentration of these species to the results of
the 25-ton erodible particle emission. Actual data were available for average sediment
concentrations of elemental and methylmercury. The concentration of mercuric chloride was
obtained by adjusting the average sediment concentration of elemental mercury to include the
molecular weight of two additional chlorine atoms.
Mercuric chloride potentially emitted as a vapor was run by taking the maximum possible
amount of mercuric chloride present in a heavy dredging year and using the 1993 Air/Superfund
National Technical Guidance Study Series - Models for Estimating Air Emission Rates from
Superfund Remedial Actions (USEPA 1993a) to estimate a volatile flux from the ponded CDF
(modeled as a lagoon). This flux was used for all periods of volatile flux for mercuric chloride.
Please see Appendix 4-9 for a detailed description of the flux calculation.
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Table 4-3: Modeling Approach for Mercury Species
Mercury
Species
Vapor
COPC or
Emission -
Dispersion
Model Run
Used
Annual
Mass of
Species
Emitted
Source for
Emission Rate
IRAP Options
Name
Particle
Phase
Emission
Rate Scalar
Fv
Hg°
(elemental)
mercury
(v)
vapor
25-ton vapor
emission with
wet gas
deposition
0.18 tons
mass balance
0.007
1
Hg°
(elemental)
mercury
particle
25-ton bulk
erodible
sediment particle
emission
25 grams
average
concentration in
sediment
1.1x10"6
(1.1 mg/kg)
0
HgCI2
(divalent)
mercuric
chloride
vapor
unit vapor
emission with
wet and dry gas
deposition
89 grams
estimated flux
from lagoon
water
2.04x10"
1
HgCI2
(divalent)
mercuric
chloride
(P)
particle
25-ton bulk
erodible
sediment particle
emission
34 grams
estimated
average
concentration in
sediment
1.49x10®
(1.49 mg/kg)
0
CH3Hg+
methyl-
mercury
(b)
particle
25-ton bulk
erodible
sediment particle
emission
0.0136
grams
average
concentration in
sediment
6.0x10"10
(0.6 pg/kg)
0
CH3Hg+
methyl-
mercury
Derived from fate and transport and methylation of other species
1
4.6 Uncertainties
The selection of site PCOCs carries with it some uncertainty. There could be contaminants
present in bulk sediments that have not been analyzed in historical sampling efforts. However,
the uncertainty in PCOC selection is reduced because the selected PCOCs are among the most
common and toxic contaminants USEPA typically evaluates for risk assessment. Furthermore,
the selected PCOCs are representative of a wide variety of contaminant types (e.g., pesticides,
metals, volatile organics, PCBs, dioxins) such that each evaluated exposure pathway likely
includes PCOCs that could have a significant impact in that pathway due to variations in
physical, chemical, and toxicological parameters.
The concentration levels assigned to PCOCs in bulk sediment are also a source of uncertainty.
Based on a review of appropriate historical analytical sample data, mean concentration levels
were calculated for PCOCs detected in bulk sediments. The use of mean contaminant
concentration levels obtained from the analysis of the in-situ Indiana Harbor sediment was
deemed appropriate and conservative for the following reasons:
1) The processes of dredging, slurrying and placement of the sediments in the CDF will
entail significant mixing. This will significantly decrease the spatial variation for the
sediments in the CDF compared to the spatial variation exhibited by the in-situ
sediments. Consequently, selecting a measure of central tendency for the particle-
bound contaminant concentrations is regarded as appropriate.
2) The contaminant data sets selected for use in the SRA commonly contain a small
number of measured concentration levels which are notably higher in magnitude than
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the rest of measurements. As such, the mean will be a more conservative estimate of
central tendency than other estimates such as the median, which would not reflect the
limited number of elevated contaminant concentrations.
3) A large portion of the in-situ contaminant data (USEPA Sediment Core Study) selected
for use in the SRA was obtained from sediment depositional areas in the Federal
navigation project. These areas are generally more quiescent and therefore associated
with finer-grained deposits. For a variety of physical and geochemical reasons, finer-
grained sediments are generally associated with elevated contaminant concentration
values. Consequently, a mean obtained from these data should be both biased high and
a conservative estimate of sediment contaminant concentrations in the CDF.
4) For PCOCs which had some bulk sediments samples reported as "non-detect" values,
the non-detect samples were included in the calculation of the mean at a value equal to
the full analytical detection limit, instead of a value of zero. As the actual concentration
should in most instances be lower than one-half of the limit of detection, the contaminant
mean values obtained in this manner should again be skewed high and would
consequently be a conservative estimate of sediment contaminant concentrations in the
CDF.
Volatile emissions are driven primarily by concentration-gradient evaporation from dredge slurry
and could essentially occur continuously. Use of a constant emission rate for the SRA is
regarded as reasonable in the absence of more detailed information. Subsequent iterations of
the work undertaken by Thibodeaux and his colleagues have shown that certain meteorological
inputs such as wind speed could significantly impact the volatile emissions estimate. However,
the long-term chronic risks from volatile emissions evaluated at the 25 TPY maximum using
naphthalene, the most toxic volatile, should still represent a conservative estimate of risk. By
contrast, the evaluation of acute (short-term) risk could include greater uncertainty because of
the potential impact of day-to-day variations in operations and weather which are not accounted
for in a constant emission rate.
Relatively few individual particle emission events are expected from the CDF in a given year
because of the episodic nature of the elevated wind velocities needed to initiate particle erosion.
Consequently, use of five years of meteorological data may not have been an adequate
sampling to reveal the true worst-case year for the CDF location. To compensate for this
uncertainty, the annual emission level was scaled up to the 25 TPY compliance limit, instead of
using the most recent estimate (i.e., average of 11 TPY) for the long-term emissions. This
should introduce a degree of conservatism that is expected to offset the meteorological
uncertainty of an unevaluated worst year. Since one year of the updated particle emission
scenario (including mitigation techniques to limit emissions) was estimated to exceed the 25
TPY limit, the acute particle emission scenario may be underestimated.
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Figure 4-2 Two-Year Operating Cycle and Emissions
¦w
Figure 4-2 2-Year Operating Cycle and Emissions
VOCs
vocs
VOCs
Sediment Slurry
Particles
w
East Cell
West Cell
Submerged
Wet Sediment
VOCs
/
z
no emissions estimated
/
/
Sediment Slurry
Wet Dewatering
Sediment
Frozen Wet Sediment
Particles
/
Wet Dewatering
Sediment
Dry Sediment
T
i
May 1 July 31 November 30
— Operating Year
L
Active
Dredging J
Sediment
Wet Dewatering
Sediment
VQ
Cs
sluny .
W
Submerged
Wet Sediment
Dry Sediment
VOCs:
/
Wet Dewatering
Sediment
no emissions estimated
Frozen Wet Sediment
May 1
July 31 November 30
Next Operating Year
Active
Dredging ...J
May 1
i
hraect supplemental Risk Analysis of Potential Air Emissions from the Confined Disposal Facility for the
Indiana Harbor and Shipping Canal Sediment Dredging and Disposal Project
Todd D. Ramaly
~Date March 7, 2006 ™rior
comments -|) Dredged sediment placed in each cell alternating every other year
2) Modeled period from the middle of the operating life such that there are sediments and
potential emissions from both cells at all times.
3) Modeled period began at the beginning of a calendar year
V®
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Figure 4-3 - Difference in Total Particle Deposition in for Constant Versus Variable
Emission Rates
FROJECT TITLE:
Figure4-3 Difference in Total Particle Deposition for Constant Versus Variable Emission Rates
-28000 -22000 -15000 -8000 -5000 -1000 -500 0 500 1000 2500 5000 6000 13000 20000 27000 34000
COMMENTS:
Gre=n indicates overestimate
versus hourly. Red indicates
undsrestimate versus hourly
MODELING OPTIONS:
CONC. DEPOS. DDEP. WDEP.
URBAN. FLAT. DFAULT
COMPANY NAME:
U.S. EPA
MODELER:
TDR
OUTPUT TYPE:
DEPOS
RECEPTORS:
5233
SCALE" 1:120325
MAX:
34501.30081
UNITS:
g/nr
DATE
6/15/2004
PROJECT NO.:
Indiana Harbor SRA
KXJralJtei
4-19
-------
Figure 4-4 - Difference in Particle Air Concentration for Constant Versus Variable
Emission Rates
PROJECT TITl£:
Figure 44 Difference in Particle Air Concentration for Constant Versus Variable Emission Rates
452000 455000 458000 461000 464000 467000
PLOT FILE OF ANNUAL VALUES FOR SOURCE GROUP: CDF ^g/rrr"
-60 -30 -10 0 10 50 100 500 1000 1500 2000 2500 3000 3500
COMMENTS:
Green indicates overestimate
versus hourly. Red indicates
underestmate versus hourly.
MODELNG OPTIONS:
CONC. DEPOS. DDEP. WDEP.
URBAN. FLAT. DFAULT
COMPANY NAME
U.S. EPA
MODELER:
TDR
OUTPUT TYPE:
CONC
RECEPTORS
5233
SCALE 1:120325
MAX:
3569 29047
UNITS:
|»g/nt»
DATE:
6/15/2004
PROJECT NO.:
Indiana Harbor SRA
4-20
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5 ATMOSPHERIC DISPERSION AND DEPOSITION MODELING OF EMISSIONS
5.1 Dispersion Model
In order to assess the potential risks posed from exposure to VOCs and particulate matter (PM)
from the contaminated sediments from the dredging and disposal operations, dispersion
modeling was conducted to estimate the potential ambient air concentrations and deposition flux
values from the CDF.
The USEPA-approved ISCST3 (version 02035) was used to generate short term averages (one-
hour average) and annual average values over a five-year period (1987-1991). The model
estimates ambient air concentrations and total (wet and dry) deposition flux values at each
receptor. Prior to November 2005, ISCST3 was identified in 40 CFR Part 51, Appendix W, as
the recommended model for most regulatory modeling analyses (USEPA 1994e).
On November 9, 2005, a new dispersion model called American Meteorological Society/
Enviroftmental Protection Agency Regulatory Model Improvement Committee (AERMIC)
Dispersion Model (AERMOD) was approved and published in the Federal Register (FR Vol. 70,
No. 216). This Federal Register became effective December 9, 2005 at which time AERMOD
replaced the ISCST3 model as the recommended tool for most regulatory uses. The rule allows
a one-year transition period during which "timely applications of ISCST3 may still be approved
at the discretion of the reviewing authority". Due to this and because most of the modeling work
had been completed using the ISCST3, USEPA decided to continue using ISCST3 model for
this analysis.
The ISCST3 model applies the steady-state Gaussian plume equation to model emissions
released from the CDF. Even though the model was set up to include actual terrain elevation,
the area source algorithm in ISCST3 is limited to flat terrain. Additional discussion can be found
in Section 5.5. Urban dispersion coefficients were used and the model was set up to produce
wet and dry deposition flux values. The regulatory default parameters which include buoyancy-
induced dispersion, default wind profile exponents, default vertical potential temperature
gradients, etc. were also applied.
For each source, the model conducts two scenarios. Scenario one is the long-term average
which calculates annual average. Scenario two estimates the one-hour average. In addition,
two specific pollutants were also calculated: 24-hour average concentrations for particulate
matter less than or equal to 10 pm in diameter (PM10), and annual average for dry and wet gas
deposition for mercuric chloride. Details of the model runs are discussed in Section 5.2. The
model will provide output in the plot file format. These plot files were later utilized in the
exposure model (I RAP). For scenario one and two, the ISCST3 model was run in three phases;
particle, particle bound, and vapor. For particle and particle bound phases, the model produces
concentrations, wet deposition flux values, dry deposition flux values, and total deposition flux
values. For the vapor phase, the model produces concentrations and wet deposition flux
values. The dry deposition flux values for gas phase were not calculated for scenario one and
two. These values would require pollutant-specific modeling with ISCST3 using different
physical parameters such as molecular diffusivity, the solubility enhancement factor, the
pollutant reactivity parameters, and the Henry's law coefficient. Also individual I RAP runs would
need to apply for each specific pollutant if dry gas deposition was calculated for all pollutants.
Table 5-3 lists the details of model runs for scenario one and scenario two.
5-1
-------
5.2 Source Information
Emissions from the proposed CDF were represented as two area sources: west cell and east
cell sediment dewatering and containment units, to be operated in alternating years. The west
cell area source was represented in the model using ten vertices and the east cell area source
using four vertices. Both cells were assumed to be approximately 41 acres in size and oriented
in the north-south direction.
The sediment containment cells were manually drawn into ARCMap version 8.3, a geographic
information system (GIS) software package developed by Environmental Systems Research
Institute, Inc. (ESRI), using USACE drawings (Thai 2005a). USEPA used the North American
Datum 1927 (NAD27) as the geodetic datum for the Indiana Harbor site and the Universal
Transverse Mercator Projection (UTM) for identifying coordinates. This datum was chosen
because it corresponded to digital elevation maps needed to import terrain heights.
Accordingly, the two cells can be defined by the following vertices.
Vertex
X
Y
East Cell
1
459584.75
4610765.58
2
459586.16
4611470.92
3
459858.32
4611309.53
4
459859.72
4610765.58
West Cell
1
459369.37
4610617.91
2
459369.38
4611405.88
3
459372.73
4611433.65
4
459382.58
4611455.45
5
459399.10
4611475.84
6
459416.68
4611491.31
7
459437.08
4611500.46
8
459462.74
4611506.08
9
459552.06
4611482.17
10
459555.21
4610617.91
Each cell was modeled separately using two different hourly emission files. The assumed
maximum of 25 TPY for each category of emissions (VOCs and PM) was applied while
developing the hourly emission files. For particle emissions, the hourly emission file was
developed based on the wind events represented by actual local meteorology data. For a 25
TPY VOC emission, an emission rate of 5.2 x 10"6 grams per second per square meter (g/s/m2)
was applied on days when VOCs were expected to be emitted. The hourly files for PM and
VOC can be found in Appendix 5-1 and Appendix 5-2, respectively. Section 4 of the SRA
Report discusses details of the 25 TPY VOC and 25 TPY particulate emissions, assumptions,
and how the CDF emissions were estimated. The release height of the CDF emissions was
assumed to be 6 meters based on USACE assumption on current design height of the
containment cell berm.
The particle information was based on the wind erosion model and assumptions performed by
Larry Hagen, PhD, which are also described and referenced in Section 4. Table 5-1 lists the
5-2
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particle size categories, particle densities, percent of mass provided by USDA (Hagen 2004c),
and fraction of total mass assigned to each size category which were calculated using Table 3-1
in the draft HHRAP (USEPA 1998b). USDA determined the particle size distribution by dry
sieving. This approach is consistent with ASTM Method D422-63 (2002), Standard Test Method
for Particle-Size Analysis of Soils for fractions at 75 |jm and above. The ASTM-recommended
sedimentation process for particles less than 75 pm was not used for the following reasons:
• The samples contained a degree of small particle aggregation
• Wet sedimentation testing has the potential to significantly alter the properties of the
small aggregates
• The samples were taken from outdoor-weathered Indiana Harbor sediments and were
considered to be consistent with dry surface particles likely to occur at the CDF.
Accordingly, USDA employed methods that are least likely to alter the sample in order to get the
best estimate of wind erosion-based emissions. The dry sieving at sizes less than 75 pm was
conducted using high-precision electroformed micro-mesh sieves manufactured to ASTM
standards for sieves and processed in a sonic sifter. USDA supplied an additional study in
support of using electroformed sieves in sonic sieve devices for high accuracy particle analysis
(Rideal 1996).
Table 5-1: Selected Characteristics of Particle Size Categories
Particle Size Categories
(Mm)
Percent of Mass
(use for particle phase)
Fraction of Total
Surface Area
(use for particle bound
phase)
Particle Density
(g/cm3)
5.0
0.05
0.24
2.0
16.0
0.26
0.40
1.94
35.0
0.34
0.24
1.8
61.0
0.20
0.08
1.7
87.0
0.15
0.04
1.68
The wet scavenging coefficients for liquid and frozen precipitation were derived from Figure 1-
11 in the ISCST3 User's Guide Volume II (USEPA 1995a). These values were required for
calculation of wet deposition flux values and are listed in Table 5-2.
5-3
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Table 5-2: Wet Scavenging Coefficients by Particle Size
Particle Size Categories (pm)
Liquid
Ice
5.0
3.6 E-04
1.2 E-04
16.0'
6.6 E-04
2.2 E-04
35.0
6.6 E-04
2.2 E-04
61.0
6.6 E-04
2.3 E-04
87.0
6.6 E-04
2.2 E-04
The wet vapor scavenging coefficients for liquid and ice are required for modeling vapor phase
wet deposition. The values listed below are recommended for vapor emissions in the HHRAP
(USEPA 1998b).
Liquid 1.7E"4
Ice 0.6E"4
Table 5- 3 lists the details of model runs for scenario one and scenario two.
Table 5-3: Details of Model Runs for Scenarios One and Two
Phases/Emission
Scenario One (Annual Average)
Scenario Two (One-Hour Average)
Gas
(VOC emission)
Concentrations and wet deposition
flux values
Concentrations
Particle
(PM emission)
Concentrations and wet and dry
deposition flux values
Concentrations
Particle Bound
(PM emission)
Concentrations and wet and dry
deposition flux values
Concentrations
For each cell, 24-hour average PM10 concentrations were calculated using the same hourly
particle emission file. Other modeling inputs are listed below. In order to ensure that all
receptor node particle concentrations are PM10 only, the entire particle emission was rerun
assuming a mean particle diameter of 10 microns. The ISCST3 model provided the high sixth
high (H6H) concentrations at each receptor over a five-year period. The final 24-hour average
for PM10 at each receptor is actually only 5 percent of these H6H concentrations based on the
particle size distribution given by Dr. Hagen, which showed particle sizes from 1 to 10
micrometers (urn) representing 5 percent of the total emissions emitted from the CDF.
Therefore, a correction factor of 0.05 was applied to the results at each node.
Additional PM10 modeling inputs:
Particle diameter
Particle density
Fraction mass
Scavenging coefficients (liquid)
Scavenging coefficients (frozen)
5-4
10 pm (for the entire particle emission)
2 gram per cubic centimeter (g/cm3)
1
6.6E-04
2.2 E-04
-------
In addition, annual average wet and dry gas deposition for mercuric chloride was also modeled
using the ISCST3 toxics option. The ISCST3 model was set up to produce the annual plot files
for wet and dry gas deposition for each cell separately. These plot files were then utilized in the
IRAP model. Below is the list of assumptions and inputs that were used in the ISCST3 Toxics
option for the wet and dry gas deposition mercuric chloride runs.
1) Gaseous dry deposition velocity is 0.029 m/s
2) Model option in this new run was set up as: MODELOPT CONC DEPOS DDEP WDEP
DRYDPLT WETDPLT URBAN TOXICS
3) Hourly VOC emission files, which have constant emission rate of 5.2 X 10"6 g/s/m2, were
modified by replacing the value of 5.2 X 10"6 g/s/m2 to 1 g/s/m2.
4) The meteorological data file was also reformatted to include columns for Incoming Short-
wave Radiation, and Leaf Area Index, which are required for modeling dry gas
deposition. However, since we used constant dry deposition velocity, these parameters
were not applied.
5.3 Meteorological Data
The study used meteorological data for the years 1987-1991 that were collected from three local
towers within 2 miles of the CDF. The three nearby meteorological data stations are identified
as Hammond, Amoco Tower, and Amoco Water Treatment. The Amoco Tower data is the
primary meteorological data set. Missing data was substituted by the Hammond and Amoco
Water Treatment sites. A table of missing meteorological data can be found in Appendix 5-3.
The hourly surface data are from the Amoco Tower (Aerometric Information Retrieval System
[AIRS] number 180892014) located about one mile west-southwest of the CDF center. The
missing wind speed and wind direction data were substituted from the Hammond station (AIRS
number 180892008), located about one mile southwest of the CDF center. The missing wind
direction deviation data was substituted from the Amoco Water Treatment station (AIRS number
180892005), located about 1.8 miles northeast of the CDF center (USEPA 2006). Precipitation
data was also taken from the Amoco Water Treatment station. The upper air (mixing height)
data from the National Weather Service (NWS) in Peoria, Illinois were used, since that site is
the nearest NWS station which collects upper air data. The meteorological data for the years
1987 to 1991 were used because it is the most recent readily available, representative data that
include on-site precipitation information (USEPA 1987). Five years of processed meteorological
data can be found in Appendix 5-4.
The wind rose plots of five years of meteorological data (1987-1991) were made using the
WRPLOT view program from Lake Environmental Software. The wind rose plot from five years
of local wind speed and wind direction data was compared with the plot from five years of NWS
data from Chicago/O'Hare International Airport. Both wind rose plots show similar prevailing
winds from the southwest. However, the wind rose plot for the local data shows more northerly
winds from the Lake than the plot with NWS data. Additionally, the local data is characterized
by somewhat lighter wind speeds overall than the NWS data. This indicates that using the local
meteorological data would better address Lake effects than using data from Chicago/O'Hare
Airport. Figures 5-1 and 5-2 are wind rose plots for the local data and the NWS data
respectively.
5-5
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The Meteorological Processor for Regulatory Models (MPRM) version 04048 was used to
process five years (1987 to 1991) of on-site meteorological data (Bailey 2004). This
preprocessor model was necessary to prepare on-site meteorological data for use with the
ISCST3 model. This new MPRM model allows us to process all three stages using one
executable file (USEPA 2003c). Table 5-4 below lists the surface characteristics at the CDF site
that were used as the inputs for the MPRM model (USEPA 1996c, 1999a). An example of
MPRM input file for one year of meteorological data can be found in Appendix 5-5.
Table 5-4: Surface Characteristics at the CDF Site
Winter
(Dec, Jan, Feb)
Spring
(Mar, Apr, May)
Summer
(Jun, Jul, Aug)
Fall
(Sep, Oct, Nov)
Albedo
0.35
0.14
0.16
0.18
Bowen Ratio
1.5
1.0
2.0
2.0
Roughness (MS)
1.0
1.0
1.0
1.0
Roughness(AS)
1.0
1.0
1.0
1.0
M-O length
50
50
50
50
Surface Heat, Flux
0.27
0.27
0.27
0.27
Anthropogenic Heat Flux
75
50
25
50
Leaf Index
0.0
0.0
0.0
0.0
MPRM uses cloud cover, station pressure, and global radiation to calculate friction velocity and
estimate the stability classes (Bailey 2004). These data, however, were not available at the
Hammond, Amoco Tower, or Amoco Water Treatment stations. The NWS surface data from
O'Hare Airport were substituted for these parameters. For the years from 1987 to 1990, the
NWS data were available in Solar and Meteorological Surface Observation Network (SAMSON)
format and included global radiation. For the year 1991, however, the NWS data were in Hourly
United States Weather Observations (HUSWO) format, which does not include global radiation.
Extra effort was made to develop Global radiation for the year 1991 using the new version of
MPRM. O'Hare Airport is located approximately 35 miles northwest of the CDF site. These
data are the best available and should provide a reasonable estimate of the cloud cover, station
pressure, and global radiation conditions in South Chicago/Northwest Indiana region.
5-6
-------
Figure 5-1: Wind Rose Plot for Five Years (1987-1991) of On-Site Meteorological Data,
AMOCO TOWER Monitoring Site, IIM
NORTH
15%
12%
9%
\
\
»
\ 1 I
.4 | 1
i EAST
! 1 i
i i
i i
SOUTH
WIND SFEED
(m/s)
~
>=11.1
¦
8.8-11.1
¦
5.7- 8.8
¦
3.6- 5.7
~
2.1 - 3.6
¦
0.5- 2.1
Calms
: 0.02%
5-7
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Figure 5-2: Wind Rose Plot for Five Years (1987-1991), NWS Data,
Chicago/O'Hare INTL. ARPT, IL
Inorth
I I 2.1 - 3.6
H 0.5- 2.1
Calms: 3.46%
5.4 Source Characterization Inputs
Source parameters required by the ISCST3 model for this analysis include hourly pollutant
emission rates, East and West Cell locations and dimensions, number of vertices (or sides) of
each cell, and release height above the ground. The hourly emission rates for PM and VOCs
for each cell were modeled separately. The operation plans for each cell were used to develop
the PM and VOC hourly emission files. On-site meteorological conditions were also
incorporated while developing the hourly emission rates for PM, as explained in Section 4.
The urban dispersion coefficient was selected based on the application of the Auer method as
specified in USEPA guidance on air quality models. The Auer method defines an area as urban
if industrial, commercial, and residential land use types within a 3-kilometer (km) radius of the
facility comprise 50 percent or more of land use by area. The 1992 National Land Cover
Classification Database showed that more than 50 percent of the land use within 3 km of the
CDF is industrial, commercial, and residential. Table 5-5 and Figure 5-3 prov de percentages of
land use within 3 km of the CDF.
5-8
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Table 5-5: Land Use Within 3 km of the CDF (1992 Data)
Land Use Code Definition
Percentages
High intensity commercial
45.749
Low intensity resident
1.748
High intensity resident
16.245
Total Urban
63.742
Open water
27.438
Bare Rock/Sand/Clay
0.004
Deciduous Forest
3.850
Evergreen Forest
0.969
Pasture/Hay
0.733
Row Crops
0.337
Small Grains
0.002
Other Grasses Urban
2.104
Woody Wetland
0.454
Emergent Herbaceous
0.322
Total Rural
36.213
5-9
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Figure 5-3: Percentages of Land Use Within 3 km of the CDF
Land Use 3 km from CDF
I I CDF
Land Use
(27.5% Open Water
1.75% Low Intensity Residential
HB 16.24% High Intensity Residential
| 45.7% Commencial/lndustrial/Trans.
I I 0.004% Bare Rock/Sand/Clay
| 0.97% Evergreen Forest
I I 0.73% Pasture/Hay
I | 0.34% Row Crops
~ 0.002% Small Grains
~ 2.1% Urban/Recreational Grasses
H 0.45% Woody V\fetlands
I I 0.32% Emergent Herbaceous Wetlands
3.85% Deciduous Forest
Data Source: 1992 USGS National Lard Cover Database
Aj gust 2006
5-10
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Source input data for the SRA are summarized in Table 5-6.
Table 5-6: Source Input Data
Source Parameter
Values
Dispersion Coefficient
Urban
Terrain Height (above sea level)
180 meters
Anemometer Height
10.0 meters
Release Height
6.0 meters
5.5 Terrain Heights
Terrain heights were imported automatically for receptor grid nodes using AERMOD-View
version 4.8 (a Windows-based interface for running USEPA-approved dispersion models
developed by Lakes Environmental Software of Waterloo, Ontario) from the following 7.5 minute
USGS Digital Elevation Model (DEM) files obtained from the WebGIS Web site
(http://www.webqis.com): Lake Calumet, IN; Whiting, IN; Calumet City, IN; and Highland, IN.
The terrain heights above sea level at the CDF site and within the receptor grid are around 180
meters. Terrain heights were assigned for all vertices of the East and West cells and for all
receptor locations. This information was included to address the actual land uses around the
CDF site but has no effect on the overall results since the ISCST3 area source algorithm
assumes flat terrain.
5.6 Receptor Grid
A Cartesian receptor grid was used in the modeling analysis. The center of the Cartesian grid is
located at the center of the CDF, which has the UTM Easting (459592.06) and UTM Northing
(4611066.99). Receptor nodes were spaced at 50-meter intervals within 2 kilometers of the
origin and 500-meter intervals within 5 kilometers of the origin. The receptor grid file can be
found in Appendix 5-6.
5.7 Output
5.7.1 Long-Term Average (Annual)
For each CDF cell, the ISCST3 model was run three times to calculate the vapor, particle, and
particle bound pollutant phases using two separate hourly emission input files (one for PM
emissions and one for VOC emissions). A total of six output files were produced for annual
average; three files for the west cell and three files for the east cell. Air concentrations and
deposition flux values were estimated at each receptor location. The ISCST3 input files and plot
files for annual average (three phases) can be found in Appendix 5-7 and Appendix 5-8
respectively.
5-11
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5.7.2 Short-Term (One-Hour) Averages
Short-term, one-hour concentrations were calculated from each cell. The one-hour deposition
flux values were not included. Similar to the annual average, the ISCST3 model was run three
times to calculate the vapor, particle, and particle-bound pollutant phases using two separate
hourly emission files. A total of six files were produced for short term averages (three files for
west cell and three files for east cell). For each cell, the three files represent three possible
phases: vapor, particle, and particle bound. Concentrations were estimated at each receptor
location. The ISCST3 input files and plot files for one-hour average (three phases) can be
found in Appendix 5-9 and Appendix 5-10, respectively.
The above ISCST3 results (long term average and short term average) were not pollutant
specific. For each run, ISCST3 was set up to produce the plot files to represent the dispersion
of a generic pollutant These plot files were then used in the IRAP exposure model to determine
the potential risks.
5.7.3 PM10 (24-hour Average)
Generally, at least one year of sequential hourly meteorological data is used to ensure that
worse-case seasonal conditions are addressed in the analysis. The National Ambient Air
Quality Standards (NAAQS) for 24-hour average PM10 is 150 microgram per cubic meter and it
is not to be exceeded more than once per year. The Allowable increments are defined as
maximum allowable increases in ambient air concentrations that are also not to be exceeded
more than once per year for other than an annual time period (USEPA 1990c). It was
understood that for PM10 modeling, one exceedance per year is permitted for the 24-hour
NAAQS as well as for the 24-hour Class II PSD.
For this analysis, five years (1987-1991) of meteorological data were used to model 24-hour
average concentration for PM10; therefore, five exceedances are permitted. This allows us to
look at the sixth highest concentration (H6H) for 24-hour average. A correction factor of 0.05
was then applied at each receptor to account for the assumption that 5 percent of the total
particle emission was comprised of PM10. After applying the 0.05 correction factor, the H6H
maximum 24-hour concentration within study area of interest was compared to the 24-hour
NAAQS standard and the 24-hour class II PSD for PM10. Additional discussion on PM10
modeling results and its impact on short -term inhalation exposure to respirable particle matter
can be found in Section 6.4.8.2.
24-hour average concentrations were estimated from each cell. Both wet and dry depositions
were selected in the model to account for plume depletion. The ISCST3 model was run and
produced the plot file of H6H concentrations at each receptor location. The ISCST3 input files
and plot files can be found in Appendix 5-11 and Appendix 5-12, respectively.
5.7.4 Mercuric Chloride Vapor (Annual Average)
We calculated annual average of total, wet and dry gas deposition fluxes for mercuric chloride
from each cell. The ISCST3 toxics option was run and produced two annual plot files. For
mercuric chloride, the model was set up to run for vapor phase only. These two vapor plot files
were then utilized in the IRAP model to estimate the impact of mercury on fish consumption.
The input files and plot files are in Appendix 5-13 and Appendix 5-14, respectively.
5-12
-------
Other forms of mercury were also evaluated for annual and acute exposures but did not require
additional dispersion modeling. We evaluated particle form of divalent (as mercuric chloride)
and methylmercury from the CDF by applying their proportional sediment concentrations to the
25-ton particle plot files. We also evaluated elemental mercury emitted as a vapor by using the
25-ton vapor plot files and modifying it to account for the maximum mass of elemental mercury
expected in the sediment.
Additional information on mercury speciation, IRAP options, and results can be found in Section
4.5 and Section 6.1.4.5.
5.8 Uncertainties
Meteorological conditions influence how pollutants will transport, disperse, and deposit at
downwind distances. Use of local meteorological data reduces the uncertainties to some
extent. Using cloud cover, station pressure, and Global radiation information from the NWS at
O'Hare Airport instead of local data has some disadvantages but was chosen as the best
approach at the time of the analysis. Some surface characteristics such as albedo, bowen ratio,
and surface roughness length are estimates based on seasons and land use classifications.
These values are sensitive to other factors, such as the reflection of radiation and the ratio of
sensible heat, and therefore will also add to the model uncertainties.
In addition, the ISCST3 model does not simulate chemical transformations or reactivity in the
plume. It assumes that the pollutant is either emitted as a vapor, as a particle, or as particle
bound and disperses in the same manner. Using such a generic pollutant approach adds
uncertainty to the overall model results. The lack of dry gas deposition may underestimate
deposition flux values and overestimate the concentrations. Because ISCST3 is a steady-state
model, it does not account the effects of varying winds on plume as it travels downwind. This
adds some uncertainties to the model predicted values as well as the locations of the impacts.
The ISCST3 model did not calculate values for hours with calm wind conditions which could add
some uncertainties. However, for this analysis, calm wind conditions over a five-year period
occurs only about 2 percent of the time. If calm wind conditions were significantly higher,
stagnation conditions should be included in the ISCST3 model.
Mercury modeling is a very complicated task due to the complex environmental behavior of this
chemical. The ISCST3 model with toxics option might not be able to address all of the
assumptions and uncertainties relevant to mercury characterization.
The predicted air concentrations and deposition flux values are calculated based on a selected
dispersion model. Dispersion modeling, like any model, has inherent uncertainties. Users
should take all uncertainties into account when interpreting the model results.
5-13
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6 HUMAN HEALTH RISK ASSESSMENT
6.1 Toxicity Assessment
The purpose of the toxicity assessment portion of the SRA is to combine the chemical
identification and dose-response assessment. The primary objectives of this step of the risk
assessment process are: to identify the types of toxic effects associated with each PCOC,
characterize the conditions of exposure (e.g., intake route, time-duration) under which these
effects might occur, and determine the relationship between the magnitude of the exposure
dose and the extent of adverse health effects. This relationship is represented through the use
of toxicity values related to cancer or noncancer health endpoints.
6.1.1 Toxicity Associated with Chronic Exposure
USEPA has conducted toxicity assessments on many frequently encountered environmental
contaminants, and has developed toxicity factor values for use in risk assessment, based on
these analyses. These assessments and the toxicity factors generally apply to chronic, long-
term exposure that could potentially occur over an extended time duration, such as multiple
years or a significant fraction of the lifespan.
6.1.2 Carcinogenic Effects
Substances classified by USEPA as potentially carcinogenic are considered by many scientists
to pose a finite cancer risk at all exposure levels. Therefore, in evaluating cancer risks, a "no-
threshold" assumption is applied. A "no-threshold" assumption means that there is not an
established exposure level below which no cancer risk is assumed. It should be noted that the '
no-threshold assumption may not apply for some classes of carcinogens that act through a
mechanism that requires a threshold dose to be exceeded prior to initiation of the carcinogenic
process. For purposes of this assessment, the no-threshold assumption is conservatively
assumed for all chemical carcinogens.
A two-step evaluation is used in assessing the carcinogenic potential of a chemical. The first
step involves evaluating the likelihood that the substance is a human carcinogen (i.e., a weight-
of-evidence assessment), and the second step involves defining the quantitative relationship
between dose and response (i.e., development of a slope factor or IUR). In the first step,
USEPA classifies a chemical into one of five groups that indicate the likelihood that the chemical
is a human carcinogen, based on the weight of evidence from human and animal investigations
as follows (USEPA 2005b):
• Carcinogenic to Humans
• Likely to Be Carcinogenic to Humans
• Suggestive Evidence of Carcinogenic Potential
• Inadequate Information to Assess Carcinogenic Potential
• Not Likely to Be Carcinogenic to Humans
Those chemicals showing evidence of being known, likely, or suggestive human carcinogens
are further evaluated.
The second step is a dose-response assessment for each tumor type identified in the relevant
data sets. The assessment occurs in two parts: (1) examination of observed data on the dose-
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response relationship for tumor formation in order to derive a point of departure (POD). The
POD is an estimated dose (expressed in human-equivalent terms) near the lower end of the
observed dose range from epidemiological or laboratory animal studies; and (2) extrapolation
from the POD to lower exposure doses below the observable range. The outcome of the
second part of the evaluation is the development of a CSF or an inhalation unit risk (IUR), which
is an estimate of the potency of the carcinogen. The CSF represents the upper 95 percent
confidence limit on the linear component of the slope of the tumorigenic dose-response curve in
the low-dose (low-risk) region. The CSF is an upper bound estimate of the likelihood that a
response will occur per unit intake of a chemical over a 70-year lifetime, and is derived by
applying a mathematical model to extrapolate from the relatively high doses administered to
experimental animals or experienced by persons in the workplace to the lower exposure levels
expected for human contact in the environment. A number of low-dose extrapolation "models
have been developed. USEPA generally uses the linear multistage model in the absence of
adequate information to support some other model. The linear multistage model is regarded as
conservative, meaning that it is likely to over predict the true CSF for a chemical. The concepts
and procedures summarized above are discussed in detail in USEPA's Guidelines for
Carcinogen Risk Assessment (USEPA 1986a, 2005b).
In practice, the CSF may be regarded as the cancer risk (proportion of affected individuals) per
unit of dose. In USEPA's derivation, the slope factor is expressed on the basis of chemical
weight: milligrams of substance per kilogram body weight per day (mg/kg/day, mg/kg-day). The
magnitude of the CSF can be used to compare the relative potency of one chemical substance
to another.
Quantitative cancer risk estimates have several uses, and the expression employed should be
tailored to each use. For example, to estimate risk from a given chemical via exposures by the
oral route, the slope factor (risk per mg/kg-day) is multiplied by the long-term daily dose (mg/kg-
day) from each oral pathway of exposure (e.g., soil, food, water). The total oral risk is found by
summing risks across all oral intake pathways.
For evaluating risks from chemicals by the inhalation route, the dose-response slope factor is
expressed as the risk per air concentration unit. This factor is called the IUR and is usually
expressed as risk per micrograms per cubic meter (risk per ng/m3) of air. To estimate risk from
a given chemical via exposures by the inhalation route, the IUR (risk per pg/m3) is multiplied by
the long-term daily air concentration (pg/m3).
6.1.3 Noncarcinogenic Effects
The basic approach used by USEPA in developing toxicity values for noncarcinogenic effects of
substances is based on the concept that some minimum (threshold) exposure level must be
reached before the effect will occur, i.e., that protective mechanisms exist that must be
overcome before an adverse health effect can occur. The estimated level of daily human
exposure below which it is unlikely that deleterious effects will result is known as the Reference
Dose (RfD). RfD values apply to the oral route of exposure and are reported in milligrams of
chemical per kilogram body weight per day (mg/kg-day). If adequate human data are available
from epidemiological studies (e.g., occupational exposure; environmental media exposure), the
RfD can be based on human effects data. In the absence of adequate human data, an RfD
value is based on data from experimental animals. If data from several animal studies are
available, USEPA first seeks to identify the animal model that is most biologically relevant to
humans (e.g., similar metabolism of the substance). In the absence of information that identifies
a given animal model as clearly most relevant, an assumption is made that humans are at least
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as sensitive to the substance as the most sensitive animal species tested. Accordingly, USEPA
selects the study using the most sensitive species tested and the most sensitive endpoint
measured as the critical study upon which the RfD is based.
From this critical study, the experimental exposure representing the highest tested dose level at
which no adverse effects were demonstrated (the no-observed-adverse-effect level, NOAEL) is
identified. In selecting the NOAEL as the basis for the RfD, the assumption is made that if the
critical toxic effect is prevented from occurring, then all toxic effects are prevented. The NOAEL
is distinguished from the no-observed-effect level (NOEL), which corresponds to the exposure
level at which no effect at all is observed; whereas, the NOAEL is the level at which no effect
considered to be of toxicological significance is observed. In some studies, only a lowest-
observed-adverse-effect level (LOAEL) is available. The use of a LOAEL in deriving an RfD
requires the use of an additional uncertainty factor as described below.
The RfD is derived from the NOAEL or LOAEL for the critical toxic endpoint by dividing the
NOAEL or LOAEL by one or more uncertainty factors. These factors are generally multiples of
10, with each factor representing a specific area of uncertainty in the extrapolation from the
available study data. For example, a 100-fold uncertainty factor is typically used when the RfD
is based on results from long-term animal studies. This factor of 100 incorporates an
uncertainty factor of 10 to account for variation in sensitivity in the human population and
another uncertainty factor of 10 to account for interspecies variability between humans and
experimental animals. Additional modifying factors ranging from 1 to 10 may be applied to
reflect qualitative judgments about limitations or uncertainties in the critical study or in the
available data base. Since the RfD is intended to be adequately protective of sensitive
individuals, such as children and the elderly, application of the RfD to the general population is
considered to be appropriate.
For the assessment of noncarcinogenic effects from inhalation exposures, USEPA has
developed values known as Reference Concentrations (RfCs). An RfC value is reported as an
air concentration in units of mass of chemical per unit volume of air (e.g., mg/m3). In analogy
with the RfD value, an RfC is also based on the concept of minimum threshold exposure and
the analysis of sensitive endpoints from critical studies. An RfC may also be developed from
toxicological data on humans or animals.
The concepts and procedures summarized above for the dose-response of noncarcinogenic
effects are discussed in detail in the document Review of the Reference Dose and
Reference Concentration Processes (USEPA 2002b).
6.1.4 Special Substances or Groups of Compounds
For certain substances or group of compounds, the methodology used to assess toxicity and
dose-response effects is somewhat different from that described above. In addition, there are
specific issues with respect to the toxicity of certain substances that should be noted.
Therefore, a separate discussion of the toxicity assessment approach is provided for the
following substances: dioxins, PAHs, PCBs, lead, mercury, chromium, and particulate matter.
6.1.4.1 Chlorinated Dioxins and Furans (Dioxins)
There are 210 individual forms or "congeners" of chlorinated dioxins and furans. A congener is
a single member of a chemical family (e.g., there are 75 congeners of chlorinated dibenzo-para-
dioxins). USEPA has developed procedures for assessing the cancer risks associated with
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exposure to the many forms of dioxins and furans based on the relative toxicity of these
compounds to the toxicity of 2,3,7,8-tetrachlorodibenzo-para-dioxin (2,3,7,8-TCDD), which is
generally believed to be the most toxic form (USEPA 2003a).
Each congener is assigned a value, referred to as a toxicity equivalency factor (TEF),
corresponding to its toxicity relative to 2,3,7,8-TCDD (i.e., 2,3,7,8-TCDD has a TEF of 1.0
and other dioxin and furan congeners have TEFs between zero and 1.0). Although various
groups and organizations have developed TEF approaches, the most recent USEPA-
recommended approach (USEPA 2003a) is used in this risk assessment. This approach is the
same as the internationally accepted approach adopted by the World Health Organization
(WHO 1998). Of the 210 possible congeners of the chlorinated dioxins and furans, only the 17
congeners having chlorine in the 2, 3, 7, and 8 positions are generally regarded as displaying
dioxin-like toxicity. The names of these congeners and their corresponding TEF values are
shown below.
PCDD/PCDF TOXICITY EQUIVALENCY FACTOR VALUES
Dioxin Congener
TEF
(unirless)
Furan Congener
TEF
(unidess)
2r3.7.8-TetrachIorodiben2o(p)dioxm
1.0
2,3,7,8-T etrachlorodibenzofuran
0.1
12.3.7.8-Pentachlorodibenzo(p)diosin
1.0
1,2,3,7,8-PentacMorodibenzofuran
0.05
1,2.3.4.7.8-Hexachlorodibenzo{p)dioxin
0.1
2,3,4,7,8-Pentaehlorcdibenzofuran
0.5
1.2.3.6.7.8-Hexachloicdibenzc(p)diosm
0.1
1,2,3,4,7,8-Hexachlorodibenzofuran
0.1
1,2.3.7.8.9-Hexachloiodibenzo(p)dioxin
0.1
1,2,3,6,7,8-Hexachlorodibenzofuran
0.1
1.2.3.4.6.7;8-HeptacMorodibenzo(p)dioxin
0.01
1,2,3,7.8,9-Hexachlorodibenzofuran
0.1
L2,3.4.6.7.8,9-Octachlorodibenzo(p)dioxin
0.0001
2,3,4,6,7,8-Hexachlorodibenzofuian
0.1
1,2,3,4,6,7,8-HeptachIorodibenzofuran
0.01
1,2,3,4,7,8,9-Heptachloradibenzofirran
0.01
1,2,3,4,6,7,8.9-OctacUorcxlibenzofuran
0.0001
The CSFs for dioxin and furan congeners other than 2,3,7,8-TCDD are derived by the
assignment of TEF values which compare the toxicity of the toxic congeners to that of 2,3,7,8-
TCDD. For 2,3,7,8-TCDD, the CSF is based on actual experimental evidence in rodents. For
the other 16 toxic congeners, the toxic potency compared to 2,3,7,8-TCDD is based on receptor
binding studies or a sensitive measure of receptor binding, namely induction of aryl hydrocarbon
hydroxylase (AHH) enzyme activity. These TEFs have been developed based on the activity of
these compounds in short-term toxicity assays that are considered predictive of their ability to
cause cancer in long-term carcinogenicity studies in experimental animals. Consequently, the
CSFs (derived from the TEF values) for these 16 toxic congeners are less certain than the
cancer slope factor for 2,3,7,8-TCDD.
In accordance with USEPA guidance (USEPA 2005c), the individual dioxin and furan congeners
are assessed separately throughout the exposure assessment process. This involves the
estimation of congener-specific emission rates (Section 4), followed by the evaluation of each
congener for partitioning into various environmental media. This approach is adopted due to the
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important differences between dioxin and furan congeners in the fate and transport properties
needed to estimate exposures through the food chain pathways (USEPA 2003a, 2005c;
Washburn 1991; McLachlan 1993). The TEFs are applied in the final step of the risk
assessment process, for estimating potential health risks.
In addition to the potential for dioxins to cause cancer, there is also concern for the potential
noncancer effects from these chemicals. USEPA has concluded that adequate evidence exists
to suggest that exposure to 2,3,7,8-TCDD and related dioxin-like compounds results in a broad
spectrum of effects in animals, some of which may occur in humans (USEPA 2003a).
This conclusion is based on results from epidemiology studies in human populations,
experiments in laboratory animals, and ancillary experimental studies. The induced effects will
likely range from adaptive changes at or near background levels of exposure, to adverse effects
with increasing severity as exposure levels increase above background levels. Enzyme
induction, alterations in hormone levels and indicators of altered cellular function are examples
of effects of currently unknown significance; they may or may not be early indicators of toxic
response. Because the threshold levels for exposure to 2,3,7,8-TCDD and dioxin-like
compounds below which toxic effects are not observed has not been established, USEPA does
not currently list RfD or RfC values for dioxin-like compounds.
The deduction that humans could respond to exposures to 2,3,7,8-TCDD and dioxin-like
compounds with adverse noncancer effects is based on the fact that these compounds impact
cellular regulation at a fundamental molecular level in a diverse variety of animal species, which
have been shown to respond with adverse effects. In addition, similar impacts on cellular
regulation have been demonstrated in human cells in experimental cell culture. It is well known
that individual animal species vary in their sensitivity to exhibit different effects due to exposure
to 2,3,7,8-TCDD. The available evidence indicates that humans most likely fall in the middle of
the range of sensitivity for individual effects among animals rather than at either extreme
(USEPA 2003a). Thus, humans do not appear to be either extremely sensitive to or extremely
insensitive to the individual effects of 2,3,7,8-TCDD and dioxin-like compounds.
In general, biochemical, cellular and organ-level effects have been observed in experiments in
which only 2,3,7,8-TCDD was studied. Specific data on the effects of other dioxin-like
homologues such as the pentachlorinated and hexachlorinated dioxins and furans are generally
not available. However, as mentioned previously, dioxin-like compounds exhibit the common
property of binding to the intracellular AHH receptor. Based on differences in receptor binding
capacity, TEFs have been developed for the 17 dioxin and furan congeners with chlorine
substituents in the 2,3,7, and 8 ring positions. The TEF for 2,3,7,8-TCDD is one; the TEFs for
the 16 other congeners are a fraction of this value (i.e., between zero and 1.0). Greater
uncertainty exists with respect to the extent of noncancer effects of the 16 other congeners as
compared to those of 2,3,7,8-TCDD due to the very limited amount of toxicology testing of these
congeners. Hence, greater uncertainty is associated with the TEFs of these congeners as
compared with the TEF for 2,3,7,8-TCDD.
USEPA's draft "Dioxin Reassessment" documents (USEPA 2000, 2003a) concluded that it
would be inappropriate to develop an RfD for dioxins. This is because dioxins are persistent
compounds in the environment and because pre-existing background exposures to dioxins are
not necessarily low compared to incremental dioxin exposures arising from a single source
under investigation. Most compounds for which RfDs are derived are not persistent, and
background exposures are generally very low and not taken into account. Therefore, the draft
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Dioxin Reassessment concluded that it is not appropriate to use the reference dose approach in
evaluating incremental exposures to dioxins.
Since the reference dose approach is considered inappropriate for evaluating the potential
noncancer effects of dioxins, USEPA Office of Research and Development (USEPA-ORD) and
Office of Solid Waste (USEPA-OSW) have recommended using a "Margin of Exposure" (MOE)
approach. This is an approach for estimating the potential for noncancer health effects arising
from incremental exposures to dioxins (USEPA 2003a, 2005c). To apply this approach, one
determines the ratio of the estimated daily dose of dioxins from a particular source (in this case,
intake of dioxin emissions from the CDF) to the average daily intake of dioxins in the general
U.S. population from existing sources, which is between 1 and 3 picograms per kilogram per
day (pg/kg-day) (USEPA 2000). The ratio of this incremental dose to the background dose of 1
- 3 pg/kg-day represents the margin of exposure to dioxins. A low ratio indicates that the
incremental source under investigation does not contribute a significant addition to the expected
background exposure to dioxin.
6.1.4.2 Polvcvclic Aromatic Hydrocarbons (PAHs)
The compounds benzo[a]anthracene, benzo[a]pyrene (BaP), benzo[b]fluoranthene,
benzo[k]fluoranthene, chrysene, dibenzo[a,h]anthracene, and indeno[1,2,3-cd]pyrene are
considered to be known or likely human carcinogens by USEPA. With the exception of
chrysene, these PAHs are all known animal carcinogens. USEPA has derived an oral CSF for
BaP; however, the remaining carcinogenic PAHs have not been assigned CSF values because
of the limitations in the dose-response cancer studies performed on these compounds. Until
individual CSF values are assigned, USEPA recommends an interim relative potency approach
to determining carcinogenic potential based on results in a group of carcinogenicity studies in
animals (USEPA 1993b). The toxicity of each carcinogenic PAH is evaluated relative to the
toxicity of BaP. The potency of BaP has been assigned a value of 1.0, which is equivalent to an
oral CSF of 7.3 per mg/kg-day. The other PAHs have been assigned a relative potency factor
(RPF) between zero and 1.0, as shown in the table below. Each of the PAHs considered in this
SRA is evaluated separately with regard to estimating CDF emissions, modeling fate and
transport in the environment, and quantifying human dose. The relative potency factors are
applied in the final step of the risk assessment process for estimating potential health risks.
Compound
RPF
Benzo(a)pyreiie
1.0 .
Benz(a)anthracene
0.1
Benzo(b)fluoranthene
o.t
Benzo(k)fhioranthene
0.01
Chrysene
0.001
Dibenz(a,li)anthracene
1.0
Indeno(l,2.3-cd)pyreiie
0.1
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6.1.4.3 Polvchlorinated Biphenvls (PCBs)
PCBs are mixtures of synthetic chlorinated organic chemicals. Different mixtures can take on
forms ranging from oily liquids to waxy solids. Although their chemical properties vary widely,
different mixtures can have many common components. Because of their inflammability,
chemical stability, and insulating properties, commercial PCB mixtures had previously been
used in many industrial applications, especially in capacitors, transformers, and other electrical
equipment. They were also used as additives in some paint products and as lubricants for
heavy machinery. These chemical properties also contributed to the persistence of PCBs after
release into the environment. The use of PCBs in the U.S. was banned in 1977, as a result of
evidence that PCBs persist in the environment and have significant potential for inducing
adverse human health and ecological effects. However, PCBs continue to be encountered in
the environment as the result of historical releases. The table below shows the chemical
composition of several commercially manufactured PCB mixtures (USEPA 1996b):
Aroclor
Clophen
Kanechlor
1016
1242
1248
1254
1260
A 30
A 60
300
400
500
Mono-CBs
2
1
Di-CBs
19
13
1
—
—
20
—
17
3
Tri-CBs
57
45
21
1
—
52
—
60
33
5
Tetra-CBs
22
31
49
15
—
22
1
23
44
26
Penta-CBs
—
10
27
53
12
3
16
1
16
55
Hexa-CBs
—
—
2
26
42
1
51
—
5
13
Hepta-CBs
—
—
—
4
38
—
28
—
—
—
Octa-CBs
—
—
—
—
7
—
4
—
—
—
Nona-CBs
—
—
—
—
1
—
—
—
—
—
Deca-CB
—
Columns may not total 100% due to rounding;" signifies less than 1%.
PCB mixtures manufactured in the United States carried the trademark "Aroclor" followed by a
four-digit number; the first two digits are "12," and the last two digits indicate the percent
chlorine content by weight. For example, Aroclor 1260 contains approximately 60 percent
chlorine by weight. Aroclor 1016 is an exception to this scheme; it contains approximately 41
percent chlorine. ("Clophens" and "Kanechlors" are PCB mixtures manufactured in Germany
and Japan, respectively, these series have their own numbering schemes). Each PCB
molecule consists of two six-carbon rings, with one chemical bond joining a carbon from each
ring. Chlorine can attach to any of the other ten carbons; these positions are said to be
substituted. There are 209 possible arrangements, called congeners; congeners with the same
number of chlorines are called isomers. The number and position of the chlorine atoms
determine a molecule's physical and chemical properties.
In earlier guidance (before 1996b), USEPA recommended that risk assessments treat all 209
PCB congeners as a mixture having a single carcinogenic potency. This recommendation was
based on the Agency drinking water criteria for PCBs (USEPA 1988), and used available
toxicological information with the following limitations;
• Aroclor 1260 was the only PCB for which a CSF had been developed; there was no
consensus procedure for applying this CSF for PCB mixtures with lower chlorine
content.
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• Available physical, chemical, fate-and-transport, and toxicological information on
individual PCB congeners was limited (primarily because separation and synthesis of
pure congeners is technically difficult).
• The number of tests conducted with various PCB mixtures and specific congeners to
demonstrate similar toxicological effects was very limited.
In the time since the drinking water criteria were published, USEPA has collected and re-
evaluated all of the accumulated research on the carcinogenic potential of PCB Aroclors. The
most significant findings were the availability of separate carcinogenesis studies of Aroclors
1016,1242,1254, and 1260 in appropriate animal models and a number of studies of the
transport and bioaccumulation of various congeners (USEPA 1996b). USEPA used this
information to derive three new CSFs to replace the former single CSF for PCBs. These new
CSFs became effective in IRIS in 1996. The CSFs and the criteria for their use are as follows
(USEPA 1996b):
Slope Factor (milligram;
per kilogram-day)-1
Criteria for Use
2
Food rhain exposure
Sediment or soil exposure
Early-life (infant and child) exposure by all routes to all PCB mixtures
Congeners with more than four chlorines comprise more than 0.5 percent of the total PCBs
0.4
(Not Typically Used)
Ingestion of water-soluble (less chlorinated) congeners
Inhalation of evaporated (less chlorinated) congeners
0.07
Congeners with more than four chlorines comprise less than 0.5 percent of the total PCBs
For evaluation of PCB cancer risk in the SRA, only the highest available CSF is employed for
the following reasons:
1) Potential exposures through the food chain and to children are being evaluated
2) The available analytical data on PCBs in Indiana Harbor sediments is reported only as
the total PCB Aroclor content; therefore the assumption is made that a significant level of
chlorination is present in the PCB sediment mixture (i.e., congeners containing more
than four chlorine atoms comprise at least 0.5 percent of the total PCB mixture).
In addition to the CSF associated with PCBs, USEPA recommends application of a noncancer
RfD for PCBs. IRIS specifies RfD values for Aroclor 1254 and Aroclor 1016. The RfD for
Aroclor 1254 is lower (i.e., more conservative) than the RfD for Aroclor 1016. Therefore, the
RfD for Aroclor 1254 is typically used for a risk assessment, such as this SRA, where analytical
information is available only for the total Aroclor content. This approach is considered valid and
conservative because approximately 77 percent of Aroclor 1254 is composed of PCB congeners
with more than four chlorine atoms (USEPA 1996b). In contrast, Aroclor 1016 is composed of
only about one percent of PCB congeners with more than four chlorine atoms (Huntzinger et al.
1974).
6.1.4.4 Lead
USEPA does not currently list an RfD or RfC for lead because an absolute threshold level for
exposure to lead below which toxic effects are not observed has not been established.
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Additionally, based on findings that neurobehavioral effects have been observed in children with
blood lead levels well below those that have caused carcinogenic effects in laboratory animals,
a CSF has not be derived by USEPA. The Agency relied upon the well-characterized
neurological effects observed in children as the sensitive endpoint for evaluating lead toxicity.
To apply a protective reference exposure level for lead in children, the goal of the Agency is to
limit exposure to lead levels in soil and air such that a typical (or hypothetical) child or group of
similarly exposed children would have no more than a five percent probability of exceeding a 10
micrograms per deciliter (pg/dL) blood lead level. This 10 yg/dl_ blood lead level is based on
analyses conducted by the Centers for Disease Control and Prevention (CDC) and USEPA that
associate blood lead levels above 10 pg/dLwith neurological health effects in children; and this
blood lead level is below a level that would trigger medical intervention (USEPA 1994a, 1998a).
This strategy is usually employed as part of determining a soil remediation goal for lead at
hazardous waste sites (e.g., Superfund, RCRA, Brownfields). But it can also be used to
determine an allowable limit for long-term air emission and deposition of lead onto soil in the
vicinity of a lead-emitting combustion unit or other lead-emitting source. USEPA has developed
an approach called the Integrated Exposure Uptake Biokinetic (IEUBK) Model, which evaluates
potential risks by predicting blood lead levels associated with exposure to lead. The IEUBK
Model for lead was originally developed by USEPA and collaborators from academia (Kneip et
al. 1983; USEPA 1990a). The IEUBK Model integrates a number of characteristics reflecting
the complex exposure pattern and physiological handling of lead by the body, and has been
validated at several sites where lead exposure data and human blood lead levels are available.
The IEUBK Model has been reviewed and recommended by the USEPA Science Advisory
Board (USEPA 1992b).
The Agency has now developed a computerized version of the IEUBK Model that predicts blood
lead levels and percentage distributions for children ranging in age from infancy to seven years
(USEPA 2001a). The IEUBK Model accounts for the major characteristics that influence the
uptake and absorption of lead from the environment, including the ability to incorporate default
or site-specific values for background levels of lead in air, soil, water, and diet. At present, it is
not possible to apply the computer model to predict potential blood lead levels in adults. In
general, however, children are more susceptible to lead exposures than adults as a result of
higher soil ingestion rates, higher absorption from the gut, nutritional variables and lower body
weight. Consequently, in the SRA, environmental concentrations of lead resulting from CDF
particulate emissions are used as inputs to the IEUBK Model to predict if child blood lead levels
could be significantly affected by lead emissions from the CDF.
6.1.4.5 Mercury
Mercury can exist in either organic or inorganic forms in the environment. Although potential
emissions of mercury from CDF particulates are expected to be in an inorganic form (as ionic
mercury), it is possible that some portion of the mercury is converted to organic forms (e.g.,
methylmercury) in the environment after deposition to land or water. The bioaccumulation
potential of methylmercury may be as much as ten times greater than that of inorganic forms of
mercury. Based on empirical measurements of mercury behavior in water bodies and
recommendations from USEPA's combustion risk guidance, the fate and transport modeling in
the SRA will assume that 15 percent of the total mercury predicted to be found in the aquatic
environment is in the form of methylmercury. The potential health risk for exposure to
methylmercury is evaluated using the specific RfD for methylmercury.
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6.1.4.6 Chromium
The oxidation state of chromium is important for evaluating the toxicity of this metal and the
risks associated with exposure. Hexavalent chromium (Cr+6) is the most toxic valence state of
chromium and has been shown to be a respiratory toxicant and a human carcinogen through
inhalation exposure. Consequently, the inhalation cancer potential for Cr+6 in air is evaluated
through an established IUR value, and the inhalation noncancer adverse effect of Cr16 in air is
evaluated through an established RfC value. Trivalent chromium (Cr+3) is the most commonly
occurring form of chromium in the environment as the naturally-occurring metal (ATSDR 2000).
Cr+3 has not been shown to be carcinogenic via inhalation or oral exposure in either humans or
laboratory animals; it has some potential for inducing noncancer adverse effects via oral
exposure, but intake levels must be relatively high.7 Therefore, the noncancer risk potential for ¦
Cr+3 is evaluated through an established RfD value.
The analytical data on chromium in the buried sediments associated with the CDF project are
reported only as total chromium. No information on the distribution of valence states is
available. Consequently, to assess potential health risks in the SRA, two separate procedures
are used to evaluate chromium risk. In the first procedure, the total chromium released from the
CDF is treated as 100 percent Cr*6 for evaluating inhalation cancer risk, inhalation noncancer
hazard potential, and oral noncancer hazard potential. In the second procedure, the total
chromium released from the CDF is treated as 100 percent Cr+3 for evaluating oral noncancer
hazard potential. The combination of these procedures should prevent underestimation of
health risks due to chromium exposure.
6.1.4.7 Particulate Matter
Particle pollution is a mixture of solid particles and liquid droplets found in the air. Some
particles are emitted directly from a source, while others are formed from complicated chemical
reactions in the atmosphere. In general, particle pollution consists of a mixture of larger
materials, called "coarse particles," and smaller particles, called "fine particles." Coarse particles
have diameters ranging from about 2.5 pm to more than 40 pm, while fine particles, also known
as known as PM2.5, include particles with aerodynamic diameters equal to or smaller than 2.5
pm. USEPA also monitors and regulates PM10, which refers to particles less than or equal to 10
pm in aerodynamic diameter. PM10 includes coarse particles that are "respirable"—particles
ranging in size from 2.5 to 10 pm that can penetrate the upper regions of the body's respiratory
defense mechanisms (USEPA 2004c).
Exposure to particles can lead to a variety of serious health effects. Scientific studies show
links between these small particles and numerous adverse health effects. Long-term exposures
to PM, such as those experienced by people living for many years in areas with high particle
levels, are associated with problems such as decreased lung function, development of chronic
bronchitis, and premature death. Short-term exposures to particle pollution (hours or days) are
associated with a range of effects, including decreased lung function, increased respiratory
symptoms, cardiac arrhythmias (heartbeat irregularities), heart attacks, hospital admissions or
emergency room visits for heart or lung disease, and premature death (USEPA 1982; 2004c).
7 In humans and animals, Cr*3 is an essential nutrient that plays a role In glucose, fat, and protein metabolism by
enhancing the action of insulin (ATSDR 2000). The biologically active form of chromium, called glucose tolerance
factor (GTF), is a complex of chromium, nicotinic acid, and possibly amino adds (glycine, cysteine, and glutamic
acid). Both humans and animals are capable of converting inactive inorganic chromium(lll) compounds to
physiologically active forms.
6-10
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Respirable particles are those which can penetrate to the lower regions of the respiratory
system and enter the lungs, and are generally assumed to be PM10. There are currently no
RfD, RfC, or CSF values for either total particles or respirable particles. However, USEPA has
established health-based criteria (i.e., the NAAQS) to provide protection against the adverse
effects of particulate matter in ambient air. The NAAQS were mandated by the Clean Air Act,
which established the following two types of national air quality standards:
1) Primary Standards are limits set to protect public health, including the health of
"sensitive" populations such as asthmatics, children, and the elderly. The 24-hour
Primary NAAQS for PM10 is 150 |jg/m3.
2) Secondary Standards are limits set to protect public welfare, including protection against
decreased visibility, damage to animals, crops, vegetation, and buildings.
Consequently, in the SRA, the predicted 24-hour average airborne concentration of particulate
matter released from the CDF was evaluated in view of the current Primary NAAQS for PM10.
To account for the episodic nature of particulate emissions from the CDF, the predicted 24-hour
average concentration was compared to the 24-hour Primary NAAQS. It should be noted that
the NAAQS pertains to monitored ambient air particulate matter concentrations that reflect
contributions from aH sources, not just the incremental particulate matter concentration
attributable to individual sources such as the CDF.
6.1.5 Selection of Chronic Toxicity Factors
Cancer and noncancer toxicity factors for many commonly encountered chemical substances in
the environment are published by USEPA in an Internet-accessible database known as IRIS.
IRIS is a compilation of toxicity factors and supporting information for the chemical substances.
Information in IRIS receives extensive internal and external peer review. At present, IRIS
contains recommended toxicity factors for the oral and/or inhalation route of exposure for more
than 500 chemical substances. As stated previously, the toxicity factors published in IRIS are
routinely applied in USEPA risk assessments to promote consistency and transparency across
the various USEPA programs, and because they represent a source of scientifically peer-
reviewed information.
For some chemical substances encountered in the environment, IRIS profiles and toxicity
factors are not available because the toxicological information is not adequate to assign toxicity
factors or because USEPA has not completed the formal peer review process required for entry
into the IRIS database. In cases where USEPA believes that a chemical substance not found in
IRIS has a toxicological potential, the Agency will review the available information and assign
"provisional" or "interim" toxicity factors for use in risk assessment. It is recognized that a higher
degree of uncertainty could be associated with the use of these provisional toxicity factors
compared to the IRIS-derived factors. In some cases, older toxicity information already
contained in IRIS could benefit from updating to better reflect current knowledge. Due to the
extensive resource requirements of adding and/or changing IRIS information, a process for
developing or revising assessments is in place (see http://www. epa.gov/iris/process. htm).
In order to manage the task of assigning toxicity factors for use in risk assessment, USEPA has
developed a recommended hierarchy or priority system for use in selecting toxicity factors for
risk assessment. The hierarchy system was developed for the Superfund program but is
generally applicable to other investigations where hazardous chemicals would be encountered.
6-11
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The hierarchy is contained in a policy directive issued by the Superfund program (USEPA
2003b). The hierarchy is summarized as follows:
• Tier 1 - IRIS Toxicity Factors. IRIS remains in the first tier as the preferred source of
human health toxicity values. IRIS contains the following preferred values for evaluating
toxicity from chronic exposure:
- Oral exposure toxicity factors
Oral Reference Doses (RfDs) for effects other than cancer
Oral CSFs for cancer
- Inhalation exposure toxicity factors
Inhalation RfCs for effects other than cancer
lURs for cancer
• Tier 2 - Provisional Peer Reviewed Toxicity Values (PPRTVs). USEPA ORD National
Center for Environmental Assessment (USEPA-NCEA) generates PPRTVs on a
chemical specific basis when requested by the USEPA Superfund program. PPRTVs
are derived after a review of the relevant scientific literature using the same methods
and sources of data employed by the IRIS program. All provisional toxicity values
receive internal review by two USEPA scientists and peer review by at least two non-
USEPA experts. A third scientific review is performed if there is a conflict between the
two original external reviewers. PPRTVs differ in part from IRIS values in that PPRTVs
do not receive the multi-program consensus USEPA review and the extensive external
peer review provided for IRIS values. This is because IRIS values are generally intended
to be used in all USEPA programs, while PPRTVs are developed specifically for the
Superfund program. The need for a PPRTV is eliminated once a corresponding IRIS
value becomes available.
• Tier 3 - Other Toxicity Values. Tier 3 includes additional USEPA and non-USEPA
sources of toxicity information. Priority should be given to those sources of information
that are the most current, have a transparent and publicly available basis, and have
been peer reviewed. Three primary sources of information have been identified under
this Tier:
- California EPA Reference Exposure Levels (RELs). The California
Environmental Protection Agency (CalEPA) publishes toxicity profiles and toxicity
values that are peer reviewed and address both cancer and noncancer effects
(CalEPA 2002, 2005). The process for developing these profiles is similar to that
used by USEPA to develop IRIS values and incorporates significant external
scientific peer review. The noncancer information includes available inhalation
health risk guidance values expressed as chronic inhalation and oral RELs.
CalEPA defines the REL as a concentration level at (or below) which no health
effects are anticipated—a concept that is substantially similar to USEPA's
noncancer RfD/RfC values. CalEPA's quantitative dose-response information on
carcinogenicity by inhalation exposure is expressed in terms of the unit risk
estimate (URE), defined similarly to USEPA's IUR.
- The Agency for Toxic Substances and Disease Registry (ATSDR) Minimal Risk
Levels (MRLs). These values are estimates of the daily human exposure to a
hazardous substance that is likely to be without appreciable risk of adverse
6-12
-------
noncancer health effects over a specified duration of exposure. The ATSDR
MRLs are peer reviewed and are available at http://www.atsdr.cdc.Qov/mr1s.html
on the ATSDR website.
- Health Effects Assessment Summary Tables (HEAST) Values (USEPA 1997b).
These tables cite dose-response assessments and toxicity factor values for some
substances that were prepared by USEPA-ORD but not submitted for internal
USEPA consensus. The level of internal USEPA and external peer review is
questionable or unknown. For some substances, older health effects
assessment documents omitted from HEAST also exist and are generally cited in
HEAST Table A-1 as USEPA-NCEA values. In 1989 and for several years
thereafter, HEAST was updated on a quarterly basis. HEAST is no longer
updated with new values and existing values are deleted as revised values
become available on IRIS.
Based on the hierarchy discussed above for selecting toxicity factors for chronic exposure, the
applicable toxicity factors (e.g., RfC, RfD, CSF, and IUR values) for the PCOCs in the SRA are
presented in Table 6-1. Table 6-1 also presents information on the origin of the toxicity factor
(e.g., IRIS, CalEPA, route-to-route extrapolation).
6-13
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Table 6-1: Toxicity Factors for the PCOCs Identified in the SRA
Constituents
Oral CSF
(mg/kg-
day)"
IUR
(Mg/mV
Oral RfD
(mg/kg-day)
Inhalation RfC
(pg/m3)
Notes
Metals
Antimony
NA
NA
4E-04 [a]
NA
[a]
Arsenic
1.5 [a]
4.3E-03 [a]
3E-04 [a]
3E-02 [b]
[a], [b]
Barium
NA
NA
0.2 [a]
NA
[a]
Cadmium
NA
1.8E-03 [a]
1E-03 [a]
2E-02 [b]
[a], [b]
Chromium:
Chromium (+3)
NA
NA
1.5 [a]
NA
[a]
Chromium (+6)
NA
1.2E-02 [a]
3E-03 [a]
1E-01 [a]
[a]
Copper
NA
NA
NA
NA
Lead
NA
NA
NA
NA
. Manganese
NA
NA
1.4E-01 [a]
5E-02 [a]
[a]
Mercury:
Mercury (Elemental)
NA
NA
NA
3E-01 [a]
[a]
Mercury (+2)
NA
NA
3E-04 [a]
1.05 [e]
[a], [e]
Methylmercury
NA
NA
1E-04 [a]
NA
[a]
Nickel
2.0E-04 [a]
2E-02 [a]
9E-02 [c]
[a], [c]
Selenium
NA
NA
5E-03 [a]
NA
[a]
Silver
NA
NA
5E-03 [a]
NA
[a]
Zinc
NA
NA
0.3 [a]
NA
[a]
PAHs
Acenaphthene
NA
NA
6E-02 [a]
2.1E+02 [e]
[a], [e]
Acenaphthylene
NA
NA
NA
NA
Anthracene
NA
NA
3E-01 [a]
1.05E+03 [e]
[a], [e]
Benzo[a]anthracene
0.73 [f]
1.1E-04 [i]
NA
NA
M. PI
BaP
7.3 [a]
1.1E-03 [b]
NA
NA
[a], [b]
Benzo[b]fluoranthene
0.73 [q
1.1E-04 [i]
NA
NA
w. PI
Benzo[k]fluoranthene
0.073 [f]
1.1E-05 p]
NA
NA
[f], P]
Benzo[g,h,i]perylene
NA
NA
NA
NA
Chrysene
0.0073 [f|
1.1E-06 [i]
NA
NA
[f], P]
Dibenz[a,h]anthracene
7.3 [f|
1.1E-03 [i]
NA
NA
m.p]
Fluoranthene
NA
NA
4E-02 [a]
1.4E+02 [e]
[a], [e]
Fluorene
NA
NA
4E-02 [a]
1.4E+02 [e]
[a], [e]
lndeno[1,2,3-cd]pyrene
0.73 [f]
1.1E-04 [i]
NA
NA
[f]J]
Naphthalene
NA
3.4E-05 [b]
2E-02 [a]
3.0 [a]
[a], [b]
Phenanthrene
NA
NA
NA
NA
Pyrene
NA
NA
3E-02 [a]
1.05E+02 [e]
[a], [e]
(PCBs) (total)
2.0 [a]
5.7E-04 [d]
2E-05 [a]
7E-02 [e]
[a], [d], [e]
6-14
-------
Constituents
Oral CSF
(mg/ka-
day)
IUR
(pg/m3)-1
Oral RfD
(mg/kg-day)
Inhalation RfC
(|ig/m3)
Notes
Dioxin/Furan Congeners
2,3,7,8-TCDD
1.5E+05
[cl
3.3E+01 [c]
NA
NA
[c]
1,2,3,7,8-PeCDD
1.5E+05
fe]
3.3E+01 [h]
NA
NA
fe], [h]
1,2,3,4,7,8-HxCDD
-1.SE+04
fa]
3.3 [h]
NA
NA
[g].[h]
1,2,3,6,7,8-HxCDD
1.5E+04
fa]
3.3 [h]
NA
NA
[g].[h]
1,2,3,7,8,9-HxCDD
1.5E+04
fel
3.3 [hi
NA
NA
[g]. [h]
1,2,3,4,6,7,8-HpCDD
1.5E+03
fa]
0.33 [h]
NA
NA
fel. [h]
OctaCDD
1.5E+01
fa]
0.0033 [h]
NA
NA
[g].[h]
2,3,7,8-TCDF
1.5E+04
fa]
3.3 [h]
NA
NA
[g]- [h]
1,2,3,7,8-PeCDF
7.5E+03
fa]
1.65 [h]
NA
NA
[g].[h]
2,3,4,7,8-PeCDF
7.5E+04
fa]
16.5 [h]
NA
NA
fe]. [h]
1,2,3,4,7,8-HxCDF
1.5E+04
fa]
3.3 [h]
NA
NA
fe], [h]
1,2,3,6,7,8-HxCDF
1.5E+04
fa]
3.3 [h]
NA
NA
[g]. [h]
1,2,3,7,8,9-HxCDF
1.5E+04
fel
3.3 [h]
NA
NA
fe]. [hi
2,3,4,6,7,8-HxCDF
1.5E+04
fel
3.3 [h]
NA
NA
fel. [h]
1,2,3,4,6,7,8-HpCDF
1.5E+03
fel
0.33 [h]
NA
NA
fe]. M
1,2,3,4,7,8,9-HpCDF
1.5E+03
fel
0.33 [h]
NA
NA
fe], [h]
OctaCDF
1.5E+01
fel
0.0033 [h]
NA
NA
fe]. [h]
Pesticides and Phenols
Aldrin
1.7E+01
[a]
4.9E-03 [a]
3E-05 [a]
1.05E-01 [e]
[a], [e]
d-BHC
NA
NA
NA
NA
Dieldrin
1.6E+01
[a]
4.6E-03 [a]
5E-05 [a]
1.75E-01 [e]
[a], [e]
ODD
2.4E-01 [a]
6.9E-05 [d]
NA
NA
[a], [d]
DDE
3.4E-01 [a]
9.7E-05 [d]
NA
NA
[a], [d]
DDT
3.4E-01 [a]
9.7E-05 [a]
5E-04 [a]
1.75 [e]
[a], [e]
Endosulfan II
NA
NA
6E-03 [a]
2.1E+01 [e]
[a], [e]
Endrin
NA
NA
3E-04 [a]
1.05 [e]
[a], [e]
Heptachlor
4.5 [a]
1.3E-03 [a]
5E-04 [a]
1.75 [e]
[a],[e]
6-15
-------
Constituents
Oral CSF
(mg/kg-
day)"
IUR
(Mg/m3)"1
Oral RfD
(mg/kg-day)
Inhalation RfC
(Mg/m1)
Notes
Heptachlor Epoxide
9.1 [a]
2.6E-03 [a]
1.3E-05 [a]
4.55E-02 [e]
[a], [e]
Lindane
18 [a]
5.1E-04 [a]
3E-04 [a]
1.05 [e]
[a], [e]
Phenol
NA
NA
3E-01 [a]
1.05E+3 [e]
[a], [e]
Toxaphene
1.1 [a]
3.2E-04 [a]
NA
NA
[a]
VOCs
Benzene
5.5E-02 [a]
7.8E-06 [a]
4E-03 [a]
3.0E+1 [a]
[a]
Ethylbenzene
NA
NA
1E-01 [a]
1E+03 [a]
[a]
PCE
5.4E-01 [b]
5.9E-06 [b]
1E-02 [a]
3.5E+01 [e]
[a], [b], [e]
Toluene
NA
NA
8E-02 [a]
5E+03 [a]
[a]
TCE
1.3E-02 [b]
2E-06 [b]
NA
6E+02 [b]
[b]
Xylene (meta-para)
NA
NA
0.2 [a]
100 [a]
[a]
Xylene (ortho)
NA
NA
0.2 [a]
100 [a]
[a]
Notes:
[a] - From USEPA IRIS database
[b] - USEPA Tier 3 chronic toxicity factor value as published by CalEPA
[c] - USEPA Tier 3 chronic toxicity factor values
[d] - IUR Factor value determined by route-to route extrapolation from the Oral CSF
[ej - Inhalation Reference Concentration factor value determined by route-to route extrapolation from the
Oral Reference Dose
[I] - Oral CSF is based on the Relative Potency Factor for this PAH and the listed Oral CSF for BaP
[g] - Oral CSF is based on the TEF for this dioxin/furan congener and the listed oral CSF for 2,3,7,8-
TCDD
[h] - IUR is based on the TEF for this dioxin/furan congener and the listed IUR for 2,3,7,8-TCDD
[i] — IUR is based on the RPF for this PAH and the listed IUR for BaP
NA - Not Available; no recommended value is available for this exposure route.
6.1.6 Toxicity Associated with Short-Term Exposure
As stated previously, the primary focus of the SRA is on long-term operating emissions from the
CDF, which is scheduled to be open for disposal of project sediments for 30 years until the CDF
site will be capped. Consequently, for the long-term operation of the CDF, emission limits of
volatiles and particulate matter were modeled based on the annual air emission limits imposed
by the CDF New Source Registration issued by the State of Indiana. The annual air emission
limits were used to calculate volatile and particulate matter emission rates from the CDF. These
rates were incorporated into the ISCST3 air dispersion model to predict average air
concentrations for modeling chronic inhalation risk for volatiles and particulate matter and for
predicting the average annual deposition rates of volatiles and particulate matter onto soil.
In addition to long-term annual emission rates and long-term exposure scenarios, the potential
for short-term or "acute" exposure to contaminants is recognized. This is because fluctuations
in the meteorological conditions (e.g., wind speed, wind direction, calm conditions) will cause
periodic deviations from the average annual predictions for air concentrations of contaminants.
From the standpoint of potential health risk due to CDF emissions, short-term deviations above
the average exposure will essentially be limited to a concern for the inhalation exposure
pathway. For indirect pathway exposures (e.g., ingestion, dermal), the level of exposure is
6-16
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based on the long-term deposition and accumulation of contaminants, which is much less
dependent on fluctuations from average meteorological conditions.
The site-specific meteorological data combined with the ISCST3 Model output can be used to
identify time periods associated with short-term air concentrations of volatiles, total particulate
matter, and particulate matter contaminants that are higher than the average case. The typical
procedure is to examine the ISCST3 Model output to identify the highest predicted air
concentrations of contaminants occurring over time periods ranging from one to 24 hours.
These concentrations are subsequently compared to health-based benchmarks for chemical
constituents that are commonly referred to as Acute Inhalation Exposure Criteria (AIEC).
AIEC values are air concentration guidelines designed to protect a variety of potentially exposed
groups including the general public, occupational workers, and military personnel. The values
are based on varying exposure durations up to 24 hours in length, and are intended to protect
against a variety of adverse health endpoints ranging from slight discomfort to mild, reversible
health effects up to serious, debilitating, and potentially life-threatening effects.
AIEC values are developed by several health research and regulatory organizations in the
United States. USEPA has recommended a general hierarchy for identifying AIEC values that
are appropriate to apply as short-term guideline values for protection of the general population,
including sensitive groups (e.g., children, the elderly). The hierarchical approach is
recommended because AIEC values are chemical-specific and no uniform methodology has
been devised for developing criteria values or benchmarks for all of the potential environmental
and industrial chemicals. The hierarchy appears in the USEPA HHRAP guidance for hazardous
waste combustor emissions, and is summarized below (USEPA 2005c):
1) Cal/USEPA Acute RELs - the concentration of a chemical in air at or below which no
adverse health effects are anticipated in the general population, including sensitive
individuals, for a specified short duration exposure period (CalEPA 1999).
http://www.oehha.ca.gov/air/pdf/acuterel.pdf
2) Acute Inhalation Exposure Guidelines - Level 1 (AEGL-1) - defined as "the airborne
concentration of a substance above which it is predicted that the general population,
including susceptible individuals, could experience notable discomfort, irritation, or
certain asymptomatic non-sensory effects. However, the effects are not disabling and
are transient and reversible upon cessation of exposure" (NOAA 2001; USEPA 2001b).
http://www.epa.gov/oppt/aegl/chemlist.htm
3) Emergency Response Planning Guidelines - Level 1 (ERPG-1) - defined as "the
maximum concentration in air below which it is believed nearly all individuals could be
exposed for up to one hour without experiencing other than mild transient adverse health
effects or perceiving a clearly defined objectionable odor" (USDOE 2001; SCAPA 2001).
http://www.bnl.gov/scapa/scapawl.htm
4) Temporary Emeroencv Exposure Limits (TEEL-1^ - defined as "the maximum
concentration in air below which it is believed nearly all individuals could be exposed
without experiencing other than mild transient adverse health effects or perceiving a
clearly defined odor" (USDOE 2001; SCAPA 2001).
http://tishg.eh.doe.gov/web/Chem Safetv/teel.html
6-17
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5) AEGL-2 values - defined as "the airborne concentration of a substance above which it is
predicted that the general population, including susceptible individuals, could experience
irreversible or other serious, long-lasting adverse health effects or an impaired ability to
escape." (An AEGL-2 value should only be used if a lower ERPG-1 or TEEL-1 value is
not available for a given chemical). (NOAA 2001; USEPA 2001b)
http://www.epa.gov/oppt/aeql/chemlist.htm
The guidelines listed above are those which have received the most extensive scientific peer
review as applicable guidelines for protection of the general population. The hierarchy is
presented in order of preference, from 1 (most preferred) to 5 (least preferred).
6.1.7 Acute Inhalation Exposure Criteria Values for Potential Chemicals of
Concern from CDF Emissions
Based on the selection hierarchy discussed above, relevant AIEC values for the PCOCs for the
SRA are presented in Table 6-2. This table presents the compilation of all published AlECs.
Since the hierarchy is a general recommendation, if a chemical has multiple AIEC values, all
values are listed along with the applicable exposure duration time. For respirable particulate
matter (i.e., PM10) there are no AIEC values since PM10 is not a specific chemical constituent.
To address short-term exposure to PM10, USEPA has promulgated a Primary Standard for
short-term exposure. The Standard requires that PM10 should not exceed 150 |jg/m3 for a 24-
hour period.
6-18
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Table 6-2: Acute Inhalation Exposure Criteria Values for PCOCs in the SRA
Constituents
Cal USEPA
Acute REL
AEGL-1
ERPG-1
TEEL-1
Metals
Antimony
NA
NA
NA
1.5E+03 pg/m
Arsenic8
1.9E-01 pg/mJ
4-hour value
NA
NA
3.0E+01 pg/m3
Barium
NA
NA
NA
1.5E+03 pg/m3
Cadmium
NA
NA
NA
3.0E+01 pg/m3
Chromium:
Chromium (+3)
NA
NA
NA
1.5E+03 pg/m3
Chromium (+6)
NA
NA
NA
3.0E+01 pg/m3
Copper
1.0E+02 pg/mJ
1-hour value
NA
NA
3.5E+03 pg/m3
Lead
NA
NA
NA
1.5E+02 pg/m3
Manganese
/ .
NA
NA
NA
7.5E+02 pg/m3
Mercury:
Inorganic Mercury
1.8E+00 pg/mJ
1-hour value
NA
NA
1.0E+02 pg/m3
Methylmercury
NA
NA
NA
3.0E+01 pg/m3
Nickel
6.0E+00 pg/mJ
1-hour value
NA
NA
7.5E+02 pg/m3
Selenium
NA
NA
NA
6.0E+02 pg/m3
Silver
NA
NA
NA
3.0E+02 pg/m3
Zinc
NA
NA
NA
1.5E+04 pg/m3
PAHs
Acenaphthene
NA
NA
NA
1.25E+03 pg/m*
Acenaphthylene
NA
NA
NA
2.0E+02 pg/mJ
Anthracene
NA
NA
NA
4.0E+02 pg/mJ
Benzo[a] anthracene
NA
NA
NA
3.0E+02 pg/mJ
BaP
NA
NA
NA
6.0E+02 pg/m1
Benzo[b]fluoranthene
NA
NA
NA
6.0E+02 pg/m3
8 CalEPA only lists a four-hour REL value.
6-19
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Constituents
Cat US EPA
Acute REL
AEGL-1
ERPG-1
TEEL-1
Benzo[k]fluoranthene
NA
NA
NA
6.0E+02 pg/m3
Benzo[g,h,i]perylene
NA
NA
NA
3.0E+04 pg/m3
Chrysene
NA
NA
NA
6.0E+02 pg/m3
Dibenz[a,h]anthracene
NA
NA
NA
3.0E+04 pg/m3
Fluoranthene
NA
NA
NA
1.0E+01 pg/m3
Fluorene
NA
NA
NA
2.5E+04 pg/m3
lndeno[1,2,3-cd]pyrene
NA
NA
NA
5.0E+02 pg/m3
Naphthalene
NA
NA
NA
7.86E+04 pg/mJ
(15 parts per million
[ppm]>
Phenanthrene
NA
NA
NA
1.0E+03 pg/m3
Pyrene
NA
NA
NA
7.5E+03 pg/m3
PCBs
(PCBs) (total)
NA
NA
NA
3.0E+03 pg/m3
Dioxin/Furan Congeners
2,3,7,8-TCDD9
NA
NA
NA
2.5 pg/m3
1,2,3,7,8-PeCDD
NA
NA
NA
2.5 pg/m3.
1,2,3,4,7,8-HxCDD
NA
NA
NA
1.25 pg/m3
1,2,3,6,7,8-HxCDD
NA
NA
NA
15 pg/m3
1,2,3,7,8,9-HxCDD
NA
NA
NA
15 pg/m3
1,2,3,4,6,7,8-HpCDD
NA
NA
NA
500 pg/m3
OctaCDD
NA
NA
NA
10 pg/m3
2,3,7,8-TCDF
NA
NA
NA
2.0 pg/m3
1,2,3,7,8-PeCDF
NA
NA
NA
7.5 pg/m3
2,3,4,7,8-PeCDF
NA
NA
NA
0.075 pg/m3
1,2,3,4,7,8-HxCDF
NA
NA
NA
7.5 pg/m3
1,2,3,6,7,8-HxCDF
NA
NA
NA
2.5 pg/m3
1,2,3,7,8,9-HxCDF
NA
NA
NA
12.5 pg/m3
9 A TEEL-1 for 2,3,7,8-TCCD is not published. The published TEEL-1 value for 1,2,3,7,8-PeCDD is used as the
surrogate value because these two congeners have the same TEF value.
6-20
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Constituents
Cal USEPA
Acute REL
AEGL-1
ERPG-1
TEEL-1
2,3,4,6,7,8-HxCDF
NA
NA
NA
1.5 pg/m3
1,2,3,4,6,7,8-HpCDF
NA
NA
NA
150 pg/m3
1,2,3,4,7,8,9-HpCDF
NA
NA
NA
250 pg/m3
OctaCDF
NA
NA
NA
7.5 pg/m3
Pesticides and Phenols
Aldrin
NA
NA
NA
7.5E+02 pg/m3
d-BHC
NA
NA
NA
1.5E+03 pg/m3
Dieldrin
NA
NA
NA
7.5E+02 pg/m3
DDD
NA
NA
NA
3E+04 pg/m3
DDE
NA
NA
NA
3E+04 pg/m3
DDT
NA
NA
NA
3E+03 pg/m3
Endosulfan II
NA
NA
NA
3E+02 pg/m3
Endrin
NA
NA
NA
3E+02 pg/m3
Heptachlor
NA
NA
NA
1.5E+02 pg/m3
Heptachlor Epoxide
NA
NA
NA
1.5E+02 pg/m3
Lindane
NA
NA
NA
1.5E+03 pg/m3
Phenol
NA
NA
NA
3.84E+04 pg/mJ
(10 ppm)
Toxaphene
NA
NA
NA
1E+03 pg/m3
VOCs
Benzene10
1.3E+03 pg/m3
6-hour value
1.7E+05 pg/mJ
(52 ppm) -1 hour
1.6E+05 pg/m3
(50 ppm)
1.6E+05 pg/m3
(50 ppm)
2.9E+04 pg/mJ
(9 ppm) - 8 hour
Ethylbenzene
NA
NA
NA
5.42E+05 pg/mJ
(125 ppm)
PCE
2.0E+04 pg/m3
1-hour value
2.37E+05 pg/mJ
(35 ppm) -1 hour
6.78E+05 pg/m3
(100 ppm)
2.37E+05 pg/m3
(35 ppm)
2.37E+05 pg/mJ
(35 ppm) - 8 hour
Toluene
3.7E+04 pg/m3
1-hour value
7.52E+05 pg/m3
(200 ppm) -1 hour
1.88E+05 pg/m3
(50 ppm)
7.52E+05 pg/m3
(200 ppm)
7.52E+05 pg/m3
(200 ppm) - 8 hour
TCE
NA
6.98E+05 pg/m*
(130 ppm) - 1 hour
5.37E+05 pg/m3
(100 ppm)
6.98E+05 pg/mJ
(130 ppm)
10 CalEPA lists only a 6-hour REL value.
6-21
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Constituents
Cal USEPA
Acute REL
AEGL-1
ERP6-1
TEEL-1
4.13E+05 pg/mJ
(77 ppm) - 8 hour
Xylene
2.2E+04 pg/m3
1-hour value
5.64E+05 pg/mJ
(130 ppm) -1 hour
NA
5.64E+05 pg/m3
(130 ppm)
5.642E+05 pg/mJ
(130 ppm) - 8 hour
IMA = Value not available
6.1.8 Toxicology Uncertainties and Limitations
In the majority of risk assessments, as in this SRA, available scientific information is insufficient
to provide a complete understanding of all the toxic properties of chemicals to which humans
are potentially exposed. Therefore, it is often necessary to infer these properties by
extrapolating them from data on the toxicological effects of chemicals in laboratory animals
under controlled conditions. Experimental animal data have been relied upon for many years by
regulatory agencies and other expert groups for assessing the hazards and safety of human
exposure to chemicals. This reliance has been supported in general by empirical observations.
There may be differences in chemical absorption, metabolism, excretion, and toxic response,
however, between humans and the species for which experimental toxicity data are available.
Uncertainties associated with the characterization of chemical toxicity in humans are also
introduced as a result of the following (USEPA 1989):
• Using dose-response information from effects observed at relatively high exposure
levels to predict effects that may occur following exposure to the much lower exposure
levels expected from contact with the chemical in the environment
• Using data from one route of exposure to predict effects from exposure via other routes
• Using dose-response data frorh short-term or subchronic exposures to predict the effects
following longer-term exposure
• Using dose-response information from homogeneous animal populations or healthy
human populations to predict effects that may occur in the general population, including
sensitive subpopulations.
The methods for addressing these uncertainties in the toxicological assessment for
cancer and noncancer effects are discussed below.
6.1.8.1 Uncertainties in the Characterization of Carcinogenic Effects
For many substances that are carcinogenic in animals, there is uncertainty as to whether they
are also carcinogenic in humans. The USEPA Office of Science and Technology Policy (USEPA
1985) has stated the following:
...known human carcinogens, with the single exception of arsenic, are carcinogenic in
appropriately conducted studies in some animal system (arsenic has recently been
reported to produce carcinomas of the respiratory tract in hamsters). This does not mean
that all chemicals found carcinogenic in animals will turn out to be carcinogenic in
humans. Because of differences in the production of critical metabolites and because of
6-22
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other differences between species, a given carcinogen may not produce cancer in all
species or in all strains of rodents.
The finding that relatively few substances are known human carcinogens may be due in part to
the difficulty in conducting adequately designed epidemiologic investigations in exposed human
populations. The available data in humans are derived mainly from retrospective epidemiology
studies of workers exposed to multiple chemicals and at dose levels that cannot be confirmed
with a high degree of reliability.
All CSFs in IRIS are accompanied by a weight-of-evidence classification, which is an indication
of the likelihood that the agent is a human carcinogen. This classification is based on the
completeness of the evidence that the agent causes cancer in experimental animals and
humans. The strength of the evidence that an animal carcinogen is a potential human
carcinogen is enhanced by such factors as the following: (1) a carcinogenic response in more
than one species, strain, and sex, and by multiple routes of exposure; (2) evidence of a clearly
definable dose-response relationship; (3) a high level of statistical significance of the increased
tumor incidence in treated compared to control groups; (4) a dose-related shortening of the
time-to-tumor occurrence or time to death with tumors; (5) a dose-related increase in the
proportion of tumors that are malignant; (6) a plausible biological mechanism for tumorigenicity;
(7) similar carcinogenic properties exhibited by structurally-related compounds; and (8)
evidence of an association between exposure to the chemical of concern and an increased
tumor incidence in human populations (USEPA 1986b, 1989).
Because of uncertainties associated with the measure of carcinogenic potency of a chemical in
humans, USEPA has adopted procedures in the calculation of CSFs that are generally
conservative. For example, USEPA uses the biologically acceptable data set from long-term
animal studies showing the greatest sensitivity. There are several mathematical models
available to derive low-dose unit risks from high exposure levels used in experimental studies.
No single model is recognized as the most appropriate for low-dose extrapolation. The model
generally used by USEPA is the linear multistage model, which provides the most conservative
estimate of risk at low doses (i.e., highest risk per unit dose). The procedure employed by
USEPA is also to use the 95 percent upper confidence limit on the slope of the dose-response
curve estimated by the linear multistage model. According to USEPA, use of the 95 percent
upper confidence limit value provides an estimate of the upper boundary on the actual risk
(USEPA 1989).
6.1.8.2 Uncertainties in the Characterization of Noncancer Effects
To adjust for uncertainties, USEPA and other regulatory agencies typically base the RfD or RfC
for noncancer effects on the most sensitive animal species—the species that experiences
adverse effects at the lowest experimental dose. This experimental dose is then adjusted
downward by the use of uncertainty and modifying factors to compensate for various sources of
uncertainty in the underlying toxicity data. The resulting toxicity factor incorporates a substantial
margin of safety, although the actual magnitude of this safety margin cannot be quantified with
certainty.
For all verified RfD and RfC values, USEPA provides in IRIS a qualitative statement of the
confidence that the evaluators have in the following: the RfD or RfC, the critical study upon
which the RfD or RfC is based, and the overall database.
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6.1.8.3 Uncertainties Associated with Route-to-Route Extrapolation
USEPA HHRAP guidance for emissions from hazardous waste incinerators (USEPA 1998b,
2005c) suggests that when a verified oral RfD has been developed for a given chemical by
USEPA, but there is no verified RfC, the RfD value should be extrapolated to a provisional
inhalation RfC value. And conversely, where a verified inhalation RfC has been developed but
there is no verified RfD for that chemical, the RfC should be used to extrapolate a< provisional
RfD value. This extrapolation approach may introduce significant quantitative uncertainties in
the estimate of noncancer effects from inhalation or ingestion of these chemicals. While this is
not an optimal approach for risk assessment practice, the alternative would be to omit the
inhalation or oral route of exposure from the quantitative risk estimate, and cause a potential
underestimation of the risk from the omitted exposure route. Therefore, using route-to-route
extrapolation of oral dose-response or inhalation information is considered preferable when no
toxicity factor value is available in the peer reviewed data sources. However, assumptions and
uncertainties involved when using toxicity factors calculated based on route-to-route
extrapolation should limit their use to screening-level or priority type risk assessments (USEPA
2005c).
As discussed in USEPA guidance for derivation of RfCs (USEPA 1994b), the ability to perform
quantitative route-to-route extrapolations is critically dependent on the availability of chemical-
specific data on both the capabilities of the chemical to reach the target site for toxicity and the
nature of the toxic effect. In cases where these data are not available, the use of default
assumptions to perform the route-to-route extrapolation results in increased uncertainty
associated-with the derived RfC value. The magnitude of the uncertainty will be chemical-
specific, and determined by the level of understanding provided by the supporting database as
to the response of the human body to exposure to the chemical.
There may be several explanations for differences in toxicity when the route of administration
differs, but the primary reason is likely to be related to the pharmacokinetics (i.e., absorption,
distribution, metabolism, and excretion) of the chemical. Different routes of exposure may
influence the factors that affect absorption at the portal of entry, such as the chemical's
physicochemical properties (e.g., dissociation state, solubility, reactivity), the nature of the
exposure (e.g., concentration, duration, regimen), or the physiologic parameters of the exposed
tissues (e.g., metabolic capabilities, cell types, pH). Similarly, factors that affect the distribution
of the chemical to the various tissues in the body (e.g., solubility, chemical reactivity), the
metabolism of the chemical (e.g., metabolic activation vs. metabolic detoxification, metabolic
capabilities of exposed tissues), and the excretion of the chemical from the body (e.g., rate of
clearance, site of excretion) all may be significantly affected by the route of exposure. Thus,
different routes of exposure may have a strong impact on the delivered dose of the chemical at
the target site of toxicity. For example, the portal of entry of the chemical may be exposed to
relatively high concentrations of the chemical. If the chemical acts directly on the local tissue
(e.g., stomach or respiratory tract), or if the local tissue can metabolize the chemical to an active
form, and if that tissue is susceptible to the effect of the chemical or its metabolites, lesions may
arise preferentially at the site of administration. Chemicals administered orally (either by
gavage, in feed, or in drinking water), pass directly from the gastrointestinal tract via the portal
system to the liver, and thus may be subject to "first-pass" metabolism. This in turn may either
increase or decrease the toxic response, depending upon whether the liver detoxifies or
activates the chemical, and what tissue is susceptible to the toxic effects of the chemical. A
similar chain of events may occur for inhalation exposures, where metabolism of the inhaled
chemical may occur at sites along the respiratory tract, thereby presenting the surrounding
tissues, and, assuming systemic absorption, remote tissues with a metabolically-modified
6-24
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chemical. Thus, one factor that must be considered in route-to-route extrapolations is the
metabolic capabilities of the tissues (in terms of both quantity and type of metabolites produced)
at the different portals of entry.
The chemicals of concern for which the procedure of route-to-route extrapolation is used to
assign an RfC value for the SRA is noted in Table 6-1.
6.1.8.4 Uncertainties Associated With Substances Without Toxicity Factor Values
Where experimental data on the toxicity of a given contaminant are so limited that no valid
toxicity factor value can be derived (i.e., either IRIS or provisional), potential cancer risks and
noncancer health effects posed by the chemical through the applicable exposure routes are not
evaluated quantitatively. However, most of the chemicals that are commonly encountered as
environmental contaminants in sediments, and that also possess a significant potential for
exposure and potential to cause cancer and/or noncancer toxic effects, have already been
identified and studied. For example, the National Toxicology Program has studied the
carcinogenic potential of approximately 450 chemicals to date and published the results in peer-
reviewed, publicly available reports (Huff 1996). Other investigators have studied the
carcinogenic potential of about 800 additional chemicals (Gold et al. 1995). The noncancer
toxic effects of a much larger number of chemicals have been investigated. Information on
these effects is published in a number of publicly available databases. Thus, the degree of
underestimation of risks based on not evaluating the toxicities of chemicals with inadequate
testing results, although not quantifiable, is expected to be relatively low.
6.2 Selection of Contaminants of Concern for the SRA
Based on the evaluation of sampling data on chemical constituents from Indiana Harbor
sediments, a list of PCOCs was developed for the SRA (Table 4-2). This PCOC list includes all
of the chemical constituents identified in the analytical data sets that were judged to be valid for
use in the SRA (Section 4).
The next step in the chemical-specific evaluation is to select a set of chemical constituents that
will be carried forward into the quantitative evaluation of cancer risk and noncancer hazard.
This set will be designated as the contaminants of concern (COCs) for the SRA. The COCs
represent the chemicals which could contribute most significantly to the cancer risk and toxic
hazard due to a combination of the following factors: concentration levels in the buried
sediments; level of cancer or toxic potency; and relative capacity to persist, biotransfer, and
bioaccumulate in the environment if released from the CDF. The COCs are the chemicals that
will be carried through all of the subsequent quantitative steps of the SRA.
The following criteria were used to develop the COC list. These criteria were judged to be
consistent with: 1) the objectives for evaluating risk in the SRA; and 2) the procedures used for
selecting COCs for risk assessment, as outlined in USEPA guidance documents for evaluating
risks from chemical releases at hazardous waste sites and from combustion emission facilities
(USEPA 1989, 1998b, 2005c).
1) PCOCs not detected in any sediment sample at a concentration level equal to or above
their corresponding analytical sample detection/reporting limit are not carried forward to
the COC list. PCOCs in this category are: silver, dibenzo[a,h]anthracene, endrin,
heptachlor, heptachlor epoxide, lindane, phenol, toxaphene, PCE, and TCE.
6-25
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2) If a PCOC was detected above the analytical sample detection/reporting limit but it
possesses no verifiable toxicity factors from any database of acceptable toxicity factors,
that PCOC is not carried forward to the COC list. PCOCs in this category are: copper,
acenaphthylene, benzo[g,h,i]perylene, and d-BHC (delta-lindane).
3) For estimating the inhalation risk from volatile constituents, select from the COPC list the
volatile constituent that possesses the highest IUR, and the volatile constituent that
possesses the lowest inhalation RfC. Assume that these chemicals represent 100
percent of the allowable annual volatile emissions from the CDF for the purpose of
estimating inhalation cancer risk and inhalation noncancer hazard (see Section 4).
Based on a review of the toxicity factors for the volatile COPCs, naphthalene is the
volatile constituent which possesses both the highest IUR and the lowest RfC.
Therefore, naphthalene is the constituent carried forward to the COC list as the
surrogate for volatile emissions.
4) All remaining PCOCs not addressed by criteria 1, 2, or 3 above are carried forward to
the COC list.
After application of the above criteria, the COC list includes the following constituents:
Metals
Dioxin/Furan Congeners
Antimony
2,3,7,8-TetraCDD
Arsenic
1,2,3,7,8-PentaCDD
Barium
1,2,3,4,7,8-HexaCDD
Cadmium
1,2,3,6,7,8-HexaCDD
Chromium
1,2,3,7,8,9-HexaCDD
Lead
1,2,3,4,6,7,8-HeptaCDD
Manganese
OctaCDD
Mercury
2,3,7,8-TetraCDF
Nickel
1,2,3,7,8-PentaCDF
Selenium
2,3,4,7,8-PentaCDF
Zinc
1,2,3,4,7,8-HexaCDF
1,2,3,6,7,8-HexaCDF
SVOCs
1,2,3,7,8,9-HexaCDF
Acenaphthene
2,3,4,6,7,8-HexaCDF
Anthracene
1,2,3,4,6,7,8-HeptaCDF
Benzo[a]anthracene
1,2,3,4,7,8,9-HeptaCDF
BaP
OctaCDF
Benzo[b]fluoranthene
Benzo[k]fluoranthene
Pesticides
Chrysene
Aldrin
Fluoranthene
Dieldrin
Fluorene
DDD
lndeno[1,2,3-cd]pyrene
DDE
Naphthalene
DDT
Phenanthrene
Endosulfan II
Pyrene
Other
PCBs
Particulate Matter
PCBs (total)
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6.3 Exposure Assessment
The exposure assessment step of the risk assessment involves the identification of the
potentially exposed population and the measurement or estimation of the magnitude of chemical
contaminant exposure to individuals in that population. This section of the SRA describes the
steps used in assessing exposure to the population residing in the vicinity of the SRA. Within
the exposed population, the magnitude of exposure is expected to vary by individual, due
primarily to differences in residential location, and differences in individual characteristics and
activity patterns. Therefore, a distribution of exposures exists across the population. Direct
measurement of this exposure distribution cannot readily be performed. Therefore, subgroups
within the population are identified which are expected to have similar exposure because of
similarities in activity and behavior patterns. A population subgroup which shares similar activity
and behavior patterns and a similar combination of exposure pathways is described by a
specific exposure scenario. This section also describes the methods used to: (1) develop a
geographically-based "Study Area" for evaluating potential contaminant exposure in the vicinity
around the CDF; (2) estimate Study Area chemical contaminant concentrations in
environmental media based on the fate and transport properties of chemicals in the
environment; and (3) estimate amounts of contaminant intakes within a population subgroup
described by a specific exposure scenario.
6.3.1 Study Area
The Study Area map for the SRA project (Figure 6-1) was generated using ArcGIS 9.1™
software. In creating the map, sequential data layers were added in ArcGIS ArcMap™
application software.1 Data layers were assembled in the following order: (1) adding a
topographic map layer and Digital Ortho Quarter Quads (aerial photos); (2) drawing polygons to
outline geographic areas of interest, such as the six residential and school zones; 3) adding line
features; and (4) by adding point features. The U.S. Geological Survey (USGS) topographic
map layer is displayed at 60 percent transparency so that aerial photography can be visible on
the map.
Data layers included in the map were obtained from several sources. The Digital Ortho Quarter
Quads (aerial photos) and the topographic map were obtained from USGS. The Indiana Harbor
Navigational Channel and the CDF layers are Computer Aided Design (CAD) files from USACE.
These CAD layers were converted to a shapefile in an ESRI data format. This was
accomplished by adding the data layer to the ArcMAP application and then exporting the data
layer as an ESRI shapefile. All other layers were generated and provided by USEPA staff.
The locations of the air monitoring sites were verified during a site visit where a Global
Positioning System (GPS) instrument was used to determine latitude-longitude (LAT-LONG)
coordinates. These coordinates were then imported into the ArcMap application software and
generated into an ESRI event file for placement onto the map. The event file was exported as
an ESRI shapefile for use in mapping. The neighborhood/school zone layers and the water
body layers were generated by digitizing the polygons using ArcGIS ArcMap editing tools. The
aerial photos and topographic map were used as reference layers in the digitizing of the
neighborhood/school zone layers and the water body layers.
11 ArcGIS 9.1™ and ArcMap™ application software are proprietary products from ESRI; Redlands, CA
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6.3.2
Exposure Scenarios
Based on the expected behaviors of populations in the vicinity of the CDF source and the
environmental media that could be impacted by airborne chemical contaminant releases from
the CDF, there could be a number of exposure scenarios selected for a risk assessment. After
evaluation of the likely potential contaminant exposures expected in the vicinity of the CDF, and
after conducting site visits to the CDF locale and discussions with local citizens, the following
exposure scenarios were selected for the SRA:
6.3.2.1 Local Area Resident
A local area resident is defined as an adult or child who lives within a known existing residential
area in the vicinity of the CDF. Specific residential areas were selected based on their distance
and direction from the CDF site. The selected residential areas were assigned geographic
boundaries determined by evaluating zoning maps, USGS Quadrant maps, local land use
maps, and site visits. Based on the geographic analysis, the following neighborhoods or
residential zones were selected for evaluation in the SRA. (These zones are illustrated in
Figure 6-1).
Residential Zone or
Neighborhood
Approximate
Distance from
Center of CDF
Approximate
Direction from CDF
Municipality or
Political Entity
Calumet
2.8 km
Southeast
East Chicago
Hammond
2.2 km
Southwest
Hammond
Marktown
1.5 km
Northeast
East Chicago
North Harbor / East Harbor
2.0 km
East/Southeast
East Chicago
Northside / Southside
1.4 km
South
East Chicago
Robertsdale
1.1 km
North/Northwest
Whiting
The exposure pathways that apply to any individual living within a residential area are:
• Inhalation of volatile contaminants and particulate contaminants
• Incidental ingestion of soil containing deposited contaminants
• Incidental dermal contact with contaminants in soil
• Ingestion of contaminants incorporated into produce from a typical home garden.
6.3.2.2 Local Area Student
A local area student is defined as a school age child or teenager who attends school in the
vicinity of the CDF. Specific schools were selected by evaluating local maps and through site
visits. Based on the evaluation, two schools were selected based on geographic proximity to
the CDF12. The two schools are:
West Side Junior High - 4001 Indianapolis Blvd., East Chicago, IN
East Chicago Central High School - 1100 W. Columbus Dr., East Chicago, IN
12 A total of ten public schools were identified in East Chicago. Based on proximity to the CDF and the prevailing
wind direction for particle release predicted by the WEPS Model, the two selected school locations would be
expected to have higher impacts of contaminants from air and soil than other school locations. In addition, these two
schools are more likely to have the types of outdoor athletic facilities and athletic programs which would favor more
significant contact time and contact opportunity with contaminants in air and soil.
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Both schools are located at approximately the same distance and direction from the CDF; 1.2
km south of the CDF, at the intersection of Indianapolis Blvd. and Columbus Dr. (The school
locations are illustrated by the area outlined in green color on Figure 6-1).
Due to the proximity of the two schools, they were combined into a single location for the
purpose of evaluating potential contaminant exposure under the Student scenario.
The exposure pathways that apply to any student attending school are:
• Inhalation of volatile contaminants and particulate contaminants during school
attendance
• Incidental ingestion of soil contaminants during school attendance or as a "student-
athlete"
• Dermal contact with soil contaminants during activities typical of a "student-athlete"
during school attendance.
6.3.2.3 Local Area Fisher
A local area fisher is defined as an adult or child who consumes fish obtained from a local water
body and is also a local area resident. A candidate local water body is one which is located
partially or completely within the 10 x 10-km air model study area and which is assumed to
support the habits of a "subsistence fisher." A subsistence fisher is a term that is often applied
to a high-end fish consumer who obtains a significant' proportion of dietary protein through fish
harvested from a local water body. Based on water bodies located in the study area and a
review of available information on the likelihood for a significant level of fishing from local water
bodies, Lake George and Powderhom Lake were chosen as the water bodies for evaluating
contaminant exposure through fish consumption.13 Lake George is located northwest of the
CDF, with a southern shoreline located approximately 1.9 km from the CDF. Powderhorn Lake
is located west of the CDF (in the State of Illinois), with an eastern shoreline located
approximately 3.7 km from the CDF. As part of the evaluation, several other water bodies were
considered, but determined to be inappropriate for inclusion in the SRA. Specifically, there are
several, relatively small water bodies located to the southwest and west of the CDF on property
currently owned and operated by the BP Amoco Refinery. These include an inactive borrow pit,
informally referred to as Lake Mary; a second inactive borrow pit used for catalyst disposal from
refinery operations; and an inactive turning basin just north of the Lake George Branch Canal.
All of these water bodies are within the boundary of the BP Amoco facility. It was confirmed by
BP Amoco personnel that access by the public is restricted and controlled, and recreation or
fishing in these water bodies by anyone from the public or refinery employees is strictly
unauthorized. Some of these water bodies, such as the catalyst pond, will be undergoing
remediation actions by the refinery. In addition, Lake Mary and adjacent wetlands are subject to
13 Information sources on local water bodies were reviewed. The primary information sources were from the Indiana
Department of Natural Resources (IDNR; http://www.in.aov/dnrt and the Illinois State Water Survey (ISWS;
http://www.sws.uiuc.eduV IDNR and ISWS present information on water bodies that are recommended for fishing,
and would therefore be candidate water bodies for supporting the needs of a high-end fish consumer. Other water
bodies are located partially within the Study Area, inclucOng the GCR and the IHSC. Available information indicates
that these water bocfies could not likely support the fish harvest needs of a high-end fish consumer, and/or these
water bodies have advisories for fish consumption because of historical problems with chemical contamination and
poor water quality (httpV/www.epa.gov/glnpo/aoc/qrandcal. htmll In addition, since sediment currently in the IHSC is
the source of the material which is being placed into the CDF, it is not appropriate that an incremental risk from
emissions should be calculated, when in fact, the dredging and removal of the material will result in an overall net
decrease of contaminants in those areas.
6-29
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a federal consent decree entered pursuant to the Natural Resource Damage Act whereby BP
Amoco will, at some future date, turn these properties over to the trustees for preservation.
Therefore, it will be the responsibility of the trustees to determine the acceptable future use of
these areas.
The exposure pathways that apply are:
• Consumption of fish fillets harvested from Lake George or Powderhorn Lake
• Exposure pathways expected for a Local Area Resident (as described above).
The exposure scenarios described above cover multi-pathway exposure situations. In addition,
one other subgroup was identified as a special population segment who may receive
contaminant exposure because of one particular pathway or activity pattern. On this basis, the
following additional subgroup was evaluated: breast-feeding infants (children up to one year old)
of local area residents.
Breast-feeding infants were assumed to reside in the same residential zones or neighborhoods
described previously. Based on current USEPA methodology and guidance for risk
assessment, the evaluation of contaminant uptake into breast milk is limited to the highly
persistent and highly lipophilic contaminants, namely chlorinated dioxins and furans (USEPA
1998b, 1999a, 2005c).
6.3.3 Exposure Pathways
The potential pathways of exposure for the population subgroups that may be exposed to
airborne chemical contaminants released from the CDF are reviewed below, including rationale
for why a pathway was included or excluded from the exposure evaluation.
6.3.3.1 Air Exposure
Direct inhalation of emissions from the CDF is the primary route of exposure to airborne
contaminants for all population subgroups.
6.3.3.2 Soil Exposure
A portion of the chemical contaminants emitted from the CDF is expected to deposit on local
surface soils due to the processes of dry and wet deposition. Residents engaged in outdoor
work and recreation may inadvertently ingest soil and absorb chemicals through the skin during
soil contact. These exposure pathways also apply to local school children, who could engage in
outdoor recreational activities on school property.
6.3.3.3 Home Garden Food Chain Exposure
Chemical contaminants deposited in the vicinity of the facility may accumulate in various parts
of the food chain. Chemicals may be incorporated into vegetation and crops as a result of
deposition on leaves, absorption from the soil through the roots, and uptake of vapors from the
air. Vegetable produce grown in home gardens could become a source of contaminant
exposure for local residents.
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6.3.3.4 Fish Consumption Exposure
Chemical contaminants may enter water bodies through direct deposition from air or by
transport and runoff from the land. After entering a water body, chemicals could be dissolved in
surface water and/or adsorbed to sediments. Depending on their potential for uptake and
bioaccumulation, chemicals may be transferred to and accumulate in fatty tissues of fish in local
water bodies. Individuals who consume locally-caught fish may be indirectly exposed to
chemical contaminants. For a typical resident in the vicinity of the CDF, fish harvested from a
single local water body in the vicinity of the CDF are not likely to represent a significant source
of food or a major portion of total dietary protein. However, it is possible that a subgroup of the
local population may exist that derives a significant fraction of their dietary protein from locally
caught fish ("subsistence fishing" as defined above). Although no information was obtained to
confirm that subsistence fishing actually occurs from local water bodies in the Study Area, the
exposure assessment assumes that subsistence fishermen reside in the vicinity of the CDF.
This activity is used to represent or model the high-end consumption of fish.
6.3.3.5 Breast Milk Exposure
Local resident women of child-bearing age may be exposed to chemical contaminants through
the exposure pathways described previously. Chemical contaminants that are persistent and
lipophilic compounds such as chlorinated dioxins and furans may accumulate in body tissues,
preferentially concentrating in adipose (fatty) tissue. Such compounds may then accumulate in
the breast milk of nursing women in the study area. Based on current USEPA guidance,
exposure of nursing infants to chlorinated dioxins and furans in breast milk is considered in the
risk assessment.
6.3.3.6 Surface Water Exposure
Chemical emissions may enter surface water in the vicinity of the facility through deposition of
emissions directly onto a water body or through runoff of contaminated soil that enters the water
body. In the vicinity of the CDF, Lake Michigan is the only known and expected source of
drinking water for residents living in the vicinity of the CDF. Lake Michigan is located a
significant distance north of the CDF site and outside of the zone where significant contaminant
deposition would occur. In addition, Lake Michigan surface water is subjected to several
treatment steps before use, and water quality is regularly evaluated for compliance with
regulations governing contaminant limits. Therefore, significant contaminant exposure through
this pathway is unlikely, and is not evaluated further in the SRA.
6.3.3.7 Groundwater Exposure
It is possible that chemicals deposited onto surface soils could become dissolved in
precipitation and percolate through surface soils to the groundwater. In a previous study,
USEPA evaluated the potential for chemicals deposited onto soil from air deposition to become
a source for groundwater contamination (USEPA 1990b). This potential route of chemical
transport was evaluated using a worst-case assumption model for leaching and transport of
organic and inorganic constituents from surface soils to groundwater. The study concluded that
a very limited potential for contamination of groundwater exists, and that further evaluation of
this pathway was unnecessary for airborne deposition of chemicals. In addition, in this highly
urbanized area in the vicinity of the CDF, the drinking water source for all residents is surface
water from Lake Michigan and the use of groundwater for drinking water is not allowed.
Consequently, the groundwater exposure pathway is not evaluated further in the SRA.
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6.3.4 Estimation of Contaminant Concentrations in Environmental Media
In order to assess the risk of exposure to chemical contaminants emitted from the CDF, an
estimate of the concentrations of chemicals of concern in air, soil, vegetables, fish, and breast
milk is necessary. The modeling of contaminant dispersion and transport in air is discussed in
Sections 4 and 5 of this SRA Report.
For other environmental media, concentrations are estimated using fate and transport models
designed to simulate the transport of substances in the environment over time. The models
used in this assessment are based on USEPA guidance (USEPA 1990b, 1993c, 1998b, 2005c)
and reflect the current understanding of environmental fate and transport processes for
chemical contaminants which originate as air emissions. This section presents an overview of
the models employed in the SRA. A very detailed presentation of the fate and transport models,
the model algorithms (i.e., equations), many recommended input values needed for the models,
and the basis for these values is found in USEPA's most recent guidance document for
assessing the fate and transport of chemical emissions from combustion facilities (USEPA
2005c). Because of the expected similarity in the fate and transport characteristics of
chemicals emitted from a combustion stack or emitted by the CDF area source, the fate and
transport models developed for combustion emissions are considered as directly applicable and
usable for assessing fate and transport in this SRA study.
Whenever reasonable, site-specific data and model inputs are applied in this assessment rather
than using only default values. It is anticipated that use of site-specific values reduces the
uncertainty associated with the modeled results. It should be noted, however, that several of
the models applied in this assessment are based on limited data and, therefore, contribute to
the uncertainty in the results. The uncertainties that result from applying these models are
discussed qualitatively at the end of this section. To compensate for the uncertainty in the
estimation process, conservative fate and transport assumptions are generally applied so that
estimated environmental concentrations are likely to be higher than what would be actually
found or measurable in the vicinity of the CDF.
6.3.4.1 Estimation of Contaminant Concentrations in Soil
Chemical contaminants emitted to the atmosphere from a point source or an area source such
as the CDF may deposit onto local surface soils due to dry and wet deposition of particles and
vapor. The general processes which could contribute to contaminants entering and
accumulating in soil at given location are illustrated below.
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CORC
Emissions
The concentration of chemicals in surface soil is required to: (1) estimate potential human
exposures through soil ingestion and dermal contact with the soil, (2) predict uptake into
vegetation for human consumption, and (3) estimate concentrations in surface water due to
runoff from contaminated soil. To estimate the chemical concentration in soil, the
recommended equation has the following form:
100 • (Dy-dp + Dym> + Ldij.) • [1.0 - exp (-ks ¦ tD)]
05 = 1 ZsBDks
where
Cs = Average soil concentration over exposure duration (mg COPC/kg soil)
100 = Units conversion factor (mg-nr/kg-cm2)
Dydp = Unitized yearly dry deposition from particle phase (s/nr-yr)
Dywv = Unitized yearly wet deposition from vapor phase (s/nr-yr)
Ldj = Dry vapor phase diffusion load to soil (g/'m--yr)
ks = COPC soil loss constant due to all processes (yr1)
tD - Time period over which deposition occurs (time period of combustion)
(yr)
Z; = Soil mixing zone depth (cm)
BD = Soil bulk density (g soil/cm3 soil)
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Soil contaminant concentrations are estimated for surface soil intervals (i.e., upper 1 centimeter)
and root zone soil (i.e., upper 20 centimeters) (USEPA 1990b). In addition, average soil
concentrations within the upper 20 centimeters are used as an input to estimating surface water
concentrations (USEPA 1994c), assuming the presence of an agricultural watershed, which
could have some tilled and some unfilled soils. Estimated soil concentrations at these depths
are based on deposition rates of constituents of concern assuming complete mixing within the
soil layer of interest (1 centimeter or 20 centimeters) and continuous operation of the CDF over
a period of 30 years. Dry and wet deposition rates for particles (Dyd and Dyw) are predicted by
the ISCST3 air dispersion model.
The parameter values used in the above equation are presented in previous USEPA guidance
along with the methodology and assumptions used in estimating soil concentrations (USEPA
1998b, 2005c). Site-specific information needed to estimate soil concentrations include: fraction
of organic carbon in soil; bulk density of soil; annual precipitation, irrigation, runoff, and
evapotransporation; soil volumetric content; universal soil loss equation (USLE) constants for
erosivity and erodability; wind speed; and air temperature, viscosity and density.
Appendix 6-1 presents a detailed description of the equations and parameters needed to
calculate contaminant concentrations in soil. The site-specific values used in this assessment
for estimating contaminant concentrations in soil are presented in Appendix 6-2.
6.3.4.2 Estimation of Concentrations in Vegetation
The concentration of constituents in vegetation is necessary to estimate the exposure to
chemicals through ingestion of vegetation (i.e., home-grown vegetables). Chemical
contaminants may bioaccumulate in plants through three mechanisms: uptake by roots, direct
deposition onto exposed plant tissues, and air-to-plant transfer of vapor-phase constituents.
The rate and amount of chemical uptake by produce is dependent on the type of vegetable and
its potential for exposure to the atmosphere. For example, contaminant deposition is more likely
to occur onto leafy vegetables (such as lettuce) than onto vegetables that are protected from the
atmosphere (such as com or root vegetables). Similarly, the uptake of chemicals from the soil
will differ for belowground and aboveground vegetables. Therefore, because of the general
differences in contamination mechanisms, garden produce is usually assigned into two broad
categories: aboveground produce and belowground produce. In addition, aboveground
produce is further subdivided into exposed and protected aboveground produce for
consideration of contamination as a result of indirect exposure.
Aboveground Produce
Aboveground produce is usually categorized in to the following types:
• Aboveground leafy produce (e.g., lettuce, broccoli)
• Aboveground protected produce (e.g., com, peas, grain)
• Aboveground exposed produce (e.g., tomatoes, green peppers).
Aboveground exposed produce is assumed to be contaminated by three possible mechanisms:
• Direct deposition of particles - wet and dry deposition of particle phase contaminants on
the leaves and fruits of plants
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• Vapor transfer - uptake of vapor phase contaminants by plants through their foliage
Root uptake - root uptake of contaminants available from the soil and their transfer to
the aboveground portions of the plant.
-Z&fM
4 .
\ J ^
Dapoallton
afMdH
(toot Uptaka
fnxn Boll
OOPO Conewrtradon In
Abemgrwnd Produc*
The total contaminant concentration in aboveground exposed produce is calculated as a sum of
contamination occurring through all three of these mechanisms.
CV = Pr.t
where:
CV =
Pr, =
Pdi =
Pv; =
+ Pdi + Pv.
total concentration of constituent in the plant group., mg/kg
concentration of constituent in i4 plant group due to root uptake, mg/kg
concentration of constituent in l* plant group due to direct deposition, mg/kg
concentration of constituent in i4 plant group due to air-to-plant transfer, mg/kg
However, edible portions of aboveground protected vegetables and fruits, such as peas, com,
and melons, are covered by a protective coating (e.g., pods, sheaths, rinds); consequently, they
are protected from contamination through deposition and vapor transfer. Therefore, root uptake
of contaminants is the primary mechanism through which aboveground protected produce
becomes contaminated.
Appendix 6-1 presents a detailed description of the equations and parameters needed to
calculate contaminant concentrations in exposed and protected aboveground produce. The
site-specific values used in this assessment for estimating contaminant concentrations in
aboveground produce are presented in Appendix 6-2.
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Belowqround Produce
For belowground produce, contamination is assumed to occur only through one mechanism—
root uptake of contaminants available from soil. Contamination of belowground produce via
direct deposition of particles and vapor transfer from ambient air is not considered because the
root or tuber is protected from contact with contaminants in the air phase.
For below ground vegetation (i.e., root vegetables), the parameter Prt can be estimated by the
method developed by Briggs (1982) based on the following relationship:
p, . CCS) fiCF,
Kds
where:
CS = soil concentration of contaminant after applicable period of deposition, mg/kg soil
RCFi = root concentration factor for the ith plant group, L/kg
VGbg = empirical correction factor, unitless
Kds = soil/water partition coefficient, L/kg
VGbg is a factor introduced into the calculation of contaminant concentrations to reflect the
reduced translocation of compounds into dense, belowground vegetables, such as carrots and
potatoes (USEPA 1994d). In general, the contaminant concentrations measured in the barley
roots of the Briggs experiments would be representative of the levels of contaminants in the
outer few millimeters of below ground vegetation which could be much higher than the average
concentration in interior of the whole vegetable. In particular, transfer of lipophilic contaminants
(log Kow greater than 4) to the interior of the produce is much less likely compared to non-
lipophilic, readily water soluble contaminants14 Thus, a VGbg value of 0.01 is used as a
correction factor for all lipophilic contaminants of concern in order to obtain a realistic estimate
of whole vegetable concentrations of contaminants (USEPA 1998b, 2005c). For non-lipophilic
contaminants (log K™ less than 4), no correction is needed (i.e., VGbg = 1).
Appendix 6-1 presents a detailed description of the equations and parameters needed to
calculate contaminant concentrations in belowground produce. The site-specific values used in
this assessment for estimating contaminant concentrations in belowground produce are
presented in Appendix 6-2.
Generally, risks associated with exposure of highly volatile contaminants through food-chain
pathways have not been found to be significant in previous USEPA exposure assessment
evaluations, primarily because volatiles are typically low-molecular-weight (< 200 g/mole)
contaminants that do not persist in the environment and do not bioaccumulate to any significant
level (USEPA 1994d, 1998b).
6.3.4.3 Estimation of Contaminant Concentrations in a Water Body
i
Surface water bodies may receive chemical contaminants from direct deposition, from runoff
14 Kow is a parameter called the "octanol-water partition coefficient.'' It is a unitless ratio that represents the tendency
of a chemical to dissolve in or adsorb to organic material as compared to water.
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of contaminated soils in the vicinity of the CDF facility, and from eroded soils. The
concentration of contaminants in the surface water is required to estimate uptake of chemicals
from the surface water by fish.
The processes by which chemical contaminants enter into a water body and the steps needed
to estimate water body contaminant concentrations are illustrated in the following diagram:
The general mechanisms considered for determination of chemical contaminant loading of the
water column are:
1) Direct deposition of particles
2) Runoff from impervious surfaces within the watershed
3) Runoff from pervious surfaces within the watershed
4) Soil erosion over the total watershed
5) Direct diffusion of vapor phase contaminants into the surface water.
The USLE and a sediment delivery ratio are used to estimate the rate of soil erosion from the
watershed.
Surface water concentration algorithms include a sediment mass balance, in which the amount
of sediment assumed to be buried and lost from the water body is equal to the difference
between the amount of soil introduced to the water body by erosion and the amount of
suspended solids lost in downstream flow. As a result, the assumptions are made that 1
sediments do not accumulate in the water body over time, and that equilibrium is maintained
between the surface layer of sediments and the water column. The total water column
contaminant concentration is the sum of the contaminant concentration dissolved in water and
the contaminant concentration associated with suspended solids. Partitioning between water
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and sediment varies with the contaminant. The total concentration of each contaminant is
partitioned between the sediment and the water column.
To evaluate the contaminant loading to a water body from its associated watershed, the
contaminant concentration in the watershed soils needs to be calculated. As described
previously, the equation for contaminant concentration in soil includes a loss term that considers
the loss of contaminants from the soil after deposition. These loss mechanisms all lower the
soil concentration associated with a specific deposition rate.
Appendix 6-1 presents a detailed description of the equations and parameters used for
calculating contaminant concentrations in watershed soils and contaminant concentrations in
the water bodies selected for evaluation in the SRA.
Site-specific values were needed for several parameters to characterize the water body and
watershed area of Lake George and Powderhorn Lake within the Study Area (e.g., water body
surface area, volume, average depth, watershed area, volumetric flow rate). These values are
presented in Table 6-3. These values were obtained from the literature or from information
supplied by IDNR (IDNR 2006). In cases where a site-specific watershed parameter was not
available for Lake George or Powderhorn Lake, a reasonable default value was obtained from
USEPA guidance on modeling of watershed characteristics.
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Table 6-3: Hydrologic Parameters for the Water bodies Selected for Evaluation in the SRA
Lake George
Water Body Parameters
Watershed Parameters
Depth of Water Column
1.95 m
Impervious Area
23%
Current Velocity
1.4E-6 m/s
USLE Cover Management Factor
0.8
Average Volumetric Flow
71,000 m3/yr
USLE Erosivity Factor
160 yr_1
Surface Area
633,301 m2
Impervious Area
Receiving Deposition
326,728 m2
Area Receiving Fallout
1,420,556 m2
Powderhorn Lake
Water Body Parameters
Watershed Parameters
Depth of Water Column
2.5 m
Impervious Area
23%
Current Velocity
1.4E-6 m/s
USLE Cover Management Factor
0.8
Average Volumetric Flow
35,170 m3/yr
USLE Erosivity Factor
160 yr"1
Surface Area
244,691 m2
Impervious Area
Receiving Deposition
111,094 m2
Area Receiving Fallout
483,018 m2
6.3.4.4 Estimation of Contaminant Concentrations in Fish
The concentration of a contaminant in fish is calculated using either a contaminant-specific
bioconcentration factor (BCF), a contaminant-specific bioaccumulation factor (BAF), or a
contaminant-specific biota-sediment accumulation factor (BSAF). For a contaminant with a log
Kow less than 4.0, BCFs are used. For a contaminant with a log Kow greater than 4.0 (except for
extremely hydrophobic compounds such as dioxins, furans, and PCBs), which is assumed to
have a high tendency to bioaccumulate, a BAF value is used. Extremely hydrophobic
contaminants like dioxins, furans, and PCBs are also assumed to have a high tendency to
bioaccumulate. However, field studies and actual field measurements of these contaminants in
water bodies have shown that they exhibit a high tendency for adsorption to the bed sediments
rather than association with the water phase. Therefore, for dioxins, furans, and PCBs, BSAFs
are generally used to calculate concentrations in fish. A detailed discussion on the sources of
the contaminant-specific BCF, BAF, and BSAF values, and the methodology used to derive
them is presented in other USEPA guidance (USEPA 1998b, 2005c).
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BCF and BAF values are generally based on dissolved water concentrations. Therefore, when
BCF or BAF values are used, the COPC concentration in fish is calculated using dissolved
water concentrations. BSAF values are based on benthic sediment concentrations. Therefore,
when BSAF values are used, COPC concentrations in fish are calculated using benthic
sediment concentrations.
Fish Concentration Estimated from Bioconcentration Factors Using Dissolved-Phase
Water Concentration
USEPA (1998b, 2005c) recommends using the following equation to calculate fish
concentrations for contaminants having a log Kow less than 4.0.
where
Cfcj, = Concentration of COPC in fish (mg COPC/kg FW tissue)
CAl, - Dissolved phase water concentration (mg COPC/L)
BCFfi.h = Bioconcentration factor for COPC in fish (L/kg)
The dissolved-phase water concentration (C^) is calculated by using the methods described
previously. The contaminant-specific BCF^ values used in this assessment are presented in
Appendix 6-3.
Fish Concentration Estimated from Bioaccumulation Factors Using Dissolved-Phase
Water Concentration
USEPA (1998b, 2005c) recommends using the following equation to calculate fish
concentrations for contaminants having a log of 4 or higher (excluding chlorinated dioxins,
furans, and PCBs).
CJhh = ' 3A^fish
Where
Cash = Concentration of COPC in fish (mg COPC/kg FW tissue)
C^ = Dissolved phase water concentration (mg COPC/L)
BAF fish = Bioaccumulation factor for COPC in fish (Ukg)
The dissolved phase water concentration (Cdw) is calculated by using the methods described
previously. The contaminant-specific BAFflsh values used in this assessment are presented in
Appendix 6-3.
Fish Concentration Estimated from Biota-To-Sediment Accumulation Factors Using Bed
Sediment Concentrations
USEPA guidance recommends the use of the following equation to calculate fish concentration
from BSAFs using concentrations adsorbed to bed sediment for very hydrophobic contaminant,
namely chlorinated dioxins, furans, and PCBs.
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where
Cfch
= Concentration of COPC in fish (mg COPC/kg FW tissue)
C*
= Concentration of COPC sorbed to bed sediment (mg COPC/kg bed
sediment)
fliptd
= Fish lipid content (unitless)
BS.4F
= Biota-to-sediment accumulation factor (unitless)
oc:cd
= Fraction of organic carbon in bottom sediment (unitless)
The recommended default value for the lipid content offish (fipd) is 7 percent, based on previous
USEPA guidance (USEPA 1993c) and other published data (Cook et al. 1991). For the fraction
of organic carbon in bottom sediment (OCsed), the recommended default value is 4 percent,
which is the midpoint in the range of 3-5 percent measured in field studies (USEPA 1998b,
2005c). The 4 percent value is higher than the usual surface soil organic carbon estimate of 1
percent. Organic carbon content in bottom sediments is higher than the organic carbon content
in soils because: 1) erosion favors lighter-textured soils with higher organic carbon contents;
and 2) bottom sediments are partially comprised of decomposed aquatic organisms and other
detritus material.
BSAFs are presented in Appendix 6-3.
6.3.4.5 Estimation of Contaminant Concentrations in Breast Milk
Based on current USEPA risk guidance and other published USEPA risk assessments (USEPA
1998b, 2005c), the evaluation of uptake of chlorinated dioxins and furans into breast milk is
recommended for this SRA because of the highly lipophilic properties of these chemicals and
their potential for bioaccumulation into breast milk.
In addition, there is a significant amount of published data and information which indicates that
chlorinated dioxins and furans are present as detectable background contaminants in human
breast milk. These chemicals could be incorporated into breast milk from a number of sources,
with the diet being a primary source (USEPA 2003a).
USEPA guidance recommends use of the following relationship for estimating the concentration
of chlorinated dioxins and furans in the lipid fraction of breast milk based on the model
published by Smith (1987).
_ m • 1*1
-------
h = Half-life of dioxin in adults (days)
fi = Fraction of ingested dioxin/furan congener stored in fat (unitless)
f2 = Fraction of fat in maternal body weight (unitless)
1x10® = Units conversion factor (pg/mg)
The recommended values for the input parameters are the following (USEPA 2005c):
h = Half-life of dioxin in adults (2555 days)
f-, = Fraction of ingested dioxins stored in fat (0.9)
f2 = Fraction of fat in maternal body weight (0.3)
6.3.5 Estimation of Contaminant Exposure Doses
The next step in the exposure assessment is the calculation of contaminant-specific exposure
rates or intake doses for each exposure pathway included in the selected exposure scenarios.
This section describes the parameters that need to be evaluated and the exposure factors that
need to be assigned for quantifying the exposure received under each exposure scenario.
The calculation of contaminant-specific exposure rates for each exposure pathway evaluated
involves solving an equation that combines the following parameters: (1) estimated
contaminant-specific media concentrations determined by the methods previously described;
(2) an intake or consumption rate for the exposure medium; (3) a receptor body weight; and (4)
values which account for the frequency and duration of exposure. The calculation is repeated
as necessary for each contaminant and for each exposure pathway included in an exposure
scenario.
The following sections describe a general exposure rate calculation and the pathway-specific
variables that may affect this calculation.
6.3.5.1 Generic Intake Dose Equation
Exposure can occur over a period of time. In the calculation of an average exposure per unit of
time, the total exposure can be divided by an appropriate exposure time period and body
weight.
The following generic equation is used to calculate contaminant intake doses (USEPA 1989):
j = C^-CR-EF-ED
BW-AT
Where:
I = Intake—the dose of contaminant at the exchange boundary (mg/kg-day) which is
available for absorption; for evaluating exposure to noncarcinogenic
contaminants, the intake is referred to as average daily dose (ADD); for
evaluating exposure to carcinogenic contaminants, the intake is referred to as
lifetime average daily dose (LADD)
Cge„ = Contaminant concentration in any media of concern (e.g., mg/kg for soil or |jg/m3
for ambient air)
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CR
Consumption rate—the amount of contaminated medium consumed per unit of
time or event (e.g., kg/day for soil and L/day for water)
EF
Exposure frequency (days/year)
ED
Exposure duration period (years)
BW =
Average body weight of the receptor over the exposure period (kg)
i
AT
Averaging time—the period over which exposure is averaged (days); for
carcinogens, the averaging time is 25,550 days, based on a lifetime of
70 years; for noncarcinogens, averaging time equals ED (years) multiplied by
365 days/year.
Variations of the above equation are used to calculate receptor-specific exposures to
contaminants. The detailed exposure dose and pathway-specific equations used in the SRA
are presented in Appendix 6-4.
The exposures calculated in a risk assessment are intended to represent RME conditions as
further described in USEPA (1989). As explained in Section 3, the use of RME values is
consistent with other USEPA guidance and analysis (USEPA 1989, 1994d, 2004b). The RME is
meant to represent an exposure level at the high end, but within the realistic range of exposure.
A study on the quantitative effects of conservative factor selection indicated that setting as few
as two exposure factors at their RME level or at the high-end (e.g., near the 90th percentile),
while setting the remaining variables at typical or "central tendency" values (e.g., near the 50th
percentile) could result in a product equivalent to setting all input variables at an RME level
(e.g., 99th percentile value) (Cullen 1994; USEPA 1998b).
USEPA guidance for assessing health risks of emissions from combustion stacks recommends
that exposure factors set at RME values should include: (1) the highest modeled ISCST3 output
values within the selected exposure scenario locations (e.g., residential zones; schools) in the
study area; (2) the exposure frequency; and (3) the exposure duration (USEPA 1998b, 2005c).
Other exposure factors are set at typical or average values. Since the SRA is an evaluation of
contaminant emissions to air, the decision was made to follow this recommendation wherever
reasonably possible in order to be consistent with the RME concept.
The exposure factors used in the SRA to estimate contaminant intake doses are listed
according to exposure scenario in Tables 6-4A and 6-4B.
The following sections provide additional information on the necessary exposure factors and the
rationale behind exposure factor selection.
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Table 6-4A: Exposure Factors and Intake/Contact Rates for Environmental Media
Local Area Resident and Local Area Fisher Scenarios
Exposure Factor or Intake
Parameter
Selected Intake or
Contact Rate
Origin of Value or Rationale for Selection
Inhalation Rate-Adult
0.63 mJ/hr
Recommended average inhalation rate for a
residential setting and activity; based on data from
USEPA 1997a
Inhalation Rate - Child
0.3 nrrVhr
Recommended average inhalation rate for a
residential setting and activity; based on data from
USEPA 1997a
Inhalation Exposure Time - Adult
24 hr/day
Conservative default to account for exposure at a
single location
Inhalation Exposure Time - Child
24 hr/day
Conservative default to account for exposure at a
single location
Exposure Duration - Adult
30 years
High-end default value for residence in a single
location; based on recommendations from USEPA
1997a, 1998b, 2005c
Exposure Duration - Child
6 years
Subgroup specific; intake evaluation for children
ages 1 to 7 years
Exposure Frequency - Adult
350 days/year
High-end default value to prevent underestimation
of time spent at a single location <
Exposure Frequency - Child
350 days/year
High-end default value to prevent underestimation
of time spent at a single location
Soil Ingestion Rate - Adult
50 mg/day
Average long-term daily soil ingestion rate based
on recommendations in USEPA 1997a, 1998b,
2005c
Soil Ingestion Rate - Child
100 mg/day
Average long-term daily soil ingestion rate based
on recommendations in USEPA 1997a, 1998b,
2005c
Garden Produce Consumption
Rate - Adult
Aboveground exposed
Aboveground protected
Belowground
21 g/day (dry weight)
39.9 g/day (dry weight)
9.8 g/day (dry weight)
Mean values based on data for consumption of
home-grown produce as given in USEPA 1997a;
derived from USDA Food Consumption Survey;
adjusted for cooking losses
Garden Produce Consumption
Rate - Child
Aboveground exposed
Aboveground protected
Belowground
6.3 g/day (dry weight)
11.6 g/day (dry weight)
3.3 g/day (dry weight)
Mean values based on data for consumption of
home-grown produce as given in USEPA 1997a;
derived from USDA Food Consumption Survey;
adjusted for cooking losses; child values represent
a time-weighted mean for data from USEPA 1997a
Fish Consumption Rate - Adult
82 g/day
Mean value based on data for consumption of
home caught/consumed fish as given in USEPA
1997a; derived from USDA Food Consumption
Survey; adjusted for cooking losses
Fish Consumption Rate - Child
11.4 g/day
Mean values based on data for consumption of
home caught/consumed fish as given in USEPA
1997a; derived from USDA Food Consumption
Survey; adjusted for cooking losses; child values
represent a time-weighted mean for data from
USEPA 1997a
6-44
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Exposure Factor or Intake
Parameter
Selected Intake or
Contact Rate
Origin of Value or Rationale for Selection
Dermal Surface Area Exposed -
Adult
5700 cm'
From recommendation in USEPA 2004a; based on
mean adult value for combination of skin area from
head, forearms, hands, and lower legs
Dermal Surface Area Exposed -
Child
2800 cm'
From recommendation in USEPA 2004a; based on
mean child value for combination of skin area from
head, forearms, hands, lower legs, and feet
Dermal Adherence of Soil - Adult
0.07 mg/cm'
From recommendation in USEPA 2004a; based on
recommendation for home gardeners
Dermal Adherence of Soil - Child
0.2 mg/cm'
From recommendation in USEPA 2004a; based on
recommendation for children playing in moist soil
Dermal Event Frequency - Adult
1/day
Default value for contact on a given day
Dermal Event Frequency - Child
1/day
Default value for contact on a given day
Dermal Exposure Frequency -
Adult
240 days/year
Professional judgment; based on 8 months of daily
dermal exposure to soil from outdoor activity in
northern Indiana climate
Dermal Exposure Frequency -
Adult
240 days/year
Professional judgment; based on 8 months of daily
dermal exposure to soil from outdoor activity in
northern Indiana climate
Body Weight - Adult
70 kg
Recommendation from USEPA 1997a and other
USEPA guidance (USEPA 1998b, 2005c) for
average in general adult population
Body Weight - Child
15 kg
Recommendation from USEPA 1997a and other
USEPA guidance (USEPA 1998b, 2005c) for
average in general child population
Averaging Time - Cancer Risk;
Adult and Child
25550 days
70 years x 365 days/year; time over which intake is
averaged to calculate a life time average daily dose
for estimating cancer risk
Averaging Time - Noncancer
Hazard - Adult
10950 days
30 years x 365 days/year; total number of days in
exposure duration period; time over which intake is
averaged to calculate an average daily dose for
estimating non-cancer hazard
Averaging Time - Noncancer
Hazard - Child
2190 days
6 years x 365 days/year; total number of days in
exposure duration period; time over which intake is
averaged to calculate an average daily dose for
estimating non-cancer hazard
6-45
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Table 6-4B: Exposure Factors and Intake/Contact Rates for Environmental Media
Local Area Student Scenario
Exposure Factor or Intake
Parameter
Selected Intake or Contact
Rate
Origin of Value or Rationale for Selection
Inhalation Rate
0.63 mJ/hr
Same as adult inhalation rate; recommended average
inhalation rate for adults; based on data from USEPA
1997a
Inhalation Exposure Time
10 hr/day
Exposure time in school setting; combination of school
class time and additional on-site recreational/athletic
activity time
Exposure Duration
6 years
School matriculation; combination of 2 years of junior
high school and 4 years of senior high school
Exposure Frequency
180 days/year
Based on total number of days in published school
calendar; inhalation, incidental soil ingestion and
outdoor dermal exposure are assumed to occur on
every school day
Soil Ingestion Rate
100 mg/day
Same as soil ingestion rate for a child; average long-
term daily soil ingestion rate based on
recommendations in USEPA 1997a, 1998b, 2005c
Dermal Surface Area Exposed
5100 cm'
From recommendation in USEPA 2004a; based on
age-adjusted mean values of body part surface area
for adolescents/teens of age 12-18 years; combination
of skin area from head, forearms, hands, and lower
legs
Dermal Adherence of Soil
0.1 mg/cm'
From recommendation in USEPA 2004a; surrogate
value for all athletic activities; based on recommended
value for rugby players
Dermal Event Frequency - Adult
1/day
Default value for contact on a given day
Body Weight
57 kg
Based on data from USEPA 1997a; corresponds to
mean age-adjusted body weight for adolescents/teens
of age 12-18 years
Averaging Time - Cancer Risk;
25550 days
70 years x 365 days/year; time over which intake is
averaged to calculate a life time average daily dose for
estimating cancer risk
Averaging Time - Noncancer
Hazard
2190 days
6 years x 365 days/year; total number of days in
exposure duration period; time over which intake is
averaged to calculate an average daily dose for
estimating non-cancer hazard
6.3.5.2 Air Exposure
Direct inhalation of vapors and particulate emissions from the CDF is a potential pathway of
exposure. Individual receptors residing or conducting activities in the Study Area could be
directly exposed to contaminants in vapor, particulate, and particle-bound phases as a result of
normal respiration. The factors that affect the amount of exposure include vapor and particulate
contaminant concentrations, respiration rate during the period of exposure, and length of
exposure.
19 Based on published school calendar for East Chicago School District (http://www.ecDs.oraV For dermal contact to
soil through outdoor athletic activity, another option was considered: if outdoor athletic activity is assumed to occur
every weekday for 8 months of the year, excluding mid-winter and summer recess (i.e., from August - November and
February - May), the total number of athletic days would be approximately 160 days/year. Since this value is less
than the total number of school days, the total number of school days (i.e., 180) was selected to represent the
estimate of the total number of outdoor dermal soil contact days.
6-46
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As presented in Tables 6-4A and B, default inhalation rates are used for adult and child
receptors in a given exposure scenario. It is recognized that inhalation rates could vary
depending on the level of activity during a given day or exposure period. Therefore, the
recommended inhalation rates from USEPA guidance reflect an averaging of inhalation rates
expected for different levels of physical activity. USEPA has evaluated an extensive set of data
and studies on inhalation rates in order to recommend reasonable inhalation rates for particular
receptors, time periods, and activities (USEPA 1997a).
In addition, three significant assumptions are used which are regarded as conservative, and
should lead to an overestimate of contaminant exposure for most individuals:
1) For a specific location and period of exposure (e.g., home day, school day), a receptor is
assumed to be continuously exposed only to air which contains contaminants. There is
no adjustment for activities or time periods spent outside the contaminated zone (e.g.,
shopping, dining, work location, field trips, etc.).
2) All inhalation exposure is assumed to result from inhalation of outdoor levels of
contaminants. Although vapors entering buildings and residences as a result of air
exchange could remain airborne and available for inhalation, particulates entering
buildings are more likely to settle out and not be inhaled. Studies of human activity
patterns indicate that for many individuals, the majority of time on most days is spent in
indoor environments (USEPA 1997a).
3) The WEPS model for erosion of sediments in the CDF indicated that particulate matter
released from the CDF should be composed of particles exhibiting a size of 100 pm or
less in diameter. The particles transported downwind of the CDF at any location will
exhibit a range of particle sizes. However, for assessing inhalation exposure, all
particles transported to any receptor area location are assumed to be respirable particles
(i.e., PM10). Respirable particles are those which can penetrate to the lower regions of
the respiratory system and enter the lungs.
6.3.5.3 Soil Contaminant Ingestion
Receptor populations can be exposed to contaminants in soil by consuming soil that has
adhered to the body, especially the hands, as a result of hand-to-mouth behavior. Factors that
influence exposure by soil ingestion include soil concentration, the rate of soil ingestion during
the time of exposure, and the length of time spent in the vicinity of contaminated soil. Soil
ingestion rate estimates in children are based on studies that measure the quantities of non-
absorbable tracer minerals in the feces of young children. Ingestion rate estimates for adults
are based on assumptions about exposed surface area and frequency of hand-to-mouth
contact. Indoor dust and outdoor soil may both contribute to the total daily ingestion (USEPA
1997a). Exposure levels are also influenced by the amount of time that the individual spends in
the vicinity of soil exposed to deposition of emitted pollutants. Based on empirical
measurements and expected differences in behavior patterns, children are assigned higher soil
ingestion rates than adults.
6.3.5.4 Food Consumption
Plants and animals impacted by emission sources may take up contaminants from the air or
after deposition onto soil or water bodies. Humans are exposed to contaminants through the
6-47
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food chain when they consume edible plants and animals as a food source. Human intake of
contaminants is determined from the following factors: (1) the types of foods consumed, (2) the
amount of food consumed per day, (3) the concentration of contaminants in the food, and (4)
the percentage of the diet derived from contaminated food sources. The other important
variables and assumptions used for the assessment of food consumption in the SRA are
described below.
Food Consumption Rate
The rate of food consumption varies within the population based on many factors including age,
sex, body weight, and geographic region. For most risk assessments, resource and time
constraints will preclude an investigation of site-specific consumption rates. Instead, food
consumption rates are derived from published studies and surveys on food consumption rates
for the U.S. population. USEPA recommends that data from U.S. Department of Agriculture
USDA food consumption surveys should be used for the risk assessment process (USEPA
1990b). USEPA has conducted an extensive analysis of food consumption rates and behavior
based on the USDA surveys and compiled the results into summary tables in the Exposure
Factors Handbook (USEPA 1997a).
In cases where homegrown food consumption is being evaluated, current USEPA risk guidance
recommends that food consumption rates should be derived from the Exposure Factors
Handbook data on U.S. populations which reported consumption of "home produced" food items
(USEPA 1998b, 2005c). These data cover consumption rates for persons who raise food in
home gardens and farms or catch fish for home consumption. The consumption rates used in
the SRA are summarized in Tables 6-4A and B and explained in detail in Appendix 6-3, based
on the analysis presented in the guidance documents (USEPA 1998b, 2005c).
Percentage of Contaminated Food
Normally, it is not expected that an individual's diet will be composed entirely of homegrown or
home-raised food items. The percentage of homegrown food consumed by the individual will
affect contaminant exposure, because not all of an individual's dietary intake will originate from
a contaminated source. For example, residents of highly populated urban areas will have a
smaller portion of their diet supplied by their own homegrown food compared to persons living in
rural or suburban areas, who can more readily raise food in home gardens or raise animals on
farms.
Current USEPA guidance (1998b, 2005c) recommends the following assumptions regarding the
percentage of contaminated food for the following scenarios:
• For the Local Resident (adult and child) living in the predominantly urbanized area of
East Chicago, IN, it is assumed that 25 percent of aboveground and belowground
produce are grown from within a source of contamination.
• For the local fisher, it is assumed that 100 percent of the fish consumed by the fisher is
harvested from a local contaminated water body (i.e., Lake George). This is a
conservative assumption because it means that no fish in the diet is supplied from a
non-contaminated water body. This assumption is included in the recommendation that
a screening-level analysis should evaluate a high-end consumer of potentially
contaminated fish.
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6.3.5.5 Exposure Frequency
The frequency at which repeated exposure occurs is specific to each scenario. Because
exposure frequency is one of the parameters intended to be set for evaluation of RME, selection
of the EF was simplified as follows for the SRA. For all residential scenarios, the EF is set to
350 days per year. This assumption is based on the conservative estimate that all residents
spend a maximum of 15 days at a location outside of a residential zone selected for evaluation.
For the exposure scenario at the school location, the conservative estimate is that exposure
could occur on every school day based on the local school district calendar. There is no
adjustment for days of absence, periods when outdoor recreational activity does not occur (e.g.,
mid-winter), or days on which weather would not actually permit outdoor recreational activity
(e.g., snow, cold, heavy rain).
6.3.5.6 Exposure Duration
Exposure duration is the length of time that a receptor is exposed through the exposure
pathways that are part of a specific exposure scenario. For the direct inhalation exposure
pathway, exposure can continue as long as the emission source is in operation. Since the
current plan for operation of the CDF calls for the CDF to receive sediments for 30 years before
closing, the longest exposure duration for inhalation would be 30 years.
For exposure via indirect pathways that result after contaminants are deposited onto soil and
transported to vegetation and water, an individual receptor could be exposed for as long as the
receptor remains in a location or area being evaluated in the risk assessment. Consequently,
USEPA guidance recommends using default RME values to estimate exposure duration for
specified receptors.
Theoretically, an individual could be exposed to contaminants via some indirect pathways for an
entire lifetime (approximately 70 years). However, U.S. census data and population
demographic data indicate that the U.S. population has significant mobility and few Americans
reside in the same small geographic area (e.g., home, neighborhood, census block) for an
entire 70-year lifetime. Based on data for population mobility and residence time, a period of 30
years is recommended as the RME value for adult exposure duration (USEPA 1997a, 1998b,
2005c).
For other receptors, the recommended exposure duration will be determined for a selected
population subgroup or for specific exposure scenario. For example, USEPA risk assessment
guidance (USEPA 1989, 2002a) has generally defined childhood as being from one to seven
years old, based on the concept that childhood represents approximately ten percent of the
lifespan. The daily intake for an exposure pathway is expressed as the dose rate per body
weight. Because children have lower body weights than adults, typical ingestion exposures
normalized to body weight for items such as soil, milk, and fruits, can be significantly higher for
children. This is the primary reason for evaluating a child resident scenario (USEPA 1998b,
2002a). Consequently, an exposure duration of six years is typically used for the child resident.
For non-resident exposure scenarios, USEPA guidance does not recommend an exposure
duration that can be defined as an RME value. For such cases, the typical options are to select
a value based on site-specific information, or to develop a value based on published data for
specific activity patterns, such as the length of time spent working in a particular occupation
(USEPA 1997a).
6-49
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For this SRA Report, the non-resident scenario is for contaminant exposure to junior and senior
high school students at the selected school location. Consequently, an exposure duration of six
years was selected to represent students who would spend their entire junior/senior high school
careers attending school the same location.
6.3.5.7 Dermal Exposure to Soil
Individuals could be exposed to chemical contaminants by absorption through the skin when it
comes into contact with chemical contaminants in soil. The process of absorption into the
bloodstream after a chemical crosses the skin barrier is often referred to as "percutaneous"
absorption. Factors that affect dermal exposure include: (1) surface area exposed, (2) contact
time, (3) capacity for soil adherence to skin, (4) amount of time spent near the contaminated
source, and (5) the fraction of a contaminant absorbed through the skin. In general, an
increased dose of a specific contaminant could potentially be absorbed through the skin as the
surface area of the skin is increased. Surface area is affected by age and body weight—for
example, children have less total surface area than adults. The amount of surface area
available for exposure to soil is also affected by the amount of clothing worn. An adult working
in a garden in long sleeves and long pants will have a smaller exposed surface than an adult
working in shorts and a short-sleeved shirt. For dermal exposure from soil, the exposed surface
area affects the amount of soil that can adhere to exposed skin.
As the time duration for which the contaminated soil stays in contact with the skin increases, so
does the amount of a contaminant that can be absorbed. "Contact time" refers to the duration of
time each day that contact with soil is possible. Dermal exposure is also affected by the amount
of time, each day, spent in the vicinity of the contaminated soil.
Seasonal exposure to soil can also be considered, because regional climate will influence this
variable. For example, in cold weather regions, dermal exposure to soil is reduced compared to
warm weather climates because of factors such as fewer days spent outdoors, higher level of
clothing coverage, and more days with snow/ice cover.
The amount of a given contaminant that can be absorbed through the skin depends on the
chemical properties of the contaminant, the properties of the soil matrix, and dermal absorption
pharmacokinetics. For example, if a contaminant cannot be readily absorbed through the skin,
the daily intake of the contaminant may be small even if other exposure characteristics, such as
contact time, are favorable.
For estimating dermal absorption of chemicals, the following algorithms are used. These are
variations of the generic Intake equation shown previously.
DAmym, x EF * ED * EV * SA
DAD = —
BW x AT
6-50
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whore:
Parameter Definition (nnirg)
DAD = Dermal Absorbed Dose (mgflcg-day)
DA^ - Absorbed dose per event (mg/cm:-evenl)
SA = Skin surface area available for contact (cm2)
EV = Event frequency (events/day)
EF = Exposure frequency (days/year)
ED = Exposure duration (years)
BW = Body weight (kg)
AT = Averaging time (days)
DAmvm, = C, x CF x AF * .4BS.
even* soil a
where:
Parameter Definition (unit.^
DA^ = Absorbed dose per event (mg/enr-event)
C„al = Chemical concentration in soil (mg/kg)
CF = Conversion factor (lO^kg/mg)
AF = Adherence factor of soil to skin (mg/cm3-
event) (Refened to as contact rate in RAGS,
Part A)
ABSj = Dermal absorption fraction
USEPA has published a specific guidance document for evaluating dermal exposure that is
followed in this SRA Report (USEPA 2004a). The guidance document provides a detailed
description of the factors and variables affecting dermal exposure as well as recommended
numerical values for exposure factors needed to evaluate dermal exposure.
There are two chemical-specific parameters needed for the dermal exposure assessment: the
chemical contaminant concentration in soil and the dermal absorption fraction (ABS). Chemical
concentrations at a given location are determined from the air dispersion/deposition modeling
and the fate and transport processes described previously. The ABS represents the capacity of
a chemical contaminant in soil to penetrate the skin barrier and become internally absorbed and
available for metabolism, excretion, or transport to a sensitive organ or organ system.16 The
number of contaminants evaluated in the risk assessment for the dermal-soil pathway will be
limited by the availability of dermal absorption values for chemicals in soil. In general, very
limited data exist in the scientific literature for deriving verifiable dermal absorption fractions for
chemicals from soil. USEPA guidance recommends dermal absorption factors for ten specific
chemicals in soil based on well-designed studies. These chemicals include mainly persistent
organic chemicals (e.g., dioxin, PCB, pesticides) and two metals (arsenic, cadmium). For other
semi-volatile organic chemicals and metals, a default surrogate ABS value is selected to enable
a screening level dermal evaluation to be performed. Based on these recommendations, the
ABS values selected for use in the SRA are shown in Table 6-5.
16 USEPA guidance on dermal exposure evaluates the systemic chronic health effects resulting from long-term
exposure at relatively low doses of chemicals adsorbed to soil. Acute chemical injury directly to the skin (e.g., allergic
responses, urticarial reactions, hyperpigmentation) is not evaluated since exposure to undiluted or high concentration
forms of chemicals (e.g., coal tar, petroleum, metal fabrication, commercial pesticide products) will not occur as a
result of releases from the CDF.
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Table 6-5: Dermal Absorption Fraction (ABS) from Soil for the COCs in the SRA
Constituent
Dermal Absorption
Fraction (ABS)
Recommendation and/or
Rationale for Selection
Metals
Antimony
0.03
USEPA 20041; based on value for arsenic
Arsenic
0.03
USEPA 2004
Barium
0.03
USEPA 2004
based on value for arsenic
Cadmium
0.001
USEPA 2004
Chromium +3
0.03
USEPA 2004
based on value for arsenic
Chromium +6
0.03
USEPA 2004
based on value for arsenic
Manganese
0.03
USEPA 2004
based on value for arsenic
Mercury
0.03
USEPA 2004
based on value for arsenic
Nickel
0.03
USEPA 2004
based on value for arsenic
Selenium
0.03
USEPA 2004
based on value for arsenic
Zinc
0.03
USEPA 2004
based on value for arsenic
PAHs
Acenaphthene
0.13
USEPA 2004
value for PAH constituents
Anthracene
0.13
USEPA 2004
value for PAH constituents
Benzo[a]anthracene
0.13
USEPA 2004
value for PAH constituents
BaP
0.13
USEPA 2004
value for PAH constituents
Benzo[b]fluoranthene
0.13
USEPA 2004
value for PAH constituents
Benzo[k]fluoranthene
0.13
USEPA 2004
value for PAH constituents
Chrysene
0.13
USEPA 2004
value for PAH constituents
Fluoranthene
0.13
USEPA 2004
value for PAH constituents
Fluorene
0.13
USEPA 2004
value for PAH constituents
Indenofl ,2,3-cd]pyrene
0.13
USEPA 2004
value for PAH constituents
Naphthalene
0.13
USEPA 2004
value for PAH constituents
Phenanthrene
0.13
USEPA 2004
value for PAH constituents
Pyrene
0.13
USEPA 2004
value for PAH constituents
PCBs
PCBs (total)
0.14
USEPA 2004
value for PCBs/Aroclors
Dioxin/Furan Cons
eners
2,3,7,8-TetraCDD
0.03
USEPA 2004
value for dioxin congeners
1,2,3,7,8-PentaCDD
0.03
USEPA 2004
value for dioxin congeners
1,2,3,4,7,8-HexaCDD
0.03
USEPA 2004
value for dioxin congeners
1,2,3,6,7,8-HexaCDD
0.03
USEPA 2004
value for dioxin congeners
1,2,3,7,8,9-HexaCDD
0.03
USEPA 2004
value for dioxin congeners
1,2,3,4,6,7,8-HeptaCDD
0.03
USEPA 2004
value for dioxin congeners
OctaCDD
0.03
USEPA 2004
value for dioxin congeners
2,3,7,8-TetraCDF
0.03
USEPA 2004
value for dioxin congeners
1,2,3,7,8-PentaCDF
0.03
USEPA 2004
value for dioxin congeners
2,3,4,7,8-PentaCDF
0.03
USEPA 2004
value for dioxin congeners
1,2,3,4,7,8-HexaCDF
0.03
USEPA 2004
value for dioxin congeners
1,2,3,6,7,8-HexaCDF
0.03
USEPA 2004
value for dioxin congeners
1,2,3,7,8,9-HexaCDF
0.03
USEPA 2004
value for dioxin congeners
2,3,4,6,7,8-HexaCDF
0.03
USEPA 2004
value for dioxin congeners
1,2,3,4,6,7,8-HeptaCDF
0.03
USEPA 2004
value for dioxin congeners
1,2,3,4,7,8,9-HeptaCDF
0.03
USEPA 2004
value for dioxin congeners
OctaCDF
0.03
USEPA 2004
value for dioxin congeners
Pesticides and Phenols
Aldrin
0.04
USEPA 2004
based on value for chlordane
Dieldrin
0.04
USEPA 2004
based on value for chlordane
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DDD
0.03
USEPA 2004; based on value for DDT
DDE
0.03
USEPA 2004; based on value for DDT
DDT
0.03
USEPA 2004;
Endosulfan II
0.04
USEPA 2004; based on value for chlordane
1 USEPA (2004a)
Dermal contact with contaminants can result in systemic toxicity after percutaneous absorption.
In an ideal situation, a route-specific (i.e., dermal) toxicity factor would consider portal-of-entry
effects (i.e., direct toxicity) and would also provide dosimetry information on the dose-response
relationship for systemic effects via percutaneous absorption. However, very few chemical
contaminants have been adequately studied in humans or animals model systems for the
purpose of defining percutaneous absorption characteristics or chemical-specific toxicity
following dermal absorption. Therefore, USEPA and other health agencies have not developed
dermal route-specific toxicity factors.
In the absence of dermal toxicity factors, USEPA has devised a simplified approach for making
route-to-route (oral-to-dermal) extrapolations for systemic effects. This process is outlined in
Appendix A of the Risk Assessment Guidance for Superfund (USEPA 1989). Primarily, the
approach accounts for the fact that most oral RfDs and oral CSFs are expressed as the amount
of substance administered per unit time and body weight, whereas exposure estimates for the
dermal pathway are expressed as absorbed dose. The approach utilizes the dose-response
relationship obtained from oral administration studies and makes an adjustment, if necessary,
for absorption efficiency to represent the toxicity factor in terms of absorbed dose.
When USEPA derives an RfD or CSF for a chemical that is based on the oral route, the value is
based on the administered dose, namely the external dose from the environmental medium
(e.g., soil, food, water) before absorption into the body occurs. For estimating intake doses of
the same chemical for other routes of exposure (i.e., dermal, inhalation), USEPA's risk methods
yield an estimation that corresponds to an absorbed dose. Therefore, to characterize risk from
the alternate exposure routes, adjustment of the oral toxicity factor to represent an absorbed
rather than administered dose is necessary (USEPA 2004a). This adjustment accounts for the
absorption efficiency in the "critical study," which forms the basis of the RfD or the CSF. For
example, in the case where oral absorption in the critical study is essentially complete (i.e., 100
percent), the absorbed dose is equivalent to the administered dose, and therefore no toxicity
adjustment is necessary. When gastrointestinal absorption of a chemical in the critical study is
poor (e.g., one to ten percent), the absorbed dose is much smaller than the administered dose.
Consequently, toxicity factors based on absorbed dose should be adjusted to account for the
difference in the absorbed dose relative to the administered dose (USEPA 2004a).
In effect, the magnitude of the recommended toxicity factor adjustment is inversely proportional
to the absorption fraction in the critical study. That means when absorption efficiency in the
critical study is high, the absorbed dose approaches the administered dose, resulting in little
difference in a toxicity factor derived from either the absorbed or administered dose. As
absorption efficiency in the critical study decreases, the difference between the absorbed dose
and administered dose increases. At some point, a toxicity factor based on absorbed rather
than administered dose should be used to account for this difference in dose. An adjustment in
the oral toxicity factor (RfD or CSF) is recommended when the following conditions are met: (1)
the toxicity value derived from the critical study is based on an administered dose (e.g., delivery
by water, diet, gavage) in the study design; and (2) documented evidence demonstrates that the
gastrointestinal (Gl) absorption of the chemical in question, from a medium (e.g., water, feed)
similar to the one employed in the critical study, is significantly less than 100 percent. In
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practice, a cutoff of 50 percent Gl absorption is recommended to reflect the intrinsic variability in
the analysis of absorption rates derived from different experimental studies and different
species. Use of this cut-off level is preferable to making comparatively small adjustments in the
toxicity value that would imply the existence of a level of accuracy that is not supported by the
scientific literature.
The recommended Gl absorption values (ABSqi) for those chemical contaminants with
chemical-specific dermal absorption factors from soil are presented in Table 6-6, as presented
in the USEPA guidance on dermal risk assessment (USEPA 2004a). A review of the available
literature indicates that organic chemicals are generally well absorbed (> 50 percent) across the
Gl tract. For those organic chemicals that do not appear on in table, the recommendation is to
assume a 100 percent ABSgi value. Absorption data for inorganics are also provided in Table
6-6, which indicates a wide range of absorption values for inorganics.
6-54
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Table 6-6: Summary of Gastrointestinal Absorption Efficiency and Recommendations for
Adjustments of Toxicity Factors for Specific Chemicals1,2
CI Absorption
IRIS Critical Toxicity Study
Adjust?
Compound
ReP
Species
Dosing Regime a
Ci Absorbed
AllSc,
Specie*;
Dosin«
Regimen
Tonicity
Knrtor
Orpioks
Chlordane
Hwing. 1985
Rats
assume aqueous
so%
Mice
diet
SF
No
Ohno. 1986
gavage
Mice
inhalation
RfD
2.4-
DicWoroptertoxyacei'tc
acid (2.4-D)
Knopp. 1992
Pelletier. 1989
Rats
assume aqueous
gavage
>90%
Rats
diet
RfD
No
DDT
Keller. 1980
Rats
vegetable oil
70-90%
Rats
dissolved in
oil. mixed
with diet
RID
No
Pen tac h loroph eno I
Korte. 1978
Rats
diet
76%
Rats
diet
RID
No
Meermon. 1983
Rats
water
100%
Polychloiinated
Albro. 1972
Rats
squalene
96%
Rats
diet
SF
No
biphcnyU(PCBs)
Muhlebach. 1981
Rats
emulsion
80%
Tanate. 1981
Rat-;
corn oil
81%
Pulveyclic aromatic
Clung. 1943
Rais
March solution
58%
Mice
diet
SF
No
hydrocaibons< PAH.s)
Hertu. 1979
Rats
diet
89%
Compound
Gl Absorption
IRIS Critical Toxicity Study
Adjust?
Ref1
Species
Dining Regimen
% Absorbed
AllSc,
Spirits
DtrJllg
Ret,'irELii
To\jcilj
F:icior
TCDD
Fries. 1975
Rats
diet
50-60%
under review
No
Piper. 1973
Rats
diet
70%
Rose. 1976
Rats
corn oilv
70-83%
Other Diosins/
Dibcnzot'urons
ATS DR. 1994a
multiple studies
>50%
under review
No
All other organic
compounds
multiple references
generally
>50%
multiple studies
RfDorSF
No
Inorg'.mics
Anumony
Waitz. 1965
Rats
water
15%
Rat
water
RID
Yes
Arsenic (ai\enite)
Betiloy. 1975
Human
assume aqueous
95%
Human
aj[LT
SF
No
Barium
Cuddihy and Griffith.
1972
Taylor. 1962
Dog
water
7%
Human
water
RID
Yes
Beryllium
Reeves, 1965
Rats
water
0.7%
Rat
water
RfD
Yes
Cadmium
IRIS.1999
Human
diet
2.5%
Human
diet and
RfD
Yes
Human
water
5%
water
Yes
Chromium (ID)
Donaldson and
Barrcms. 1996
Keim. 1987
Rats
diet/water
1.3%
Rat
diet
RfD
Yes
6-55
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Compound
Gl Absorption
IRIS Critical Toxicity Study
Adjust?
ReP
Species
Dosing Regimen
Ci* Absorbed
AUSc,
Species
Dosing
Regimen
Tovicity
Factor
Chromium (VI)
Donaldson and
Barreras. 1996
MacKenzie. 1959
Sayato. 1980
Rats
water
2.5%
Rai
water
RID
Yes
Cyanate
Farooqui and Ahmed,
1982
Rats
assunv aqueous
>41%
Rni
diet
RfD
No
Manganese
Davidsson. 1989
IRIS.1999
Ruoff. 1995
Human
diet/water
4%
Human
diet/water
RID
Yes
Mercuric chloride
(other soluble salts)
IRIS.1999
Rats
water
7%
Rat
oral gavage
in water:
2XAveek
RID
Yes
Insoluble or metallic
mercury
ATSDR, 1994b
Human
acute inhalation
oF Hg vapor
74-80%
Human
Inhalation
RfC
No
Methyl mercury
Abcrg. 1969
Hitman
aqueous
<>5%
Human
diet
RfD
No ¦
Nickel
EhkJiov*.lcaya. 1972
Human
diet/wnter
4%
Rat
diet
RID
Yes
Selenium
Young. 1982
Human
diet
30-80Ci
Human
diet
RfD
No
Silver
Furchner. 1968
IRIS.1999
Dogs
aqueous
4%
Human
i.v. dose
RfD
(based on
estimated
oral dote)
Yes
1 This table is derived from USEPA (2004a)
2 All literature references in Column #2 are listed in USEPA (2004a)
These ABSGi values in Table 6-6 are recommended for the adjustment of toxicity values for the
assessment of dermal absorption through contact of chemical contaminants in soil. The
practical significance of the ABSgi value on risk assessment is the following: as the ABSGi value
decreases, the greater is the contribution of the dermal pathway to overall risk relative to the
ingestion pathway. Therefore, the ABSGi can significantly influence the comparative importance
of the dermal pathway in a risk assessment. The quantitative significance is illustrated by the
following proportional relationship:
Dermal Risk 1
«
Ingestion Risk ABSQl
where:
Parameter Definition (units)
ABSq, - Fraction of contaminant absorbed in
gastrointestinal tract (dimensionless) in the
critical toxicity study
Once the criteria for adjustment have been defined and a specific ABSgi value has been
identified, a toxicity factor that reflects the absorbed dose can be calculated from the oral toxicity
values by employing the following equations:
R&abs = R&o x ABSGI
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where:
Parameter Definition (units)
RfD^gj = Absorbed reference dose (mg/kg-day)
RfD0 = Reference dose oral (rag/kg-day)
ABSct = Fraction of contaminant absorbed in
gastrointestinal tract (dimeasionless) in the
critical toxicity study
SF
ASS
SFo
ABSGi
where:
Parameter Definition (units)
SFabs = Absorbed slope factor
SF0 = Oral slope factor (mg/kg-day)"'
ABSa = Fraction of contaminant absorbed in
gastrointestinal tract (dimensionle^s) in the
critical toxicity study
Based on the approach for toxicity factor adjustment presented in USEPA guidance (USEPA)
and the information in Table 6-6, toxicity factor adjustment was applied for the following
contaminants of concern in the SRA: antimony, barium, cadmium, chromium, manganese,
nickel, and zinc.
6.3.5.8 Breast Milk Consumption
Based on current USEPA guidance (USEPA 2005c), exposure of nursing infants to chlorinated
dioxins and furans in breast milk is considered in this risk assessment.
The equation used to calculate the intake dose of an infant to a dioxin/furan congener is a
refinement of the generic intake dose equation presented previously:
,r>n _ Cmi&a ' A ' A ' ^
*
-------
ED = Exposure Duration (1 year)
BWi„fant = Body Weight of infant during feeding period (10 kg)
AT = Averaging time for intake period (1 year)
With regard to the value for exposure duration, many infants could be breast-fed for less than
one year, while some may be breast-fed for more than one year. Available guidance and
published survey data on breast-feeding patterns in the U.S. indicate that one year is a
reasonable or typical value for breast-feeding duration (USEPA 2002a, 2005c).
6.3.5.9 Intake of Lead: IEUBK Model for Lead
USEPA and public health agencies (CDC, State agencies) have relied upon the well-
characterized neurological effects observed in children as the sensitive endpoint for evaluating
the potential for adverse health effects from lead exposure. To apply a protective reference
exposure level for lead in children, the goal of the agencies is to limit lead levels from a
combination of sources (e.g., soil, air, water, food) such that a typical child or group of similarly
exposed children would have no more than a five percent probability of exceeding a 10 |jg/dL
blood lead level. This 10 |jg/dL blood lead level is based on analyses conducted by CDC and
USEPA that associate blood lead levels above 10 |jg/dL with the on-set of neurological deficits
in some children. This blood lead level is below a level that would require medical intervention
(USEPA 1994a, 1998a).
USEPA has developed an approach called the IEUBK Model, which evaluates potential risks by
predicting blood lead levels associated with exposure to lead. The IEUBK Model integrates a
number of characteristics reflecting the complex exposure pattern and physiological handling of
lead by the body, and has been validated at several sites where lead exposure data and human
blood lead levels are available. The IEUBK Model has been reviewed and recommended by the
USEPA Science Advisory Board (USEPA 1992b). The CDF is an example of an area source
from which lead emissions are possible due to particulate emissions to air followed by air
transport and deposition to soil.
The Agency has now developed a computerized version of the IEUBK Model that predicts blood
lead levels and percentage distributions for children ranging in age from infancy to age seven
(USEPA 2001a). The IEUBK Model accounts for the major characteristics that influence the
uptake and absorption of lead from the environment, including the ability to incorporate default
or site-specific values for background levels of lead in air, soil, water, and diet. At present, it is
not possible to apply the computer model to predict potential blood lead levels in adults. In
general, however, children are more susceptible to lead exposures than adults as a result of
higher soil ingestion rates, higher absorption from the gut, nutritional variables and lower body
weight. Consequently, in most risk assessments, children are identified as the subgroup of
primary concern for lead exposure.
The IEUBK Model is used to predict blood lead levels for an individual child or population of
children, and was specifically designed to evaluate lead exposure in young children because
this age group is known to display enhanced sensitive to lead exposure. The IEUBK Model is a
versatile assessment tool that allows the user to make rapid calculations from a complex array
of intake, absorption, distribution, and elimination equations by building site-specific and age-
dependent exposure scenarios. The IEUBK Model allows the user to input different media
concentrations and dietary intake rates for lead for the set of consecutive years being modeled
(i.e., different concentrations/ingestion rates can be entered for different years to reflect
changing site conditions; the model does not allow a temporal resolution finer than a year). The
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IEUBK Model then uses the input data to generate a yearly average blood lead level for the
population being modeled. The IEUBK Model is comprised of four distinct components that work
together in series:
• Exposure component - Determines how much lead enters the child's body over the
exposure period. This component combines media-specific (e.g., air, soil, food, water)
lead concentrations and age-dependent media intake rates to calculate age- and media-
specific lead intake rates.
• Uptake Component - Calculates how much of the lead that enters the body through the
exposure routes is actually absorbed into the blood.
• Biokinetic Component - Models the distribution of the lead from the blood to other body
tissues and/or elimination from the body.
• Probability Distribution Component - Calculates a probability distribution of blood lead
for a hypothetical child or population of children. The geometric mean blood lead
concentration is calculated. This is combined with a prescribed Geometric Standard
Deviation representing inter-individual variability in lead uptake to generate a blood lead
distribution from which the probability (e.g., the estimated proportion) of the target
population to exceed a blood lead level of 10 pg/dL is estimated.
The IEUBK Model uses standard age-weighted exposure parameters for consumption or intake
rates of food, drinking water, soil, dust, and inhalation of air. These parameters are combined
with the available site-specific information on the concentrations of lead in these media in order
to estimate exposure for the child. The model inserts default values whenever site-specific
information is not used. The default values (e.g., dietary lead concentrations, consumption
values) are typical of a child's environment and were derived from research and published
information on lead levels in environmental media and child-specific consumption and intake
rates for U.S. children.
The IEUBK Model is generally applied to characterize lead exposure for sites or situations
where the local background environmental media concentrations of lead have already been
impacted or could be impacted by emissions of lead from a specific local source. Examples
include lead emissions present at contaminated waste sites and lead emissions into air from
point sources or area sources.
The CDF is an example of an area source from which lead emissions are possible due to
particulate emissions to air followed by air transport and deposition to soil. Consequently,
operation of the CDF could cause an incremental addition of lead to air and soil in the vicinity of
the CDF. For the SRA, the IEUBK Model is used to evaluate the whether lead emissions from
the CDF could have a significant impact on the predicted blood lead level of children assumed
to reside in the vicinity of the CDF. The IEUBK Model evaluates a typical child resident
assumed to live in each local neighborhood selected for evaluation within the risk assessment
study area.
The input parameters needed to run the IEUBK Model are presented in Table 6-7. These
parameters represent a combination of site-specific parameters, conservative default
parameters, and child-specific exposure parameters. The table provides a rationale for the
parameter selection and the origin of the selected values.
6-59
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Table 6-7: Input Values for the IEUBK Lead Model
Medium
Parameter
Model Default Value(s)1'
Value Used
Comment
Air
Background lead
air concentration
0.1 |jg/mJ
0.035 pg/mJ
Value used is site-specific; based
on air monitoring at E.C. Central
High School18
Air
Addition to lead air
background
concentration due
to CDF emission
Site-specific
Site-specific value for each
location determined by lead
emission rate and air dispersion
modeling
Air
Inhalation Rate
6-12 months: 2.0 rrrVday
12-24 months: 3.0 m3/day
24 - 36 months: 5.0 m3/day
36 - 48 months: 5.0 m3/day
48 - 60 months: 5.0 m3/day
60 - 72 months: 7.0 m3/day
72 - 84 months: 7.0 m3/day
Model default
Soil
Background lead
surface soil
concentration
200 mg/kg
Model default
Model default is a reasonable
estimate for an urban setting if
verified site-specific data not
available
Soil
Addition to lead soil
background
concentration due
to CDF emission
Site-specific
Site-specific value for each
location determined by lead
emission rate and air dispersion/air
deposition modeling
Soil
Soil ingestion rate
6-12 months: 85 mg/day
12-24 months: 35 mg/day
24 - 36 months: 35 mg/day
36 - 48 months: 135 mg/day
48 - 60 months: 100 mg/day
60 - 72 months: 90 mg/day
72 - 84 months: 85 mg/day
Model default
Diet
Lead intake from
food
6-12 months: 5.53 pg/day
12-24 months: 5.78 Mg/day
24 - 36 months: 6.49 Mg/day
36 - 48 months: 6.24 Mg/day
48 - 60 months: 6.01 Mg/day
60 - 72 months: 6.34 Mg/day
72 - 84 months: 7.00 Mg/day
Model default
Water
Background lead
drinking water
concentration
4 pg/Liter
Model default
Water
Water ingestion
rate
6-12 months: 0.2 Liter/day
12 - 24 months: 0.5 Liter/day
24 - 36 months: 0.52 Liter/day
36-48 months: 0.53 Liter/day
48 - 60 months: 0.55 Liter/day
60 - 72 months: 0.58 Liter/day
72 - 84 months: 0.59 Liter/day
Model default
Maternal
blood
lead
Maternal blood lead
concentration at
birth
2.5 Mg/deciliter
Model default
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17 Model default values are taken from USEPA (2001a)
13 The value of 0.035 yg/m3 is the highest quarterly mean value for all lead monitoring data reported for the air
monitoring station located at East Chicago Central High School for the period April 2002 through October 2005.
The data are from the USACE Long-Term Perimeter Air Monitoring Project for the Inrfana Harbor CDF
(https://web.ead.anl.aov/inharbor/datafl
6.4 Risk Characterization and Results
In the risk characterization step of the risk assessment process, the information from the
preceding steps and procedures of the assessment are combined and integrated. In particular,
the dose-response analysis and chemical toxicity factors for the selected chemical contaminants
are combined with dose estimates representing potential chemical contaminant exposure from
each of the applicable exposure pathways. Exposure pathways are combined to evaluate the
health risks associated with specific exposure scenarios. Health risks are defined in terms of
the potential for cancer risk and noncancer health effects, usually referred to as health hazards.
In addition to the quantitative aspects of the risk assessment (i.e., "number crunching"), the risk
characterization is also intended to place the estimated risks in context through a discussion of
the qualitative elements of the risk assessment, including the major factors influencing the risk
estimates, important underlying assumptions, and the rationale for these assumptions. In
addition, the risk characterization generally includes a discussion of the uncertainty and
variability associated with the quantitative results.
6.4.1 Modeling Methodology
As described earlier in Section 3, the risk assessment for the SRA employs a combination of
"model" procedures based on previously developed and reviewed USEPA guidance for risk
assessment:
• Risk Assessment Guidance for Superfund (USEPA 1989) outlines the general
methodology that can be followed to define chemical exposure pathways and to evaluate
health risks for chemical contaminants released to air, soil, and water. The
methodologies are applicable for chemical releases from practically any source.
• Human Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities
(HHRAP; "combustion guidance") (USEPA 1998b, 2005c). The combustion guidance
outlines a comprehensive procedure for calculating estimated environmental media
(e.g., air, soil, vegetables, fish, meat) concentrations, human intake rates, and health
risks due to the emission of chemicals from combustion stacks. While the guidance was
written specifically for hazardous waste combustion facilities, the procedures are
applicable to other sources that generate chemical emissions to ambient air (e.g.,
municipal waste combustors, boilers, area sources).
6.4.2 Methodology for Estimating Cancer Risk
A cancer risk is an expression of the probability that an individual will develop cancer, based on
a unique set of exposure, model, and toxicity assumptions. For example, a risk of 2 x 10"5 is
interpreted to mean that an individual has no more than a 2 in 100,000 chance of developing
cancer over a lifetime from the exposure being evaluated. An alternative interpretation is that
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no more than 2 cases of cancer would be expected in a population of 100,000 individuals who
all received exposure at the same level of chemical intake.19
As described above, for carcinogenic chemicals, risk estimates represent the incremental
probability that an individual will develop cancer as a result of a specific exposure to a
carcinogenic chemical. These risks are calculated as follows:
Cancer Risk = LADD x CSF
Where:
LADD = Lifetime average daily dose (mg/kg-day)
CSF = CSF (mg/kg-day)'1
Within a specific exposure pathway, receptors may be exposed to more than one chemical.
The total risk associated with exposure to all chemicals through a single exposure pathway is
estimated as follows:
Cancer Risky = It Cancer Riskt
Where:
Cancer RiskT = Total cancer risk for a specific exposure pathway
ICancer Riski = Sum of cancer risks for all chemicals in a specific exposure pathway
At a given exposure scenario location, receptors may be exposed through a number of
exposure pathways. Risks from multiple exposure pathways that apply to the same individual
should be summed within each exposure scenario. That is, risks should be summed across the
scenario-exposure pathway combinations which have been identified for the study. The total
risk posed to a receptor is the sum of total risks from each individual exposure pathway
expressed as follows:
Total Cancer Risk = ICancer Riskr
Where:
Total Cancer Risk = Total cancer risk from multiple exposure pathways
ICancer RiskT = Sum of cancer risks for individual exposure pathways
The oral and inhalation CSF values used for this analysis are discussed in Section 6.1 and are
incorporated into the IRAP software model.
6.4.3 Methodology for Estimating Noncancer Health Risk - Hazard Quotient
A hazard quotient (HQ) is an expression of the potential for developing a noncarcinogenic
health effect as a result of exposure to potentially toxic chemicals, averaged over an appropriate
19 Cancer risk estimates can be presented in a number of notations or short-hand forms. For example, a cancer risk
of 2 in 100,000 could be abbreviated as 2 x 10 s or as 2E-05; each notation has the same quantitative meaning.
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exposure period. A HQ is not a probability but actually an indicator (calculated as a ratio) that
the exposure level of a chemical would be expected to cause adverse health effects by
comparison to a standard exposure level. The standard exposure level (i.e., an RfD or RfC) is a
chemical dose or chemical concentration that is projected to pose no significant likelihood of
adverse health effects even with long-term exposure.
Standard risk assessment models assume that noncarcinogenic effects exhibit a threshold; that
is, there is a level of exposure below which no adverse effects will be observed. The potential
for noncarcinogenic health effects resulting from exposure to a chemical is generally assessed
by: (1) comparing an exposure estimate to an RfD for oral exposures, or (2) comparing an
estimated chemical-specific air concentration to an RfC for direct inhalation exposures. An RfD
is a daily oral intake rate that is estimated to pose no appreciable risk of adverse health effects,
even to sensitive populations, over a specific exposure duration. Similarly, an RfC is an
estimated daily concentration of a chemical in air, the exposure to which over a specific
exposure duration poses no appreciable risk of adverse health effects, even to sensitive
populations.
The comparisons of exposure estimates or chemical-specific air concentrations to RfD and RfC
values are known as HQs, which are calculated as follows:
HQ = ADD or HQ = Ca
RfD RfC
Where:
HQ = Hazard quotient (unitless)
ADD = Average daily dose (mg/kg-day) of the chemical
Ca = Chemical air concentration (mg/m3)
RfD = Reference dose (mg/kg-day)
RfC = Reference concentration (mg/m3)
The general interpretation of HQ is that a value of less than or equal to 1 is considered health-
protective. Because RfDs and RfCs do not have equal accuracy or precision, and are not
based on the same severity of effect, the level of concern does not increase linearly as an HQ
approaches and exceeds 1. This means that adverse health effects are not predicted to occur
as soon as an HQ exceeds a value of 1. But in general, the more that the HQ value exceeds 1,
the greater the level of concern becomes.
As with carcinogenic chemicals in a specific exposure pathway, a receptor may be exposed to
multiple chemicals associated with noncarcinogenic health effects. The total noncarcinogenic
hazard for each exposure pathway is calculated by following the procedures outlined in USEPA
(1986). Specifically, the total noncarcinogenic hazard attributable to exposure to all COCs
through a single exposure pathway is known as a hazard index (HI). Consistent with the
procedure for addressing carcinogenic risks, the noncarcinogenic hazards are summed for each
chemical constituent in a given exposure pathway. The HI is calculated as follows:
HI = IHQ,
Where:
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HI = HI; total hazard for a specific exposure pathway
IHQi = Sum of HQs for all chemicals in a specific exposure pathway
This summation methodology assumes that the health effects of the various chemicals to which
an individual is exposed are additive. Specifically, this methodology is a simplification of the HQ
concept because it does not directly consider the portal of entry (i.e., oral or inhalation)
associated with each exposure pathway or the differences in toxic endpoints, target organs, and
toxicity mechanisms of the various chemicals.
The potential uncertainty created by the use of the simple summation methodology has been
discussed in the Risk Assessment Guidance for Superfund (USEPA 1989). As stated in the
guidance, the assumption of dose additivity most properly applies to chemical contaminants
which induce the same toxicological effect by the same mechanism of action. Consequently,
application of the HI additivity concept to a number of chemicals that are not expected to induce
the same type of effects or that do not act by the same mechanism could overestimate the
potential for effects. However, the additivity approach is appropriate to apply for a screening
level evaluation of the HI. The uncertainty associated with the approach should not be a
concern if only one or two chemical substances are responsible for driving the HI above unity
(i.e., above 1). If the HI is greater than unity as a consequence of summing several HQs of
similar value, it would be more appropriate to segregate the chemicals by target effect and by
mechanism of action. Then chemicals which share a similar target effect or mechanism of
action should be placed into separate groups for deriving His.
For this SRA, the screening level approach presented in the Risk Assessment Guidance for
Superfund (USEPA 1989) was applied with the understanding that the resulting HI values may
cause an overestimate of the actual potential for adverse health effects.
As discussed earlier for carcinogenic risks, a receptor may be exposed to chemicals associated
with noncarcinogenic health effects through more than one exposure pathway. For the
purposes of the risk assessment, it is reasonable to estimate a receptor's total hazard as the
sum of the His for each of the identified exposure pathways. Specifically, a receptor's total
hazard is the sum of hazards from each individual exposure pathway, expressed as follows:
Total HI = I HI
Where:
Total HI = Total HI from multiple exposure pathways
HI = Sum of HI values for individual exposure pathways
The reference toxicity factors (RfDs or RfCs) used for this analysis are discussed in Section 6.1
and are incorporated into the IRAP software model.
6.4.4 Estimates of Cancer Risk and Hazard Index using IRAP-h
Because the evaluation of multiple chemicals, multiple exposure pathways, and multiple fate
and transport processes can be a very challenging computational exercise, the SRA utilized a
computer software program to accomplish running the risk assessment model for the SRA. For
this project, the software system called Industrial Risk Assessment Protocol - Human Health
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(IRAP-h View™1) was used. This software package (abbreviated "IRAP') was developed by
Lakes Environmental Software (Waterloo, Ontario, Canada). IRAP was expressly designed to
closely follow the recommendations, chemical-specific parameters, and fate and transport
algorithms given in USEPA's 2005 combustion risk guidance. IRAP is a Microsoft Windows
application that can be run in the Windows 3.1, Windows 3.11, Windows 95, Windows 98, and
Windows NT operating systems. (The USEPA-Region 5 copy of IRAP is a 32-bit version that
runs in the Windows NT operating system).
The major features of the IRAP system are its ability to:
• Import ISCST3 plot files containing the output from the ISCST3 air dispersion/deposition
model runs
• Provide a graphical display of the ISCST3 receptor grid node locations
• Directly import GlS-generated land use/land cover data (e.g., residential, farming, and
water body locations)
• Define the perimeter of water bodies and water sheds using a polygon drawing tool
• Define an area of concern by selecting the receptor grid nodes that cover important land
use characteristics such as residential zones, recreational zones, and agricultural land
• Guide the user through the process recommended in the HHRAP combustion guidance
for defining exposure scenarios and selecting exposure pathways
• Eliminate the need to perform hand calculations and write multiple interconnected
computation spreadsheets
• Simultaneously calculate risk values (cancer risks and HQs) for multiple chemicals
emitted from a single source or from multiple sources at multiple locations.
The IRAP system incorporated information on the geographic location of the CDF and local land
use and demographic information in order to construct a Study Area of interest and define
specific residential neighborhoods/zones and activity areas (e.g., schools) for which human
health risk will be evaluated. (The development of the Study Area was described in Section 4
and Section 6.3.1).
Due to its computation power, the IRAP software is capable of generating a very large number
of potential health risk estimates within the Study Area. The risk estimates (cancer risk and HQ)
could vary significantly by geographic location based on the air dispersion/deposition model
results combined with the exposure scenario which is applied at a given location. In order to
generate a consistent and understandable representation of risk estimates within the Study
Area, the IRAP risk estimation procedure was utilized in the following way for the this SRA:
1) IRAP recognizes the geographical boundary placed on each residential neighborhood/
zone and the school zone. Within each boundary zone, IRAP recognizes all receptor
grid node points associated with the ISCST3 air model output files.
2) From the collection of ISCST3 grid points, IRAP selects the grid points associated with
the "highest-parameter points" from the ISCST3 output. In each boundary area, there
can be up to sixteen highest-parameter points. These "highest-parameter points" are
determined from the air dispersion modeling results and are based on the emissions
phase (i.e., vapor, particle and particle-bound, air concentration, dry deposition rate, wet
deposition rate, and total deposition rate). In practice, there are usually between one
and six distinct highest-parameter point locations in the air modeling output files, with all
other highest-parameter points overlaying these point locations (i.e., co-located).
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3) For each distinct highest-parameter point location, I RAP calculates total cancer risk and
HI using the exposure pathways and exposure factors that apply within each zone.
4) Based on the calculated risk and hazard results, the I RAP user can identify the
parameter point location corresponding to the highest calculated risk and hazard for the
combination of exposure pathways that apply within a boundary. The results for this
location are referred to as "highest-combined exposure pathway risk" estimate for the
boundary zone.
The procedure described above was adopted to derive cancer risk and HQ estimates for the
SRA. In addition to the total cancer risk and HI, IRAP also estimates individual contaminant
cancer risks and contaminant HQs so that chemicals which contribute the most to cancer risk
and HI can be identified.
Using the methodology described in Section 6.4.2 and Section 6.4.3, cancer risk estimates and
noncancer hazard estimates were derived for each exposure scenario selected in the SRA:
6.4.4.1 Local Resident Scenario
The applicable exposure pathways are:
• Inhalation of volatile contaminants and particulate contaminants
• Incidental ingestion of soil containing deposited contaminants
• Dermal contact with soil containing deposited contaminants
• Ingestion of contaminants incorporated into produce from a typical home garden.
Table 6-8 lists the estimated cancer risks for an adult resident individual assumed to reside in
one of the five residential neighborhood zones selected for evaluation in the SRA. The
estimated cancer risks are displayed by exposure pathway and by additive risk across the
combination of pathways.
TABLE 6-8: Local Adult Resident Cancer Risk - Exposure Pathway Estimates
Residential Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Sum of
Pathway
Risks
Calumet
3.3E-07
4.9E-08
1.2E-08
2.3E-07
6.2E-07
Hammond
1.6E-06
3.8E-08
9.3E-09
1.8E-07
1.8E-06
Marktown
4.6E-06
6.9E-08
1.7E-08
3.2E-07
5.0E-06
North Harbor/East ,
Harbor
8.0E-07
2.6E-08
6.3E-09
1.2E-07
9.5E-07
Northside/Southside
4.2E-06
8.4E-07
2.1E-07
4.0E-06
9.2E-06
Robertsdale
7.8E-06
< 1.0E-10
3.2E-10
< 1.0E-10
7.8E-06
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Table 6-9 lists the estimated cancer risks for a child resident individual assumed to reside in one
of the five residential neighborhood zones selected for evaluation in the SRA. The estimated
cancer risks are displayed by exposure pathway and by additive risk across the combination of
pathways.
TABLE 6-9: Local Child Resident Cancer Risk - Exposure Pathway Estimates
Residential Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Sum of
Pathway
Risks
Calumet
6.6E-08
9.2E-08
1.6E-08
6.5E-08
2.4E-07
Hammond
3.2E-07
7.1E-08
1.2E-08
5.0E-08
4.5E-07
Marktown
9.2E-07
1.3E-07
2.2E-08
9.1E-08
1.1E-06
North Harbor/East
Harbor
1.6E-07
4.8E-08
8.3E-09
3.4E-08 I 2.5E-07
Northside/Southside
8.4E-07
1.6E-06
2.7E-07
1.1E-06 I 3.8E-06
Robertsdale
1.6E-06
< 1.0E-10
4.1E-10
< 1.0E-10 I 1.6E-06
Table 6-10 lists the estimated noncancer HI values for an adult resident individual assumed to
reside in one of the five residential neighborhood zones selected for evaluation in the SRA. The
estimated HI values are displayed by exposure pathway and as a sum across the combination
of pathways.
TABLE 6-10: Local Adult Resident Hazard Index - Exposure Pathway Estimates
Residential Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Sum of
Pathway Index
Calumet
0.0079
0.00015
0.00018
0.0024
0.011
Hammond
0.0390
0.00012
0.00014
0.0019
0.041
Marktown
0.1120
0.00022
0.00026
0.0035
0.116
North Harbor/East
Harbor
0.0196
0.00008
0.00009
0.0013
0.021
Northside/Southside
0.0990
0.0026
0.00301
0.0399
0.144
Robertsdale
0.1907
0.00001
0.00002
0.00033
0.191
Table 6-11 lists the estimated noncancer HI values for a child resident individual assumed to
reside in one of the five residential neighborhood zones selected for evaluation in the SRA. The
estimated HI values are displayed by exposure pathway and as a sum across the combination
of pathways.
6-67
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TABLE 6-11: Local Child Resident Hazard Index - Exposure Pathway Estimates
Residential Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Sum of
Pathway Index
Calumet
0.0079
0.0014
0.00115
0.0033
0.013
Hammond
0.0390
0.0011
0.00092
0.0026 I 0.044
Marktown
0.1120
0.0021
0.00167
0.0049
0.121
North Harbor/East
Harbor
0.0196
0.00076
0.00062
0.0018
0.023
Northside/Southside
0.099
0.0245
0.0197
0.0558
0.199
Robertsdale
0.1907
0.00012
0.00012
0.00046 | 0.191
6.4.4.2 Local Fisher Scenario
A local fisher is an individual (adult or child) who is a resident of the local area in the vicinity of
the CDF and who also obtains a significant portion of the diet from consuming fish harvested
from a local water body. Consequently, the applicable exposure pathways are:
• Consumption of fish fillets harvested from a local water body
• Exposure pathways expected for a Local Area Resident (as described above).
A water body located within the Study Area is determined to be candidate water body for
evaluation if: (1) significant fishing is known to occur, and/or (2) information is available to
indicate that access for fishing is possible and fishing is recommended by a State natural
resource agency or other organization which promotes recreational fishing.
The individual who harvests fish from one of these lakes is assumed to be a high-end fish
consumer in keeping with the concept that the SRA will evaluate RME levels within the selected
scenarios. The two water bodies selected for evaluation were Lake George and Powderhorn
Lake (Section 6.3). Because of similarities in the size of the two lakes and their distance and
direction from the CDF, it was not possible, a priori, to determine which lake might receive
higher impacts from CDF contaminants due a combination of direct deposition and overland
runoff of contaminants. Consequently, it was necessary to evaluate contaminant impacts to
both lakes. The following estimates of cancer risk and noncancer hazard were obtained based
on the assumption that each water body could support the intake level of a high-end consumer.
Table 6-12: Estimated Cancer Risk and Hazard Index from Local Fish Consumption
Water body
Cancer Risk
Hazard Index
Adult Fisher
Child Fisher
Adult Fisher
Child Fisher
Lake George
< 1.0E-08
< 1.0E-08
0.0738
0.0479
Powderhorn Lake
5.3E-06
6.8E-07
0.0655
0.0425
6-68
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As shown in Table 6-12, the evaluation indicated that fishing from Powderhorn Lake gave
significantly higher estimates of cancer risk than fishing from Lake George. Fishing from Lake
George gave slightly higher estimates of HI than fishing from Powderhorn Lake. The values
shown in Table 6-12 were used to complete the following tables which summarize the estimated
cancer risks and HI values for a Local Fisher who is also assumed to be a local resident.
Table 6-13: Adult Resident Fisher Cancer Risk - Exposure Pathway Estimates
(Fish Obtained from Lake George)
Residential
Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Fish
Consumption
Sum of
Pathway Risks
Calumet
3.3E-07
4.9E-08
1.2E-08
2.3E-07
< 1.0E-08
6.3E-07
Hammond
1.6E-06
3.8E-08
9.3E-09
1.8E-07
< 1.0E-08
1.8E-06
Marktown
4.6E-06
6.9E-08
1.7E-08
3.2E-07
< 1.0E-08
5.0E-06
North Harbor/
East Harbor
8.0E-07
2.6E-08
6.3E-09
1.2E-07
< 1.0E-08
9.6E-07
Northside/
Southside
4.2E-06
8.4E-07
2.1E-07
4.0E-06
< 1.0E-08
9.3E-06
Robertsdale
7.8E-06
< 1.0E-10
3.2E-10
< 1.0E-10
< 1.0E-08
7.8E-06
Table 6-14: Child Resident Fisher Cancer Risk - Exposure Pathway Estimates
(Fish Obtained from Lake George)
Residential
Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Fish
Consumption
Sum of
Pathway Risks
Calumet
6.6E-08
9.2E-08
1.6E-08
6.5E-08
< 1.0E-08
2.5E-07
Hammond
3.2E-07
7.1E-08
1.2E-08
5.0E-08
< 1.0E-08
4.6E-07
Marktown
9.2E-07
1.3E-07
2.2E-08
9.1E-08
< 1.0E-08
1.2E-06
North Harbor/
East Harbor
1.6E-07
4.8E-08
8.3E-09
3.4E-08
< 1.0E-08
2.6E-07
Northside/
Southside
8.4E-07
1.6E-06
2.7E-07
1.1E-06
< 1.0E-08
3.8E-06
Robertsdale
1.6E-06
< 1.0E-10
4.1E-10
< 1.0E-10
< 1.0E-08
1.6E-06
6-69
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Table 6-15: Adult Resident Fisher Hazard Index - Exposure Pathway Estimates
(Fish Obtained from Lake George)
Residential
Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Fish
Consumption
Sum of
Pathway Index
Calumet
0.0079
0.00015
0.00018
0.0024
0.0738
0.084
Hammond
0.0390
0.00012
0.00014
0.0019
0.0738
0.115
Marktown
0.1120
0.00022
0.00026
0.0035
0.0738
0.190 .
North Harbor/
East Harbor
0.0196
0.00008
0.00009
0.0013
0.0738
0.095
Northside/
Southside
0.0990
0.0026
0.00301
0.0399
0.0738
0.218
Robertsdale
0.1907
0.00001
0.00002
0.00033
0.0738 S 0.265
Table 6-16: Child Resident Fisher Hazard Index - Exposure Pathway Estimates
(Fish Obtained from Lake George)
Residential
Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Fish
Consumption
Sum of
Pathway Index
Calumet
0.0079
0.0014
0.00115
0.0033
0.0479
0.062
Hammond
0.0390
0.0011
0.00092
0.0026
0.0479
0.092
Marktown
0.1120
0.0021
0.00167
0.0049
0.0479
0.168
North Harbor/
East Harbor
0.0196
0.00076
0.00062
0.0018
0.0479
0.071
Northside/
Southside
0.099
0.0245
0.0197
0.0558
0.0479
0.247
Robertsdale
0.1907
0.00012
0.00012
0.00046
0.0479
0.239
6-70
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Table 6-17: Adult Resident Fisher Cancer Risk - Exposure Pathway Estimates
(Fish Obtained from Powderhom Lake)
Residential
Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Fish
Consumption
Sum of
Pathway Risks
Calumet
3.3E-07
4.9E-08
1.2E-08
2.3E-07
5.3E-06
5.9E-06
Hammond
1.6E-06
3.8E-08
9.3E-09
1.8E-07
5.3E-06
7.1E-06
Marktown
4.6E-06
6.9E-08
1.7E-08
3.2E-07
5.3E-06
1.0E-05
North Harbor/
East Harbor
8.0E-07
2.6E-08
6.3E-09
1.2E-07
5.3E-06
6.2E-06
Northside/
Southside
4.2E-06
8.4E-07
2.1E-07
4.0E-06
5.3E-06
1.4E-05
Robertsdale
7.8E-06
< 1.0E-10
3.2E-10
< 1.0E-10
5.3E-06
1.3E-05
Table 6-18: Child Resident Fisher Cancer Risk - Exposure Pathway Estimates
(Fish Obtained from Powderhom Lake)
Residential
Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Fish
Consumption
Sum of
Pathway Risks
Calumet
6.6E-08
9.2E-08
1.6E-08
6.5E-08
6.8E-07
9.2E-07
Hammond
3.2E-07
7.1E-08
1.2E-08
5.0E-08
6.8E-07
1.1E-06
Marktown
9.2E-07
1.3E-07
2.2E-08
9.1E-08
6.8E-07
1.8E-06
North Harbor/
East Harbor
1.6E-07
4.8E-08
8.3E-09
3.4E-08
6.8E-07
9.3E-07
Northside/
Southside
8.4E-07
1.6E-06
2.7E-07
1.1E-06
6.8E-07
4.5E-06
Robertsdale
1.6E-06
< 1.0E-10
4.1E-10
< 1.0E-10
6.8E-07
2.3E-06
6-71
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Table 6-19: Adult Resident Fisher Hazard Index - Exposure Pathway Estimates
(Fish Obtained from Powderhorn Lake)
Residential
Zone
Inhalation
Soil
Ingestion
Dermal
Absorption .
Home Garden
Consumption
Fish
Consumption
Sum of
Pathway Index
Calumet
0.0079
0.00015
0.00018
0.0024
0.0655
0.076
Hammond
0.0390
0.00012
0.00014
0.0019
0.0655
0.106
Marktown
0.1120
0.00022
0.00026
0.0035
0.0655
0.182
North Harbor/
East Harbor
0.0196
0.00008
0.00009
0.0013
0.0655
0.086
Northside/
Southside
0.0990
0.0026
0.00301
0.0399
0.0655
0.210
Robertsdale
0.1907
0.00001
0.00002
0.00033
0.0655
0.256
Table 6-20: Child Resident Fisher Hazard Index - Exposure Pathway Estimates
(Fish Obtained from Powderhorn Lake)
Residential
Zone
Inhalation
Soil
Ingestion
Dermal
Absorption
Home Garden
Consumption
Fish
Consumption
Sum of
Pathway Index
Calumet
0.0079
0.0014
0.00115
0.0033
0.0425
0.056
Hammond
0.0390
0.0011
0.00092
0.0026
0.0425
0.086
Marktown
0.1120
0.0021
0.00167
0.0049
0.0425
0.164
North Harbor/
East Harbor
0.0196
0.00076
0.00062
0.0018
0.0425
. 0.066
Northside/
Southside
0.099
0.0245
0.0197
0.0558
0.0425
0.242
Robertsdale
0.1907
0.00012
0.00012
0.00046
0.0425
0.234
6.4.4.3 Local Area Student Scenario
For a local student who attends school in the zone corresponding to the location of Central High
School and West Side Junior High School, the applicable exposure pathways are the following:
• Inhalation of volatile contaminants and particulate contaminants during school
attendance
• Incidental ingestion of soil contaminants during school attendance or as a "student-
athlete"
• Dermal contact with soil contaminants during activities typical of a "student-athlete"
during school attendance.
Table 6-21 lists the estimated cancer risks and noncancer HI values.
6-72
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Table 6-21: Local Area Student Cancer Risk and Hazard Index - Exposure Pathway Estimates
Exposure Pathway
Cancer Risk
Exposure Pathway
Hazard Index
Inhalation
1.3E-06
Inhalation
0.1579
Soil Ingestion
2.3E-07
Soil Ingestion
0.0036
Dermal Absorption
1.0E-07
Dermal Absorption
0.0077
Sum of Pathway Risk
1.6E-06
Sum of Pathway Hazard
Index
0.169
6.4.5 Intake of Lead: Uptake-Biokinetic Model for Lead
The CDF is an example of an area source from which lead emissions are possible due to
particulate emissions to ambient air followed by air transport and deposition to soil.
Consequently, operation of the CDF could cause an incremental addition of lead to air and soil
in the vicinity of the CDF. The results of the air emissions modeling and the air
dispersion/deposition modeling were combined with the fate and transport characteristics of
lead in soil after deposition. The IRAP Model calculated estimates of the incremental
contribution of lead to ambient air and soil within the Study Area. The results of the lead
transport and deposition analysis are summarized in Table 6-22.
6-73
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Table 6-22: Estimated Incremental Increases in Soil and Air Lead Concentrations Due to
Particulate Lead Emissions from the Confined Disposal Facility
Residential Zone or
Neighborhood
Emission Source
at the CDF
Estimated Soil Lead
Concentration
Estimated Lead
Ambient Air
Concentration
(jig/m3)
Average3
(mg/kg)
Maximum4
(mg/kg)
Calumet
East Cell:
0.74
1.39
1.16E-05
West Cell:
0.10
0.18
1.83E-06
Total:
0.84
1.57
1.34E-05
Hammond
East Cell:
0.11
0.21
1.81E-06
West Cell:
0.55
1.02
1.15E-05
Total:
0.66
1.23
1.33E-05
Marktown
East Cell:
0.50
0.93
9.87E-06
West Cell:
0.70
1.30
1.32E-05
Total:
1.20
2.23
2.31 E-05
North Harbor / East Harbor
East Cell:
0.17
0.33
3.03E-06
West Cell:
0.27
0.50
4.95E-06
Total:
0.44
0.83
7.98E-06
Northside / Southside
East Cell:
6.3
11.8
9.60E-05
West Cell:
8.2
15.3
1.63E-04
Total:
14.5
27.1
2.59E-04
Robertsdale
East Cell:
<0.01
<0.01
< 1.00E-06
West Cell:
<0.01
<0.01
< 1.00E-06
Total:
<0.01
<0.01
< 1.00E-06
School Location
East Cell:
5.8
10.9
9.21 E-05
West Cell:
25.6
47.8
5.16E-04
Total:
31.4
58.7
6.08E-04
Predicted increase in ambient air lead concentration compared to existing background level.
3 Average increase in soil lead concentration during time period of deposition (30 years).
4 Maximum increase in soil lead concentration at end of deposition period (30 years).
Table 6-22 presents the average and maximum predicted increases in soil lead concentration
due to CDF emissions within each residential zone and at the school zone.20 The average soil
lead concentration corresponds to the approximate average or mean increase in lead
concentration which is predicted during the time period (i.e., zero to 30 years) in which the CDF
is in active operation. The maximum soil lead concentration corresponds to the highest
increase in lead concentration which is predicted at the completion of the active CDF operation
(i.e., at completion of 30 years).
USEPA's IEUBK Model was used to evaluate whether lead emissions from the CDF could have
a significant impact on the predicted blood lead level of children assumed to reside in the vicinity
of the CDF. The IEUBK Model is used to evaluate children assumed to live in each local
neighborhood selected for evaluation within the risk assessment study area. The required
The predicted incremental increase in soil lead and ambient air lead at the School Zone is shown for comparison
purposes. Since young children (infant to seven years) will not reside at or frequent the School Zone in the
foreseeable future, the School Zone is not evaluated in the IEUBK Model for child lead exposure.
6-74
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inputs to the IEUBK Model were described in Section 6.3.5.9 and listed in Table 6.7. The site-
specific inputs to the IEUBK Model include the following quantitative values:
1) A background ambient air concentration of lead that applies before the CDF begins
operating. Ambient air monitoring data reported at a monitoring station located at East
Chicago Central High School were evaluated in order to obtain a site-specific value.
From these data, the highest quarterly ambient air lead concentration was determined
for the time period from April 2002 - December 2005. This value was determined to be
0.035 ng/m3.
2) A background soil lead concentration that applies before the CDF begins operating.
Site-specific data on lead (or other contaminants of interest) within East Chicago soils
that could be used for determining a valid site-specific background level of lead in soil
were not available at the time the SRA was developed. Consequently, the IEUBK
Model-recommended default background level of 200 mg/kg (200 ppm) was used for the
analysis. This is considered a reasonably conservative (i.e., reasonably high) value to
apply in the absence of site-specific data (USEPA 2001a).
3) The incremental increase in soil lead due to CDF operation. For each residential zone,
the IEUBK Model was run using the maximum incremental increase in soil lead as given
in Table 6-22. (The maximum incremental increase corresponds to the assumption that
a child's exposure to soil begins after deposition of lead from the CDF is complete).
4) The incremental increase in the ambient air concentration of lead during the period of
deposition from operation of the CDF. IRAP calculates an annual average increase in
the ambient air concentration of lead during the CDF operating period.
The IEUBK Model generates two primary output predictions of interest to the general user:
1) A probability distribution curve that determines the geometric mean blood lead
concentration for a population of children each exposed to lead under a specific
exposure scenario (e.g., a fixed set of lead environmental levels and intake exposure
factors).
2) The probability of exceeding the specified blood lead level of concern. In this case, the
blood lead level of concern is the CDC reference exposure level of 10 |jg/dL. This
probability may be interpreted as the percentage of children at the same specific
exposure scenario who are expected to exceed the level of concern.
The IEUBK Model was run for each residential neighborhood scenario using the corresponding
input values described above. The results are summarized in Table 6-23. The corresponding
probability distribution curves and text output files are presented in Appendix 6-5.
6-75
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Table 6-23: Summary of IEUBK Model Results for Child Exposure to Lead
Residential Zone
or Neighborhood
Soil Lead Input to Model
Predicted
Geometric Mean
Blood Lead Level
(jig/dL)
Predicted
Percent of
Children Above
10 pg/dL
All Zones - CDF
Not in Operation
Background soil lead
(200 mg/kg)
3.36
0.97
Calumet
Background soil lead
(200 mg/kg)
+
Incremental soil lead
(1.6 mg/kg)
3.37
0.97
Hammond
Background soil lead
(200 mg/kg)
+
Incremental soil lead
(1.2 mg/kg)
3.37
0.97
Marktown
Background soil lead
(200 mg/kg)
+
Incremental soil lead
(2.2 mg/kg)
3.38
0.97
North Harbor/
East Harbor
Background soil lead
(200 mg/kg)
+
Incremental soil lead
(0.8 mg/kg)
3.36
0.97
Northside/
Southside
Background soil lead
(200 mg/kg)
+
Incremental soil lead
(27.1 mg/kg)
3.60
1.39
Robertsdale
Background soil lead
(200 mg/kg)
+
Incremental soil lead
(0.01 mg/kg)
3.36
0.97
6.4.6 Margin of Exposure Evaluation for Dioxin Intake
Most chemical compounds for which RfDs are derived are not widely distributed and/or
persistent in the environment. Therefore, background exposures are generally very low and not
taken into account in a risk assessment. USEPA's draft "Dioxin Reassessmenf documents
(USEPA 2000, 2003a) concluded that it would be inappropriate to develop a reference dose for
6-76
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