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EPA/600/R-06/013A
March 2006
Final External Review
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Considerations for Developing Alternative
Health Risk Assessment Approaches for
Addressing Multiple Chemicals,
Exposures and Effects (External Review Draft)
National Center for Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, OH 45268
in collaboration with
U.S. Department of Energy Argonne National Laboratory
Environmental Assessment Division
Argonne, IL 60439
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NOTICE
This report is an external draft for review purposes only and does not constitute
Agency policy. Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
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TABLE OF CONTENTS
LIST OF TABLES vii
LIST OF FIGURES viii
LIST OF TEXT BOXES xi
LIST OF ABBREVIATIONS xiii
PREFACE xvi
AUTHORS, CONTRIBUTORS AND REVIEWERS xvii
EXECUTIVE SUMMARY xix
1. INTRODUCTION TO CUMULATIVE RISK AT THE U.S. EPA 1-1
1.1. PURPOSE AND SCOPE OF THIS REPORT 1-2
1.1.1. Cumulative Risk Framework 1-5
1.1.2. Relationship to Other Programs and Documents 1-8
1.1.3. Scope and Terminology 1-10
1.1.4. Report Organization 1-15
1.2. EXAMPLES OF EXISTING U.S. EPA GUIDANCE 1-16
1.2.1. Mixtures Risk Assessment 1-19
1.2.2. Superfund Site Assessment 1-20
1.2.3. Pesticide Group Cumulative Risk Assessment 1-21
1.3. OVERVIEW OF APPROACH TO CUMULATIVE HEALTH RISK
ASSESSMENT FOR MULTIPLE CHEMICALS, PATHWAYS,
TIMEFRAMES AND EFFECTS 1-22
1.3.1. Identify the Trigger for the Cumulative Risk Assessment 1-25
1.3.2. Characterize the Community and Population Based on
the Trigger 1 -30
1.3.3. Generate Initial Chemical List 1-30
1.3.4. Identify Links Between Chemicals and Subpopulations 1-32
1.3.5. Quantify Exposure for General Populations and
Subpopulations 1 -33
1.3.6. Quantify Dose-response for Initial Toxicity Grouping 1-35
1.3.7. Integrate Exposure and Dose-response Information 1-35
1.3.8. Conduct Risk Characterization 1 -36
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TABLE OF CONTENTS cont.
2. INITIAL CHARACTERIZATION OF THE POPULATION AND
CHEMICALS OF CONCERN 2-1
2.1. INITIAL DESCRIPTION OF THE POPULATION 2-1
2.1.1. Preliminary Characterization of the Population Based
on the Trigger 2-2
2.1.2. Characteristics of Vulnerable Subpopulations 2-4
2.2. INITIAL ASSESSMENT OF EXPOSURE DATA 2-6
2.2.1. Initiating the Exposure Assessment when Health Endpoint
is the Trigger 2-6
2.2.2. Initiating the Exposure Assessment when Elevated
Chemical Concentrations are the Trigger 2-12
2.2.3. Initiating the Exposure Assessment when One or More
Sources is the Trigger 2-14
2.2.4. Summary 2-16
2.3. LINKING THE LIST OF CHEMICALS OF CONCERN TO THE
POPULATION PROFILE THROUGH A CONCEPTUAL MODEL 2-17
3. CUMULATIVE EXPOSURE ASSESSMENT 3-1
3.1. DEFINING CUMULATIVE EXPOSURE ASSESSMENT 3-2
3.2. EPA EXPOSURE ASSESSMENT GUIDANCE 3-3
3.3. CUMULATIVE EXPOSURE ASSESSMENT: ANALYSIS PHASE 3-4
3.3.1. Exposure Setting 3-6
3.3.2. Exposure Pathways and Routes 3-12
3.3.3. Exposure Quantification 3-48
3.4. ILLUSTRATION OF CUMULATIVE CONCEPTS FOR THE AIR
PATHWAY AT A CONTAMINATED SITE 3-73
3.4.1. Em ission Inventories 3-75
3.4.2. Dispersion Modeling 3-80
3.5. SUMMARY COMPARISON AND SCREENING SUGGESTIONS 3-87
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TABLE OF CONTENTS cont.
4. CUMULATIVE TOXICITY ASSESSMENT 4-1
4.1. DEFINING CUMULATIVE TOXICITY ASSESSMENT 4-2
4.2. U.S. EPA TOXICITY ASSESSMENT GUIDANCE 4-2
4.2.1. U.S. EPA Practices for Evaluating Chemical Mixtures 4-4
4.3. TOXICOLOGY OF INTERNAL CO-OCCURRENCE 4-11
4.4. CHEMICAL MIXTURES GROUPING AND TOXICITY
ASSESSMENT SCHEME 4-17
4.4.1. Chemical Groupings by Common Effects 4-18
4.4.2. Refinement of Toxicity Groups 4-24
4.4.3. Cumulative Toxicity Assessment Scheme 4-28
4.4.4. Evaluating Subpopulations 4-31
4.5. EVALUATING MULTIPLE EFFECTS 4-31
4.5.1. A Quantitative Method for Evaluating Multiple Effects 4-32
4.5.2. Interpretation 4-37
4.6. EVALUATING INTERACTION EFFECTS 4-37
4.6.1. Toxicology of Interactions 4-38
4.6.2. A Quantitative Method for Evaluating Interaction Effects 4-41
4.7. EVALUATING MULTIPLE ROUTE EXPOSURES 4-45
4.7.1. Quantitative Approaches to Evaluating Multiple Route
Exposures to Mixtures 4-46
4.7.2. Internal Dose Estimates 4-51
4.8. SUMMARY RECOMMENDATIONS 4-52
5. CUMULATIVE RISK CHARACTERIZATION 5-1
5.1. SPECIAL CONCERNS WITH CUMULATIVE RISK
CHARACTERIZATION 5-7
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TABLE OF CONTENTS cont.
5.2. EXAMPLE EVALUATIONS OF QUANTITATIVE APPROACHES
TO CUMULATIVE RISK CHARACTERIZATION 5-10
5.2.1. Example Cumulative Risk Characterization: Cumulative
Hazard Index 5-10
5.2.2. Ordinal Regression Calculations for Multiple Effects
and Pathways 5-15
5.2.3. Combination of Exposures of Different Time Frames 5-19
5.3. DESCRIPTION OF RESULTS 5-20
5.3.1. Risks for Population of Concern 5-21
5.3.2. Risks for Population Subgroups 5-23
5.3.3. Important Interaction Factors 5-23
5.4. DISCUSSION OF UNCERTAINTY 5-24
5.4.1. Environmental Media Concentrations and Population
Contact 5-26
5.4.2. Dose-response Data 5-27
5.4.3. Multiplicity Issues with Exposures or Effects 5-28
5.4.4. Decision Steps in the Assessment Process 5-28
5.5. SUMMARY RECOMMENDATIONS 5-31
5.5.1. Combined Characterization of Health Risk 5-31
5.5.2. Interpretation of Results in Context of the Formulated
Problem 5-32
5.5.3. Summary 5-32
6. REFERENCES 6-1
7. GLOSSARY 7-1
APPENDIX A: CUMULATIVE RISK TOOLBOX A-1
APPENDIX B: TOXICITY INFORMATION TO SUPPORT GROUPINGS B-1
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LIST OF TABLES
No. Title
2-1 Examples of Illnesses Linked to Environmental Factors 2-9
3-1 Properties of Selected Organic Chemicals and Degradation
Products to Demonstrate Availability of Such Information 3-15
3-2 Grouping Chemicals by Common Migration Behavior 3-30
3-3 Grouping Chemicals by Environmental Fate Measures 3-31
3-4 General Grouping Categories for Key Fate Parameters 3-36
3-5 Specific Parameter Values for Example Chemicals 3-37
3-6 Summary Comparison and Screening Suggestions 3-39
3-7 Example of Cumulative Exposures for Current Land Use 3-52
3-8 Example of Cumulative Exposures for Future Land Use 3-55
4-1 Example Severity Assignments for Cholinesterase Inhibition Data 4-35
4-2 Joint Toxicity: Non-additive Effects of Metal Pairs on Systems/Organs
Using Oral Exposure 4-39
4-3 Default Weighting Factors for the Modified Weight of Evidence 4-44
5-1 Joint Toxicity: Summary of Pairwise Toxic Interactions by Organ/System 5-25
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LIST OF FIGURES
No. Title
1 -1 Assessing Integrated Multiples: Focus on Human Health 1-4
1 -2 Integrated Process for Cumulative Risk Assessment 1-6
1-3 Key U.S. EPA Resources for this Report: Precedent U.S. EPA Guidance
and Reports Containing Specific Approaches for Assessing Major Parts
of Cumulative Health Risks 1-9
1-4 Highlights of Recent Cumulative Risk-related Program Guidance and
Research Reports 1-11
1-5 MAS Risk Assessment Paradigm Modified for Cumulative Risk, with
Concepts Beyond Issues for Single Chemicals or Mixtures 1-24
1-6 Key Steps in a Cumulative Risk Assessment 1-26
1-7 Information Gathering and Processing from Common Triggers to
the Resulting Cumulative Health Risk Characterization 1-27
2-1 Example Triggers and Data Elements for Cumulative Risk Analyses 2-7
2-2 Key Elements of an Integrated Conceptual Model 2-19
2-3 Schematic of Sources/Releases, Transport/Fate, and Exposure Routes 2-20
2-4 Example Second-tier of the Conceptual Model for Cumulative Health Risk.... 2-22
3-1 Conceptual Model for Hypothetical Cumulative Exposure Assessments
Illustrating Pathways Considered and Complete Pathways 3-5
3-2 Illustration of Global Background from Atmospheric Fallout of Tritium 3-24
3-3 Approach for Estimating Exposure in Cumulative Risk Assessments 3-28
3-4 Assessing Relative Mobility in Soil to Support Chemical Groupings 3-34
3-5 Example Changes in Exposure Profile from Degradation and Partitioning 3-43
3-6 Illustration of Changing Media Concentrations Affecting Potential
Exposures 3-44
3-7 Ten Steps in Perform ing Aggregate Exposure and Risk Assessment 3-57
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LIST OF FIGURES cont.
No. Title
3-8 Pathway-specific and Combined Exposure to a Single Hypothetical
Chemical 3-59
3-9 Dose Metrics for Environmental Contaminants 3-64
3-10 Linking Exposure Assessment Modeling with a PBPK Model for DBPs 3-65
3-11 Levels of Dose Specificity that Can Be Estimated in a Cumulative
Exposure Assessment 3-67
3-12 Multipathway Potential Doses and Target Organ Doses 3-69
3-13 Human Residence Time for Selected Contaminants 3-70
3-14 Conceptual Illustration Showing the Persistence of a Biological Effect
Exceeds the Duration of the Exposure 3-72
4-1 Approach for Assessing Mixtures Based on Available Data 4-5
4-2 Level of Specificity for Dose-response Relationships 4-13
4-3 Human Residence Time for Selected Contaminants 4-14
4-4 Conceptual Illustration of Persistence of Mixture Components 4-15
4-5 Conceptual Illustration of Effects of Metabolism on Toxicity 4-16
4-6a Chemical Grouping by Co-occurrence in Media and Time 4-19
4-6b Chemical Groupings by Common Target Organs and Effects 4-19
4-6c Grouping Chemicals for Cumulative Risk Assessment 4-20
4-7 Information on Primary and Secondary Effects Linked with Hypothetical
Exposure Sources to Show Example Chemical Groups 4-22
4-8 Example Chemical Groupings for Toxicity Assessment 4-23
4-9 Examples of Toxicity Group Refinements 4-27
4-10 Complex Mixture Reference Dose 4-30
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LIST OF FIGURES cont.
No. Title
4-11 Schematic for Relative Potency Factor Approach 4-48
4-12 Combining Grouped RPF Estimates Across Exposure Routes 4-50
5-1 Considerations of Multiples in Cumulative Risk Analysis 5-2
5-2 Risk Characterization Decisions 5-30
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LIST OF TEXT BOXES
No. Title
1-1 This Report: Basic Q&A 1-3
1 -2 Key Terms for Cumulative Health Risks 1-13
1-3 Summary of Traditional Risk Assessment Steps 1-17
2-1 Example of Pesticides and Farmer Characteristics 2-5
2-2 Example of Illness Trigger from Pesticide Incident 2-6
3-1 Cumulative Exposure Assessment Questions 3-1
3-2 Selected Information Guides 3-3
3-3 Exposure Assessment: Analysis Steps 3-6
3-4 Example Data Sources and Uses 3-8
3-5 Information for Susceptibility Assessment 3-10
3-6 Exposure Pathway Elements 3-13
3-7 Example of Possible Release Sources 3-41
3-8 Weathering Example: Toxaphene 3-45
3-9 Chemical Groupings by Coexistence in Media/Time 3-47
3-10 Examples of Chemical Pairs Influenced by Exposure Timing 3-48
3-11 Examples of Chemical Groupings by Coexistence in Media/Time 3-61
3-12 Basic Steps for Cumulative Air Analysis 3-74
3-13 Benefits of Dispersion Models 3-75
3-14 Multiple Emissions during Cleanup 3-75
3-15 Emission Factors for Multiple Sources 3-76
3-16 Mobile Sources and Multiple Chemicals 3-77
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LIST OF TEXT BOXES cont.
No. Title
3-17 Comparison of PM Properties 3-78
3-18 Example Participate Factors 3-79
3-19 Air Dispersion Model Inputs 3-81
3-20 Example Model Input Considerations 3-82
3-21 Meteorology and Receptor Data 3-83
3-22 Factors to Adjust 1-Hour Averages to Other Times 3-84
3-23 Model Capabilities for Cumulative Air Analyses 3-86
3-24 Comparison of Exposure Assessment Processes 3-88
4-1 Selected Information Guides for Toxicity Assessment 4-3
4-2 Target Organ Toxicity Doses 4-21
4-3 Procedure for Estimating Whole Mixture Toxicity Values 4-29
4-4 Agency Uses of Route To Route Extrapolations U.S. EPA Workshop
Report on Inhalation Risk Assessment 4-45
4-5 RPF Formulas for Risk Estimation of a Two Chemical Mixture 4-47
5-1 Elements of Risk Characterization 5-1
5-2 Example: Site Closure vs. Public Access 5-4
5-3 Example: Site Safety 5-16
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LIST OF ABBREVIATIONS
The main acronyms and abbreviations used in this guidance document are identified
below. Where use is essentially limited to tables or equations, the term is specified with
those tables and equations. Where use is primarily in an appendix, the term is specified
in that appendix.
ARARs applicable or relevant and appropriate requirements
atm atmosphere
ATSDR Agency for Toxic Substances and Disease Registry
BAF bioaccumulation factor
BCF bioconcentration factor
BMD EPA benchmark dose
BMDL lower confidence limit on BMD
BP boiling point
BTEX benzene, toluene, ethylbenzene, and xylene
°C degrees Celsius or centigrade
CDC Centers for Disease Control and Prevention
CEP Cumulative Exposure Project
CERCLA Comprehensive Environmental Response, Compensation, & Liability Act
CSM conceptual site model
DBP disinfection byproduct
DCE dichloroethylene
DDT dichlorodiphenyltrichloroethane
DMA deoxyribonucleic acid
DNAPL dense nonaqueous phase liquid
DOE U.S. Department of Energy
EPA U.S. Environmental Protection Agency
ETS environmental tobacco smoke
foe fraction of organic carbon
CIS geographic information system
HAP hazardous air pollutant
Hg mercury
IPCS International Programme on Chemical Safety
IRIS Integrated Risk Information System (EPA database)
Kd soil-water partition coefficient
KH Henry's constant
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LIST OF ABBREVIATIONS cont.
Kow octanol-water partition coefficient
Ksp solubility product
L liter
LNAPL light nonaqueous phase liquid
LOAEL lowest observed adverse effect level
log Koc logarithm of the soil organic carbon-water partition coefficient (centimeter3
water per gram carbon)
log Kow logarithm of the octanol-water partition coefficient (centimeter3 water per
centimeter3 octanol)
m3 cubic meter
mg milligram
mg/kg milligram per kilogram
mg/kg-day milligram per kilogram body weight per day
mm millimeters
mol moles
MP melting point
MSA metropolitan statistical area
MAS National Academy of Sciences
NATA National Air Toxics Assessment
NCEA National Center for Environmental Assessment, EPA
NHEXAS National Human Exposure Assessment Survey
NOAEL no observed adverse effect level
NPL National Priorities List (EPA)
NRC National Research Council (NAS)
OP organophosphorous (pesticide)
ORD Office of Research and Development (EPA)
PAHs polycyclic aromatic hydrocarbons
PBPK physiologically based pharmacokinetic (model)
PCBs polychlorinated biphenyls
PD pharmacodynamics
PK pharmacokinetics
PM2.5 particulate matter with a diameter of 2.5 |j,m or less
PM10 particulate matter with a diameter of 10 |j,m or less
POM particulate organic matter
ppb parts per billion
ppm parts per million
QA/QC quality assurance/quality control
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LIST OF ABBREVIATIONS cont.
RAGS Risk Assessment Guidance for Superfund (EPA)
RAPIDS Regional Air Polluntant Inventory Development System
RfC reference concentration
RfD reference dose
Sw solubility in water
TCDD tetrachlorodibenzo(p)dioxin
TCE trichloroethylene
TCEQ Texas Commission on Environmental Quality
TD toxicodynamics
TK toxicokinetics
TPA tris(2-ethylhexyl) phosphate
TRI Toxics Release Inventory (EPA)
UCL95 upper 95% confidence limits on the arithmetic averages
UF uncertainty factor
|j,g microgram
|j,m micrometer
USGS U.S. Geological Survey
VP vapor pressure
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PREFACE
This report was developed as a joint effort between the U.S. Environmental
Protection Agency's (EPA) Office of Research and Development (ORD), National
Center for Environmental Assessment - Cincinnati Office (NCEA-Cin) in collaboration
with the Department of Energy's Argonne National Laboratory. It offers information that
can be used to implement basic cumulative risk concepts within the framework set forth
by EPA. The aim is to illustrate approaches and resources that can be used to more
explicitly assess cumulative health risks from multiple chemicals for specific sites and
situations. This scope can involve evaluating many different sources and contaminants,
several media (soil, water, air, and structures) and associated exposure pathways,
various representative individuals or population subgroups who could be exposed over
time, and multiple health effects. The overall goal of using cumulative risk approaches is
to produce more accurate and effective assessments of these sites and situations,
leading to more informed and ultimately better decisions for managing potential
cumulative health risks. An external review was conducted by under EPA
Contract No
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AUTHORS, CONTRIBUTORS, AND REVIEWERS
This research was sponsored by the U.S. Environmental Protection Agency
(EPA), Office of Research and Development, National Center for Environmental
Assessment - Cincinnati Division (NCEA). Through an interagency agreement, NCEA
researchers collaborated with scientists from the Department of Energy's Argonne
National Laboratory to conduct this research and to author this report. These
individuals are listed below.
AUTHORS
National Center for Environmental Assessment, U.S. EPA, Cincinnati, OH
Richard C. Hertzberg (Project Lead)
John C. Lipscomb
Glenn E. Rice
Linda K. Teuschler
Argonne National Laboratory, U.S. Department of Energy, Argonne, IL
Margaret MacDonell (Project Lead)
James Butler
Young-Soo Chang
Heidi Hartmann
John Peterson
Kurt Picel
Tetra Tech EM, Inc., Dallas, TX
Shanna Collie
Shannon Garcia
Alan Johns
Camarie Perry
ENVIRON Corporation, Emeryville, CA
Lynne Haroun
CONTRIBUTORS AND REVIEWERS
Gary Bangs
U.S. Environmental Protection Agency
National Center for Environmental
Assessment
Washington, DC
Edward Bender (retired)
U.S. Environmental Protection Agency
Office of Assistant Administrator
Office of Science Advisor
Washington, DC
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CONTRIBUTORS AND REVIEWERS cont.
David Cooper
U.S. Environmental Protection Agency
Office of Solid Waste and Emergency
Response
Washington, DC
Tony Fristachi
U.S. Environmental Protection Agency
National Center for Environmental
Assessment
Cincinnati, OH
Audrey Galizia
U.S. Environmental Protection Agency
National Center for Environmental
Assessment
Cincinnati, OH
Ihor Hlohowskyj
U.S. Department of Energy
Argonne National Laboratory Team
Argonne, IL
Jeremy Johnson
U.S. Environmental Protection Agency
Region 7
Kansas City, KS
Jason Lambert
U.S. Environmental Protection Agency
National Center for Environmental
Assessment
Cincinnati, OH
Sarah Levinson
U.S. Environmental Protection Agency
Region 1
Boston, MA
Margaret McDonough
U.S. Environmental Protection Agency
Region 1
Boston, MA
Chuck Nace
U.S. Environmental Protection Agency
Region 2
New York, NY
Michael Posson
ENVIRON
Emeryville, CA
Kaitlin Prieur
TetraTech EM, Inc.
Dallas, TX
Jon Reid
U.S. Environmental Protection Agency
National Center for Environmental
Assessment
Cincinnati, OH
Libby Stull
U.S. Department of Energy
Argonne National Laboratory Team
Argonne, IL
Robert Sullivan
U.S. Department of Energy
Argonne National Laboratory Team
Argonne, IL
David Tomasko
U.S. Department of Energy
Argonne National Laboratory Team
Argonne, IL
Michael Wright
U.S. Environmental Protection Agency
National Center for Environmental
Assessment
Cincinnati, OH
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1 EXECUTIVE SUMMARY
2
O
4 U.S. EPA, in its 2003 Framework for Cumulative Risk Assessment, defines
5 cumulative risk assessment as the evaluation of risks from exposures to multiple
6 chemicals and other stressors, possibly including multiple exposure routes and times
7 and multiple health endpoints. In addition, cumulative risk assessment has a population
8 focus rather than a source-to-receptor focus. U.S. EPA has published several general
9 and Program Office-specific guidance documents relating to chemical mixture risk
10 assessment. This report is the result of an exploratory effort to provide explicit
11 approaches for addressing some of the complicating "multiples" in cumulative risk
12 assessment. These approaches include new methods and the extension of existing
13 methods to address health risk from multiple chemicals and multiple exposure pathways
14 and times. Quantitative methods are also discussed for characterizing cumulative
15 health risks while taking into account multiple health endpoints and interactions among
16 multiple chemicals. In U.S. EPA's 2000 Supplementary Guidance for Conducting
17 Health Risk Assessment of Chemical Mixtures, interactions are addressed only in terms
18 of altered or joint toxicity. The approaches in this report extend those ideas to include
19 kinetic modeling to integrate exposures occurring through multiple routes, interactions
20 affecting fate and transport and interactions affecting multi-route joint toxicity. Exposure
21 and toxicity characterizations of mixtures are strongly dependent on mixture
22 composition (chemicals and concentrations) and timing of exposure and health effects.
23 Consequently, recurrent in this report is the emphasis on the iteration and collaboration
24 between exposure assessment and dose-response assessment to ensure compatible
25 and relevant information.
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1 The areas of the 2003 Framework addressed herein include primarily the
2 information gathering phase of Problem Formulation and the subsequent phases of
3 Analysis and Risk Characterization. This report discusses technical issues and possible
4 simplifications and shows the feasibility of such a multi-factor assessment using existing
5 information. Specific suggestions are presented to simplify the complexity of a
6 cumulative risk assessment by forming groups of exposures, chemicals or toxic effects
7 with the highest likelihood of significant joint contribution to the cumulative health risk.
8 Although sensitive population groups are often mentioned, there is no detailed guidance
9 on how to identify such groups nor how to quantify the population factors for inclusion in
10 the risk assessment.
11 This report is not guidance but rather a presentation of concepts that could assist
12 the development of guidance. It presents risk assessment approaches and information
13 on a subset of issues that are identified in the 2003 Framework for Cumulative Risk
14 Assessment. The sequence of procedural steps suggested in this report is designed to
15 emphasize the links between the exposed population and the multiple factors being
16 addressed. The audience for this report is anyone involved in chemical risk assessment
17 who needs to address the joint impact of multiple chemicals, exposures and effects.
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1 1. INTRODUCTION TO CUMULATIVE RISK AT THE U.S. EPA
2
3 Public interest in the environment continues to grow as more information is
4 shared about multiple chemicals in air, water, and soil from different sources, with
5 health risks being a major concern. The U.S. Environmental Protection Agency (U.S.
6 EPA, or the Agency) has responded to increasing requests for a way to understand and
7 evaluate the combined impacts of these conditions by preparing a set of reports on
8 various aspects of cumulative risk assessment. Those documents have provided
9 information to help explain, scope, and organize cumulative risk assessments. A recent
10 report defined the general framework for these assessments (U.S. EPA, 2003a), and
11 earlier reports laid the broad foundation for the initial stages involving planning and
12 scoping (U.S. EPA, 1997a, 2002a). Additional documents have been prepared to
13 address cumulative risk issues within specific programs, and further efforts are under
14 way.
15 This document is an initial step toward identifying specific approaches for
16 implementing cumulative health risk assessments. This report is not a regulatory
17 document and it is not guidance, but rather a presentation of concepts that could assist
18 the overall EPA development of Program specific approaches and cumulative risk
19 guidance. Building on the concepts that have been identified in earlier reports and
20 offering examples to illustrate how those concepts can be applied, this report focuses
21 on approaches for assessing health risks associated with multiple sources, chemicals,
22 exposures and effects, with examples pertaining to contaminated sites, drinking water,
23 and ambient air. Most of the approaches described in this report can also be applied to
24 assess similar risk issues beyond the example applications. It must be emphasized that
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1 "cumulative risk assessment is not going to be appropriate to every task; it is most
2 useful when addressing the risks from multiple stressors acting together" (U.S. EPA,
3 2003a).
4 The purpose and scope of this report, including its relationship to other U.S. EPA
5 cumulative risk documents, is explained in Section 1.1 with the report organization
6 summarized in Section 1.1.4. A brief overview of key examples of existing U.S. EPA
7 approaches from which this integrated approach has evolved is provided in Section 1.2,
8 and the overview of the integrated approach for multiple chemicals, pathways,
9 timeframes, and effects is given in Section 1.3.
10 1.1. PURPOSE AND SCOPE OF THIS REPORT
11 The purpose of this report is to describe information and risk assessment
12 approaches that can be used to implement the basic cumulative risk concepts set forth
13 in the U.S. EPA's Framework for Cumulative Risk Assessment (U.S. EPA, 2003a), but
14 with a reduced scope and a limited number of example applications. The intent is to
15 illustrate that approaches and resources are available to more explicitly assess the
16 multifactor aspects of cumulative health risks for specific scenarios and sites. Because
17 of the variety of these scenarios, such an assessment can involve evaluating many
18 different sources and contaminants, several media (soil, water, air, and structures) and
19 associated exposure pathways, various representative individuals or population groups
20 who could be exposed over different time frames, and multiple health effects. The
21 overall goal of using cumulative risk approaches is to produce more accurate and
22 effective assessments of these sites and situations, leading to more informed and
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1 ultimately better decisions for managing potential cumulative health risks (see Text
2 Box 1-1).
3 By addressing many different
4 pieces of the risk picture together,
5 from sources to effects, this report is
6 designed to support an assessment
This Report: Basic Q&A (Text Box 1-1)
iA/h ti- ^ f i r> Human health, joint & multiple
What kind of risk? ,, , J K
effects
From what/where? Multiple chemicals, sources, routes
What time frame? All, including mixed time frames
To address public concerns over
Why? elevated toxicity from multiple
sources, exposures, or effects
7 of "integrated multiples" for human
8 health, as highlighted in Figure 1-1. With stressors limited to chemicals and effects
9 limited to human health, this scope is much narrower than that of a comprehensive
10 assessment that would cover all of the aspects of cumulative risk described in the
11 framework document (U.S. EPA, 2003a). Such a comprehensive cumulative risk
12 analysis would also address other stressors (including physical and biological agents,
13 as indicated) and their additional sources, and it would integrate effects on other kinds
14 of receptors (e.g., ecological) and resources (e.g., sociocultural) to evaluate several
15 types of risks or impacts, as illustrated in the background of Figure 1-1.
16 A key reason for the targeted scope of this report is to focus first on a stated
17 need. Many communities near contaminated sites, large agricultural areas or in
18 industrial cities have voiced concerns about the combined effects of multiple chemicals
19 on public health. Awareness of chemical-chemical interactions is also high. For
20 example, many news articles of risks from pesticides have focused on exposure to
21 multiple pesticides, including those designed to have synergistic component chemicals.
22 The Agency for Toxic Substances and Disease Registry (ATSDR) conducts public
23 health consultations that routinely address exposures to chemical mixtures and
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Huma
Healt
sources
sfressors
pathways/routes
population groups
effects
time frames
Sociocultural
Resources
Economics
5
6
1
FIGURE 1-1
Assessing Integrated Multiples: Focus on Human Health
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1 maintains a Web site containing chemical profiles on toxicity and toxicologic interactions
2 (http://www.atsdr.cdc.gov). A second reason for the scope being limited to chemicals is
3 that U.S. EPA has regulatory guidance and newly proposed methods to assess risk
4 from exposures to multiple chemicals and pathways, so that addressing these multiples
5 is often possible with only slight modification and integration of existing tools.
6 To summarize, the purpose of this report is to provide a structured collection of
7 approaches for addressing the chemical interactions and joint toxicity issues in
8 cumulative health risk assessment by describing key concepts and illustrating steps that
9 can be taken to more explicitly evaluate cumulative risks. This report builds on recent
10 U.S. EPA documents (highlighted in the following sections) to extend their concepts into
11 a first phase of implementation that addresses the joint and interactive impacts of
12 multiple chemicals, exposures and effects. Chemical and toxicologic interactions are a
13 primary focus because these are areas where methodological advances allow the
14 traditional process (evaluating chemicals individually) to be enhanced. Approaches for
15 grouping are presented in order to simplify complexities and combine components for
16 joint analysis, so attention can be focused on the factor combinations that could
17 contribute most to adverse cumulative health risks.
18 1.1.1. Cumulative Risk Framework. The Framework for Cumulative Risk Assessment
19 (U.S. EPA, 2003a) identifies three phases of a cumulative risk assessment. (1) problem
20 formulation, (2) analysis, and (3) risk characterization (see Figure 1-2). Planning and
21 scoping, an iterative dialogue between the technical scientists, risk managers and
22 stakeholders, takes place mostly during problem formulation, but may be revisited as
23 needed during the risk analysis and risk characterization phases.
24
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(Includes the four
analytic elements of the
earlier NRC approach;
see Section 1.2)
Updated management needs
Planning
&
scoping
(Technical,
stakeholder,
& manager
dialogue)
conomic, political-science^
social, & other analyse
2
3
4
5
6
7
FIGURE 1-2
Integrated Process for Cumulative Risk Assessment
(Source: adapted from U.S. EPA, 2002f)
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1 During the problem formulation phase, the goals, breadth, depth, and focus of
2 the assessment are established by a team of risk assessors, risk managers and other
3 stakeholders, producing a conceptual model and an analysis plan. The conceptual
4 model establishes the stressors to be evaluated, the health or environmental effects to
5 be evaluated, and the relationships among various stressor exposures and potential
6 effects. The analysis plan lays out the data needed, the approach to be taken, and the
7 types of results expected during the analysis phase.
8 The analysis phase in the framework includes the determination of the analytic
9 and calculation methods to use for exposure assessment, dose-response assessment,
10 and risk estimation. In contrast to the NRC risk assessment paradigm for single
11 chemicals, the exposure and dose-response processes for cumulative risk are expected
12 to occur simultaneously and iteratively to ensure information compatibility. Because of
13 this interaction, this phase also includes the initial estimates of joint health risk from the
14 multiple stressors (chemicals, in this report) to which the study population and sensitive
15 population subgroups are exposed (U.S. EPA, 2003a, p. xviii).
16 The final phase, the risk characterization, involves further analysis so that the risk
17 estimates are placed into perspective in terms of significance and uncertainties. It is
18 also where the risk assessment process is evaluated to determine whether the
19 objectives and goals of the first phase (planning, scoping, and problem formulation)
20 have been met. The present report does not address planning and scooping, but
21 begins with the activity in the problem formulation part of the first phase, i.e., the initial
22 development of the list of chemicals and effects of concern as well as the preliminary
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1 characterization of the population assessed. The report then continues on to describe
2 approaches for the analysis and risk characterization phases.
3 1.1.2. Relationship to Other Programs and Documents. This report is closely linked
4 to, and relies upon, several key guidance documents across U.S. EPA, as illustrated by
5 the examples in Figure 1-3. The Agency has been addressing many aspects of
6 cumulative risk assessment for some time. The Office of Research and Development
7 (ORD) has prepared and coordinated a number of major reports that cover the topics
8 shown in the following paragraph, and other U.S. EPA Program Offices have developed
9 issue papers and guidance reports on some of the key factors in cumulative risk
10 assessment. The general scope and timeline of these documents are highlighted in
11 Figure 1-4. (There are several other Agency guidance documents and reports that
12 address issues related to risk assessment, such as Data Quality Objectives, but do not
13 explicitly address the multiples issues of cumulative risk; they are discussed in
14 Appendix A.) Dates shown on that figure are for selected major reports within the
15 program areas; additional documents are described in the following chapters (e.g., see
16 U.S. EPA, 2001 a, 2002a,b, 2003b). Other reports are underway; for example, a follow-
17 up report on the National Air Toxics Assessment (NATA) air toxics study of 1999 data is
18 expected soon, and guidance for addressing PCBs by combining mixture data with
19 information on the component chemicals is under review. Documents developed by
20 other organizations (such as the Agency for Toxic Substances and Disease Registry,
21 ATSDR) to support cumulative health risk analyses are described in other sections of
22 this report.
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Analysis Phase
Planning and
Scoping Phase
Risk Assessment Guidance
for Superfund
(1989)
Planning & Scoping for
Cumulative Risk Assessment
(1997)
Methodology for
Multipathway Combustor Emissions
(1998)
Guidance for Assessing
Health Risks of Chemical Mixtures
(2000)
Planning & Scoping
Lessons Learned
(2002)
Guidance on
Cumulative Risk of Pesticides
(2002)
Framework for
Cumulative Risk Assessment
(2003)
5
6
1
FIGURE 1-3
Key U.S. EPA Resources for this Report: Precedent U.S. EPA Guidance and Reports
Containing Specific Approaches for Assessing Major Parts of Cumulative Health Risks
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1 The documents shown in Figure 1-4 focus on distinct parts of the cumulative risk
2 picture rather than covering all aspects described in the U.S. EPA cumulative risk
3 framework. This is because those reports were prepared to address specific issues, as
4 defined by (1) a regulatory requirement, e.g., for air toxics, pesticides, and drinking
5 water, (2) a public demand, e.g., for community-based studies, or (3) a new
6 assessment approach or policy, e.g., for mixtures, and planning and scoping. Other
7 reports will continue to be developed to address the various steps and issues in the
8 U.S. EPA framework.
9 To illustrate how certain cumulative risk topics are not covered when the scope is
10 limited to a targeted issue, consider three reports highlighted in Figure 1-4, each of
11 which focuses on health risks (i.e., only one risk type is being addressed). The national
12 air toxics study of more than 30 priority urban air toxics does not address toxic
13 interactions (the dose-additivity and risk-additivity defaults are applied), the pesticide
14 assessment only focuses on a limited set of organic compounds (which act by the same
15 toxic mode of action to exert the same general effect), and the mixtures guidance does
16 not address aggregate exposures (only multiple chemicals by the same route). Several
17 existing U.S. EPA risk guidance documents, however, contribute substantially to the
18 approaches for addressing major issues with cumulative risk. Three of the more
19 influential guidance documents are discussed in more detail in Section 1.2.
20 1.1.3. Scope and Terminology. The scope of this report has been limited to one type
21 of risk (health) for one type of stressor (chemicals) so it can remain manageable while
22 still addressing a specific need. Thus, only a subset of the full range of cumulative risk
23 issues is covered here. For example, while multiple chemicals and exposures and both
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Chemical mixtures
What: health risks for whole mixtures, for combinations of similar,
independent, & interacting chemicals
Why: update 1986 guidelines for multiple chemicals to enhance methods
Who'. National Center for Environmental Assessment
When: 2000 (guidance)
Pesticides
What: health risks for common mode of action, multiple exposure routes
Why: address Food Quality Protection Act "no harm" requirements
Who: Office of Pesticide Programs
When: 1999-2002 (guidance and organophosphates assessment)
Planning and scoping for cumulative risk assessment
What: description of concepts for up-front thinking to lay out process
Why: guide the first step, emphasizing broad scope & integrated dialogue
Who: Office of Science Policy
When: 1997 (guidance)
Planning and scoping lessons learned
What: summary of experience from studies since the 1997 guidance
Why: encourage formal planning & scoping of environmental assessments
Who: Office of Science Policy
When: 2002 (report with case studies)
Community-based pilot studies
What: range of multiple urban chemicals/sources, exposures, health effects
Why: address public concerns about combined risks in urban communities
Who: Regional Offices, with local organizations and citizen groups
When: latel990s -2004 (individual studies)
Research needs for cumulative risk assessment
What: user-based evaluation of current programs, approaches, and needs
Why: focus and prioritize Agency research, leverage interagency efforts
Who: Office of Science Policy, with Regional Offices
When: 2002 (workshop summary)
National air toxics assessment
What: inhalation health risks of outdoor air toxics from multiple sources
Why: define baseline & driving chemicals/sources, prioritize data collection
Who: Office of Air Quality Planning and Standards
When: 2001 (national-scale report for 1996 data, updates coming)
Framework for cumulative risk assessment
What: description of umbrella issues, concepts, and general approaches
Why: guide overall integrated organization for many types of assessments
Who: Risk Assessment Forum
When: 2003 (framework report)
Disinfection byproducts in water
What: health risks of multi-route exposures to water treatment residuals
Why: address Safe Drinking Water Act "complex mixtures" requirements
Who: National Center for Environmental Assessment
When: 2003 (initial risk report, other reports coming)
Case studies for cumulative risk assessment
What: summary of examples, including community-based pilot studies
Why: provide insights to help others conduct cumulative risk assessments
Who: Risk Assessment Forum
When: 2005 (effort underway, no report yet)
1
2
Novel health risk assessment approaches for addressing
multiple chemicals, exposures and effects
What: combined health risks for multiple chemicals, pathways, effects
Why: provide simplifying methods and show feasibility
Who: National Center for Environmental Assessment
When: 2005 (this report)
FIGURE 1-4
Highlights of Recent Cumulative Risk-related Program Guidance and Research Reports
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1 cancer and noncancer health endpoints are addressed, approaches for interactions with
2 non-chemical stressors, such as noise, or for other kinds of risk are not included. The
3 important issues related to stakeholder involvement are also not included.
4 Nevertheless, within its targeted scope, this report does address each of the main
5 analysis and characterization steps involved in implementing a cumulative risk
6 assessment, and most of the approaches should be applicable to broader types of
7 stressors, complex exposures, interactions, and multiple effects. Specifically, the initial
8 steps in the framework of planning and scoping and of problem formulation are not
9 discussed in any detail here, with the focus instead on information gathering, analysis
10 and risk characterization. The technical topics in cumulative risk assessment included
11 in this report are
12 population characterization
13 exposure to multiple chemicals
14 exposures by multiple pathways considering different time frames
15 potential toxicologic interactions considering time frames of kinetics and effects
16 multiple health endpoints and
17 characterization of cumulative risks and the attendant uncertainty.
18 Terminology often used for cumulative risk assessment overlaps primarily with
19 terms of mixture risk and population sensitivity. Some of the more common terms are
20 defined in Text Box 1 -2. Fuller definitions for these and other terms in this report are
21 provided in the glossary (Chapter 7).
22 For U.S. EPA, cumulative risk assessment involves combined risks from multiple
23 exposures to multiple stressors (chemicals are the focus here) from all contributing
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
sources. This assessment
addresses a given receptor
population, whether this be an
actual community or an
imaginary group (such as
projected possible residents of
a cleanup site). This integrated
approach then extends beyond
assessments that produce
separate estimates for each
contributing source (such as
releases from a waste pit,
emissions from an incinerator,
Cumulative risk
Effect
Exposure pathway
Key Terms for Cumulative Health Risks (Text Box 1-2)
Aggregate exposure Combined exposure to one chemical;
can be from multiple sources, pathways
Combined risk from exposures to
multiple chemicals; exposures may be
aggregate
Health end point estimated from toxicity
studies (first-observed is critical effect;
secondary effect seen at higher doses)
A complete pathway has (1) source &
mechanism of release, (2) contaminant
fate & transport (through environmental
media), (3) point of receptor contact with
the source or affected medium, and
(4) exposure route
How a contaminant gets inside a person
(e.g., via inhalation, ingestion, or dermal
absorption)
One chemical acting on another to
influence fate or transport
Toxic action exerted by two or more
chemicals acting together
Joint toxicity that is greater or less than
expected under additivity (note: forms of
additivity include summing of doses,
risks or biological measurements across
chemical components of a mixture)
Receptor population Group actually or potentially exposed
Source Origin of contaminant (e.g., a landfill)
Exposure route
Environmental
interaction
Joint toxicity
Toxicological
Interaction
or effluent from a wastewater treatment facility) by estimating risk from the joint
exposure via all identified sources.
A cumulative assessment can involve multiple exposure pathways and exposure
routes that reflect different ways contaminants can be taken into the body from different
media (e.g., breathing air and drinking water). These assessments also consider
multiple effects within two main categories: cancer and noncarcinogenic systemic
effects. For the latter, a cumulative risk assessment should consider critical and
secondary (and higher) effects. The critical effect is the first effect observed as the
chemical's dose is increased above a no-effect range in the relevant toxicity study, and
it serves as the basis for the Reference Dose (RfD, see definition in Chapter 7) or other
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1 noncancer toxicity value; secondary and further effects are those seen at higher doses
2 and are rarely incorporated into single chemical risk assessments.
3 Multiple stressors are central to cumulative risk analyses. If exposures are
4 evaluated for only one chemical, even if it is present from many sources and in different
5 media, and even if it is taken in by multiple exposure routes, the U.S. EPA defines this
6 as an aggregate exposure assessment. Because an aggregate assessment only
7 addresses a single chemical, it is not formally considered a cumulative assessment.
8 However, if a set of aggregate exposures is combined, addressing two or more
9 chemicals and their joint effects, then that would constitute a cumulative assessment.
10 Interactions that consider location and timing are a main emphasis in this report.
11 In the environment, interactions can alter the fate and transport of combined chemicals,
12 e.g., by facilitating mobility in soil or sorption onto air particulates. Once taken into the
13 body, a key emphasis of this evaluation \sjoint toxicity, which is simply the collective
14 toxicity of two or more chemicals. This can be additive (the default assumption), less
15 than additive (antagonism), or more than additive (synergism). The Agency has defined
16 the specific term, toxicological interactions, to represent interactions that are other than
17 additive (U.S. EPA, 2000a). The Agency has developed an interaction formula based
18 on departures from dose addition (see Chapter 4). Toxicological interactions are then
19 commonly defined by U.S. EPA as those that result in effects that are either lower or
20 higher than expected from the individual chemicals acting under an assumption of dose
21 additivity, such as the synergistic effect of cadmium and lead on the neurological
22 system or the antagonistic effect of cadmium and lead on the kidney (see Chapters 4
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1 and 5). Such interactions are a common concern at contaminated sites, and they
2 represent an important focus of this initial report.
3 1.1.4. Report Organization. Cumulative health risk assessment covers a breadth of
4 topics, as explained in the Agency's recent framework document. That is, the process
5 is not limited to combination toxicology, nor does it just involve evaluating how multiple
6 chemicals and multiple exposure pathways can combine to produce adverse health
7 effects in people exposed over time. Rather, the cumulative risk assessment process
8 extends from identifying how the assessment was initiated, to determining how the
9 analysis will be conducted and how results will be presented. This report is organized
10 to cover this range of topics for cumulative risk assessments, as follows.
11 Chapter 1, Section 1.2 identifies examples of existing U.S. EPA guidance that
12 addresses at least part of the multiples issues with cumulative risk assessment.
13 Section 1.3 presents a summary of the steps in addressing the multiples issues,
14 emphasizing the factors that could trigger the cumulative assessment and the
15 interconnections between these steps.
16
17 Chapter 2 discusses the initial characterization of the population and
18 chemicals of concern as influenced by the trigger factor that initiated the
19 cumulative health risk assessment, ending with the initial appraisal of links
20 between environmental exposures and target populations.
21
22 Chapter 3 describes exposure assessment concepts and offers resources
23 and approaches that can be used to characterize the setting, group the
24 chemicals and pathways based on joint and interactive processes, and
25 quantify exposures for a cumulative assessment. The influence of toxicity
26 information on the exposure assessment is included.
27
28 Chapter 4 explains and illustrates key toxicity concepts, including common
29 target organs and systems, internal overlaps of doses and effects,
30 interaction toxicity, and receptor characteristics that can affect toxicity.
31 The influence of exposure information on the toxicity assessment is
32 included.
33
34 Chapter 5 provides information for the risk characterization step, including
35 ways to address uncertainty for cumulative risk assessments and the need
36 for comparison with the goals from the planning and scoping phase.
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1 Chapter 6 identifies reference information for the documents and articles
2 cited in this report.
o
4 Chapter 7 defines basic terms used in cumulative health risk
5 assessments.
6
1 Supporting details are provided in the appendices.
8 Appendix A presents a toolbox of selected resources that can be useful in
9 conducting cumulative risk assessments.
10
11 Appendix B illustrates how primary toxicity information can be organized to
12 support grouping for cumulative health risk assessments.
13 1.2. EXAMPLES OF EXISTING U.S. EPA GUIDANCE
14 The National Research Council issued Risk Assessment in the Federal
15 Government: Managing the Process (NRC, 1983), commonly called the red book, over
16 20 years ago. This document identified four basic steps for risk assessment, which
17 provided the original foundation for risk-based programs across many federal agencies:
18 hazard identification, dose-response assessment, exposure assessment, and risk
19 characterization. These general steps are reflected in most U.S. EPA guidance for
20 assessing risks, such as that under the Superfund program (U.S. EPA, 1989a), which
21 has served for many years as the common basis for contaminated site cleanups and
22 federal and state waste management programs. Other programmatic risk assessment
23 guidance documents, such as those addressing national air standards, drinking water
24 standards, and regulation of pesticides, also are structured roughly along these four
25 steps. Risk assessment other than standard setting is specific to the site or situation of
26 concern and has an additional first step of preliminary analysis of environmental
27 chemical levels. The traditional four steps of the process as applied to assess risks for
28 specific contamination events or sites are summarized in Text Box 1-3.
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1 In risk-based standard setting, contaminants have historically been evaluated
2 one at a time. Consider, however, the example of the assessment of contaminated
3 sites, where more complex
4 exposures are included;
5 chemical exposures are
Summary of Traditional Risk Assessment Steps
(Text Box 1-3)
Hazard identification/ Identify contaminant hazards and determine
data evaluation their levels in various media (soil, water, air)
Exposure assessment Evaluate who could be exposed, how much
Dose-response Quantify dose-response relations and
. assessment define toxicity values from scientific studies
7 environmental media and
8 exposure pathways to estimate total exposures, cancer risks, and the combined
9 potential for noncancer effects (U.S. EPA, 1989a). Although the basic site assessment
10 guidance calls for considering multiple chemicals, exposure routes, and effects (thus
11 cumulative risks), few specific suggestions were provided that would enable a
12 practitioner to extend beyond the basic additive approach in the original U.S. EPA
13 mixture guidelines (U.S. EPA, 1986), primarily because of limitations in extant
14 understanding of environmental and toxicological interactions.
15 As more has been learned about the environmental behavior and toxicology of
16 chemicals through ongoing research, the risk assessment process has kept pace. Ten
17 years ago the National Research Council recommended moving away from the single-
18 chemical assessment focus (NRC, 1994), and the emphasis has continued to shift
19 toward a receptor- (population-) based focus. As noted in the recent U.S. EPA mixture
20 guidance (U.S. EPA, 2000a), the four originally distinct steps are now closely linked; in
21 particular the exposure and toxicity evaluations should be jointly performed so that the
22 exposure assessment can be refined based on toxicity information and vice versa.
23 During the past several years the Agency has published several cumulative risk
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1 documents (as illustrated in Figure 1-4) that capture this shift and extend assessment
2 concepts well beyond the original basic approach.
3 The U.S. EPA planning and scoping documents identify iterative problem
4 formulation as a key element of the cumulative risk assessment process (U.S. EPA,
5 1997a, 2002a). This broadens the process beyond the four original data-driven
6 (analytic) steps by bringing in the key scoping (or deliberative) component. The broad
7 U.S. EPA Framework for Cumulative Risk document defines a flexible structure that
8 includes planning, scoping, and problem formulation, as well as specific assessment
9 and characterization issues (U.S. EPA, 2003a). That document describes main
10 concepts and the underlying technical factors across a range of risk types and
11 applications. Together, this set of Agency reports provides a general view of how risk
12 analyses can better reflect real-world conditions. These include complex exposure and
13 effect processes as well as "human interactions" that involve stakeholders and
14 regulators discussing a given risk issue to better understand and address cumulative
15 risks.
16 These recent Agency documents respond to the public's desire to bring together
17 individual pieces of the environmental risk picture (many of which are regulated under
18 separate federal programs) so risks that consider all sources, stressors, exposures,
19 affected population groups, and effects can be better understood and ultimately better
20 managed. Thus, while the four-step NRC paradigm from two decades ago provided an
21 essential foundation, the approach for assessing health risks from exposures to
22 chemicals in the environment has evolved considerably since then.
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1 One major difference from the historical approach is that today's analyses, in
2 terms of the scope of this report, are more closely integrated with careful attention paid
3 to potential interactions among them. Emerging science is offering new ways to
4 evaluate how one chemical could affect the behavior of another in the environment, how
5 one could affect how another is absorbed, distributed, metabolized, or eliminated from
6 the body, and whether their combined toxicity could differ from that estimated from the
7 single chemical toxicities. This report aims to illustrate how this new information can be
8 applied to better address cumulative health risks. The following sections provide some
9 detail on three existing U.S. EPA guidance documents that form a foundation for
10 addressing the multiplicity issues with the exposure and toxicity assessment steps of
11 cumulative risk, along with brief discussion of their weaknesses that this current
12 document addresses.
13 1.2.1. Mixtures Risk Assessment. Until recently, the most common application of
14 mixture risk assessment was to Superfund waste sites. The applicable legislation
15 passed in 1980, the Comprehensive Environmental Response, Compensation and
16 Liability Act (CERCLA), specifically calls for the evaluation of risks from mixtures. In the
17 original U.S. EPA mixtures guidelines (U.S. EPA, 1986), the recommended approach
18 was dose or response additivity based on evaluations of individual chemicals. While
19 interactions were discussed and addressing them was recommended (if data were
20 available), no specific approaches were described because toxicologic understanding
21 and quantitative data on interactions were limited. To help address this issue, the
22 Agency recently released guidance for assessing the health risks of mixtures
23 (U.S. EPA, 2000a), which updates the earlier guidelines to provide further
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1 methodological detail that reflects evolving toxicological knowledge. By describing a
2 process for quantitatively evaluating toxic interactions of multiple chemicals, that
3 guidance offers a clear step forward from past practice. Specific approaches address
4 complex mixture risk values, environmental transformations of complex mixtures,
5 toxicologic similarity based on varying evidence (from similar mechanisms to similar
6 target organs), and toxicologic interactions. The main weakness in the 2000 guidance
7 is the lack of approaches for multichemical and multipathway exposure assessment, as
8 well as approaches for multiple effects from mixtures.
9 1.2.2. Superfund Site Assessment. The standard guidance for assessing site health
10 risks (U.S. EPA, 1989a and subsequent companion documents) calls for consideration
11 of multiple chemicals, sources, exposure routes, receptors, and effects. Thus, a basic
12 cumulative assessment is already being conducted at these sites. As mentioned
13 previously, the guidance does not explain how to assess toxic interactions because
14 quantitative methods were limited at that time. Instead, a default approach was defined
15 under which chemicals are evaluated individually, and doses and toxic responses are
16 assumed to be additive, providing the first U.S. EPA Program Office approaches to
17 component-based mixture risk assessment. For independent toxic endpoints, such as
18 different types of cancer, component risks are added. For toxicologically similar
19 endpoints, component doses are scaled and added to give the familiar Hazard Index.
20 The Superfund guidance also pioneered the quantitative evaluation of multiple pathway
21 exposures with the total hazard quotient concept (see Chapter 4). Because their
22 Hazard Index and risk addition formulas used single chemical risk values readily
23 available from U.S. EPA's IRIS (Integrated Risk Information System) database, the
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1 mixture assessment was feasible and continues to be widely implemented. In addition
2 to leaving out toxic interactions, the main weaknesses of the 1989 guidance are that the
3 screening approaches for multiple pathways are minimally described, and key details on
4 how and when to use the total hazard quotient concept are not presented.
5 1.2.3. Pesticide Group Cumulative Risk Assessment. Following the passage of the
6 Food Quality Protection Act (FQPA) in 1996, U.S. EPA programmatic guidance was
7 developed to address a much more focused risk than that of previous site assessments.
8 FQPA called for the estimation of health risk from combinations of pesticides with a
9 common toxicological mode of action, from any source. The resulting cumulative risk
10 guidance includes a modified Hazard Index formula for the mixture aspect and an
11 aggregate risk formula that is functionally similar to the total Hazard Quotient formula in
12 the Superfund guidance (U.S. EPA, 2002c). Sophisticated guidance was developed for
13 evaluating toxicity data to decide which pesticides qualify for the common mode of
14 action group (U.S. EPA, 1999a), and guidance was also developed for estimating the
15 likely intakes from aggregate exposure from dietary and other sources based on
16 multiple types of national or regional information (U.S. EPA, 2001 a). The cumulative
17 risk guidance was then demonstrated by an extensive risk assessment of the
18 organophosphate pesticide group and its common mode of action, cholinesterase
19 inhibition (U.S. EPA, 2002a). The main weaknesses of the pesticide guidance is that
20 only the toxic effect for the common mode of action is assessed, chemicals not sharing
21 the common mode of action are not included, and toxic interactions are not addressed.
22 Many site and situation health risk assessments can be adequately addressed
23 using single chemical and single pathway evaluations. For other cases, multiple
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1 chemicals and complex exposures will need to be evaluated jointly. Many basic
2 cumulative risk concepts - including consideration of multiple sources, chemicals, and
3 exposures - are in the standard guidance from the last 15 years, as these three
4 examples illustrate. This report builds on those standard U.S. EPA guidance
5 approaches along with new approaches so that together they provide the conceptual
6 and procedural methodology that in many cases will be feasible and sufficient for
7 addressing the multiple factor issues with cumulative health risk assessment.
8 1.3. OVERVIEW OF APPROACH TO CUMULATIVE HEALTH RISK ASSESSMENT
9 FOR MULTIPLE CHEMICALS, PATHWAYS, TIMEFRAMES AND EFFECTS
10
11 Cumulative health risk assessment as defined in the framework (U.S. EPA,
12 2003a) is usually highly specific to the identified population and set of chemicals in the
13 exposure setting. Steps can be described, however, that apply in general and that
14 highlight the differences between cumulative risk assessment and the traditional source-
15 based or chemical-based risk assessments performed by the U.S. EPA. Although the
16 minimum requirement by U.S. EPA of a cumulative risk assessment is that it address
17 joint health effects from multiple chemicals, in this report we also emphasize the
18 community or population focus of the assessment. As described in the introduction, this
19 report does not include all steps identified in the Framework, but assumes that the initial
20 steps of Planning and Scoping and Problem Formulation have been mostly completed.
21 The areas outlined below then apply mostly to the information gathering phase of
22 Problem Formulation, and the subsequent steps of Analysis and Risk Characterization.
23 There are many situations that do not involve a population focus or that do not
24 involve multiple chemicals and so would not need a cumulative risk assessment. This
25 section, then, begins with a discussion of those factors that would lead to a cumulative
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1 risk assessment, denoted here as triggers. The section then briefly describes key steps
2 in a cumulative health risk assessment within the scope stated previously of addressing
3 the multiples of chemicals, pathways, timeframes, and effects in a population-based
4 setting. The activities in a cumulative risk assessment that are summarized in this
5 section include:
6 characterizing the population or community of concern
7 developing the list of chemicals
8 compiling information on exposure conditions and toxicity
9 identifying sensitive population subgroups and
10 iterating those steps to improve the relevance of the exposure and population
11 factors to the health risks of greatest concern.
12 The traditional sequence for risk assessment involves (1) hazard identification,
13 (2) exposure assessment, (3) dose-response assessment, and (4) risk characterization.
14 An important difference for cumulative risk assessment is that the steps no longer are
15 conducted independently, nor in a set sequence, but involve information sharing and
16 cross-evaluation, particularly between the exposure and toxicity assessment steps
17 (Figure 1-5). This means that dose-response information needs to be considered
18 during the exposure assessment, and characteristics of the exposure assessment need
19 to be incorporated into the compiling of toxicity information and then reflected in the
20 dose-response assessment. The exposure and dose-response assessment steps are
21 then expected to be iterative.
22 One important goal of the risk assessment process is to evaluate the strength of
23 any links between the chemical exposures to the receptor population and the
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Hazard identification:
- identify possible multiple
effects from multiple route
exposures
- identify potential sensitiv
subpopulations
Exposure assessment:
- account for multiple route
exposures, including fate
and transport for several
media
- identify potential time
overlaps including fate
interactions
Exposure
Assessment
- account for total absorbed
dose across exposure
routes overtime
- assess dose-response for
sensitive subpopulations
Note: &
are
- use metrics accounting for disparate risks,
detail uncertainties associated with
combining risks, discuss qualitative factors
affecting risk outcomes
FIGURE 1-5
MAS Risk Assessment Paradigm Modified for Cumulative Risk, with Concepts Beyond
Issues for Single Chemicals or Mixtures
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1 information or event that triggered the cumulative risk assessment. For example,
2 consider the case where awareness of multiple sources raises concerns over
3 cumulative risk. The data from U.S. EPA's Toxic Release Inventory might include more
4 than 20 chemicals, but it does not provide exposure levels or evidence that all 20
5 chemicals reach anyone in the population of concern. Establishing those links (e.g.,
6 between the TRI data and actual exposure) is a key part of many of the initial steps of
7 cumulative risk assessment. In this chapter, the steps are briefly described in order to
8 show their contributions to the risk assessment and their interconnections (Figure 1 -6).
9 More complete discussions are contained in subsequent chapters on exposure
10 assessment (Chapter 3), toxicity assessment (Chapter 4), and risk characterization
11 (Chapters).
12 1.3.1. Identify the Trigger for the Cumulative Risk Assessment. The initial phase of
13 a cumulative risk assessment (planning, scoping and problem formulation) forms a
14 systematic, iterative process that defines the risk problem to be assessed and the
15 technical elements to be emphasized (U.S. EPA, 2003a), with problem formulation
16 where the first analysis occurs. The main backdrop for problem formulation and initial
17 data review is provided by the regulatory context and the particular information or
18 technical factors (termed "triggers" in this report) that led to the decision to consider
19 cumulative risk. Three typical triggers are shown in Figure 1-7, along with common data
20 elements that link the triggers with the population resulting in the cumulative risk
21 characterization. These triggers can be displayed within the preliminary conceptual
22 model that is developed during the problem formulation phase. The identification and
23 discussion of trigger factors in the planning stages should improve the understanding of
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STEPS
SECTION
1.3.1
1) Identify "Trigger" for CRA
2.1
2) Characterize Population
based on Trigger
2.2
3) Generate Chemical List
2.3
4) Identify Links between
Chemicals & Subpopulations
OUTPUTS
Population Profile
List of Chemicals
of Concern
^^
3
5) Quantify Exposure for
General Population and
Subpopulations
\~
4
6) Quantify Dose-Response
for Initial Toxicity-based
Chem Grouping
3&4
7) Integrate Exposure & D-R;
Refine Exposure and Toxicity Assmts
8) Conduct Risk Characterization
Chemical Groups
By Media & Time
Chemical Groups
By Toxicity
Integrated
Chemical Groups
Final Cumulative RA
4
5
FIGURE 1-6
6 Key Steps in a Cumulative Risk Assessment. The interdependence of exposure and
7 toxicity assessments is indicated by blue arrows.
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2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Triggers
Data
Elements
public health
data
Population
illness
Sources,
releases
multiple-
chemical
fate
population
subgroup
Combined \ features
characterization
multi-route
exposures
mixtures
toxicity
Chemical
concentrations
FIGURE 1-7
Information Gathering and Processing, from Common Triggers to the Resulting
Cumulative Health Risk Characterization
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1 any links between the population risk estimate, which is the result of the cumulative risk
2 assessment, and the trigger, which initiated the risk assessment. In general, the trigger
3 factor should be a prominent part of the final risk characterization.
4 1.3.1.1. Health Endpoint as the Trigger Evidence of abnormal health effects
5 is one of the easier triggers to understand. When serious health effects occur in a
6 community with no clear cause, there can be a demand for an investigation. With many
7 health endpoints, there are several possible chemical causes, so that the investigation
8 readily becomes a cumulative risk project. For example, a cluster of leukemia cases in
9 Woburn, Massachusetts in the 1970s triggered environmental health action, and was
10 the inspiration for a 1995 book and subsequent movie (Durant et al., 1995). Although
11 the eventual emphasis was on trichloroethylene exposure, the initial chemical
12 investigation focused on several organics, while a later study investigated metal
13 exposures (U.S. EPA, 2005a). Higher than average visits to emergency rooms and
14 other reported unusual levels of health indicators can raise public health concerns and
15 initiate a cumulative health risk assessment. In many cases, existence of higher than
16 expected health effects is not easily connected to a cause, so the initial investigation
17 might begin with a critical examination of the available health effects information.
18 Variation in the quality of such information can be high, ranging from anecdotal articles
19 in the press to published results in scientific journals. Having the Agency and the
20 stakeholders gain an understanding of the details and quality of trigger information is a
21 primary objective of the planning and scoping stage.
22 1.3.1.2. Chemical Concentrations as the Trigger One of the more common
23 initiators of a risk assessment is the detection of toxic chemicals in the environment at
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1 unexpected concentrations, or at levels that are likely to cause toxicity. As with the
2 health effects trigger, the variability of data quality can be high. For example, chemical
3 levels in ambient air can have particularly high uncertainties in terms of exposure but
4 might be easily interpreted in terms of increased health risks. High levels of urban
5 smog, e.g., visible ground level particulates and ozone, frequently lead to public health
6 intervention (e.g., cautions for young children and elderly to stay indoors). When
7 combined with information on elevated chemical concentrations in soil and groundwater,
8 it can lead to a cumulative risk assessment, such as the Cumulative Risk Initiative (CRI)
9 for Cook County (IL) and Lake County (IN) (see U.S. EPA, 2003a, p. 32). As when
10 health effects are the trigger, it is important to document the quality and variability of the
11 concentration data and whether such measurements indicate possibly complete
12 exposure pathways. The measured concentrations have even greater influence in
13 starting a cumulative risk assessment when there are elevated concentrations of
14 additional chemicals elsewhere, such as in food, that also impact the same population.
15 1.3.1.3. Multiple Sources or Release Events as the Trigger Multiple
16 sources of chemical contamination can be a trigger for a cumulative risk assessment,
17 often when they are the consequence of a proposed change such as an upcoming siting
18 decision for a new manufacturing plant. Observations of multiple uncharacterized
19 releases can also elevate concerns. For example, repeated discharges from multiple
20 outfalls into streams have led to actions by Georgia Riverkeeper groups, ranging from
21 lawsuits to scientific sampling of the water and biota (Richardson, 2004). A proposed
22 increase of multiple sources is often a stronger motivation for a cumulative risk
23 assessment when the potentially exposed population includes known susceptible
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1 subgroups. One of the first activities is to determine all sources with potential exposure
2 to the population of concern, particularly sources with chemicals similar to those in the
3 trigger sources. For example, an investigation into possible pesticide drift to a
4 residential neighborhood from nearby farms could also estimate concurrent exposures
5 from household use of similar pesticides by residents of the neighborhood of concern.
6 1.3.2. Characterize the Community and Population Based on the Trigger. The
7 population characterization usually would include a physical description of the study
8 area and a demographic description of the population in that study area. The study
9 area could be a political unit, such as that defined by a county or city boundary, or could
10 be delimited by geographical features, such as a lake and surrounding watershed. The
11 population could be a neighborhood or the community in an entire city or could be the
12 public using a resource, such as a lake. The population description would also include
13 sensitive or susceptible subgroups based on increased exposure or vulnerability. Often
14 the definition of the population and study area could be influenced by the trigger factor
15 that initiated the risk assessment. Because a cumulative risk assessment is population
16 focused so that all relevant exposures and effects are considered, as the potential
17 exposures and toxic effects are further investigated, the population characterization will
18 be refined.
19 1.3.3. Generate Initial Chemical List. The U.S. EPA Framework for Cumulative Risk
20 (U.S. EPA, 2003a) distinguishes cumulative risk assessment from the traditional risk
21 assessments by its population focus. Consequently, once the initial population
22 description is complete, including the boundaries of the study area, information on
23 chemical releases and environmental concentrations are evaluated in light of the
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1 identified population to develop the initial list of chemicals of concern. Existing U.S.
2 EPA approaches for exposure assessment are likely to be sufficient for this step. Partly
3 because of stakeholder involvement in the cumulative risk assessment, this initial
4 chemical list is likely to be closely tied to the trigger factor. The influence of the trigger
5 factor is discussed in more detail in the exposure assessment chapter.
6 1.3.3.1. Use Program and Regional Office Procedures Determination of
7 chemicals of concern is covered in several guidance documents from the U.S. EPA
8 Program and Regional Offices (see Appendix A). For exposures by multiple media, the
9 chemicals might need to be identified using approaches from several Programs or using
10 guidance from U.S. EPA's Office of Research and Development (ORD). The initial
11 chemical list should be overly inclusive so that potential interactions from joint
12 exposures and joint toxicity can be evaluated in later steps of the assessment. For
13 example, chemicals that might be screened out in a single chemical assessment
14 because their Hazard Quotient (HQ) was less than 1 might be retained in a cumulative
15 assessment unless their HQ was less than 0.1, in order to allow for potential dose
16 additivity or interactions.
17 1.3.3.2. Identify Chemicals Related to the Trigger Factor The three types
18 of trigger factors in this report have only subtle differences in their influence on the
19 chemical list. When health endpoints are the trigger, the preliminary list of chemicals
20 could include any that have been shown in human or animal studies to cause or
21 contribute to those health effects. When environmental concentrations or sources are
22 the trigger, the preliminary chemical list could be at first restricted to those measured or
23 likely to be in the emissions. Chemicals known to be similar to or toxicologically
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1 interactive with those on the first list might then be added if their exposure to the
2 population defined in the step in Section 1.3.2 is considered plausible, such as similar
3 chemicals in food. That determination of potentially interactive chemicals should also
4 consider multiple endpoints for each chemical, not just the critical effect used to define
5 the IRIS risk values. In any case, the resulting list of chemicals is preliminary and
6 perhaps most useful in refining the population description by identifying subgroups that
7 could be sensitive to chemicals on this list.
8 1.3.4. Identify Links between Chemicals and Subpopulations. Once the general
9 receptor population has been identified and characterized and the preliminary chemical
10 list exists, the next step is to attempt to link those chemicals with population groups,
11 including sensitive population subgroups in the defined population of concern.
12 Population groups can be of heightened sensitivity to toxic chemicals because of higher
13 exposure or increased vulnerability. Higher exposures can often be estimated by
14 occupational and lifestyle information and have been addressed by U.S. EPA for some
15 time. One difference for cumulative risk assessment is that elevated exposures can
16 include the combined exposure to multiple toxicologically similar chemicals, e.g.,
17 chemicals in workplace or lifestyle exposures (e.g., food sources) that are not on the
18 preliminary chemical list. Because of the population focus and stakeholder involvement,
19 cultural or other lifestyle factors might be identified by stakeholders that could suggest
20 additional sources of chemicals or exposure levels of significance that could then lead
21 to additional sensitive population subgroups. Vulnerability can be more complex,
22 ranging from existing disease (e.g., hospital patients) to genetic predisposition (e.g., for
23 some lung cancers) to socioeconomic factors (e.g., access to health care). Vulnerability
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1 is discussed in some detail in the next chapter but many issues are poorly understood
2 and are foci of current research.
3 The chemical list should then be combined with the description of likely sensitive
4 population subgroups. This information could be arranged in several ways. For
5 example, a table could list the chemicals ranked by the strength of their link to the
6 trigger factor. For example, chemicals linked to population subgroups that are also
7 identified in emissions from the multiple sources (the trigger factor) would be listed first.
8 Chemicals linked to sensitive subgroups of the population of concern could be further
9 described by an indicator of the strength of that link (e.g., based on human data or
10 extrapolated from experimental animal studies) and the size of the sensitive
11 subpopulation. Chemicals could be further identified by their potential for joint exposure
12 (e.g., by multiple routes) or joint toxicity with other chemicals on the list. Any chemicals
13 that could not be adequately evaluated (e.g., lack of toxicity information), or that initially
14 were deemed unlikely to pose significant health risks, could be placed on a "watch list"
15 pending further analysis during the iteration of the exposure and toxicity assessment
16 steps.
17 1.3.5. Quantify Exposure for General Populations and Subpopulations. The initial
18 exposure assessment is next. Up to this point, no actual exposure assessment has
19 been performed, only a listing of chemicals. Extensive U.S. EPA guidance is available
20 for conducting assessments for the three major routes of exposure: dermal, oral, and
21 inhalation (see Chapter 3 for details and citations). For multiple sources and pathways,
22 detailed exposure guidance exists for combustor emissions (U.S. EPA, 1998a) along
23 with programmatic guidance on Superfund sites and multiple pesticide exposures (U.S.
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1 EPA, 1999a,b). In general, the assessment might need to reflect guidance across
2 several Programs or from ORD. For example, general exposure guidance and
3 information on exposure factors are available from the National Center for
4 Environmental Assessment (U.S. EPA, 1992a, 1997c, 1998a, 2002i), guidance on
5 aggregate exposures to pesticides is available from the Office of Pesticide Programs
6 (U.S. EPA, 1999e, 2001 a), guidance on exposure from hazardous waste combustion
7 facilities is published by the Office of Solid Waste and Emergency Response (OSWER)
8 (U.S. 2005d), and dermal exposure to soil is covered by the supplemental OSWER
9 guidance (U.S. EPA, 2004a).
10 Quantification of exposure for cumulative risk assessment should begin with a
11 clear definition of the population and study area (see Section 1.3.2) so that the assessor
12 can identify all existing and future completed pathways. The assessment should also
13 identify the relevant exposure factors, with particular attention to unique factors for the
14 sensitive subpopulations. Once the exposure is characterized for the population of
15 concern and its sensitive subpopulations, the next step is to attempt to simplify the
16 combinations of chemicals, pathways, and timing (including duration and intermittency
17 of exposure) by grouping the chemicals according to media or pathway, and according
18 to timing.
19 Any issues that cannot be quantified should be described qualitatively regarding
20 their relative importance to the population exposure and for possible future
21 quantification should information become available. Information from the dose-
22 response assessment would be useful in this evaluation of those unquantified issues,
23 particularly in terms of exposures of sensitive subpopulations.
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1 1.3.6. Quantify Dose-response for Initial Toxicity Grouping. The focus of toxicity
2 assessment regarding cumulative risk revolves around timing issues of exposure and
3 toxicity. The grouping resulting from the exposure quantification (by timing, media,
4 pathway) should then be further evaluated in terms of toxicological timing factors:
5 toxicological overlap of internal dose, kinetics interactions, toxicodynamic interactions,
6 and persistence of effects (see Chapter 4 for details and additional references).
7 Simultaneous exposures are the ones most often evaluated for potential joint toxicity,
8 but sequential exposures can also result in joint effects. Initiators and promoters of
9 cancer and delayed or persistent toxicity are examples where potential joint toxicity
10 could occur from exposures at different times.
11 Chemicals previously put on the "watch list" could be reexamined in this step
12 through consideration of the potential or expected toxicity at the estimated exposure
13 levels. Toxicologic interactions could be further considered for the watch list chemicals,
14 perhaps via structure-toxicity relationships or other similarity procedures, as could
15 interactions involving characteristics of the sensitive subpopulations. An example of the
16 latter interaction is nutritional deficiencies enhancing toxicity of some metals (U.S. EPA,
17 2004b). Any dose-response or other toxicity issues that cannot be quantified should be
18 described qualitatively, especially regarding importance to potential health effects in the
19 sensitive subpopulations.
20 1.3.7. Integrate Exposure and Dose-response Information. In this final analysis
21 step, the exposure assessment should interface with the dose-response assessment in
22 order to refine the information on joint exposures of main toxic significance and to
23 identify timing issues of most concern regarding increased toxicity. Any matches of
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1 toxicity overlaps (toxic interactions or persistent effects) with exposure overlaps should
2 be highlighted for consideration of improvements in the exposure information. The
3 refined exposure and toxicity characterizations and the resulting initial risk estimates,
4 the products of this step, are the main inputs to the risk characterization.
5 1.3.8. Conduct Risk Characterization. A risk characterization is usually described in
6 U.S. EPA guidance as having two parts: an integrative analysis, which contains the risk
7 estimates and can be highly technical, and a risk characterization summary, which has
8 minimal jargon and focuses on recommendations and uncertainties. As mentioned
9 previously, the sequence is slightly different in the Framework for Cumulative Risk
10 (U.S. EPA, 2003a), where the initial risk estimates are developed in the previous steps
11 because of the interplay and coordination of the exposure and toxicity assessments.
12 The cumulative risk characterization can also differ from a traditional risk
13 characterization in a number of ways (detailed in Chapter 5) that are often caused by
14 missing data or a lack of understanding of the various multiples and their interactions.
15 Some of the more important differences are:
16 Recommendations could be multivariate, i.e., the assessor might not be able
17 to identify a single chemical, pathway, or critical effect that drives the risk.
18 Recommendations might be based on grouping of chemicals, pathways and
19 effects, but such grouping can be subjective.
20 Uncertainty analysis might be predominantly qualitative because of the need
21 for numerous defaults, e.g., for addressing interactions and multiple effects.
22 Time dependence of exposure and mixture composition might be addressed
23 by surrogates (e.g., annual averages) or simplified factors (e.g., index
24 chemical concentration) resulting in complex analyses and unknown
25 information gaps.
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1 The cumulative risk characterization will also differ from more common single chemical
2 and source-based assessments by its focus on the population of concern and its
3 sensitive subgroups.
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1 2. INITIAL CHARACTERIZATION OF THE POPULATION AND
2 CHEMICALS OF CONCERN
3
4 Once the trigger factor has been described, the next steps involve defining the
5 population of concern and its study area, the chemicals of concern, and links between
6 environmental chemical exposures and sensitive subgroups of the population. The
7 steps in this chapter then form the initial collection and organization of information to
8 focus on the cumulative aspects of the risk assessment, shown as steps 2-4 in Figure
9 1-6. Sections 2.1 and 2.2 describe the preliminary evaluations of population and
10 exposure information including the influence of the trigger factor on those evaluations.
11 Section 2.3 describes the linking of population and exposure information to identify any
12 subgroups of that population that would be sensitive to effects from those exposures
13 and the use of conceptual models to help organize the information and analysis. As
14 shown in Figure 1-6, the expected product of the linking step is a refined
15 characterization of the population and its sensitive subgroups along with a refined list of
16 chemicals of concern. Subsequent steps in Chapters 3-5 will involve more detailed
17 evaluation and quantification of exposure, dose-response, and then cumulative health
18 risk.
19 2.1. INITIAL DESCRIPTION OF THE POPULATION
20 In contrast to the source-based approach that begins with releases and
21 addresses all populations impacted by those releases, a receptor-oriented study could
22 begin by defining the population group of interest, and addressing all sources impacting
23 that population. The population group could be determined by geographic,
24 demographic, or other criteria. This population group can be identified from the findings
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1 of a recent exposure study or might simply reflect locations of concern to U.S. EPA or
2 certain stakeholders, which could range from school yards or parks to homes and
3 sacred lands. Under this orientation, the exposures are traced back to evaluate all
4 pathways by which a given subpopulation could be exposed to a variety of chemicals,
5 which could include diet and other lifestyle contributions. As described in the Agency's
6 framework document, this approach is often applied to community-based cumulative
7 health studies (U.S. EPA, 2003a). It can also play a role in other applications that are
8 more often source-based. For example, the assessments for contaminated sites could
9 use a population-based approach to address a specific group for whom unique
10 exposure or vulnerability/susceptibility issues are of concern (see Chapters 3 and 4).
11 The analysis plan for a cumulative health risk assessment could then reflect a
12 combination of source- and receptor-based approaches.
13 2.1.1. Preliminary Characterization of the Population Based on the Trigger. The
14 initial population characterization usually would include a description of the study area
15 and the population in that study area. The trigger factor could influence whether the
16 study boundary or the population is defined first. Consequently, the initial population of
17 concern could be the community in an entire city or county, especially any identified
18 sensitive or susceptible subgroups of that population or community, or it could be those
19 in frequent contact with a geographic area, such as a park or lake. In general, the
20 trigger factor should be a prominent part of the final risk characterization. Sometimes
21 the stakeholders and U.S. EPA agree after further evaluation that the trigger factor has
22 been determined to be of lesser significance, and that another factor will be the key
23 motivation for continuing the cumulative risk assessment. The initial description of the
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1 study area and population of concern should then be considered preliminary and
2 subject to change during the course of the risk assessment.
3 2.1.1.1. Population Defined by the Health Endpoint If a population group is
4 associated with the trigger health effect, then that subgroup automatically is in the initial
5 population of concern. For example, if the trigger is an increased absence from school
6 for children 12 years and younger because of respiratory problems, then that group of
7 children forms the initial population of concern and could be deemed the sensitive
8 subgroup as well. Because cumulative risk assessment can include multiple endpoints,
9 the population could be initially defined in broad and somewhat vague terms, with
10 refinement following the later steps when links are determined between the trigger
11 health endpoints (as well as other endpoints) and chemical exposures.
12 2.1.1.2. Population Defined by Chemical Concentrations Monitoring
13 locations where elevated chemical concentrations were detected can define the bounds
14 of the study area. If transport is plausible for those chemicals, then the study area and
15 population can be much larger than the initial contamination zone. Chemical
16 concentrations limited to specific resources or geographic features can lead to a study
17 population defined by those with likely access to that resource or location.
18 Contamination of a recreational lake might lead to the population defined as those
19 known and potential users of the lake. At this stage, the identification of sensitive
20 population subgroups might only be based on known sensitive groups in the defined
21 population. Common example sensitive groups are children, pregnant women, and the
22 elderly.
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1 2.1.1.3. Population Defined by Multiple Sources When multiple sources
2 are the trigger factor, exposures have not yet been estimated. The initial boundaries of
3 the population of concern might then be roughly defined by possible dispersion
4 characteristics of existing and possible future emissions, as well as populations with
5 possible future exposures. The trigger sources could initially be considered in isolation.
6 As the assessment proceeds, the refinements would consider all sources so that the
7 trigger sources might be evaluated both for their incremental population risk as well as
8 in the context of risk from other sources.
9 2.1.2. Characteristics of Vulnerable Subpopulations. U.S. EPA's Framework for
10 Cumulative Risk (2003a) adopts "vulnerability" concepts that encompass the topic of
11 receptor characteristics. Four areas are articulated where "human and biological
12 ecosystems, communities, and populations may be vulnerable: susceptibility/sensitivity,
13 differential exposure, differential preparedness, and differential ability to recover."
14 Given this context, receptor population characteristics may include diverse factors such
15 as genetic susceptibility, age, stress, disease state, economic status, ethnicity, health
16 status, proximity to sources, activity patterns, etc. Factors that affect a population's
17 vulnerability should be considered in the conduct of a cumulative risk assessment.
18 Risks should be calculated separately for populations with specific receptor
19 characteristics to yield more realistic estimates of the health risks from cumulative
20 exposures.
21 Studies in the literature suggest that certain receptor characteristics might
22 contribute to the toxicity caused by chemical mixture exposures. For example, Perera
23 et al. (2004) present molecular epidemiologic evidence that combined exposures to
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environmental levels of two mixtures, polycyclic aromatic hydrocarbons (PAH) and
environmental tobacco smoke (ETS), in New York City adversely affected fetal
development in inner city minorities. In this case, minorities were thought to be
differentially exposed to ETS, increasing their susceptibility to environmental levels of
PAH. There were no PAH-related developmental effects in the absence of ETS. The
results of this study
revealed an unexplained
ethnic difference in that
"mean birth weight and
head circumference were
lower and there was
greater variability in these
outcomes among African
Americans than in
Dominican infants." Fora
cumulative risk
assessment, a factor such
as differential exposure to
Example of Pesticides and Farmer Characteristics
(Text Box 2-1)
A large, prospective epidemiologic study, The Agricultural Health
Study, is an ongoing effort to evaluate health effects in agricultural
cohorts in North Carolina and Iowa from pesticide exposures
(Alavanja et al., 1996). On aspect of this study is to examine the
impacts of lifestyle, cultural, ethnic and genetic factors on the health
of farmers in conjunction with pesticides exposures, making it an
important contribution to the literature on cumulative risk
assessment. Results from this study will likely be published for
years to come, but a few articles are already available. Current
results include:
Increased prostate cancer risk for study subjects with a
family history of prostate cancer (Alavanja et al., 2003).
Increased prostate cancer risk for applicators over 50
years in age who used chlorinated pesticides (Alavanja et
al., 2003).
Identification of poor financial condition of the farm, limiting
the purchase of safety equipment, as a significant risk
factor for acute effects from high pesticide exposure
events (Alavanja et al., 2001).
Higher pesticide exposures and more pesticide-related
health effects in white farmers than in black farmers, which
may be explained by farm characteristics or economics
(Martin etal., 2002).
Association of specific pesticides (i.e., paraquat, parathion,
malathion, chlorpyrifos, thiocarbamate) with respiratory
symptoms of farmers (Hoppin et al., 2002).
ETS should be taken into account when evaluating an environmental mixture.
In the assessment of rural communities, the literature suggests that impacts from
exposures to mixtures of pesticides should be evaluated from a cumulative risk
perspective (see Text Box 2-1). Another example involving multiple route exposures to
24 organophosphorus (OP) pesticides (U.S. EPA, 2002a) is discussed in Section 4.4.2.
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2.2. INITIAL ASSESSMENT OF EXPOSURE DATA
As mentioned previously, the need to conduct a community-based cumulative
risk assessment could be initiated by any of the three triggers (i.e., multiple
sources/release events, elevated chemical concentrations, or a concern about
population illness) individually or in combination (Figure 2-1). This section provides a
general description of the types of chemical information likely available and initially
needed in the early part of the exposure assessment process and its dependence on
the trigger factor. It also discusses specific population data that need to be collected
initially in order to conduct the exposure assessment. Specific approaches to the
cumulative exposure assessment are discussed in Chapter 3.
2.2.1. Initiating the Exposure Assessment when Health Endpoint is the Trigger.
When an increased incidence of health endpoints triggers an assessment, the initial
goal of the investigation is to determine if environmental chemicals/stressors present in
a community are linked in some way to those health endpoints. These types of
analyses are similar to primary epidemiologic investigations, such as that conducted to
determine why there
are elevated rates of
female breast cancer
in a region
(Aschengrau et al.,
2003; Paulu etal.,
2002). Text Box 2-2
provides an example
of an illness trigger
Example of Illness Trigger from Pesticide Incident
(Text Box 2-2)
Information reported 5 children with abdominal pain. 2 days later,
to health officials additional 2 children with all 7 showing respiratory
arrest, symptoms of organophosphate (OP)
poisoning. 2 children died. All 7 were siblings.
Setting observations Household, recently sprayed with unknown
insecticide by adult resident.
Illegal pest-control application of methyl parathion
inside home at 3x concentration used in
agricultural spraying (this organophosphate
pesticide is only intended for outdoor use)
Affects central nervous system: nausea, dizziness,
headache, vomiting, high levels can be fatal
Samples from sprayer, food, water, air.
Biomonitoring (fluid samples) to identify people
exposed (multi-pathway) & focus response actions
Decontamination of house and increased
publication of dangers of inappropriate OP use.
CDC (1984).
Investigative
discovery
Specific chemical
toxicity
Exposure
assessment
Risk management
action
Source
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1
2
3
6
7
8
9
10
11
12
13
14
15
16
17
18
19
>40 industrial
facilities
& disposal areas
igh cancer rates,
low^birth weights
infant morality
relative risk
public health
data
Population
illness
multiple-
chemical
fate
population
subgroup
Combined \ features
characterization
organics in air
or soil,
transported to
water & fish
subsistence
fishers
multi-route
exposures
mixtures
toxicity
Chemical
concentrations
inhalation,
ingestion, dermal
from
air, water, soil,
fish, produce
high blood lead
levels in children, .
soil and indoor dust
aroclor: reproductive tox,
diesel exhaust: lung cancer,
water disinfectant
byproducts: reproductive tox
FIGURE 2-1
Example Triggers and Data Elements for Cumulative Risk Analyses
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2-7
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1 initially attributed to general organophosphate (OP) poisoning and later focused to
2 exposure to a single pesticide. Health registries can serve as important resources for
3 evaluating cumulative risks from environmental exposures, and a number already exist.
4 For example, most states maintain cancer registries, as do national organizations, e.g.,
5 the Centers for Disease Control and Prevention. A number of birth defect registries also
6 exist (over 30 states), but the quality of most data is considered inadequate for an
7 effective tracking program (EHTPT, 2000), particularly regarding implications of
8 environmental exposure to multiple chemicals.
9 When an increased incidence of health endpoints triggers an assessment, the
10 initial phase of the data gathering involves a collection effort that focuses on identifying
11 chemicals (individually or in groups) that are known to cause the effect in humans or
12 some animal species (e.g., effect identified in rodent bioassays). Although Table 2-1
13 identifies a number of illnesses that are linked to environmental contaminant exposures,
14 chemical combinations and exposure conditions can be highly situation-specific, so that
15 identification of chemicals and chemical mixtures related to specified health effects is
16 typically initiated through a literature review. The literature review should not be limited
17 to primary effects but should consider secondary effects as well; for example, the RfD of
18 a chemical may be based on hepatotoxicity (i.e., hepatotoxicity was the most sensitive
19 endpoint), but the literature review may show that the chemical is also a potential
20 reproductive toxicant at doses higher than the LOAEL. The initial data collection for the
21 exposure analysis may be conducted in conjunction with the dose-response and toxicity
22 analysis, so that specific chemical mixtures of concern (given the health endpoints) are
23 identified, and chemicals with known toxic interactions can be considered for additional
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TABLE 2-1
Examples of Illnesses Linked to Multiple Environmental Factors3
Illness/
Health Effect
Hypothesized Causes/
Epidemiological Links
Associated Levels
Remarks
Reference
Acute mylogenous
leukemia (AML)
Benzene, ionizing
radiation, alkylating
agents, and
topoisomerase
inhibitors.
Increased incidence of
leukemia observed in
lifetime occupational
studies at 10-50 ppm
benzene and higher.
However, these levels
exceed the U.S.
occupational 8-hour
standard of 1 ppm for
benzene in air so are
unlikely to occur.
Benzene is present in gasoline,
automobile exhaust, and cigarette
smoke, the latter of which also emits
radiation. AML is also a secondary
cancer after treatment for primary
cancers, and links between AML and
genetic (inherited) conditions and
viruses have also been established.
Hricko, 1994;
U.S. EPA,
1997b
Allergic contact
dermatitis
Nickel and chromium
The European Union (EU)
has prevented sale of
nickel-containing objects
that release over 0.5 ug
nickel/cm2 skin per week.
Delayed skin inflammation and rash
can occur; nickel is commonly used
in some jewelry. Note that the EU
nickel limit might not protect all
sensitized persons (no similar
U.S. limit has been placed on nickel
content in jewelry or other consumer
products).
Nickel Institute,
1999; Amduret
al., 1993
Asthma
Particulates, including
high molecular weight
(HMW) allergens
(polymers or proteins of
animal, plant, bacterial,
or fungal origin in range
of 20-50 kilodaltons).
A 14% increase in
emergency room visits due
to asthma was associated
with very fine particulate
matter (PM2.5) averaging
12 ug/m3 (for 15 months).
Asthma is exacerbated by both
indoor and outdoor pollutants as well
as allergens. Correlations have
been observed between asthma and
sensitivity to cockroaches and to
HMW allergens.
Norris etal.,
1999; O'Connor
and Gold, 1999
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TABLE 2-1 cont.
Illness/
Health Effect
Hypothesized Causes/
Epidemiological Links
Associated Levels
Remarks
Reference
Blackfoot disease
Arsenic
Observed in people
consuming well water with
170 ug/L arsenic and
higher. (This concentration
is much higher than the
U.S. drinking water
standard of 10 ug/L.)
Blackfoot disease, a severe form of
arteriosclerosis, is a vascular
complication of arsenic exposure.
Blackfoot incidence increases with
age.
U.S. EPA,
2005c; Amdur et
al., 1993
Liver cancer
Many (MOO) chemicals,
including chlorinated
solvents, aflatoxin, and
animal products (meat,
eggs).
For aflatoxin (which can be
found in peanut butter),
Americans could consume
up to 0.15-0.50 ug/day.
Organic solvents are
ubiquitous at low levels in
urban air and hazardous
waste sites.
Causes of liver cancer are many and
varied; this organ is the most
common site for mutagens and non-
mutagens. To illustrate for aflatoxin,
effects can be confounded by
hepatitis B infection, which is
endemic in areas where high intake
is common.
NTP, 2002;
Gold etal.,
2001;CPDP,
2004; ATSDR,
2001
Lung cancer
Dozens of chemicals,
including those in
cigarette smoke, and
radon.
Average U.S. radon levels
of 4.4 to 11 becquerels/m3.
Tobacco smoke is the leading cause
of lung cancer. Lung cancers
increase multiplicatively when radon
is combined with cigarette smoking.
NTP, 2002
Neurological
damage/
reduced
intelligence
quotient (IQ)
Lead in lead-based
paint; mixtures of
polychlorinated
biphenyls (PCBs) and
dioxins; fetal irradiation.
An increase in blood lead
levels from 10 to 30 ug/dL
resulted in an IQ reduction
of 4 to 5% (4.4 to
5.3 points) in 7-year-old
children
People can be exposed to lead via
many sources, e.g., paint, soil and
dust, drinking water, food,
occupational exposure, burning
candles with lead wicks, and
hobbies.
Baghurstetal.,
1992; NYSDOH,
2003; Birnbaum,
1995
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TABLE 2-1 cont.
Illness/
Health Effect
Hypothesized Causes/
Epidemiological Links
Associated Levels
Remarks
Reference
Parkinson's
Disease and
Parkinsonism
(which might be
reversible)
Many pesticides,
including
organophosphates,
organochlorines,
carbamates, various
herbicides and
household fumigants;
and copper and
manganese.
Increases in Parkinson's
disease has been observed
in connection with chronic
pesticide exposures.
Reversible Parkinsonism
has been seen following
acute pesticide exposures.
One occupational study
found 6% of workers
exposed to >5 mg/m3
manganese exhibited acute
Parkinson's symptoms.
Risk factors have been identified for
people in farming areas, especially
those with a history of pesticide
exposure. Some who die of
Parkinson's have higher levels of
organochlorine pesticides in brain
tissue than the general population.
Idiopathic causes account for >85%
of all cases; suspected links exist to
MPTP,b organomercury,
encephalitis, major tranquilizing
drugs, carbon monoxide or disulfide
poisoning, and frequent head
injuries.
Hileman, 2001;
Feldman, 1992;
Gorell etal.,
1999
1 a This table illustrates illnesses or health effects that have been linked with various environmental exposures (some lifestyle factors
2 are also shown) and that might trigger a cumulative assessment concern because of the number of possible chemical causative
3 agents and their likely joint toxicity.
4 b MPTP is the drug 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine.
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1 exposure measurements and analysis. In conjunction with dose-response analyses, the
2 analysis should examine if there are specific subpopulations sensitive to the identified
3 health effects or whether chemical exposures could exacerbate an existing condition in
4 potentially sensitive individuals, based on toxicokinetic or toxicodynamic information. In
5 summary, the goal of this first step is to determine the pollutants of concern (either
6 individually or in groups) that have been linked to the trigger effect and similar health
7 effects, and the combinations of subpopulations and pollutants of concern that might
8 require more detailed exposure assessement because of higher exposure and/or
9 enhanced toxicity in those subpopulations.
10 2.2.2. Initiating the Exposure Assessment when Elevated Chemical
11 Concentrations are the Trigger. When increased chemical concentrations trigger a
12 risk assessment, the initial goal of the investigation is to determine if those
13 concentrations could result in exposures that could cause potentially important health
14 effects in the community, including secondary health endpoints and toxicological
15 interactions. The initial phases of these types of analyses are similar to the steps
16 undertaken in traditional risk assessment analyses such as those presented in the Risk
17 Assessment Guidance for Superfund (U.S. EPA, 1989a). From an exposure
18 perspective, following identification of the chemicals of interest, aspects of which are
19 discussed next, such analyses will determine the spatial bounds of the assessment,
20 examine the fate of the identified pollutants, determine whether (and which) individuals
21 in the community are or could be exposed and quantify such exposures. These are
22 standard components of an exposure assessment.
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1 When increased chemical concentrations trigger an assessment, the initial phase
2 of the data gathering focuses on identifying the chemicals present in the community,
3 documenting the locations of these elevated concentrations (existing data on the
4 locations of these elevated concentrations could be supplemented with information
5 provided by stakeholders about the locations of previous polluting operations practiced
6 in the community) and examining the health effects associated with these chemicals. In
7 conjunction with dose-response analyses, the primary and secondary health effects
8 associated with the individual chemicals or groups of chemicals should be identified.
9 Because a cumulative assessment is being initiated, the analysts should evaluate
10 whether there are other chemical exposures that could be occurring in the community
11 that could increase the toxicity of the chemicals known to be at high concentration. This
12 could involve an examination of potential sources of pollution in the community (the
13 Toxic Release Inventory (TRI) reports on pollutants typically released from these
14 sources) followed by monitoring of related environmental media. Other U.S. EPA
15 documents (e.g., Human Health Risk Assessment Protocol for Hazardous Waste
16 Combustion Facilities [U.S. EPA, 2005d]) can be of help in identification of the types of
17 compounds typically released from a source class. In summary, the goals of this first
18 phase are (1) to identify likely multichemical exposures to those chemicals with high
19 environmental concentrations, (2) to characterize the primary and secondary health
20 effects potentially associated with those chemicals, and (3) to determine if there are
21 other pollutants (either individually or in groups) that should be monitored in other media
22 (e.g., household pesticide use) because of their influences on exposure or because they
23 produce similar health effects .
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1 2.2.3. Initiating the Exposure Assessment when One or More Sources is the
2 Trigger. When one or more sources trigger an assessment, the initial goal of the
3 investigation is to determine if the chemicals released from those sources could cause
4 exposures high enough to cause important health effects in the community. For
5 example, releases of highly volatile chlorinated solvents into ambient air are usually only
6 considered significant for populations close to the source as they disperse rapidly
7 (ATSDR, 2001). With multiple sources, of most importance for cumulative risk
8 assessment is the determination of which chemicals from those sources will reach the
9 population of concern. Sources of chemical pollutants include (1) point sources, such
10 as industrial and commercial boilers, electric utility boilers, turbine engines, wood and
11 pulp processers, paper mills, industrial surface coating facilities, refinery and chemical
12 processing operations, and petroleum storage tanks and (2) area sources such as
13 piping leaks, industrial wastewater treatment ponds, quarry operations, tank farms, and
14 on-road and off-road vehicles. The initial phases of these types of analyses are similar
15 to the steps undertaken in traditional risk assessment analyses that analyze single
16 sources such as those presented in the Risk Assessment Guidance for Superfund
17 (U.S. EPA, 1989a) and those presented in the Methodology for Assessing Health Risks
18 Associated with Multiple Pathways of Exposure to Combustor Emissions (U.S. EPA,
19 1998a). Following identification of the source(s) and chemicals of potential interest,
20 aspects of which are discussed next, such analyses will
21 characterize the source(s) by compiling basic facility information
22 determine the spatial bounds of the assessment
23 examine the fate of the released pollutants
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1 determine whether (and which) individuals in the community could be
2 exposed and
3 quantify such exposures.
4 These steps are standard components of an exposure assessment.
5 When one or more sources trigger an assessment, the initial phase of the data
6 gathering focuses on identifying the types of chemicals released from those sources,
7 including potential future releases, that could impact the community. There may be
8 different types of sources involved, so that exposure assessment guidance from several
9 U.S. EPA Program Offices might have to be consulted. Most Agency Program Offices
10 have procedures for determining the important chemicals released from different point
11 sources of concern. For example, Chapter 2 of the draft Human Health Risk
12 Assessment Protocol for Hazardous Waste Combustion Facilities (U.S. EPA, 2005d,
13 Volume 1) presents an approach for identifying compounds of potential concern that are
14 emitted from hazardous waste combustors. In addition to the chemicals released from
15 the identified sources, the analyst may wish to examine other sources, including
16 nonpoint sources, of specific pollutant exposures to the community. In addition, in
17 conjunction with dose-response analyses, the primary and secondary health effects
18 associated with the individual chemicals or groups of chemicals need to be identified so
19 that the exposure assessment can group those chemicals in the identified sources that
20 jointly influence the same health effects. In summary, the goal of this first phase is to
21 determine those pollutants (either individually or in groups) from the identified sources
22 that are of concern for the community because of likely co-exposures at concentrations
23 of toxicological significance.
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1 2.2.4. Summary. During the initial assessment step, approaches are available to focus
2 on what emissions sources, chemicals or population locations should be included in the
3 cumulative assessment and what chemicals should be evaluated together. In
4 evaluating which chemicals are of concern for a community, it is useful to consider the
5 specific triggers for the cumulative assessment and any issues that might be of special
6 interest to the stakeholders. Although more detailed approaches to exposure
7 assessment are discussed in Chapter 3, some insight on focusing the assessment can
8 be gained from criteria commonly used for retaining or excluding chemicals. The
9 chemical selection criteria recommended by Agency Program Offices typically include:
10 chemical toxicity
11 mass of chemical released or mass of chemical present in media
12 the potential for physical or chemical interactive effects with other chemicals
13 in the area and with other media
14 the tendency to persist, bioaccumulate, and/or be transported between
15 environmental media
16 the potential for relatively high exposures to sensitive populations.
17 In addition, for a population-focused cumulative risk assessment, the chemical selection
18 criteria should also include:
19 the possible contribution to induction of health effects that exist at relatively
20 high levels in the study population
21 likelihood of exposure to the population of concern
22 potential for overlapping exposures (times and routes) to toxicologically
23 similar or interacting chemicals.
24 Depending on the community and the trigger, these criteria could be adapted or
25 augmented.
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1 2.3. LINKING THE LIST OF CHEMICALS OF CONCERN TO THE POPULATION
2 PROFILE THROUGH A CONCEPTUAL MODEL
3 Following the initial data collection, the chemicals and endpoints of concern
4 should be evaluated for linkages to sensitive population subgroups in the community or
5 the population being assessed. The first goal of this phase is to determine if any of
6 these chemicals or subpopulations are present in the community. In addition to
7 identifying and examining chemical releases from local sources, the cumulative
8 assessment could include an examination of possible regional and national sources of
9 these potentially hazardous chemicals. The assessment could also examine if there are
10 unique exposure sources or pathways for the sensitive populations identified. The
11 analysis could also examine the spatial relationship between the identified sources and
12 residences, sources of food, playgrounds, schools, etc. to identify individuals or groups
13 of people in the community who might be affected. Other community-based methods
14 highlight the importance of community involvement in the risk assessment planning
15 process (U.S. EPA, 1997a).
16 One of the desired outputs from the planning and scoping phase of cumulative
17 risk assessment (U.S. EPA, 2003a) is a conceptual model. This model provides both a
18 written and visual representation of the structure and dynamics of the system being
19 assessed that is subsequently converted into an implemented approach (Suter, 1999;
20 Suter et al., 2003). Conceptual models typically identify the links between main system
21 components, i.e., the sources, chemicals, exposure pathways, exposure routes,
22 subpopulations, and health endpoints that will be analyzed (Suter, 1999). Conceptual
23 models should identify what sources, endpoints, and processes are included and which
24 are excluded, and what assumptions are being made. Once the initial exposure and
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1 population descriptions are completed, a preliminary conceptual model can then be
2 developed jointly by the exposure and dose-response analysts, to ensure that all
3 relevant exposures and endpoints are included. During the analysis phase of the
4 exposure assessment, the preliminary conceptual model is refined by incorporating
5 further information gained during the analysis steps (Chapter 3, Section 3.3).
6 Some key elements of a conceptual model for evaluating cumulative exposures
7 are shown in Figure 2-2. This figure depicts sources, processes, receptors, and flows
8 between them, but in general terms, showing how the same model components can
9 apply beyond the scope of this report to include other receptors and effects. Particularly
10 for cumulative risk assessments that consider several multiples (e.g., sources,
11 chemicals, pathways, effects), such as at a contaminated site, it is better to develop a
12 hierarchy of conceptual models instead of trying to represent the multiples in one model
13 (Suter, 1999). In the case of a Superfund site, soils are typically contaminated, and
14 contaminants are also often found in surface water, groundwater, and indoor air of
15 buildings on or surrounding the site, so a first level conceptual model can be a fairly
16 simple picture (Figure 2-3). As described in the U.S. EPA Risk Assessment Guidance
17 for Superfund (U.S. EPA, 1989a) and from a cumulative exposure assessment
18 perspective, unique exposures in populations living near this site might require detailed
19 evaluation. In the next chapter, Figure 3-2 displays in more detail the components of a
20 cumulative exposure assessment along with primary exposure routes for potential
21 receptors, suggesting possible populations of elevated exposure, such as individuals
22 who consume large quantities of local fish (recreational exposure to surface water).
23 More detailed conceptual models and diagrams for cumulative exposure are presented
24
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Starting point:
Source & release
Can move into and through:
Chemical hazards:
stack emissions,
surface runoff,
volatilization,
leaching
What, where, how much? I
Environmental media
To reach:
Receptors exposed
(resources)
Ground
water
Air
Soil
Surface
water
What, where, when, how much?
And possibly cause:
Effects
Humans,
animals & plants
other resources
/
\
Risks to
human health/
ecological
function/service
Who/what, where,
when, how much?
Impacts on
social-cultural
and economic
resources
What could happen?
FIGURE 2-2
Key Elements of an Integrated Conceptual Model
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2-19
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airtransport
deposition
1
2
3
4
5
6
7
8
c
' ". " I ' ". .
1
contact »
drinking wetter
leaching to ,.-...... .'..*'
. gfoundwatBrtianspoft
&>
?
-
$
ncidental
dermal
contact
FIGURE 2-3
Schematic of Sources/Releases, Transport/Fate, and Exposure Routes
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2-20
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1 in Chapters (e.g., Figures 3-5, 3-9, 3-11, 3-12) that suggest specific mechanisms and
2 processes to be evaluated.
3 Conceptual models for cumulative risk cannot present all the complexities,
4 especially those dealing with physical and toxicologic interactions. Consideration of all
5 combinations and their potential interactions can be conceptually difficult and
6 impractical, so that some kind of sorting or reduction of the potential combinations of
7 chemicals, routes, effects must be first undertaken. That step is better represented by a
8 decision tree or influence diagram. A site oriented, second-tier conceptual model may
9 also be useful, as depicted in Figure 2-4. In addition to the usual boxes describing the
10 scenario, processes, receptors, etc., there are also indications of places where
11 environmental, toxicokinetic and toxicodynamic interactions could be considered.
12 Those potential interactions can then be simplified by grouping (e.g., Section 3.3.2.2 for
13 exposure based grouping) and prioritized using decision criteria. For example,
14 toxicologic interactions could be screened based on toxicologic significance, as
15 indicated by the relative importance of each chemical's environmental concentration
16 using screening values such as the hazard quotient. Schematics and decision
17 flowcharts for joint toxicity and toxicologic interactions are given in Figures 4-6a, b,
18 and c. Once that initial screening or grouping is done, a revised conceptual model
19 could be created, followed by more detailed analysis of the toxicologic interactions such
20 as is described in Chapter 4.
21
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1
2
Geographic
area
3
4
5
Environmental setting Contaminants (Other stress*
i ^^^^^^
i I mu
|. M 1 II 1 1
! ' ' ' ' ' ' landscape fRmjh/ , ,hcc
form/matrix
tple chemicals
1
physicochemical amou
properties (volume, cone
volatility, rr
environ me
obility, persistence contai
ital transformation sta
t
entration)
iment
tus
environmental interactions \ «
O Medium/
transport
7 pathway
o Exposure
activity/use
9
Receptor
10
11 Efcot "I
i i i
soil || air surface | seeps | 9round
1 1
sediment | | plants || anims
1
| |
exposure point | rou(e | in
concentration ' ' ar
1 1
1 1
take/ internal
nount dose
tox/co
/ntera
1 (parti
| general populaiion | | sensiTive subgroups | individual |
Note' ^ L
' potential for 1 joint toxicity
environmental or carcinogenicity
1
noncarcinogenicity
Is
kinetic
itions
>f joint toxicity)
internal interaction. \ ' toxicodynamic interactions J
12
13
multiole svstemic effects:
genotoxicity reproductive | | neurological | | cardiovascular
non-genotoxicity teratoqenic immunoloqical qastrointestinal
mutagemcity musculoskeletal 1 1 inte
gumentary respiratory
hepatic
renal/
urinary
whole body
14
15
16
17
18 FIGURE 2-4
19 Example Second-tier Detail of the Conceptual Model for Cumulative Health Risk
20
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1 3. CUMULATIVE EXPOSURE ASSESSMENT
2
O
4 This chapter provides detailed information on cumulative exposure assessment,
5 to be conducted after completion of the steps described in Chapter 2, i.e., identifying the
6 exposed population, conducting an initial exposure assessment, and developing a
7 conceptual model for a cumulative assessment. The goal of Chapter 3 is to describe
8 cumulative exposure assessment issues, highlighting existing data, methods and
9 approaches that can be used to address these issues. To answer the questions for
10 cumulative exposure assessments
11 listed in Text Box 3-1, methods are
12 described that can be used to
13 determine if individuals are co-
14 exposed to multiple pollutants and the
Cumulative Exposure Assessment Questions
(Text Box 3-1)
How can people be exposed to multiple chemicals?
In which media, at what levels, where and when?
What are the intensity and duration of these
exposures?
Are there any unique subpopulation susceptibility or
vulnerability issues?
15 time periods over which these exposures occur (i.e., toxicologically relevant time
16 periods). In Section 3.1, cumulative exposure assessment is defined. In Section 3.2,
17 an overview is provided of some documents that describe current Agency practice.
18 Section 3.3 discusses the conduct of a population-focused cumulative exposure
19 assessment, providing a brief overview of the basic steps undertaken in any exposure
20 assessment and highlighting the issues that are not routinely evaluated in a
21 conventional (i.e., single chemical-focused or single source-focused) exposure
22 assessment. This includes grouping of potential chemicals of concern by exposure
23 pathway and media with examples from different chemical groups (Section 3.3.2.2). In
24 Section 3.4, cumulative concepts for atmospheric pollutants are illustrated. Finally,
25 Section 3.5 summarizes the information in this chapter.
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1 3.1. DEFINING CUMULATIVE EXPOSURE ASSESSMENT
2 Exposure assessments that support cumulative health risk assessments evaluate
3 a population's exposures to multiple chemicals through multiple routes of exposure over
4 time. Such population-based assessments may need to consider multiple exposure
5 timeframes: specifically, the timing and intensity of exposures to different chemicals
6 may need to be evaluated relative to each other, based on an understanding of the
7 potential toxicokinetic interactions and the potentially overlapping or complementary
8 toxicodynamics associated with the chemicals of concern. In addition to evaluating
9 exposures in the general population through standard environmental exposure
10 pathways, exposure assessments that support cumulative health risk assessments also
11 focus on the identification of potentially susceptible or vulnerable subpopulations in the
12 study area and pathways of exposure unique to those subpopulations.
13 Cumulative exposure assessments rely on environmental occurrence data and
14 environmental fate models to estimate the concentrations of multiple chemical pollutants
15 in environmental media that individuals in the community may contact. Unlike chemical-
16 focused assessments or single source-focused assessments, the community's
17 boundary may define the geographic region of study. If the timing of different chemical
18 exposures is important, then fate models may need to estimate changes in the
19 concentrations in environmental media over time. The pollutants may occur in these
20 media as a consequence of releases from multiple and different sources that could be
21 located close to or distant from the population of concern. The environmental fate
22 information needed for a community assessment could be site dependent; for example,
23 the data could include the degradation of chemicals or chemical mixtures in the
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
environment, interactions of pollutants in the environment that influence their fate and
interactions between chemicals and the environment (e.g., killing off or promoting soil
microbes that normally degrade some of the chemicals or altering the soil binding so
that transport through soils is enhanced).
3.2. EPA EXPOSURE ASSESSMENT GUIDANCE
The general methods the Agency
uses to evaluate human exposures are
presented in the Guidelines for Exposure
Assessment (U.S. EPA, 1992a). Agency
Program Offices follow these Guidelines
and develop additional guidance
documents that describe exposure
assessment methods relevant to the
specific types of chemicals they evaluate.
For example, the basic process for
Selected Information Guides (Text Box 3-2)
Guidelines for Exposure Assessment (U.S. EPA,
1992a)
Risk Assessment Guidance for Superfund
(U.S. EPA, 1989a)
Methodology for Assessing Health Risks
Associated with Multiple Pathways of Exposure to
Combustor Emissions (U.S. EPA, 1998a)
Human Health Risk Assessment Protocol for
Hazardous Waste Combustion Facilities (U.S. EPA,
2005d)
DOE Information Brief: Baseline Risk Assessment
Human Health Evaluation Manual (U.S. DOE,
1992)
General Principles for Performing Aggregate
Exposure and Risk Assessments (U.S. EPA,
2001 a)
assessing exposures at Superfund sites is described in the Risk Assessment Guidance
for Superfund (U.S. EPA, 1989a) (see Text Box 3-2).
The assessment of exposures to chemicals released during combustion is
described in Methodology for Assessing Health Risks Associated with Multiple
Pathways of Exposure to Combustor Emissions (U.S. EPA, 1998a) and in Human
Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities (U.S.
EPA, 2005d). While these documents focus on conventional exposure assessment
approaches, many cumulative exposure assessment issues are presented.
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3-3
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1 At times, Program Office guidance is developed specifically to address
2 cumulative exposure issues. For example, in response to the 1996 Food Quality
3 Protection Act, the Office of Pesticide Programs developed General Principles for
4 Performing Aggregate Exposure and Risk Assessments (U.S. EPA, 2001 a). Finally,
5 Agency documents that describe exposure approaches to chemical mixtures, such as
6 the Site-Specific Assessment Procedures volume in the review draft Exposure and
7 Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and
8 Related Compounds (U.S. EPA, 2003c), describe methods for examining chemical-
9 specific cumulative exposure issues that can be applied in other situations. In
10 summary, there are a number of Agency resources that describe methods and
11 approaches that can be used to address various aspects of exposure assessments for
12 community-based cumulative risk assessments.
13 3.3. CUMULATIVE EXPOSURE ASSESSMENT: ANALYSIS PHASE
14 As described in EPA risk assessment guidance documents, the analytic phase of
15 an exposure assessment begins after a preliminary list of chemicals of potential concern
16 has been developed and the population and subpopulations of concern have been
17 identified. The materials presented in Chapter 2 identify data sources and approaches
18 that can be considered when conducting a cumulative exposure. As described in
19 Chapter 2, the linkages between relevant aspects of the analysis can be depicted using
20 a conceptual model; Figure 3-1 provides an example conceptual model for a
21 contaminated site. Although the initial triggers could vary across communities, as
22 indicated in Figure 2-1, the same exposure assessment steps are addressed. The
23 basic steps for quantifying human exposures to chemicals are identified in Text Box 3-3.
24
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2
O
A Sourc
5
6 ContaminE
Surface S
7
8
9
10
1 1 Contamin
Subsurfac
12
Contamin
Surface W
13 Sludge,
Sedime
14
Buildin
15
16
Backgr
18
19
20
91
Primary Release
e Mechanism
Particulate or
oil Emis
30US
sion
h. ^ _c
Runoff |
»1 1
ated . Percolation
2 Soil 1 -^ ,
ated
ater,
nt
iS 1 * Gaseous E
ate or
Emission
Primary
Environmental
Transport Medium
-H Air 1 *
Contact
. Surface Water
and Sediment
i
\
->| Groundwater | ^
-H Air 1 »
Contact
r
3 Water
-
-
> Home
(Food, Soil, etc.)
22
* The resident or visitor scenario may be expanded for cu
of specific sensitive populations (e.g., subsistence fishe
90 Grey f II boxes indicate complete exposure pathways.
Open boxes indicate exposure pathways that are not com
24 FIGL
25 Conceptual Model for Hypothetical (
26 Illustrating Pathways Conside
»
>
mula
s).
jlete.
IRE
3ur
rec
Primary
Exposure
Route
Potential Receptor (Current or
Future)
Worker
Resident*
Recreational
Visitor
Inhalation
Ingestion
Dermal Absorption
Ingestion
Dermal Absorption
Ingestion
Inhalation
Dermal Absorption
Ingestion
Dermal Absorption
Inhalation
Ingestion
Dermal Absorption
Inhalation
Ingestion
Inhalation
Dermal Absorption
Ingestion
Inhalation
Dermal Absorption
ive assessments to consider unique exposures
13-1
nulative Exposure Assessments
J and Complete Pathways
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3-5
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
In each section, cumulative exposure
issues are identified and existing
approaches are shown that can be
used to address the issue. Typically,
exposures are estimated for complete
exposure pathways. Complete implies
that each exposure assessment
Exposure Assessment: Analysis Steps
(Text Box 3-3)
Characterize the
exposure setting
(3.3.1)
Identify environmental features
and potential receptors
Identify potential Describe sources, release
exposure pathways mechanisms, receiving media,
(3.3.2) and locations for chemicals
Quantify exposures Estimate medium-specific
through multiple
exposure routes
(3.3.3)
chemical concentrations at
points of human exposure, and
calculate intakes (considering
time, frequency, duration)
component is present from the occurrence of the chemical through relevant exposure
pathways and routes to the receptor. Exposures may be estimated for pathways that
are not currently complete but are considered likely to be complete be in the future.
3.3.1. Exposure Setting. Describing the environmental characteristics of the study
area and identifying the people who are, or could be, exposed to multiple chemicals are
the two main elements of the exposure setting for a community-based assessment.
The following subsections describe cumulative assessment issues related to these
elements.
3.3.1.1. Environmental Features Characterizing the exposure setting
potentially involves compiling basic data on topography, surface hydrology, soil geology,
vegetation, groundwater hydrology, climate and meteorology, land use, pollution
sources and demography of the community. Geographic and meteorological data are
routinely assembled when conducting an exposure assessment. Basic geographic
information about a community is available through sources offered by the U.S.
Geological Service and U.S. Department of Agriculture; climate and meteorology data
are generally available from the National Weather Service. Land use includes the
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3-6
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1 identification of all residential areas, work places, recreational areas and places where
2 foods are grown or collected. Relevant pollution sources inside and outside1 the
3 community also need to be identified. Community input to these identification
4 processes is important. This includes gaining an understanding of how different
5 locations in a community are currently used and how they were used, which provides
6 information on past polluting practices and potential past exposures.
7 In a community assessment, in addition to examining the contaminants present,
8 there may be a need to examine environmental conditions in the broader region. For
9 example, if there are atmospheric sources of concern for an affected community in
10 which there is a Superfund site, a cumulative analysis may examine the concentrations
11 in the local environment from these atmospheric sources and the potential for airborne
12 contamination from the Superfund site as required by U.S. EPA (1989a). Ambient data
13 that can be used in such an analysis can be obtained from various organizations, such
14 as EPA regional offices and state, county, or city environmental agencies. (Several
15 resources for these data are given in Appendix A.)
16 To illustrate how different types of data can be used, Text Box 3-4 illustrates data
17 sources tapped for a recent cumulative study of air toxics in an urban area. The
18 broader scope of a cumulative exposure assessment could include background data on
19 chemical concentrations in local soil and water, both naturally occurring (such as
20 metals) and anthropogenic chemicals (such as PAHs, PCBs, and dioxins) as well as
21 concentrations of chemical pollutants in the U.S. food supply. For example, Volume 2,
22 Properties, Environmental Levels, and Background Exposures, of the draft U.S. EPA
1 For example, the analyst may wish to evaluate whether there are regional emissions sources that could
be impacting pollutant levels in the community.
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
(2003c) dioxin document lists typical
concentrations of dioxin congeners in the
U.S. food supply. These nationally
representative samples could be
incorporated into a cumulative exposure
analysis, if relevant. For example, such
exposure pathways when combined with
local exposure pathways could be shown
to be a significant source of exposure.
The analysis of environmental
features identifies potentially vulnerable
Example Data Sources and Uses
(Text Box 3-4)
A recent air screening hazard assessment
(U.S. EPA, 2004c) used data from several regional
and local sources, including emissions data from the
Toxics Release Inventory (TRI), Cumulative
Exposure Project (CEP), and Regional Air Pollutant
Inventory Development System (RAPIDS), as well
as outdoor air monitoring data. These data were
combined and compared to identify any consistently
higher hazard areas, pollutants, and sources. Two
methods were used to estimate relative inhalation
hazards of outdoor air toxics: one for emissions
mass (using TRI and RAPIDS data) and the other
for outdoor concentrations (using CEP and
monitored data). Emissions data enabled sources
and release locations to be identified which
improved the exposure assessment. (Note that TRI
and RAPIDS emissions databases differ: TRI data
are self-reported by facilities, while RAPIDS data
are estimated by states from permits and other
information sources.) Ambient data provided limited
information on spatial distribution, without regard to
specific sources. A weight-of-evidence approach
was used to assess data among different sources.
populations (see Section 3.3.1.2) and the locations where people in a community could
be exposed. Community members may provide valuable input into the locations of such
sites, the relevant activities that may occur there, and the frequency with which a site is
used. This information can provide insights into potential exposures and potential
subpopulations being exposed through use of the location. Cumulative exposure
assessments need to evaluate exposures where community members gather. For
example, community members gather in schools and at playgrounds; an assessment
may need to evaluate exposures in asthmatic children at these locations. Exposures
that occur in and around facilities that care for the elderly and disabled members of a
community may also require evaluation.
3.3.1.2. Receptor Characteristics Considered in Community-based
Cumulative Risk Assessments In community-based cumulative risk assessments,
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3-8
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1 individuals and population groups that could be exposed to contaminants are identified
2 during characterization of the exposure setting. Then, information on the residential
3 locations, activity patterns, and workplaces is collected.
4 Cumulative assessments also examine exposures among both "typical" members
5 of a community and vulnerable populations. Identification of the potentially vulnerable
6 populations is typically developed jointly with dose-response analysts. U.S. EPA's
7 Framework for Cumulative Risk (2003a) adopts "vulnerability" concepts described by
8 Kasperson that encompass the topic of receptor characteristics. Four areas of
9 vulnerability are articulated in the EPA document:
10 differential exposure
11 susceptibility/sensitivity
12 differential preparedness and
13 differential ability to recover.
14 Typical exposure assessments routinely identify some subpopulations that are,
15 or may be, differentially exposed due to close proximity to a source or contaminated site
16 and some exposure assessments also may identify subpopulations that exhibit activity
17 patterns that may result in high exposures to pollutant concentrations. In these cases,
18 detailed recreational uses and activity patterns are based on survey data, especially for
19 fishing and hunting. Such data may be obtained from state or county departments of
20 environment, conservation, natural resources, or parks and recreation. Community-
21 specific surveys can be conducted to fill important gaps. If specific groups are, or could
22 be, affected, they should be consulted to assess possible unique exposures. For
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1 example, Native Americans may gather special vegetation or wildlife for food, medicine,
2 or ceremonies or visit lands that are sacred.
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Exposures in subpopulations exhibiting susceptibility/sensitivity, differential
preparedness, and differential ability to recover are not always considered in typical
exposure assessments but are given special consideration in a cumulative assessment.
Exposures may be calculated separately for identified subpopulations with specific
receptor characteristics to yield more realistic exposure estimates for those
subpopulations. The receptor population characteristics considered in a cumulative
assessment may include diverse factors such as genetic susceptibility, age, stress,
disease state, economic status, ethnicity, health status, availability of health care, etc. It
is particularly important to evaluate whether some potentially susceptible populations
are exposed to high levels of pollutants. Examples of information resources that can be
reviewed to support this evaluation are highlighted in Text Box 3-5. Pregnant women
can represent a subgroup of special concern due to sensitivity for potential effects to the
developing fetus. For example, the fetal nervous system is considered the most
sensitive target of
methylmercury and the U.S.
EPA's reference dose (RfD)
has been developed based on
neurological effects associated
with intrauterine exposures
(U.S. EPA, 2001 b).
Information for Susceptibility Assessment
(Text Box 3-5)
Type of Information
Demographic data
Subpopulation groups
Locations (e.g., schools,
Resources
U.S. Census Bureau (www.census.gov)
EPA report: Sociodemographic Data
Used for Identifying Potentially Highly
Exposed Populations (U.S. EPA, 1999c)
Plat maps, city and county health
hospitals, nursing homes) departments
Exposure data (e.g., blood State registries, county and city health
lead levels) department reports
Cancer registries Centers for Disease Control (national data
and links to state cancer registries,
www.cdc.gov/cancer/npcr/statecon.htm)
Other health effect State registries of birth defects, asthma
registries
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1 Young children can be more biologically sensitive to many chemicals because
2 certain protective body functions (e.g., liver enzyme production) are developing during
3 the early stages of life. They also can incur higher exposures than the general
4 population because of their different behaviors (e.g., pica or recreational swimming) and
5 because their doses per unit body weight are higher than those of adults. Following the
6 1997 Executive Order for the protection of children from environmental health and
7 safety risks, the Agency continues to develop approaches to account for differences
8 such as body weights and toxicokinetics so risks to infants and children can be
9 evaluated in further detail, whenever there appears to be a greater concern for adverse
10 health effects than for the general population.
11 People with higher than average biological sensitivity to environmental stressors
12 also include allergies and others with pre-existing medical conditions (e.g., asthma),
13 especially when these individuals are housed together such as in hospitals or nursing
14 homes. Some state health departments have established health registries for
15 conditions such as asthma and for exposure measurements such as blood lead levels.
16 These agencies can be consulted to determine if any clusters of affected individuals live
17 in the community. Elderly and immunocompromised populations can be more
18 susceptible to environmental exposures due to their health status. Other factors, like
19 socioeconomic status, can affect access to health care or contribute to poor diet. Thus,
20 poverty could indicate a potential increased susceptibility or biological sensitivity.
21 3.3.1.3. Cumulative Exposure Assessment Practices for Receptors Once
22 the land uses and sources of pollutants in the community have been identified (Section
23 3.3.1.1), it is common practice in exposure assessments to identify representative
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1 default receptors, such as a current or future resident, trespasser, home gardener, and
2 recreational angler. Exposures among these default receptors are subsequently
3 estimated. The exposure factors associated with these receptors (e.g., quantities of
4 homegrown vegetables consumed daily) can be obtained from sources such as the
5 Exposure Factors Handbook (U.S. EPA, 1997c).
6 In typical assessments, the individual receptors are located in close proximity to
7 a pollution source (e.g., at the fenceline, the nearest housing development, or the
8 closest fishable lake). Cumulative assessments may evaluate other receptors who are,
9 or could be, subjected to higher than average exposures, including people living near
10 multiple sources of pollution (e.g., waste facilities, urban industrial areas, or
11 transportation corridors) as well as residents of older homes with lead-based paint, and
12 people whose jobs or recreational activities can cause specific chemical exposures or
13 increased opportunities for exposure. Cumulative assessments also evaluate
14 exposures in vulnerable populations (Section 3.3.1.2). If these screening practices do
15 not reveal exposures of concern, then the receptors can be dropped from the analysis,
16 after consultation with the dose-response analyst.
17 If the exposure levels are deemed to be of concern, then demographic data can
18 be used to estimate the typical ages and ethnicity of these hypothetical community
19 members who may be differentially exposed to pollutants from a source. These data
20 may be used to refine the exposure estimate (see Section 3.3.3).
21 3.3.2. Exposure Pathways and Routes. An exposure pathway tracks how chemicals
22 are transported from a source to an exposed person or subpopulation. An analysis of
23 the exposure routes addresses how the contaminant can enter the body. The basic
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1 process elements are summarized in Text Box 3-6. This section identifies
2 considerations for how exposure pathways can be evaluated in an assessment.
3 The overall analysis plan for a risk assessment typically describes the general
4 data, models, and assumptions that will be
5 used to characterize exposure (Chapter 2).
6 A main emphasis for cumulative
7 assessments is on how sources,
8 chemicals, media, and receptors can be
9 grouped for joint pathway analyses.
10 Various examples are offered in this
Exposure Pathway Elements (Text Box 3-6)
Locations of sources, mechanisms by which
chemicals could be released from sources, and
identification of receiving environmental media
Transport of chemicals in the receiving media and
movement from receiving media into other
environmental media (e.g., from soil to air or
water), degradation and transformation (change in
speciation, sorption, etc.)
Estimated concentrations of contaminants at
points of potential human contact (i.e., exposure
points) and associated routes of exposure (e.g.,
incidental ingestion of soil, inhalation of airborne
chemicals, or drinking water)
11 section, with additional detail for one pathway (air) offered in Section 3.4 to illustrate
12 how cumulative assessment issues can be considered.
13 3.3.2.1. Sources and Fates of Chemicals and Chemical Mixtures
14 Cumulative assessments of environmental contaminants identify all sources being
15 considered and all potential exposure pathways for each medium of exposure. The
16 pathways are then reviewed to determine if they are relevant to the study. The
17 completeness of each exposure pathway is considered in determining whether it should
18 be included in the evaluation. A pathway is complete when these four components are
19 present:
20 a source and a mechanism of contaminant release
21 an environmental transport medium
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1 a point of human contact with the contaminated source or transport medium and
2 a route of exposure at that point.
3 Criteria for inclusion are typically developed after discussion with the dose-response
4 analyst so that resources can be efficiently focused on toxicologically relevant
5 exposures. The pathways selected for inclusion are then characterized, and the
6 exposures from all relevant pathways are jointly evaluated for the cumulative
7 assessment.
8 In cumulative exposure assessments, an evaluation of environmental
9 transformation of each chemical under consideration is a critical component for each
10 selected pathway. While environmental transformation is recognized as a major factor
11 for organic compounds, some metals can be altered in the environment, e.g., via
12 methylation by biological processes, which can change bioavailability and toxicity.
13 Environmental transformation is a critical consideration when addressing
14 exposures to environmental mixtures. For organic chemicals such as common
15 solvents, environmental transformation or degradation can produce a number of new
16 chemicals of potential concern in addition to those originally released. While some
17 degradation products are less toxic than their parent compounds, this is not always the
18 case. Thus, it is helpful to review historic operations records and other readily available
19 data to consider additional contaminants that might warrant consideration. To illustrate,
20 the solvent tetrachloroethylene is a common groundwater contaminant, and this volatile
21 organic compound is converted over time to the more toxic vinyl chloride. Key
22 properties of selected organic chemicals and degradation products are illustrated in
23 Table 3-1 to show that data are available to characterize cumulative exposures.
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TABLE 3-1
Properties of Selected Organic Chemicals and Degradation Products to Demonstrate Availability of Such Information*
Chemical
Key
Degradation
Products
General
Fate/Persistence
Environmental Half-
Life
Log Kow
(unitless)
Log Koc
(unitless)
Indicative U.S.
Concentration
IRIS
Toxicity
Value
Toxicity
Relative
to Parent
Pesticides
Aldrin
Chlordane
Dieldrin
Not applicable,
is not typically
transformed in
the
environment
Binds tightly to soil
and does not leach
readily, so is not
usually found in
groundwater;
moderately
persistent;
bioaccumulates
As foraldrin, but
very persistent;
As fordieldrin, and in
surface water will
volatilize and adsorb
to sediments
Soil: 53-1 09 days
(converts fairly
rapidly to dieldrin)
Soil: 5 years
Air: 2.8 days
(mean);
water: 239 days;
soil: 4.2 years
(mean) (U.S. EPA,
2000b)
6.50
(bioaccumu-
lation likely)
6.2
(bioaccumu-
lation likely)
5.54
(bioaccumu-
lation likely)
7.67
(expected
to strongly
adhere to
soil)
6.67
(expected
to strongly
adhere to
soil)
4.06
(mean)
(expected
to adhere
to soil)
Air: 0.00003 ppb
(mean); sediment:
1.3 ppb (mean) Gulf
Coast
Air: 0.0001 ppb
(mean);
soil: 1-49 ppb
(mean);
sediment: 3.2 ppb
(mean) Gulf Coast)
Surface and ground
water:
0.1 ppb (mean) in
specific areas; soil:
<1 ppb -141 ppm
RfD:
0.00003
RfD,:
0.00005
RfD:
0.0005
60%
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TABLE 3-1 cont.
Chemical
DDT
Key
Degradation
Products
ODD
DDE
General
Fate/Persistence
Binds tightly to soil
and does not leach
readily, so is not
usually found in
groundwater; very
persistent;
bioaccumulates
As for DDT
As for DDT
Environmental Half-
Life
Air: 37 hours;
soil: 25 years
(mean) but varies
widely, depending
on soil type and
temperature
Air: 30 hours;
soil: 10-15 years but
varies widely,
depending
on soil type and
temperature (CDC,
2003)
Air: 17 hours;
soil: >20 years
(mean) but varies
widely, depending
on soil type and
temperature
Log Kow
(unitless)
6.79
(bioaccumu-
lation likely)
5.87
(bioaccumu-
lation likely)
6.00
(bioaccumu-
lation likely)
Log Koc
(unitless)
5.35
(expected
to strongly
adhere to
soil)
5.19
(expected
to strongly
adhere to
soil)
5.19
(expected
to strongly
adhere to
soil)
Indicative U.S.
Concentration
Ambient water:
0.001 ppb (median);
sediment: 0.1 ppb
(median); soil:
4.67 ppb (geometric
mean) mid-central
United States
Ambient water:
>0.001 ppb
(median);
sediment: 0.2 ppb
(median); soil:
1 .20 ppb (geometric
mean) mid-central
United States
Ambient water:
0.001 ppb (median);
sediment: 0.1 ppb
(median); soil: 3.75
ppb (geometric
mean) mid-central
United States
IRIS
Toxicity
Value
SF:
0.34
RfD:
0.0005
SF:
0.24
SF:
0.34
RfD:
0.0005
Toxicity
Relative
to Parent
70%
Same as
parent
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TABLE 3-1 cont.
Chemical
Key
Degradation
Products
General
Fate/Persistence
Environmental Half-
Life
Log Kow
(unitless)
Log Koc
(unitless)
Indicative U.S.
Concentration
IRIS
Toxicity
Value
Toxicity
Relative
to Parent
Solvents
Carbon
tetrachloride
Chlorine
(in air)
Chloroform
(in water)
Stable in air;
volatilizes rapidly into
air from soil and
surface water; very
little binds to soil
(most leaches into
groundwater); stable
in air; does not
bioaccumulate
In air and water,
reacts with water to
form hypochlorous
acid and hydrochloric
acid; volatilizes from
soil; persists in
groundwater; does
not bioaccumulate
Persistent in
groundwater; does
not bioaccumulate
Air: 330 years;
groundwater:
2.2 days (mean;
with minerals);
surface water:
9 months (mean for
aerobic conditions),
17.5 days (mean for
anaerobic
conditions);
soil: 6-12 months
Surface water:
3 hours (mean)
Surface water:
44 days
2.64
(not likely to
bio-
accumulate)
0.85
(not likely to
bio-
accumulate)
(TCEQ,
2003)
1.97
(not likely to
bio-
accumulate)
2.04
(expected
to move
with
ground-
water)
Not
identified
(organic
carbon in
soil does
not appear
to play a
major role)
2.03
(mean)
(expected
to move
with
ground-
water)
Air: 0.168 ppb
(mean); drinking
water: 0.5 ppb
(mean), for the 3%
of samples with
detectable levels
Air: 807 ppb
(mean)
Drinking water:
23 ppb (mean)
RfD:
0.0007
RfD:
0.1
RfD:
0.01
0.7%
7%
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TABLE 3-1 cont.
Chemical
Tetrachloro-
ethylene
Key
Degradation
Products
1,1-
Dichloroethylene
General
Fate/Persistence
Volatilizes rapidly
from surface water
and soil; leaches
rapidly from soil to
groundwater; does
not bioaccumulate
Volatilizes relatively
quickly from surface
water and soil; moves
with groundwater;
stable in water; does
not bioaccumulate
Environmental Half-
Life
Air: 134 days
(mean);
groundwater:
estimates vary from
9 months to 1 billion
years (hydrolyzes),
differences likely
due to errors in
extrapolation and
presence/absence
of microbes; surface
water:
volatilization half-life
is <4 hours;
soil: volatilization
half-life is 2 to
16 days
Air: 2.5 days (mean);
surface water:
4 days (mean),
volatilizes
Log Kow
(unitless)
3.40
(not likely to
bio-
accumulate)
1.3
(not likely to
bio-
accumulate)
Log Koc
(unitless)
2.5 (mean)
(expected
to
moderately
bind to soil
and
moderately
move with
ground-
water)
1.81
(not
expected
to bind to
soil;
expected
to move
with
ground-
water)
Indicative U.S.
Concentration
Air: 0.50 ppb
(mean) including
areas close to
emission sources;
drinking water:
0.75 ppb (median)
from ground water,
for the 8% of
samples with
detectable levels;
sediment: 5 ppb
(median)
Air: 4.6 ppb
(mean);
drinking water:
0.6 ppb (mean) for
the 3% of samples
with detectable
levels
IRIS
Toxicity
Value
RfD:
0.01
RfD:
0.05
Toxicity
Relative
to Parent
20%
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Does Not Constitute EPA Policy
3-18
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TABLE 3-1 cont.
Chemical
Key
Degradation
Products
trans-1 ,2-
Dichloroethylene
(cis- degradation
products also
form; trans- is
shown here
because an RfD
exists for this
compound)
Trichloro-
ethylene
General
Fate/Persistence
Volatilizes quickly
from surface water
and soil; moves with
groundwater; does
not bioaccumulate
Volatilizes quickly
from surface water;
binds to soil;
persistent in
groundwater; does
not bioaccumulate
Environmental Half-
Life
Air: 8.5 days (mean);
groundwater:
30.5 weeks (mean);
surface water:
4.6 hours (mean)
(volatilizes)
Air: 7 days;
groundwater:
estimates vary
widely from
10 months to
1 million years
(hydrolyzes),
differences likely
due to errors in
extrapolation and
presence/absence
of microbes);
mean volatilization
half-life in surface
water is 2 hours
from modeled data,
and 20 days from
measured data;
Log Kow
(unitless)
2.09
(not likely to
bio-
accumulate)
2.42
(not likely to
bio-
accumulate)
Log Koc
(unitless)
1.56
(not
expected
to bind to
soil;
expected
to move
with
ground-
water)
2.35
(mean)
(expected
to
moderately
bind to soil
and
moderately
move with
ground-
water)
Indicative U.S.
Concentration
Air: 0.037 ppb
(median);
drinking water/
groundwater: 173
ppb (mean)
Air: 0.56 ppb
(mean) including
areas close to
emission sources;
drinking water:
1 ppb (median)
from groundwater,
for the 10% of
samples with
detectable levels;
sediment: <5 ppb
(median)
IRIS
Toxicity
Value
RfD:
0.02
N/A
Toxicity
Relative
to Parent
50%
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Does Not Constitute EPA Policy
3-19
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TABLE 3-1 cont.
Chemical
Trichloro-
ethylene
Key
Degradation
Products
Vinyl chloride
1,1-
Dichloroethylene
trans-1 ,2-
Dichloroethylene
(cis- also forms)
Vinyl chloride
(in water)
General
Fate/Persistence
Volatilizes quickly
from surface water
and soil; moves with
groundwater; does
not bioaccumulate
As for
tetrachloroethylene
As for
tetrachloroethylene
As for
tetrachloroethylene
As for
tetrachloroethylene
Environmental Half-
Life
Mean volatilization
half-life is 29 hours
in surface water and
12 hours in soil
Log Kow
(unitless)
1.36
(not likely to
bio-
accumulate)
Log Koc
(unitless)
1.99
not
expected
to bind to
soil;
expected
to move
with
ground-
water)
Indicative U.S.
Concentration
Air: 5 ppb (mean)
neighborhood close
to hazardous waste
site; drinking water:
detected in 0.74%
of groundwater
supplies, maximum
concentrations of
1.1 and 8.4 ppb, for
random and
nonrandom sites,
respectively
IRIS
Toxicity
Value
RfD:
0.003
N/A
RfD:
0.05
RfD:
0.02
RfD:
0.003
Toxicity
Relative
to Parent
333%
0.6%
1 .5%
10%
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Does Not Constitute EPA Policy
3-20
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TABLE 3-1 cont.
Chemical
Key
Degradation
Products
General
Fate/Persistence
Environmental Half-
Life
Log Kow
(unitless)
Log Koc
(unitless)
Indicative U.S.
Concentration
IRIS
Toxicity
Value
Toxicity
Relative
to Parent
Nitroaromatic Compounds
2,4,6-
Trinitrotoluene
Nitrobenzene
Can leach relatively
quickly from soils to
groundwater; can
bioaccumulate but
not to a large extent
Leaches to
groundwater; does
not bioaccumulate
Air: 7.5 hours
(mean);
surface water:
43 minutes (mean),
catalyzed by
sunlight;
groundwater:
6 months or longer
(mean), varies;
soil: 3.5 months
(mean)
Soil: 7 days
(aerobic
biodegradation) or
22 days (anaerobic
degradation);
surface water:
40 days
2.2 (mean)
(not likely to
bio-
accumulate)
1.87
(not likely to
bio-
accumulate)
2.76
(mean)
(tends to
moderately
bind to soil
and
moderately
move with
ground-
water
1.56
(not
expected
to bind to
soil;
expected
to move
with
ground-
water)
Groundwater:
1-320 ppb in
contaminated areas;
soil: 24,000 ppm
(mean) in highly
contaminated areas
Air: 0.12 ppb
(mean)
RfD:
0.0005
RfD:
0.0005
Same as
parent
2
3
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Does Not Constitute EPA Policy
3-21
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1 TABLE 3-1 cont.
2
3 * Organic compounds illustrated here are often found at Superfund sites; others also commonly found include acetone, benzene, 2-butanone,
4 chloroform (included above as a degradation product), 1,1-dichloroethene, methylene chloride, naphthalene (designated by EPA as "pending" for
5 this list), pentachlorophenol, polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs) (designated by EPA as "pending" for this
6 list), toluene, vinyl chloride, and xylene (designated by EPA as "pending" for this list). (Source: EPA's Common Chemicals Found at Superfund
1 Sites, see http://www.epa.gov/superfund/resources/chemicals.htm.) Trinitrotoluene is also included here because of its presence at certain federal
8 sites. Much of the fate information and environmental levels are from the ATSDR toxicological profiles (see below). Toxicity values are oral
9 reference doses (RfDs) as mg/kg-day and oral slope factors (SFs) as per mg/kg-day from the Integrated Risk Information System (IRIS) current
10 through November 2005 (U.S. EPA, 2005c). N/A = not available. Gray shading indicates the entry is not applicable because this is the parent
11 compound.
12
13 Environmental half-life is used to generally represent the time it takes for the initial amount of a chemical to be reduced by half in the indicated
14 medium. The Kow indicates whether a chemical is hydrophilic and will be predominantly found in water, or is lipophilic and will be found in fatty
15 tissue of animals or associated with other organic materials in aquatic systems. The Kow values are presented as logarithms because this
16 measure varies widely across compounds. A log Kow of 0 indicates an equal affinity for lipids and water. A high log Kow indicates the chemical is
17 not very soluble and will not move with water; a low log Kow indicates the chemical is very soluble and will move with water (it also indicates the
18 chemical will be readily absorbed from the gastrointestinal tract after being ingested or from the lungs after being inhaled). As the log Kow
19 increases, the solubility in lipids increases, which means the potential to bioconcentrate in aquatic organisms increases; when the log Kow
20 reaches 5 to 6 it indicates the chemical can bioconcentrate significantly in aquatic organisms, but as it increases above 6, the chemical is less
21 likely to bioconcentrate, approaching no bioconcentration at a log Kow of 12. (Source: EPA Pollution Prevention (P2) Framework, Physical and
22 Chemical Properties Models, see http://www.epa.gov/oppt/p2framework/docs/pchem.htm.)
23
24 The Koc indicates how the organic compound will partition between water and the organic carbon portion of soil/sediment and biota. The Koc
25 indicates whether or not a chemical will move with ground water. These are also presented as logarithms because this measure also varies
26 widely across compounds. A high log Koc (e.g., 3.5 or higher) indicates the chemical is likely to sorb to soils, sediments, or sludges and is less
27 likely to move with surface water or groundwater. A low log Koc (e.g., 2.4 or below) indicates the chemical is not likely to sorb to soils, sediments,
28 or sludges, and thus is more is likely to move with water. Contaminants with a log Koc between 2.4 and 3.5 likely partition to soils, sediments, or
29 sludges and surface water or groundwater. (Source: EPA Pollution Prevention (P2) Framework, Environmental Fate Models, see
30 http://www.epa.gov/oppt/p2framework/docs/envfate.htm).
31
32 (Sources: ATSDR, 1990, 1994a,b, 1995, 1996, 1997a,b,c,d, 2002a,b; CDC, 2003; U.S. EPA, 1999b,d, 2000b, 2001 c, 2003d, 2005d,e; IPCS,
33 1982)
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1 When evaluating environmental fate and transport across media for these
2 assessments, it is important, but not mandatory2, that mass should be maintained when
3 predicting concentrations of parent chemicals and degradation products. Chemical
4 speciation can also be important for cumulative risk assessments. Different oxidized or
5 reduced forms of metals react differently in the environment and have different
6 toxicities; trivalent and hexavalent chromium provide a good example, with the latter
7 being much more toxic. Thus, it is important to characterize the soil and water
8 chemistry at sites to assure that appropriate physicochemical characteristics are being
9 reflected in the assessment. In evaluating combined chemicals, care must be taken to
10 assure that assumptions are internally consistent among all chemicals within a given
11 setting. For example, assuming the presence of a reduced form of a metal may be
12 incorrect, especially in an aerated environment where other chemicals are assumed to
13 be in the oxidized form.
14 For radioactive compounds, the natural physical decay process causes
15 radionuclides to change over time. For these contaminants, natural attenuation
16 (radioactive decay) will reduce contaminant levels over time. The basic concepts of
17 half-life and natural attenuation over time are illustrated in Figure 3-2 (from Brown,
18 1999, as cited in U.S. DOE, 1999). Table 3-1 shows that the half-life for tritium is
19 approximately 123 years. Figure 3-2 illustrates natural attenuation over time showing
20 that ambient levels of tritium are predicted to be approximately 10% of original levels
21 after 50 years. The parallel evaluation for nonradioactive chemicals reflects
22 environmental half-life.
23
2 Some useful models do not maintain mass balance.
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2
3
4
5
3500
3000
2500
Global
tritium 2000 -
inventory
1500
1000
500
0
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95100
Elapsed time from 1963 (years)
8
9
10
FIGURE 3-2
Illustration of Global Background from Atmospheric Fallout of Tritium
Source: Brown (1999)
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3-24
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1 Once released from different sources in various forms, chemicals can migrate to
2 other locations and media. The degree to which a particular chemical substance favors
3 a given transport path depends on the form of the chemical released, its physical state,
4 and the nature of any particulate matter to which it might adsorb upon or following
5 release. These pathways are generally predictable from the known release processes
6 and expected physical forms of the chemicals.
7 The transport and fate of mixtures of chemicals released to the environment are
8 not random but can be predicted to varying degrees by considering a number of factors
9 related to the release, migration, and persistence of their constituents. Following
10 release from a source, mixture components are typically differentially transported
11 through the environment. These chemical mixtures are subject to transformation
12 reactions in the environment which can change their composition. Some chemicals are
13 degraded, while others are formed through various environmental reactions. Changes
14 in the mixture composition can be specific to the environmental medium. It is important
15 to document these changes in the mixture composition. (The differential nature of
16 transport can be an important consideration in the toxicity of a mixture because the
17 composition of the mixture to which a community is exposed could be very different
18 from the mixture that has undergone toxicological testing. See discussion of sufficient
19 similarity in U.S. EPA, 2000a.3) It is useful to consider three types of transfers that can
20 occur between environmental compartments:
3 Sufficient similarity is a key concept for evaluation of a complex mixture. It is applied when inadequate
toxicity data are available directly on a mixture of concern, but toxicity data can be acquired on a mixture
composed of similar chemical components in similar proportions. If the two mixtures are judged to be
sufficiently similar, then the toxicity data for the latter can be used as surrogate data in conducting a
quantitative risk assessment for the mixture of concern. The U.S. EPA has proposed this general
concept for the evaluation of complex mixtures in its risk assessment documentation (U.S. EPA, 2000a).
The exposure analyst and dose-response analyst should jointly discuss this issue.
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1 differential transfer between different abiotic media (e.g., soil and surface water)
2 differential transfer between abiotic and biotic media and
3 differential transfer between different biotic media.
4 Mixture components can be differentially transferred between abiotic media. For
5 example, drinking water disinfection by-products (DBFs) such as chloroform and
6 bromodichloromethane are highly volatile; others, such as monochloroacetic acid, are
7 not (U.S. EPA, 2003b). Consequently, the composition of a DBP mixture in the indoor
8 air differs considerably from the DBP mixture in a glass of water. The insecticide
9 toxaphene provides a second example. Technical grade toxaphene, which contains
10 over 670 chemicals, was one of the most heavily used insecticides in the United States
11 until 1982 when it was canceled for most uses. It was used primarily in the southern
12 United States to control insect pests on cotton and other crops. Some components of
13 technical toxaphene may volatilize to air; others do not dissolve well in water. The
14 composition of the toxaphene mixture will differ depending on whether it is measured in
15 soil at a hazardous waste site, the air around the site, or sediment at the bottom of lakes
16 or streams near the site (ATSDR, 1996).
17 Mixture components can be differentially transferred between abiotic and biotic
18 media. For example, the Site-Specific Assessment Procedures volume in the review
19 draft Exposure and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-
20 Dioxin (TCDD) and Related Compounds (U.S. EPA, 2003c) provides methods for
21 predicting differential uptake of different dioxin congeners from the atmosphere into
22 plant tissue and the selective retention of dioxin congeners in fish adipose tissues.
Review Draft: Do Not Cite or Quote 3-26
Does Not Constitute EPA Policy
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1 Some components of technical toxaphene have been measured in shellfish and fish
2 (ATSDR, 1996).
3 Mixture components can be differentially transferred between biotic media. For
4 example, the Site-Specific Assessment Procedures volume in the review draft Exposure
5 and Human Health Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and
6 Related Compounds (U.S. EPA, 2003c) provides methods for predicting the selective
7 uptake and retention of different dioxin congeners from grass into the adipose tissues of
8 grazing cattle.
9 3.3.2.2. Grouping Chemicals for Cumulative Risk Analysis Mixtures
10 occurring in a community may originate from different sources. In this section, a set of
11 six tables is provided that illustrates how information about sources of chemical
12 pollutants, chemical properties, and fate can be organized to guide chemical groupings
13 for cumulative risk assessments in contaminated communities. These tables provide
14 context regarding the normal uses of chemicals often found in mixtures and their
15 behavior in the environment that leads to their coexistence in media to which people
16 can be exposed. The grouping of the chemicals should be based on the potential for
17 their co-occurrence in each compartment/medium, potential for interactions affecting
18 transformation, and potential for co-occurrence and interaction along each transport
19 pathway between media. Figure 3-3 provides an overview of how this information might
20 be organized according to media and the processes of fate and transport.
21 While chemicals can be easily grouped based on common sources and releases
22 (e.g., chemicals in diesel exhaust), the usefulness of groupings for various chemical
23 classes can be improved based on typical primary release mechanisms that would be
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Does Not Constitute EPA Policy
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Pollution Source
Pollution Source^
Pollution Source,.
Transformation
Transformation
* Transformation refers to a group of
processes that can act to change the
composition of a mixture.
** Intracompartment transport refers to the
processes that move a mixture through an
individual compartment (e.g., turbulence and
wind will move a mixture through the
atmosphere) and intercompartment transport
refers to processes that move a chemical
mixture from one medium to another.
Receiving Media
Intracompartment*
Transport
Intercompartment Transport*
Other Media
Concentrations at
Points of Exposure in
Multiple Media
Human Activity Patterns
Exposed
Subpopulations
Toxi co kinetics
Target Tissue Doses
FIGURE 3-3
Approach for Estimating Exposure in Cumulative Risk Assessments
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Does Not Constitute EPA Policy
3-28
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1 expected to control initial contamination and migration behavior in the environment, as
2 illustrated in Table 3-2. Released chemicals can disperse quickly over a fairly wide area
3 by convection (such as via wind or surface water flow), and they can also migrate
4 following waste placement. The dominant processes at a given location determine what
5 will be the "receiving medium" into which a particular class of chemicals is introduced
6 and from which they can migrate.
7 Contaminant properties relevant to fate and transport include volatility, water
8 solubility, and partition coefficients for:
9 water and available organic phases (as represented by the octanol-water
10 partition coefficient, Kow)
11 water and solid phases (Kd) and
12 water and air (Henry's constant, KH).
13 Additional properties for soil and sediment include the fraction of organic carbon (foe)
14 and the clay content, which indicates the amounts and types of sorption sites available.
15 Table 3-3 can be used to group chemicals per their expected general partitioning in
16 media based on well-known physical constants for the chemicals and media. Chemical-
17 specific soil-water partition coefficients in various soil textures can be displayed to help
18 evaluate possible chemical grouping based on similar mobility, as shown in Figure 3-4.4
19 The soil type, geochemistry, and other data should be evaluated in determining
20 generally appropriate values, and site-specific studies are important to the selection of
21 the actual values for key contaminants.
22 To illustrate how grouping tables can be applied to assess multiple chemicals in
23 different classes for a cumulative risk assessment, an example is offered for PCBs
4 Note that the Kd values overlap given the wide range of soils used to develop the figure. Kd values for
specific types of soil or additional data may be needed to implement this grouping step.
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TABLE 3-2
Grouping Chemicals by Common Migration Behavior
Migration Initiation
Process
Volatilization to air
Dissolution in
groundwater
Dissolution in surface
water
Particulate emissions
from combustion
(stacks)
Gaseous emissions
from combustion
(stacks)
Dust-blown migration
Waste placement
Leaching to
groundwater
Organic Chemicals
Chlorinated solvents
Petroleum-based solvents
Fuels
Chlorinated solvents
Aromatic hydrocarbons
(BTEX)
Pesticides
Phenols, amines, ethers,
alcohols, organic acids
Products of incomplete
combustion (PICs)
- PCBs, PAH, dioxins,
furans
Light hydrocarbons
Nonvolatile organics
- PAHs, PCBs, dioxins
All listed above
Chlorinated solvents
(DNAPLs)
Inorganic Chemicals and
Gases
C\2, ammonia, tritium, S02,
NOX, CO, C02
Cations
Anions
Cations and anions (e.g.,
perchlorates)
Heavy metals
S02, NOX, CO, ammonia
Heavy metals
All listed above
NA
Heavy metals are as indicated in Table 3-1 . Acronyms not previously defined (in
Table 3-1) are: C0=carbon monoxide; C02=carbon dioxide; DNAPLs=dense non-
aqueous phase liquids; and S02=sulfur dioxide.
2
3
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Does Not Constitute EPA Policy
3-30
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TABLE 3-3
Grouping Chemicals by Environmental Fate Measures3
Environmental
Compartment
Persistence
(environmental half life)
Environmental Partitioning
(equilibrium-based)13
Mobility
(convection- and dispersion-based)
Organic matter in soil
and sediments,
soil organisms
High for:
High Kow/Kd
Low biodegradability
Low for:
High Kow/Kd
High biodegradability
Presence favored by:
High Kow/Kd
High persistence
High binding for:
High-Kow/Kd organics and inorganics
Low binding for:
Low-Kow/Kd organics and inorganics
Soil inorganic phase
High for:
High-Kd inorganics,
Low-Ksp inorganics
(including metals that form
complexes in soil)
Low for:
Low Kow/Kd
organics/inorganics
Presence favored by:
High-Kd and low-Ksp
inorganics
High mobility for:
Cations, anions, water- soluble organics
(low Kow/Kd)
High-Ksp colloids
Low mobility for:
High-Kow/Kd organics
High-Ksp solids
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Does Not Constitute EPA Policy
3-31
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TABLE 3-3 cont.
Environmental
Compartment
Persistence
(environmental half life)
Environmental Partitioning
(equilibrium-based)13
Mobility
(convection- and dispersion-based)
Surface water
Higher for:
Insoluble (high Kow)
Non-photodegradable
Non-biodegradable
Lower for:
Water soluble (low Kow)
Volatile (low KH)
Photodegradable
Biodegradable
Presence favored by:
Low Kow/Kd
High KH
(low volatility to air)
High-Ksp inorganics
High transport for:
High solubility
Low volatility
Low transport for:
Precipitates (low Ksp)
Low solubility
(high Kow)
Biodegradable
Photodegradable
Groundwater
Higher for:
Low biodegradable
DNAPL-forming
Lower for:
Biodegradable
Highly soluble (low Kow/Kd)
LNAPL-forming
Presence favored by:
High solubility
(low Kow/Kd)
Ionic forms
(cations and anions)
High-Ksp inorganics
High mobility for:
Low Kow/Kd organics and inorganics
Ionic forms
Low mobility for:
High Kow/Kd organics and inorganics
Inorganic solids
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Does Not Constitute EPA Policy
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TABLE 3-3 cont.
Environmental
Compartment
Persistence
(environmental half life)
Environmental Partitioning
(equilibrium-based)13
Mobility
(convection- and dispersion-based)
Air
Higher for:
Low photodegradable
Low reaction rate with
hydroxyl radical & other
free radicals
Low wash out rate (low KH)
Gas phase
Lower for:
Photodegradable
High reaction rates
High wash out (high KH)
Particulate phase
Presence favored by:
High volatility substances
(gases and low boiling point
liquids)
High volatility from water
(low KH)
High mobility for:
Gas phase
High persistence
Small-particle bound
Low mobility for:
Low persistence
Large-particle bound
Aquatic and terrestrial
biota
Higher for:
Lipid soluble (high Kow)
Non-biodegradable
Low depuration rates
Lower for:
Water soluble (low Kow)
High depuration rates due to:
enzyme-oxidizable and/or
forms complexes with GHS,
other agents
Presence favored by:
High organic solubility (high
Kow)
High BCF
Persistence in biota/prey (high
BAF)
Mobility enhanced by:
High persistence in biota
High vegetative uptake factors (high
Kow), specific binding factors)
Mobility reduced by:
High degradation rates
High elimination rates
Low uptake factors
1 a Acronyms not previously defined: BAF=bioaccumulation factor, BCF=bioconcentration factor, GHS=glutathione, LNAPL=light non-
2 aqueous phase liquid, Kd=soil/water partition coefficient, KH=Henry's constant (water/air distribution constant), Kow=octanol/water
3 partition coefficient (octanol approximates soil organic matter, or biomass), Ksp=solubility product constant for inorganic complexes.
4 b"Presence favored by" indicates that concentrations would be relatively higher compared to adjacent compartments, i.e., activity
5 coefficients for the substances are relatively low in the given compartment/medium.
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1
2
4
5
6
1
6
5
4
logKd
(L/kg) 3
* median
2
1
0
-1
i
i
t
:
i
t
i
i
i
Chromium: Silver
hexavalent
Cadmium Nickel Mercury Chromium: Lead
trivalent
9
10
11
12
13
14
15
FIGURE 3-4
Assessing Relative Mobility in Soil to Support Chemical Groupings
(Source: represents soil-water partition coefficient data from U.S. EPA, 1999d)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
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1 (representing a group of congeners). First, the properties for PCBs are discussed, and
2 then other chemicals and chemical classes that might be included in the PCB groups
3 based on their similar physical-chemical properties are identified. The general grouping
4 information in Table 3-3 can be combined with illustrative parameter information in
5 Tables 3-4 and 3-5, and from this information, the persistence of PCBs in soil organic
6 matter would be expected to be high given the high Kow values and low
7 biodegradability. Also, concentrations would likely be high in soil organic matter
8 compared to other media such as soil inorganic matter or soil pore water, again
9 because high Kow values indicate higher partitioning to organic phases. Their mobility
10 in soil would be controlled by two processes: dissolution in water (e.g., moving laterally
11 as surface transport or generally downward with percolating water) and retardation due
12 to sorption onto inorganic soil particles (assuming foe is low for subsurface soils, as the
13 near-surface soil horizons contain the bulk of organic matter that has not yet been
14 mineralized).
15 In this example, groundwater concentrations of PCBs are expected to be very
16 low based on likely partitioning of PCBs to solids in the soil. If some PCB congeners
17 could migrate through the soil and reach the groundwater, this would lead to dilute PCB
18 congener concentrations in this medium. The concentrations reaching groundwater
19 would likely be very low, perhaps undetectable by usual measurement methods. In
20 addition, the congener composition would change during transport, in accordance with
21 the varying solubility and sorption properties of compounds with different levels of
22 chlorination (e.g., more highly chlorinated compounds are less soluble). Additional data
23 show that PCBs degrade slowly in soils.
24
Review Draft: Do Not Cite or Quote 3.35
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TABLE 3-4
General Grouping Categories for Key Fate Parameters3
Parameter13
Partition coefficient: Kow
Solubility product: Ksp
Water solubility: Sw (ppm)
Henry's constant: KH (mol/L*atm)
Vapor pressure: VP (mm Hg)
Melting point : MP (°C)
Boiling point: BP (°C)
General Categories and Examples
Low | Medium | High
<100
<1 xlO'50
<10
O.01 to 1
<0.001
<0
<50
100 to 10, 000
1 x 1Q-10to1 xlO'50
10 to 1000
1 to 1000
0.001 to 1
0 to 100
50 to 300
>1 0,000
>1 x 10'10
>1000
>1000
>1
>100
>300
2 a General ranges indicated in this table illustrate the principles outlined in Table 3-3;
3 other general bounds would also be appropriate. For example, a Ksp of 10~5 could be
4 used as a delineator for "readily soluble" for one-molar electrolyte solutions, while formal
5 water solubilities <0.003 mole/liter could indicate the compound is "not readily soluble."
6 b Kow is the partition constant between water and octanol, which represents a generic
7 "organic" phase; this coefficient applies mainly to organic chemicals (those containing
8 carbon). Ksp is the solubility product of inorganic compounds, which describes the
9 equilibrium between the (excess) solid form and dissolved (or solvated) ions, and is
10 used to determine if a solid is readily soluble in water. The Ksp is a function of the
11 water solubility, Sw. KH is the distribution constant for a chemical between air and water
12 phases, based on the partial pressure of the gas above the solution to its dissolved
13 concentration; the extent to which a given gas dissolves in solution (here, water) is
14 proportional to its pressure (Henry's law), and KH is the proportionality constant for this
15 relationship. VP is the pressure exerted by a vapor in equilibrium with its solid or liquid
16 phase, typically used for a vapor in contact with its liquid (so it would represent the
17 vapor-phase pressure of the pure liquid). MP and BP, the melting and boiling point s,
18 are simple physical constants; they are used here to help guide the grouping of organic
19 chemicals.
20
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TABLE 3-5
Specific Parameter Values for Example Chemicals3
Chemical"
Toluene
Trichloroethylene
Phenol
Benzo(a)pyrene
PCBs
Dioxin (2,3,7,8-
TCDD)
Pentachlorophenol
Atrazine
Mercury (Hg)
Hg sulfide (HgS)
Lead chloride
(PbCI2)
Kow
(unitless)
540
260
29
1,300,000
12,600,000
6,300,000
132,000
410
4.2
NA
NA
KH
(mol/L*atm)
0.15
0.1
3,000
2,200
2.4
20
40,800
420,000
0.12
NA
NA
Ksp
(unitless)
NA
NA
NA
NA
NA
NA
NA
NA
NA
1.6x 10'52
1.6x 10~5
Sw
(ppm)
526
1,280
83,000
0.001
0.7
0.0002
14
35
0.06
2x 10'21
3,300
BP
(°C)
111
87.2
182
311
NA
NA
309
NA
357
NA
NA
VP
(mm Hg)
28
69
0.35
5x 10~9
0.0005
1.5x 10'9
0.0001
3x 10~7
0.002
NA
NA
MP
(°C)
-95
-84.7
40.9
176.5
NA
305
174
173
-39
NA
NA
2 a Parameters are defined in Table 3-4. NA=not applicable. Representative values shown here
3 are taken from a number of sources and are offered simply for illustration; to calculate
4 environmental behavior for a specific case, setting-specific information should be used to
5 determine the appropriate value for a given parameter.
6 b Chemicals were selected to represent a wide range of physical properties, applications, and
7 sources. Values for dioxin are for the tetrachlorodibenzodioxin isomer generally regarded as
8 most toxic.
9
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1 Moving down Table 3-3, one would predict that while PCB concentrations would
2 be low to intermediate in soil inorganic phases and very low in surface water and
3 groundwater, some volatilization to air might occur for low-chlorinated congeners as
4 indicated by their relatively low boiling points and appreciable vapor pressures. Some
5 volatilization from water would be expected based on the relatively low KH values of
6 PCBs. Migration through air might be possible via adsorption to particulate matter, and
7 rain washout would depend on the relative fraction of PCBs in the vapor phase versus
8 the particulate phase, as well as the partitioning between air and rain water as indicated
9 by Henry's constant. (This constant defines the wet removal process for soluble gases;
10 the effective Henry's constant is used to predict dry deposition velocity for gases and
11 particles, in a calculation that also includes molecular weight and surface reactivity and
12 diffusivity ratios.)
13 Further, expected levels of PCBs in aquatic and terrestrial biota (i.e., via food
14 web transfers) might be high relative to surrounding media (water or inorganic soil), and
15 these levels would be expected to persist due to high lipid solubility (high Kow) and low
16 biodegradability. Finally, given their persistence in fatty tissues, these levels might be
17 expected to be accumulated in the food chain; apex predators would likely have the
18 highest concentrations.
19 Grouping of PCBs with other chemicals can then be explored by applying
20 concepts presented in Table 3-3 using Tables 3-4, 3-5, and 3-6. As seen from Table
21 3-6, PCBs in soil organic matter could be grouped with other persistent organics such
22 as PAHs (see Table 3-5 for details on benzo(a)pyrene), dioxins and atrazine.
23
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TABLE 3-6
Summary Comparison and Screening Suggestions
Media/Compartments
Soil organic phase
(upper soil horizon)
Soil inorganic phase
(lower horizons)
Aquatic sediments
Surface water
Groundwater
Air
Aquatic biota
Terrestrial biota
Suggested Chemical Grouping (for contaminated sites, overtime)
Low volatility, high Kow, persistent organics:
PCBs, dioxins, PAHs; moderately persistent: atrazine
High Kd inorganics:
Metal oxides, hydroxides, carbonates
High Kow organics, low Ksp inorganics:
PCBs, chlorinated pesticides, dioxins, insoluble metal complexes
High water-soluble organics, high Ksp inorganics:
Phenols, ethers, esters, nitro- and amino-organics, soluble metal
complexes
Medium Kow, medium volatility, medium water-soluble persistent and
dense organics, medium to high water-soluble, medium to low Kd
inorganic complexes and free ions:
TCE, vinyl chloride, BTEX, ethers (e.g., met hyl-tert- butyl ether,
MTBE), phenols, atrazine, soluble metal complexes, colloidal metals
Volatile organics, particle-associated organics and inorganics:
Chlorinated solvents, light hydrocarbons, freons, BTEX, and particle-
bound PCBs, dioxins, and metals
High Kow, persistent organics:
PCBs, chlorinated pesticides, PAHs, methyl mercury
High Kow, persistent organics, bioaccumulated metals and
radionuclides:
PCBs, DDT, mercury, lead, radium
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1 The general grouping scheme in Table 3-4 is based on relative ranges of values
2 for a number of important physical constants that determine the behavior of chemicals
3 in the environment (including constants identified in Table 3-3). These ranges have
4 been drawn from information on a wide variety of chemicals in order to illustrate an
5 approach that can be used to group chemicals. Physical properties are given for
6 several chemicals in Table 3-5; these example chemicals were selected to illustrate a
7 wide range of values for the parameters discussed above.
8 Groups of chemicals that might be expected to be distributed to various
9 environmental compartments (or media) as described above are illustrated in
10 Table 3-6. These examples assume that sufficient time has passed for transport
11 and system equilibration to occur. In some cases, such as deposition in aquatic
12 sediments or transport through the food chain, this can take from months to years
13 following an initial release of contaminants. By the same token, after an extended
14 time, chemicals from a variety of different sources would be expected to ultimately
15 reach similar environmental sinks. In cumulative risk assessments, it might be
16 important to examine when these chemical movements would occur.
17 An example that illustrates how available information can be evaluated to
18 determine what release processes and receiving media are most significant,
19 considering past, current, and possible future releases, is offered in Text Box 3-7
20 (U.S. EPA, 2004c). Note that both the transfer of contaminants from one medium to
21 another and environmental transformation are considered as part of the fate and
22 transport evaluation.
23
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4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
In this example, the
identification of the most
significant sources leading to air
contamination would involve
consideration of information
such as chemical form, physical-
chemical properties (such as
volatility), transformation,
partitioning and mobility,
persistence, and bio-uptake
(including combined
Example of Possible Release Sources (Text Box 3-7)
To assess cumulative hazards of urban air toxics in the
Chicago area, it was determined to be most useful to focus on
multiple releases to air. Most source release data identified in
an environmental loadings profile were for point releases;
some data for area and mobile sources of air pollution were
also available. Although data on discharges to surface waters
could have been obtained, the potential for exposure through
this source was considered more limited than for exposure
through source releases to air. Similarly, because the source
of tap water for much of the Chicago area is Lake Michigan,
very limited (if any) exposure to groundwater exists via the
drinking-water pathway. Finally, if a chemical spill occurred,
cleanup was assumed to be relatively quick (following
environmental regulations) when compared to other sources
of exposure, so the potential for exposure to soil contaminated
from a recent spill was considered very low.
One study finding was that relatively few point sources
account for a high percentage of point-source hazards,
suggesting that such sources provide a logical starting point
for hazard management actions. In summary, focusing on
suspected predominant sources can reduce the complexity
and cost of the initial exposure assessments.
environmental fate and co-location). A quantitative fate and transport analysis is not
conducted until later in the process (see Section 3.3.2.3); the intent at this point is to
identify what media are receiving chemicals from the identified source (or sources). A
number of tools and databases exist to support the evaluation of contaminant fate and
transport. Selected highlights are offered in the cumulative risk toolbox in Appendix A.
For a given set of chemicals, only one medium might be contaminated under
current conditions (e.g., site soil), but different media could be affected over time, e.g.,
as contaminants migrate to groundwater or surface water or are taken up in food
products. Thus, other time-related considerations include differential travel times for
multiple contaminants (e.g., migrating to groundwater) and for subsequent transport to
an exposure point. In addition, interactions could influence the mobility of multiple
chemicals present together, or interactions could occur among transformation products
that are formed over time. These concepts of migration and transformation are
illustrated by the differential toxicity of the degradation products of trichloroethylene
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1 (TCE), notably 1,2-dichloroethylene and vinyl chloride, as was described in section
2 3.3.2.1 and as shown in Table 3-1. This concept is illustrated by an example in
3 Figures 3-5 and 3-6, which shows that while the exposure profile changes in the
4 temporal scale, so can the toxicity profile. For example, in a chlorinated plume, the
5 parent compound tetrachloroethylene degrading through TCE to vinyl chloride can
6 actually pose greater risk later (as the plume contaminants gradually degrade) both in
7 groundwater and via the passive (indoor air) inhalation pathway as the more volatile
8 vinyl chloride preferentially passes through the vadose zone and could become trapped
9 closer to the receptors at the land surface.
10 Cumulative assessments may also evaluate combined sources and joint
11 environmental fate and transport. Although some traditional assessments do consider
12 multiple sources and multiple contaminants, differential partitioning into environmental
13 media over time is often overlooked. As examples:
14 dioxin congeners can partition differently between soil and vegetation;
15 site-specific soil characteristics will determine the extent of volatilization for
16 volatile organic compounds;
17 the extent of vegetative cover determines soil runoff into surface water; and
18 weathering can change the composition of an original contaminant mixture.
19 The composition of spilled oil has been shown to change over time, as has that
20 of the toxaphene mixture described in Text Box 3-8 (from U.S. EPA, 1997d). Methods
21 to account for differential partitioning continue to evolve. For example, the EPA soil
22 screening guidance considers the potential for individual soil contaminants to migrate to
23 groundwater, based on a simple soil screening-level partitioning equation and the use of
24 either of two dilution attenuation factors (U.S. EPA, 1996a). This approach could be
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Indoor Air
Ambient air:
can also reflect industrial or
nonpoint inputs to the
ambient air source term
Vadose Zone .<
Soil Gas
Soil J
Contamination [_
(residual or
mobile NAPL)
I
I
I
Chemical Vapor Migration
Different chemical properties
and degradation/migration
constants change exposure
profile over time
^x" Groundwater NAPL = non-aqueous phs
Contamination T (in minutes)
PCE
^TCE~
VCC
a
b
c
First-Order GW a
Decay Constant b
<0.1-110(avg4)
<0.1-90(avg1)
O.2-20 (avg 0.6)
Abbreviations as follows
T0 Concentration (ppm)
Soil GW IA
100
30
0.5
5.2
6.7
2
ND
ND
ND
T1 Concentration (ppm)
Soil GW IA
10
3
0.05
0.1
2.5
1.1
4
2.4
3.1
T10 Concentration (ppm)
Soil GW IA
ND
ND
ND
avg=average. GW=ground water. IA = indoorair. ND = not detectable.
ND
0.0003
0.005
3.5
0.5
ND
PCE -perchloroethylene(tetrachloroethene). ppm -parts per million.! -time. TCE -trichloroethylene. VC -vinyl chloride.
U.S. EPA 1998. Technical Pro to col for Evaluating Natural Attenuation of Chlorinated Solvents in Ground Water.
Office of Research and Development, Washington DC. EPA/600/R-98/128. September.
Assuming natural attenuation and degradation are occuring all the way thro ugh ethane, excess VC is not generated, as shown
here. However, if incomplete degradation occurs, VC may accumulate, and the reductions shown here may not occur.
FIGURE 3-5
Example Changes in Exposure Profile from Degradation and Partitioning
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Soil PCE source started at 100
ppm atTime0soil TCE source
started at 30 ppm at Time0
Soil Change in Concentration
(Exposure) Over Time
E
Q.
Q.
o
1
CD
O
c
o
O
0 1
234567
Time (years)
9 10
Groundwater Change in Concentration (Exposure)
Over Time
PCE
TCE
VC-Degrading
VC-Stalled
23456
Time (years)
8910
Indoor Air Change in Concentration
0 ^~
0 1
FIGURE 3-6
Illustration of Changing Media Concentrations Affecting Potential Exposures
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
used for screening multiple
contaminants to support grouping
for a cumulative risk assessment.
3.3.2.3. Exposure Points
and Routes The next phase of
the exposure assessment involves
identifying who is likely to come in
contact with chemical pollutants,
where, and by what route(s) of
exposure. The exposure points
(the geographical locations where
Weathering Example: Toxaphene (Text Box 3-8)
Until the 1970's, toxaphene was the most heavily used
pesticide in the United States. It was formulated using
multiple ingredients, and their relative amounts change
after the pesticide is released because of differential
partitioning and transformation processes in air, water, and
soil. (The soil half-life can be 1 to 14 years.) Overtime
these components continue to change, so the composition
of weathered toxaphene differs significantly from the
original mixture. Samples collected from different sources
might also differ, depending on the location-specific
environmental processes to which the original mixtures
were exposed. For example, weathered toxaphene in an
anaerobic soil does not resemble that in an aerobic soil,
and that in an air sample from the Arctic does not resemble
residues found in the blubber of an Arctic seal. Some
components of this environmental mixture might not be
routinely identified through standard analyses. Site-specific
partitioning and transformation processes must then be
considered to properly assess what compounds could be
present at a given time. It is also important to link this
information with the toxicity evaluation, because weathered
compounds will also exhibit different toxicities from the
original mixture components.
people could come in contact with the chemicals) and routes (ingestion, inhalation, and
dermal absorption) are identified for each exposure pathway, and then integrated for the
cumulative assessment. It is important to consider also interactions that might enhance
exposures or associated effects and to evaluate when these exposures may occur.
Non-chemical factors can change exposures and potentially influence the
toxicokinetics (e.g., rate of disposition to a target tissue). The higher ventilation rates for
joggers running near an emission source are an example of an exposure factor that
influences exposure. This, in turn, could increase the rate at which he or she inhales
airborne chemicals. Co-exposure to toluene and noise offers an example of synergism
because this organic compound damages the auditory system and can also potentiate
22 additional damage by noise, a physical stressor, beyond what would be expected by the
23 two acting separately (U.S. EPA, 2003e).
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1 At this point of the assessment, available information is integrated to link the
2 sources of multiple chemicals, their releases and fate/transport, the exposure points
3 for likely receptors, and the exposure routes (U.S. EPA, 1989a). The focus is on
4 exposure pathways that are currently complete or are likely to become complete.
5 Thus, relevant time frames of these exposures are appropriate to consider at this
6 point, to guide the evaluation of the frequency, duration, intensity, and possible
7 overlaps of exposures to multiple chemicals, as well as the sequence of those
8 exposures. The level of detail needed in the exposure assessment with respect to
9 exposure overlaps should be evaluated with the dose-response analyst. The dose-
10 response analyst may provide information on whether the overlap of exposures
11 co-occurring on the same day within a week, a month, or a year matters
12 toxicologically.
13 Information on background exposure levels to common environmental
14 contaminants can be important to cumulative assessments. A key resource for this
15 information is available through the National Human Exposure Assessment Survey
16 (NHEXAS) program (U.S. EPA, 2004d). That program was designed to address some
17 of the limitations of single-chemical and single-media exposure studies as one of its
18 goals is to test and evaluate different techniques and design approaches for performing
19 multimedia, multipathway human exposure studies. The NHEXAS data can be used as
20 baseline information for exposure assessments to indicate if specific populations are
21 exposed to increased levels of environmental contaminants. These data are available
22 in the Human Exposure Database System (HEDS), which contains chemical
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1 measurements, questionnaire responses, documents, and other information related to
2 EPA studies of human exposures to environmental contaminants (see Appendix A).
3 To evaluate what chemicals might coexist at places where receptors are, or
4 could be, exposed, site-related contaminants can be grouped by considering when they
5 might coexist in space and time. This grouping should reflect transport and fate
6 considerations, including transformation, that are appropriate for the time intervals
7 studied. Minimally, four groups are defined to guide this evaluation of possible
8 exposures to multiple chemicals in various environmental media over time, as shown in
9 Text Box 3-9. Clearly, for analyses that evaluate multiple
10 chemicals, there can be multiple media and multiple time
11 points to evaluate. Assuming that these chemicals co-
12 occur in media that individuals in the community may
13 contact, these exposure groupings can then be linked
Chemical Groupings by
Coexistence in Media/Time
(Text Box 3-9)
Media
Time Same Different
Same Group 1 Group 3
Different Group 2 Group 4
14 with toxicity information to assess joint impacts, as described in Chapter 4. Note that
15 these can be evaluated as potential doses. (In refined cumulative exposure
16 assessments, toxicokinetic and toxicodynamic information could be used to provide a
17 comprehensive understanding of the magnitude of tissue doses over time (see Sections
18 3.3.3 and 3.3.4).
19 The Agency identifies several time-course issues in the Framework for
20 Cumulative Risk document (U.S. EPA, 2003a). Certain chemical pairs can demonstrate
21 different toxicity depending on the sequence of exposures, with cancer initiators and
22 promoters being the classic example; exposure to a promoter has no effect if it occurs
23 prior to exposure to an initiator. This illustrates the same media/different time and
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1 different media/different time
2 concepts indicated above.
3 Examples of chemical pairs for
4 which the toxicological effect is
7 Specific joint toxicity issues
8 are discussed in Chapter 4.
Examples of Chemical Pairs Influenced by Exposure
Timing (Text Box 3-10)
Benzo[a]pyrene (BaP) and tris(2-ethylhexyl) phosphate (TPA)
are an initiator/promoter pair.
TPA does not have a tumorigenic effect in mouse skin assays,
but applying it after initiation with BaP, greatly enhanced
tumorigenic activity (Verma et al., 1985).
5 influenced by exposure timing _ . . _,,_,.**
} r ° Cadmium and lead illustrate antagonism:
, . T . R o .p. Initial exposure to cadmium has been shown to decrease the
b are snown in I ext box j-1 u. absorption of lead following subsequent exposure, which has
the effect of decreasing the blood lead level and causing less-
than-additive hematopoetic toxicity (other data suggest different
joint toxicity, as affected by the order of exposure, from
ATSDR, 2004).
9 Several commercial exposure models have been developed to capture the time aspects
10 of exposures, and several tools are indicated in Appendix A.
11 3.3.3. Exposure Quantification. Outputs of fate and transport models, such as from
12 air dispersion modeling, can be used to define the temporal and spatial distribution of
13 chemicals needed to quantify human exposures. When monitoring data are available,
14 estimates of exposure could primarily be based on those measures of contaminant
15 concentrations in the environment, as indicated by the type and quality of the data.
16 Cumulative exposures to a given population could be estimated for various
17 exposure pathways and for contaminants of interest to the community. For this
18 assessment, as many of the following data as are applicable are used to determine
19 cumulative exposures to a given population:
20 body burdens (e.g., concentrations of lead in blood)
21 measured concentrations in air, groundwater, surface water, soil, sediments, and
22 food or
23 modeled concentrations in the ambient environment (not linked to sources).
24 Prior exposures could also be considered if data are available.
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1 Such a total exposure approach could result in certain sources being essentially
2 unidentifiable and might include non-industrial contaminant sources such as consumer
3 products, environmental tobacco smoke, radon, and pesticide residues on foods.
4 However, the end result could be comprehensive exposure estimates for the population,
5 which would include environmental contaminants that are showing up in the monitoring
6 data. Some stakeholders might desire such an assessment, but it would typically be
7 beyond the scope of a contaminated site assessment project. The assessment may
8 identify an evaluation of unknown sources of contaminants as a potentially important
9 research need. The information offered in this report and many other resources can be
10 used to support such complementary analyses by other groups, as desired.
11 3.3.3.1. Exposure Point Concentrations The concentrations of chemicals to
12 which people are, or could be, exposed over the time period of interest can be
13 represented by a combination of monitoring data and transport and fate models. To
14 review the concepts discussed in earlier sections, models are the only way future
15 concentrations can be estimated. Models are used to fill gaps in data for current
16 conditions.
17 Models can be applied at different levels during a cumulative risk analysis,
18 beginning with a simple screen to winnow down the list of chemicals of concern and
19 exposure pathways by eliminating those clearly not expected to contribute to adverse
20 effects. Using known (not missing) information, this screen reduces the list of chemicals
21 included in the more detailed analysis, thus facilitating a more focused analysis. Simple
22 fugacity models can be used to predict movement and phase change in the
23 environment, for example, to identify which chemicals volatilize, stay soil bound, lodge
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1 in fat of fish or other food species. Environmental breakdown products should be
2 identified as indicated by the data or acknowledged as potentially present where those
3 data do not exist. Rare events that might result in different combinations of chemicals
4 being released to the environment at higher levels may be considered.
5 The next step could be to rank mixtures by defining the chemical and exposure
6 combinations of main concern and those mixtures that are unlikely to pose a problem.
7 Exposures to the population of concern could be quantified assuming steady state, also
8 indicating expected departures from steady state conditions. If needed, a final iteration
9 would involve applying more detailed dynamic fate and transport models to predict time-
10 varying concentrations in each media, also including spatial changes in exposure
11 concentrations.
12 For more precision, this kind of exposure modeling over time could consider
13 physiological factors as indicators of likely overlap of internal doses and of possible
14 damping of external exposure fluctuations (internal overlaps are discussed in Section
15 3.3.3.4). Quantitative estimates of exposure would then be determined over these
16 different time periods. Selected exposure models that can be used to support these
17 exposure analyses are included in the cumulative risk toolbox in Appendix A.
18 3.3.3.2. Intake Estimates Using measured and predicted estimates of the
19 concentrations of multiple chemicals at each exposure point of interest, exposure
20 factors relevant to each receptor are then applied to calculate pathway-specific intakes.
21 These intakes are calculated using equations that generally include intake variables for
22 media concentrations (over time), the contact rate, exposure frequency, exposure
23 duration, body weight, and exposure averaging time, as indicated in the basic EPA
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1 guidance (U.S. EPA, 1989a). The Exposure Factors Handbook (U.S. EPA, 1997c)
2 identifies specific intake rates for air, water, and foods. These equations are then
3 adapted to the specific exposure route: oral, inhalation, or dermal.
4 The general intake equation is:
5 Intake (mg/kg-day) = C x IR x EF x ED (3-1)
6 BW x AT
7 where:
8 C = concentration (i.e., exposure point concentration) (e.g., mg/L for water)
9 IR = intake rate (e.g., L/day for water)
10 EF = exposure frequency (days/year)
11 ED = exposure duration (years)
12 BW = body weight (kg)
13 AT = averaging time (period over which exposure is averaged, in days)
14 Community-specific exposure factors are preferred in calculating intakes, but
15 generic values can be used for conservative screening-level analyses. The cumulative
16 risk across all chemicals, media, and exposure routes will be estimated from these
17 combined calculations linked with toxicity data. For example, rare events that might
18 result in different combinations of chemicals could yield different exposure point
19 concentrations that would not normally be evaluated but would be included in the
20 exposure assessment.
21 An example scenario was developed for current and future land use at a
22 hypothetical contaminated site to illustrate the evaluation of multiple pathways and
23 degradation products. As shown in Table 3-7, receptors under current conditions are
24 assumed to be an on-site maintenance worker and off-site resident. Exposures are
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TABLE 3-7
Example of Cumulative Exposures for Current Land Use*
Chemicals/
Transformation Products
Exposure Medium
and Locationcd
Chemical Intakes
(mg/kg-day)
Ingestion
Inhalation
Dermal
On-Site Maintenance Worker
Tetrachloroethylene
Chlorine
Trichloroethane
Vinyl chloride
Benzo(a)pyrene
Anthracene
PCBs (as Aroclor 1254)
Aldrin
Dieldrin
Site soils
Ambient air
Ambient air
Site soils
Ambient air
Ambient air
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
2x10'5
4x10"8
8x10'4
1 x10'6
2x10'7
9x10-10
2x10'5
7x10'7
2x10'3
5x10'5
1 x10'6
2x10'6
5 x 1 0'6
7 x 1 0"7
3 x 1 0'9
6x10-10
2 x 1 0'5
6 x 1 0"8
6 x 1 0"6
1 x 1 0'5
4 x 1 0"7
5x10'7
8x10-10
7x10'6
2x10"8
4x10'9
3x10"11
2x10'7
5x10'9
4x10'5
4x10'7
1 x10"8
4x10-10
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TABLE 3-7 cont.
Chemicals/
Transformation Products
Arsenic
Chromium
Lead
Mercury
Exposure Medium
and Location001
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Chemical Intakes
(mg/kg-day)
Ingestion
8x10"6
5x10'7
8x10"7
7x10-9
3x10"6
9x10"9
4x10'5
6x10"7
Inhalation
3 x 1 0'7
5 x 1 0'8
2 x 1 0'7
8 x 1 0'6
Dermal
2x10"8
9x10'10
2x10-9
3x10"11
8x10"8
1x10-10
3x10'7
2x10-9
Off-Site Resident
Tetrachloroethylene
Chloroform
Chlorine
Trichloroethane
Vinyl chloride
Aquifer - tap water
Vapors from shower
Aquifer - tap water
Vapors from shower
Aquifer - tap water
Vapors from shower
Vapors from shower
1 x 1 0"5
9 x 1 0"6
7 x 1 0'8
6x10'8
5 x 1 0"7
4x10-9
9x10-10
2x10"7
3x10"7
2x10-10
2 *The example scenarios assume exposures at the site under current conditions, e.g., degradation
3 products are identified for chemicals that undergo conversion on the order of hours or days. The source
4 release is assumed to be a spill to surface soils with subsequent leaching to subsurface soils and
5 groundwater. The exposure point concentrations are assumed to be unit concentrations of 1 mg/kg, 1
6 mg/m3, or 1 mg/L for calculating intakes of soil/biota, air, or water, respectively. The exposure media are
7 site soils at or beneath the spill location, ambient air from resuspended particulate matter, surface soils
8 from deposition of resuspended particulate matter, in groundwater at the tap, and water vapors from
9 showering. Estimates will depend on the default and/or site-specific exposure factors used in the intake
10 equations.
11
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1 assumed to occur via several pathways following a chemical spill. To account for
2 changes over time, cumulative intakes are calculated for exposures to original
3 chemicals as well as degradation products that can result from relatively rapid
4 conversion. Intakes for ingestion, inhalation, and/or dermal contact are calculated for
5 applicable media and are then used to calculate cumulative risk estimates in the risk
6 characterization step.
7 For a future land use scenario, exposure assessments would be appropriate for
8 on-site residents and an off-site recreational visitor. As noted in Table 3-8, exposures
9 occur by several pathways that reflect the much longer time frame (e.g., 20 years).
10 Again, to account for changes over time, cumulative intakes are calculated for exposure
11 to chemicals plus conversion products that result from relatively slow degradation (on
12 the order of months or years). Volatile organics in surface or near-surface soils are
13 assumed to have dissipated so are not considered in future exposure assessments.
14 Intakes for the exposure routes of ingestion, inhalation, and/or dermal contact are
15 calculated for applicable media and are then used to calculate cumulative risk estimates
16 in the risk characterization step.
17 3.3.3.3. Calendar Approach While no Agency-wide standardized procedure
18 exists for detailed consideration of exposure timing in dose/response assessment, the
19 Office of Pesticide Policy provides an approach in General Principles for Performing
20 Aggregate Exposure and Risk Assessments (U.S. EPA, 2001 a). Figure 3-7 provides an
21 overview of their calendar approach. The calendar approach estimates sequential, daily
22 chemical exposures by linking episodic exposures (e.g., seasonal exposures to
23 pesticides through surface water contact following residential lawn applications of
24
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TABLE 3-8
Example of Cumulative Exposures for Future Land Use*
Chemicals /
Transformation Products
Exposure Medium
and Location
Chemical Intakes (mg/kg-day)
Ingestion
Inhalation
Dermal
On-Site Resident
Benzo(a)pyrene
Anthracene
PCBs (as Aroclor 1254)
Dieldrin
Arsenic
Chromium
Lead
Mercury
Benzo(a)pyrene
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Site soils
Ambient air
Surface soils
Surface runoff to lake
3x10'4
1 x10'6
2x10'3
8x10'6
2x10'6
4x10'8
1 x10'6
3x10"8
9x10"3
2x10'6
5x10"3
2x10"5
8x10'3
9x10'5
1 x10'6
2x10"7
1 x10"8
2x10'5
6x10'5
5x10"5
9x10"6
1 x10'5
7x10'4
4x10'4
6x10'6
2 x 1 0'8
2x10-10
5 x 1 0'4
2 x 1 0'7
6 x 1 0"7
2 x 1 0'9
2 x 1 0'8
2x10-10
7 x 1 0"7
6 x 1 0'9
2 x 1 0"5
8 x 1 0"7
3 x 1 0'7
2 x 1 0"9
5 x 1 0"8
5x10-10
2x10"11
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TABLE 3-8 cont.
Chemicals/
Transformation Products
Exposure Medium
and Location
Chemical Intakes (mg/kg-day)
Ingestion
Inhalation
Dermal
Off-Site Recreational Visitor
Anthracene
PCBs(asAroclor1254)
Dieldrin
Arsenic
Chromium
Lead
Mercury
Methyl mercury
Surface runoff to lake
Surface runoff to lake
Fish in lake
Surface runoff to lake
Surface runoff to lake
Surface runoff to lake
Surface runoff to lake
Surface runoff to lake
Fish in lake
4x10'7
9x10'9
5x10'6
2x10"9
3x10"7
8x10"8
1 x10"7
2x10"8
3x10"5
1x10-10
4x10'12
8x10"12
6x10-10
2x10"11
7x10-10
5x10"11
2 * These example scenarios assume exposures at the site under future conditions, e.g., degradation
3 products are identified for chemicals that undergo conversion on the order of months or years. In
4 addition, TCE and PCE in surface soils are assumed to have completely volatilized by the time the future
5 land use scenario begins, with aldrin having been converted fairly rapidly to dieldrin. The source release
6 is assumed to be a spill to surface soils with subsequent leaching to subsurface soils and groundwater.
7 The exposure point concentrations are assumed to be unit concentrations of 1 mg/kg, 1 mg/m3, or 1
8 mg/L, for calculating intakes of soil/biota, air, or water, respectively. The exposure media are site soils at
9 and beneath the spill location, ambient air from resuspended particulate matter, surface soils from
10 deposition of resuspended particulate matter, surface water, and lake fish. Estimates will depend on the
11 default and/or site-specific exposure factors used in the intake equations.
12
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2
O
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
Step 1 Identify toxicological
endpoints for each potential
exposure route and duration
Step 2 Identify potential
exposures for each pathway
Step 3 Reconcile routes and durations of
potential exposures with routes and durations
of health effects
Step 4 Determine co-occurrence of chemicals
through different exposure scenarios
Step 5 Determine magnitude, frequency and
duration for all pertinent exposure
pathway/route combinations
Step 6 Determine data treatment method
Step 7 Assign route-specific risk metrics
Step 8 Conduct Aggregate Exposure and
Risk Assessment
Step 9 Conduct sensitivity analysis
Step 10 Aggregate Exposure and
Risk Characterization
FIGURE 3-7
Ten Steps in Performing Aggregate Exposure and Risk Assessment
(Adapted from U.S. EPA, 2001 a)
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1 pesticides in the spring and summer) with routine exposures (e.g., contaminants in the
2 food supply). Figure 3-8 illustrates the pattern of results that may be predicted using
3 this approach. The discussion that follows adapts this approach, which covers
4 aggregate exposures, to cumulative exposure practices. This discussion focuses on
5 Steps 1-6, followed by additional information about the calendar approach.
6 The first and third steps are conducted by both the dose-response analyst and
7 the exposure analyst. The goal of these steps is to identify the health effect(s)
8 associated with each chemical or group of chemicals identified. This includes an
9 analysis of which exposure route(s) and exposure duration(s) produced the effect(s)
10 and a step (step 3) to ensure that the dose-response assessment and the exposure
11 assessment are concordant. A previous document (U.S. EPA, 1999e) describes five
12 general durations of exposure considered:
13 acute - in a cumulative assessment this could include one-day exposures
14 through oral (food and water pathways, which reflects distribution of daily food
15 consumption and daily water residue values), inhalation (atmospheric
16 concentrations) and dermal routes, which reflects daily water and soil residue
17 values)
18 short-term - could include 1- to 30-day exposure scenarios
19 intermediate-term - could include 30- to 180-day exposure scenarios
20 chronic/long-term - could include exposures of greater than six months in
21 duration, and
22 cancer - lifetime assessment.
23 Following the identification of the toxicologic endpoint(s), duration of exposure(s),
24 exposure scenario(s) of concern, Step 4 requires the analyst to examine residential
25 exposures that might occur to potential receptors (e.g., home pesticide or herbicide)
26 (U.S. EPA, 2001 a). This is accomplished by appropriately combining information about
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4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
A. Food Exposure
Acute toxicity
endpoint
Short-term
toxicity endpoint
Time (Days)
B. Drinking Water Exposure
Time (Days)
C. Residential Exposure
Acute toxicity
endpoint
Short-term
toxicity endpoint
Time (Days)
Time (Days)
FIGURE 3-8
Pathway-specific and Combined Exposure to a Single Hypothetical Chemical
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1 a potentially exposed individual's demographic (e.g., age, gender, and racial/ethnic
2 background), temporal (season), and spatial (region of the country) characteristics.
3 A cumulative exposure assessment could undertake the same steps combining
4 national data to estimate background exposures with site-specific data to estimate local
5 exposures. This point is illustrated using a single chemical exposure. Methylmercury
6 exposures can result from consumption of locally-caught fish and commercial fish (i.e.,
7 two different sources of fish). An analysis could examine the correlation between
8 consumption rates of locally-caught and commercially-caught fish and use both average
9 local fish methylmercury levels and average commercial fish methylmercury levels to
10 estimate methylmercury exposures in individuals consuming a mix of these fish. Such
11 an analysis could also capture seasonal consumption patterns (and associated
12 exposure patterns) of locally-caught fish. Furthermore, U.S. EPA (1999e) suggests that
13 distributional data analyses (as opposed to a point estimate approach) are preferred
14 because this tool allows an aggregate exposure analyst to more fully evaluate exposure
15 and resulting risk across the entire population, not just the exposure of a single, high-
16 end individual.
17 Steps 5 and 6 integrate the magnitude, frequency, and duration of exposure for
18 all relevant pathway and route combinations. Consequently, the hypothetical
19 individual's temporal, spatial, demographic, and behavioral exposure characteristics
20 need to be considered for each relevant duration in the assessment. This results in a
21 calendar approach to the exposure assessment because the timing of the multi-route
22 exposure relative to each other is critical to the evaluation of the health endpoint.
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1 Figure 3-8 (adapted from a figure in U.S. EPA, 2001 a) illustrates the combination of
2 exposure pathways over time (in this case, days) for a single chemical.
3 Exposures to two or more chemicals can overlap if the chemicals coexist in the
4 same environmental medium during the same exposure period of interest. If there are
5 multiple pathways that involve different chemicals, independence should not be
6 assumed. Instead, joint exposure should be evaluated for potential overlap of potential
7 doses (e.g., chemicals in local fish and air that result in overlapping potential doses) and
8 internal dose (including metabolites), for potential toxicological interactions, or for
9 potential overlap of effects. Information on environmental fate is important input to this
10 evaluation. For example, a screening-level comparison of Kd values in soil could be
11 used to gauge the potential for simultaneous
12 migration of a group of chemicals (see Table
13 3-3).
14 People can be exposed to chemicals at
15 the same time but in different media. For
16 example, exposure to inorganic mercury in soil
17 and shellfish, to DBPs in drinking water and
18 during showering, and to volatile organic
19 compounds in indoor air (originating from a site
20 or from the use of household or office products)
21 could all be combined for a full cumulative
22 assessment. Text Box 3-11 uses the chemical
23 groupings based on coexistence in media and
Examples of Chemical Groupings by
Coexistence in Media/Time
(Text Box 3-11)
Media
Same Different
Time
Same
Group 1 Group 3
Coexposures Coexposures to
to mixture of volatile and non-
DBPs via volatile DBPs
consumption via inhalation
while showering
and
consumption of
unheated
tapwater
of unheated
tapwater
Different Group 2 Group 4
exposures via VOC exposures
contaminated via inhalation
drinking water due to
to different temporary
pesticides with incinerator to
short remediate a site
environmental and, years later,
half-lives exposures to
metal mixture
via consumption
of contaminated
groundwater
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1 time to illustrate chemical combinations highlighted in this paragraph and other potential
2 combinations.
3 3.3.3.4. Combining the Calendar Approach with Toxicokinetic Models
4 The calendar approach (U.S. EPA, 2001 a) can be combined with toxicokinetic models
5 to estimate tissue doses for mixture components over time. U.S. EPA (2001 a)
6 described a calendar approach that estimates daily exposures up to a full year. The
7 calendar approach can be used to assess exposures resulting from seasonal activities
8 such as timing of pesticide applications over a year or the timing of pesticide runoff
9 during the year. Such an approach can also be used to evaluate exposures via indoor
10 air, which could change seasonally. The approach integrates exposures by route using
11 probabilistic5 input data (e.g., this approach could integrate oral exposures that result
12 from food intake, drinking water consumption, and soil ingestion). The approach
13 predicts distributions of potential doses via different exposure routes (see Figure 3-7).
14 Clearly, this type of approach is most useful for pollutant concentrations that vary over
15 relatively short periods of time (daily or weekly).
16 Figure 3-8 illustrates the results of a multipathway exposure assessment using a
17 calendar based approach. Panel A of Figure 3-8 shows that the potential doses of this
18 hypothetical pesticide through food consumption are relatively constant over the period
19 of time evaluated. Panel B shows that the potential doses of this hypothetical pesticide
20 are generally low. However, the potential doses from this exposure pathway may be
21 quite high during a fraction of the period of time evaluated. The high exposures through
22 the consumption of private drinking water might be due to runoff of this pesticide from
5 In probabilistic exposure assessments, the population's exposures are characterized by distributions of
exposure factors and contaminant concentrations.
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1 lawns or agricultural lands. Panel C illustrates a residential exposure. It suggests that
2 there is no pesticide dose from this pathway during certain periods of time (e.g., winter
3 months), but a relatively large dose during other periods of time. Panel D combines
4 these three pathways of exposure showing the potential dose of the hypothetical
5 pesticide for each day of the exposure duration evaluated.
6 U.S. EPA (2003b) conducted research to examine the feasibility of conducting a
7 cumulative risk assessment for DBP mixtures by combining exposure modeling and
8 physiologically-based toxicokinetic (PBTK) modeling. Initially, a comprehensive
9 exposure modeling effort was implemented to estimate population-based exposures
10 and absorbed doses for 13 major DBPs, incorporating parameters for chemical
11 volatilization, human activity patterns, water use behaviors, ingestion characteristics,
12 building characteristics, physiological measurements, and chemical concentrations in
13 the water supply. Daily exposure estimates were made for an adult female and an adult
14 male and for a child (age 6) of total absorbed doses inclusive of exposures via oral,
15 dermal, and inhalation routes. Estimates were developed for 13 major DBPs,
16 accounting for human activity patterns that affect contact time with drinking water (e.g.,
17 tap water consumed, time spent showering, building characteristics) and
18 physicochemical properties of the DBPs (inhalation rates, skin permeability rates,
19 blood:air partition coefficients, etc.). Combining daily exposure information with a
20 toxicokinetic model provides additional insights into the exposures, including residual
21 concentrations in the body. Figure 3-9 provides an overview (from a biological
22 perspective) of the exposure metrics that can be used. Figure 3-10 illustrates how an
23 exposure assessment model was linked with a PBTK model for DBPs to estimate the
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Source.,
Source.,
Source,,
Environmental Concentrations in Various Media
Activity
Potential
Dose
Dermal Exposure,
Inhalation; Exposure
Oral Exposure
Balrier
Absorbed
Dose
* T
Skin Lung Intestinal Tract
^x
X
X
X
Dermal AbsorbeUJDose
X
X
X
X
X
Inhalation
. Absorbed Dose
/
s
sOra\
s
sf
Absorbed Dose
Total Absorbed Dose
(Internal Dose)
Pharmac
sokinetics .
Tissue
Dose
Tissue/Organ Dose
FIGURE 3-9
Dose Metrics for Environmental Contaminants (Source: U.S. EPA, 2003b)
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Modeling of Input Data on Chemical Properties, Human Activity
Patterns, Human Intake Parameters, Building Characteristics
24 Hour Exposure Time Histories
Simulated by TEM for a human of a specified age and sex
Modeling of Data on
Physiological Parameters
Input Ds
Measure
Concent
Drinking
At the F«
i
fa
xJDBP
rations In
Water
aucet
Estimated DBP
Concentrations
In Household Air
DBP Oral
External
Exposure
Estimates
DBP Dermal
External
Exposure
Estimates
DBP
Inhalation
External
Exposure
Estimates
DBP Oral
Absorbed
Dose
Estimates
DBP Dermal
Absorbed
Dose
Estimates
DBP
Inhalation
Absorbed
Dose
Estimates
i
DBP
Multiple
Route
Total
Absorbed
Dose
Estimates
i
FIGURE 3-10
DBP Multiple Route
Tissue and Organ
Dose Estimates
- AUC* Kidney
- AUCTestes
- AUC Liver
- AUC Venous Blood
*AUC - Area under the curve
Linking Exposure Assessment Modeling with a PBTK Model for DBPs (Adapted from U.S. EPA, 2003b)
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1 organ-specific doses (estimated as an area under the curve (AUC)). PBTK models
2 provide a useful approach for integrating exposures across multiple exposure routes.
3 The kinetics of toxicants, when combined with exposure information, can be an
4 important factor in determining whether chemicals will be present in the same target
5 tissue within the body at the same time. While estimates of potential doses and the
6 potential daily or seasonal variability in such doses are useful (based on the
7 concentration of pollutants encountered in the environment, activity patterns, and intake
8 rates), toxicokinetic models can provide refinements to this measure that may be critical
9 to the cumulative exposure assessment. These refinements may include differential
10 absorption of mixture components across boundaries, differences in the distribution of
11 mixture components in the body, differential metabolism, and differences in elimination
12 (e.g., clearance rates). Models can also be developed to estimate the kinetics of by-
13 products of metabolism.
14 Figure 3-11 summarizes different levels of dose specificity that may be needed in
15 a cumulative exposure assessment. Moving from level 1 to level 4 requires additional
16 analytic detail. Depending on the chemicals being evaluated, levels 1 and 2 may
17 require the use of dynamic fate and exposure models (e.g., the calendar approach).
18 Depending on the variability of the exposures in the pathways being evaluated,
19 undertaking an analysis as depicted in levels 3 or 4 would likely require a dynamic
20 exposure model that could simulate daily potential doses of multiple chemicals.
21 Because of the chemical-specific nature of absorption, distribution, metabolism, and
22 elimination, chemicals contacted at the same time may not remain in the tissues of the
23 body for the same period of time. Thus, some compounds may be quickly eliminated
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
Environmental
Mixture
Concentrations
Environmental
Mixture
Concentrations
Environmental
Mixture
Concentrations
Environmental
Mixture
Concentrations
Potential
Doses
Potential
Doses
Potential
Doses
Potential
Doses
Internal Doses
(Parents)
Internal Doses
(Parents)
Internal Doses
(Parents)
Tissue Doses
(Parents)
Tissue Doses
(Active Chemical Species)
FIGURE 3-11
Levels of Dose Specificity that Can Be Estimated in a Cumulative Exposure Assessment
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1 and others may be slowly eliminated resulting in prolonged tissue exposure. Figure
2 3-12 builds upon Panel D of Figure 3-8. It illustrates the target organ doses that
3 correspond to the cumulative exposure depicted in panel A depend on whether the
4 chemical is rapidly eliminated (panel B) or slowly eliminated (panel C). Figure 3-13
5 illustrates the different retention times exhibited by Chromium (III), Chromium (VI), and
6 tritium. The disposition of chemicals absorbed through different exposure routes may
7 differ. Undertaking an analysis as depicted in levels 3 or 4 (Figure 3-11) may be
8 needed to determine if the exposures through different routes result in overlapping
9 internal doses. The analyses depicted in levels 3 and 4 require a thorough
10 understanding of toxicokinetic conditions. Level 3 estimates concentrations of the
11 parent compounds in the target tissues over time. Level 4 requires knowledge of
12 whether the compounds are toxic in their parent form or as metabolites and would
13 predict concentrations of the toxicologically active chemical species in the target tissue
14 overtime.
15 In summary, doses may be considered at different levels of specificity. Each is
16 potentially useful and differentially resource-intensive. The level of detail selected in the
17 analysis should be determined through consultation with the dose-response analyst.
18 The dose-response analysis may provide information demonstrating the biological
19 longevity of contaminants to determine potential overlap of tissue concentrations or
20 provide important toxicodynamic information. If available, information on the tissue
21 dosimetry of single chemical exposures and information identifying sensitive
22 tissues/organs and interaction with key biochemical pathways (whether related to
23 metabolism/excretion or cellular function) should be combined to allow a more complete
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
0)
E
in
8.
A. Total Exposure
0)
E
in
8.
D)
Time (Days)
B. Target Organ Dose: Rapid Elimination
Time (Days)
C. Target Organ Dose: Slow Elimination
Time (Days)
FIGURE 3-12
Multipathway Potential Doses and Target Organ Doses
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Whole
Body
Cr(lll)
Cr(VI)
Tritium
Dose
Absorption
Urine
Feces
Dose
Metabolism to Cr(lll)
Absorption
Feces
Dose
Absorption and Incorporation
+=100%
3H - body water
3H - organically bound
10
i
100
I
1000
I
10000 hours
i
0.42
4.2
42
420
days
FIGURE 3-13
Human Residence Time for Selected Contaminants
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1 evaluation of interactions among mixture components leading to changes in internal
2 exposure duration.
3 As illustrated in Figure 3-14, biological effects can continue even after the
4 chemical(s) has been eliminated from the system. Persisting biological and/or
5 biochemical effects can have multiple effects including those based on chemical
6 distribution and tissue effects. These effects can relate to subsequent exposures to the
7 same chemical and to other chemicals, depending upon the extent to which multiple
8 chemicals interact with the same biochemical or cellular targets.
9 Finally, even a qualitative description of the possible alteration of effects based
10 on exposure sequence and pattern constitutes a step forward. The exposure sequence
11 could be an issue for chemicals in different media at different times. For example,
12 combined exposures from multiple routes could have occurred if an individual's past
13 exposure history is considered. These current and past exposures via the same or
14 different exposure routes/media may increase an individual's susceptibility to a chemical
15 (U.S. EPA, 2003e). A database of chemical pairs for which exposure timing should be
16 considered would be useful for cumulative assessments. The Agency has developed
17 initial information in its Mixtox database, which is described in Chapter 4. Some
18 information related to exposure is included in the interaction profiles that have been
19 drafted by ATSDR for a limited set of chemical combinations (see Appendix A). Further
20 discussion of toxicity as influenced by exposure sequence is presented in Chapter 4.
21
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Persistence of
Compound
Persistence of
Biological Effect
T
(Time)
Exposure
2
3
FIGURE 3-14
Conceptual Illustration Showing the Persistence of a Biological Effect Exceeds the Duration of the Exposure
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1 3.4. ILLUSTRATION OF CUMULATIVE CONCEPTS FOR THE AIR PATHWAY AT
2 A CONTAMINATED SITE
3 Local communities are understandably concerned about possible exposures to
4 chemicals from contaminated sites, with air and groundwater being two main transport
5 pathways. When the water table is reasonably shallow and local citizens are using
6 nearby wells, the groundwater pathway can be a main concern under the current no-
7 action condition. The air pathway can be an issue, for example, when the surface is still
8 contaminated with volatile compounds, when wind speeds are high enough to carry
9 contaminants in surface soil off-site, or when operating facilities with stacks are present.
10 Sites without operating facilities are not usually of concern for ambient air quality
11 or public health under baseline conditions. However, cleanup of these sites can be a
12 much different story. Air is considered the principal pathway by which the public could
13 be exposed to site contaminants during the cleanup period. To emphasize the
14 importance of evaluating risks associated with possible cleanup measures for both
15 workers and the public, the following discussion illustrates cumulative considerations for
16 the air pathway during the cleanup period for a contaminated site. Many of the same
17 general concepts discussed here would also apply to the assessment of the
18 groundwater pathway. A number of tools that may help evaluate the groundwater
19 pathway are included in tables within Appendix A.
20 Several cleanup alternatives are typically evaluated for contaminated sites,
21 ranging from no action (the baseline case) to various actions that can include
22 excavating soil and waste, decontaminating and demolishing buildings, treating wastes,
23 and transporting them for disposal, all of which involve airborne releases. Thus, for the
24 cleanup period, air contamination is typically a community's major environmental
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1 concern. The basic steps of an air pathway analysis for a cumulative assessment are
2 summarized in Text Box 3-12. Results are ultimately used to guide emission control
3 strategies to minimize impacts. In assessing this pathway, emission rates are estimated
4 for site-related sources and air
5 dispersion is modeled to predict the
6 amounts and possible distributions
Basic Steps for Cumulative Air Analysis
(Text Box 3-12)
1. Create an emissions inventory for multiple sources
2. Model air dispersion for multiple chemicals
3. Estimate exposures for receptors (to translate to risks)
7 of multiple contaminants at locations '
8 of interest, which typically include the site boundary and representative receptor
9 locations such as homes or schools.
10 Of course, actual measurements of particulate and multiple airborne chemicals
11 would best characterize current site conditions, however, a comprehensive air
12 monitoring program is extremely expensive and accuracies decrease near the threshold
13 of detectability, which is often the level of interest for environmental projects. Thus,
14 measured data are usually limited and air quality models must be applied to assess
15 impacts. Uncertainties related to air modeling are thought to be acceptable when
16 considering the high cost of monitoring.
17 These models combine relevant meteorology data with site emission estimates to
18 mathematically simulate atmospheric conditions and calculate where and when
19 released contaminants will reach receptor locations, as well as where and how much
20 particle deposition will occur. Even when some data are available, monitoring will never
21 be able to measure concentrations for all chemicals at all locations. Therefore, modeled
22 estimates will be needed to fill those gaps. Models can also determine impacts of one
23 source from among many (source attribution) and forecast how concentrations will
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change if a given emissions source is modified. In addition, air dispersion modeling is
the only way to assess impacts from
sources that do not yet exist. They are
valuable tools for assessing potential
impacts associated with both existing
Benefits of Dispersion Models (Text Box 3-13)
Fill gaps in monitoring data to predict levels & co-
locations of combined chemicals from site releases
Avoid detectability constraints, high monitoring costs
Identify contributing sources to joint concentrations
Project impacts from new facilities being considered
emission sources and those projected during the cleanup period. Their benefits are
summarized in Text Box 3-13. Illustrative information to guide the development of
emission inventories for a cumulative assessment at a contaminated site is offered in
Section 3.4.1, and information to guide dispersion modeling for these sites is given in
Section 3.4.2.
3.4.1. Emission Inventories. Cleanup of a contaminated site can involve many
different sources of emissions. Various source configurations and examples are point
(incinerator stack), area (waste
impoundment or pile), volume (water
treatment facility), and line (road).
Some sources are stationary while
others are mobile. Common emission
sources at these sites are summarized
in Text Box 3-14. At many sites,
distinct areas of contamination can
contain different combinations of
chemicals at different concentrations.
Multiple Emissions during Cleanup
(Text Box 3-14)
Fugitive dust from mechanical disturbance of soil by
heavy construction equipment during excavation
(scaled to chemicals/concentrations at each area)
Dust emissions from construction and material/waste
transportation vehicles
Contaminant emissions from on-site treatment systems
(such as an incinerator or air stripper)
Windblown dust from cleared areas (when threshold
wind speed is exceeded)
Emissions of volatile and semivolatile organic
compounds due to soil disturbance (otherwise trapped
in subsurface soil pore spaces, migrating only slowly)
Particulates and mixtures exhaust from diesel-burning,
heavy construction equipment (bulldozers, front-end
loaders, field generators) and transport vehicles
For cumulative assessments it is important to clearly group the chemicals at each
source area so they can be appropriately scaled to the fugitive emissions estimated for
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1 that source. This will assure that the model projects the appropriate chemicals and
2 concentrations from that source at the receptor locations, and it will enable the
3 combined chemicals at those receptor locations from multiple sources to be back-
4 tracked to the originating source and activity.
5 Emission factors are developed for these activities, but they do not provide any
6 information on the temporal or spatial patterns of releases nor on the greatest potential
7 emission source, which is needed to develop effective control measures. That
8 information is developed at the next step when emission estimates are used in the air
9 dispersion models. To guide the development of emissions inventories for many
10 situations including contaminated sites, the Agency has developed a number of
11 databases and methods. The Air/Superfund series provides considerable coverage of
12 topics and methods, including an overview of air assessments, estimation of emissions
13 from baseline and cleanup activities, and ambient air monitoring and modeling. Specific
14 types of emissions that would be
15 grouped in a cumulative (Text Box 3-15)
Information Resource
16 assessment are also discussed,
17 such as emissions of volatile
18 and semi-volatile compounds
Emission Factors for Multiple Sources
Emissions EPA Technology Transfer Network, AP-42
from point and (www.epa.gov/ttn/chief/ap42/index.html)
area sources
Methods to Air/Superfund National Technical Guidance Study
assess Series
specific (www.epa.gov/ttn/amtic/files/ambient/other/airsuper/
emissions superfnd.txt)
19 from disturbed SOil. Key Estimation EPA Clearinghouse for Inventories and Emission
software Factors (CHIEF) (www.epa.gov/ttn/chief/)
20 resources are highlighted in Text
21 Box 3-15. Users of these and similar information sources should characterize whether
22 they likely lead to an overestimate, underestimate, or central tendency estimate of the
23 emissions from these sources.
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Of special interest for cumulative assessments are exposures to chemical
mixtures. Notably for site workers, engine emissions from equipment and vehicles
represent such a chemical mixture since
diesel exhaust is considered a chemical
mixture for which some toxicity information
exists (see Chapter 4). These and other
mobile source emissions can be evaluated
using tools developed by EPA, as
summarized in Text Box 3-16. As noted
for Text Box 3-15, users should
characterize their confidence in emissions
estimates developed from sources, such
as those cited in Text Box 3-16.
Although these tools do not
Mobile Sources and Multiple Chemicals
(Text Box 3-16)
Source Type:Model Emissions Estimated
On-road mobile
MOBILE62:
www. epa. gov/otaq/
m6.htm
Criteria pollutants (sulfur
dioxide, nitrogen oxides,
carbon monoxide, PM10,
PM2.5, lead);
hydrocarbons; carbon
dioxide; ammonia; & six
toxics (benzene; methyl
tertbutyl ether; 1,3-buta-
diene; formaldehyde;
acetaldehyde; acrolein).
Non-road mobile Criteria pollutants and
(vehicle/ equipment hydrocarbons
engines): NONROAD
www. epa. gov/otaq/
nonrdmdl.htm
Mobile, toxic Fraction-specific
fractions of emissions for speciated
hydrocarbons (e.g., hydrocarbons
engine exhaust) ftp://ftp.epa.gov/pub/Emislnve
n tory/fin aln ei99ver3/criteria/
www. epa. gov/ttn/chief/ documentation/nonroad/99no
net/1999inventory.html nroad_vol1_oct2003.pdf
consider interactions among chemicals, hydrocarbon fractionation is included. By
accounting for that specific input in the exposure assessment, component toxicities can
be assessed with mixtures approaches that consider relative potencies (discussed in
Chapter 4).
In many cases the particulate releases will dominate and other criteria pollutants
will be negligible. For that situation a screening worst-case analysis could be conducted
for those other pollutants to assure that estimated maximum impacts are captured in the
analysis, integrated with the other projections, and presented to decision makers and
stakeholders. If this approach showed that the other pollutants likely posed little risk to
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1 the population, then this approach would lead to an increase in the attention given to the
2 particulates.
3 Both contaminated and uncontaminated particulate matter (PM) may be released
4 during site cleanup activities. The former can be released when contaminated materials
5 are excavated and staged in stockpiles and then treated in an on-site operation or
6 placed for transport or disposal. Uncontaminated emissions can be associated with
7 excavating local borrow soil (used for filling, mostly sand and gravel) and backfilling and
8 re-grading areas that are excavated on-site, or with transporting project materials
9 (including treatment supplies) on paved or unpaved roads.
10 Both types of releases are
13 to consider in grouping PM and
14 associated chemicals for these
15 assessments are summarized in
16 Text Box 3-17. Contaminated or
Comparison of PM Properties (Text Box 3-17)
Characteristic PM10:<10 urn PM2.5: <2.5 urn
11 addressed in a cumulative , x. . U1 ,,: ,~~~
Relative weight Heavier Lighter
12 assessment. The characteristics Airborne time Minutes to hours Days to weeks
Travel distance in air 100 yards to Farther, to
(depends on wind speed 30 miles 10Os of miles
atmospheric stability) (~ I ike a gas)
Movement in airway Impinge on sides, Pass through
after being inhaled wedge in narrow small airways,
passages deeper in lung
Ratio of surface area to Lower Higher
volume, relative potential
for adsorbed toxics
Associated toxicity Generally lower Often higher
17 not, inhaled particles can affect human health as with asthma (see Chapter 4 for the
18 toxicity discussion). Of course the multiple chemicals such as metals or organic
19 compounds attached to particle surfaces or incorporated into the matrix are of specific
20 interest for their joint toxicities.
21 Fugitive emissions during cleanup can be estimated by considering these three
22 factors: (1) total mass of material handled (based on the estimated volume and density),
23 (2) total number of activity hours (e.g., for bulldozing or scraping), and (3) total number
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1 of vehicle miles traveled (e.g., by dump trucks). In defining the mass handled, for
2 cumulative assessments it is important to consider what materials are being combined
3 together so representative concentrations of those materials can be appropriately
4 grouped and scaled to the estimated emissions. For the second factor, production rates
5 for each equipment are taken from standard reference sources (such as the Caterpillar
6 handbook) then combined with the mass
7 handled (determined for the first factor) to
8 estimate the activity hours. Examples of
additional factors used to estimate the
10 emissions inventory for fugitive dust are
11 given in Text Box 3-18.
12 Further, at many sites the
Example Participate Factors (Text Box 3-18)
Fugitive dust emissions can be estimated using a
lumped emission factor for heavy construction
activities, which is given as 1.2 tons total
suspended particulates (TSP) per acre per month
of activity. To estimate PM10 and PM2.5
emissions, respective particle size multiplication
factors of 26% and 3.8% can be applied to the TSP
for unpaved roads, considering that equipment
traffic over temporary roads at construction
(cleanup) sites are major dust emission sources
(U.S. EPA, 1995a, Chapter 4). A similar lumped or
grouped approach could also be considered for
emissions from contaminated areas.
13 contaminated source areas will be widely scattered. Thus, in estimating fugitive
14 emissions for cumulative assessments it is useful to consider when different areas will
15 be addressed so the emissions estimated for activities conducted in the same time
16 period can be appropriately grouped for joint evaluation in the dispersion modeling.
17 To illustrate how site-specific information can be reflected in an exposure
18 assessment, the construction plan and schedule for cleanup activities are often
19 available in general contractor plans, as well as information on expected equipment,
20 based on preliminary engineering estimates. These data can be used to select
21 emission factors for those specific unit operations per construction phase (see
22 U.S. EPA, 1995a, Chapter 4).
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1 3.4.2. Dispersion Modeling. The Agency has developed guidelines for air quality
2 modeling and has made many air dispersion models available within two general
3 categories: screening and refined. (These can be obtained via the EPA Support Center
4 for Regulatory Air Modeling www.epa.gov/scram001, as indicated in Appendix A.)
5 Screening models involve relatively simple estimation techniques and generally use
6 preset, worst-case meteorological conditions to produce conservative estimates of the
7 air quality impact of a specific source or source category. They are used instead of
8 more detailed (and more expensive) models to assess sources that clearly will not
9 cause or contribute to ambient concentrations above any of the following:
10 ambient standards (such as the National Ambient Air Quality Standards
11 [NAAQS] or Prevention of Significant Deterioration (PSD) levels)
12 health criteria (such as threshold limit values [TLVs] or permissible exposure
13 limits [PELs]) developed for daily workplace exposures, or
14 risk-based public health guidelines.
15 If results of conservative screening analyses indicate that multiple chemical
16 concentrations from one source or a combination of sources might not meet ambient
17 standards and health criteria, then refined models would be applied for a more
18 representative assessment.
19 Refined models include methods to address physical and chemical atmospheric
20 processes, and more detailed input data produces more site-specific estimates. These
21 two levels of modeling are often paired, with a conservative screening approach used
22 first to eliminate contributors that clearly do not pose a concern in the cumulative
23 context, followed by a more refined analysis. However, for many situations the
24 screening models are practically and technically the only viable option for estimating
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Air Dispersion Model Inputs (Text Box 3-19)
Source characteristics: Emission data scaled for
multiple chemicals by source, location, type, and
geometry (for type and geometry, (1) point: stack
height and diameter, stack exit temperature, and exit
velocity; (2) area: length and width, release height, and
initial vertical dimensions; (3) volume: release height,
and initial lateral and vertical dimensions)
Data for nearby buildings, to address downwash effects
Meteorological data, for both surface and upper air
Topographic information for sources and receptors
Model control options (e.g., for dust control efficiency)
1 impacts of multiple sources with
2 multiple chemicals. In those cases, it
3 is especially important to ensure that
4 input data are sound. (These issues
5 are discussed a bit later when specific
6 models are discussed.) Inputs to the
7 model are summarized in Text
8 Box 3-19.
9 Air dispersion models are not designed to address certain cleanup activities. For
10 example, they do not directly model dispersion from specific contaminated soil
11 excavations, as emissions can only be estimated for a select set of standard source
12 types (point, area, volume, and line). For this reason, some simplifications and
13 modifications are usually needed to approximate characteristics of emission sources
14 using engineering judgment, so they can be considered generally representative of
15 actual site conditions.
16 Before beginning the calculations for a cumulative assessment, emission sources
17 should be identified and grouped into a manageable number of sources and types for
18 the modeling effort. To illustrate, air strippers, incinerators, and in-situ vapor extraction
19 units would be grouped as point sources, while lagoons or surface impoundments would
20 be grouped as area sources, conveyor belts or material dumping would be volume
21 sources, and mobile (vehicle) emissions along haul roads would be line sources. The
22 geometries of these emission sources also serve as inputs to the model.
23 The presence of nearby buildings is also of interest for cumulative analyses,
24 notably when addressing stack releases from existing facilities or those predicted from a
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1 facility being considered (e.g., incinerator for site wastes). Turbulent wakes downwind
2 of structures can affect concentrations of stack releases in the vicinity, especially when
3 the stack height is not much taller than the building. This phenomenon, referred to as
4 building downwash, generally tends to increase maximum ground-level concentrations
5 of pollutants because it brings part of the stack effluents to the ground near the source
6 (instead of their being carried at a height to a farther distance from the stack).
7 Compared to when there are no buildings nearby, downwash changes the location of
8 the maximum pollutant concentrations as well as the spatial distribution of the
9 concentrations, in particular for near-field receptors (e.g., within several miles). Thus,
10 estimated pollutant levels can differ considerably depending on whether the model
11 considers nearby buildings, and this can affect estimates for nearby receptors.
12 Additional considerations for modeling
13 releases of multiple chemicals from a
14 stack and for assessing impacts of
15 multiple sources at multiple receptor
16 locations, are indicated in Text
Example Model Input Considerations
(Text Box 3-20)
When the height of a stack for an existing or planned facility
is lower than suggested by good engineering practice (GEP),
building downwash should be considered. (The GEP stack
height is 2.5x the building height for common configurations,
i.e., for buildings wider than they are tall; the actual formula is
the height plus 1.5x the lesser of the structure height or
projected width.) To account for terrain elevation effects,
elevation data for multiple emission sources and receptors
are also needed.
17 Box 3-20 (from U.S. EPA, 1985).
18 For the air dispersion model to produce relevant results, the meteorological data
19 inputs must represent site conditions. Some sites have meteorological towers (such as
20 larger federal research/industrial sites), but in many cases meteorological data are
21 taken from National Weather Service stations. To define the array of receptor points for
22 which concentrations of released contaminants will be predicted, a receptor grid is
23 developed for the model. These inputs are highlighted in Text Box 3-21.
24 Also important is the nature of the input data used to define the concentrations of
25 multiple chemicals at the receptor locations of interest. In some studies, data from an
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1 emissions database are used (e.g.,
2 TRI data). Because these do not
3 represent ambient levels from which
4 exposures can be estimated, it is
5 useful to indicate what proportion of
6 input data is from that database
7 versus other information sources
Meteorological and Receptor Data (Text Box 3-21)
Meteorological data: the station selected to represent the site is
based on similar spatial characteristics regarding terrain features,
land use, and synoptic flow patterns. Typically, hourly surface and
twice-daily upper air data are available from the National Climatic
Data Center, NCDC (www.ncdc.noaa.gov/oa/ncdc.html)', data for
1984-1992 for selected National Weather Service stations are
available from EPA's Support Center for Regulatory Air Models,
SCRAM (www.epa.gov/scram001/tt24.htm).
Two types of receptors are assessed: discrete and gridded.
Discrete receptors generally represent where people actually are
(e.g., in homes or schools), or monitoring stations, or places on
the site boundary or property line that could be accessed by the
public. Hypothetical gridded receptors are used to identify where
maximum concentrations of multiple chemicals are predicted.
8 that are more relevant to exposure concentrations. Implications for the results should
9 be addressed in the uncertainty discussion (see Chapter 5). Similarly, when monitoring
10 data are used, it is helpful to indicate their relevance to exposure point concentrations,
11 for example to identify what subset reflects ambient measurements and at what height
12 those measurements were made, e.g., on rooftops, at ground level, or within the
13 breathing zone (on the order of 2 m), along with some discussion of data quality.
14 A model commonly used for conservative screening analyses is the steady-state
15 Gaussian model SCREENS (available at www.epa.gov/scram001 /tt22.htm#screen).
16 This model estimates 1-hour ambient concentrations from only one source (point, area,
17 or flare), but it can address many combinations of wind speed and atmospheric stability
18 class. Its main benefit is that it is quick and easy to use. It runs interactively on a
19 personal computer to calculate 1-hour maximum ground-level concentrations (but not
20 24-hour estimates for complex terrain), as well as the distance to the maximum
21 concentration from the single source.
22 In order to apply this model for multiple release points, some combine these
23 multiple emission sources to be represented by a single theoretical point. In that case,
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1 the basis should be justified with setting-specific information, including relative proximity
2 to other sources and to receptors, and relative impact (insignificance) for predictions at
3 those receptor locations. While this simplifying approach is quite appropriate when
4 emission sources are far from potential receptors, it can lead to inaccurate results if the
5 site is near a populated area.
6 A key disadvantage is that because of its conservative assumptions, it can
7 generate quite unrealistic results, e.g., highly conservative values that expectedly would
8 never be measured. The fact that this model for cumulative assessments cannot
9 consider multiple sources, actual meteorological data, or averaging periods other than
10 an hour is another disadvantage. Predicted short-term concentrations are used to
11 assess acute effects, while long-term concentrations are used to assess chronic effects.
12 Thus, SCREENS results for the 1-hour period must be manually converted to other
13 averaging times, and contributions from multiple sources must be combined to address
14 cumulative issues.
15 To illustrate how this averaging time adjustment is made, multiplication factors
16 are given in Text Box 3-22 (from U.S. EPA, 1992b). These scaling factors are
Factors to Adjust 1-Hour
Averages to Other Times
(Text Box 3-22)
17 recognized as conservative and could overestimate impacts
18 by 2 to 10 times. (The actual magnitude of the overestimation
Time Factor
19 is unknown and likely depends on site and source 3 hours 0 g ,± 0 -
20 characteristics.) When a model produces unrealistic
24 hours 0.4 (+0.2)
21 estimates, the generalizing assumptions should be revisited
annual 0.08 (+0.02)
22 and replaced with more situation-appropriate inputs (for example, releases might initially
23 have been assumed to be ground-level rather than stack or exit height from the
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1 building). In this way the assessment is iterated from an overly conservative but quick
2 and cheap screening approach to a more representative but resource-intensive
3 approach as warranted to produce realistic results that can be used for the decisions.
4 Refined dispersion models are used when more detailed analyses are needed.
5 These include steady-state Gaussian plume models such as ISC3-PRIME or AERMOD,
6 which require relatively intensive efforts and computer resources. (They are available at
7 www.epa.qov/scram001 /tt26.htm#iscprime, www.epa.qov/ttn/scram/tt26.htmffaermod.J
8 The main advantage of these models for cumulative assessments is that they can
9 simultaneously evaluate a large number and different types of emission sources to
10 estimate particulate (and scaled multiple-contaminant) levels over a wide range of
11 averaging times, to address exposure periods from acute (e.g., for 1, 3, 8, and
12 24 hours) to annual time frames. Concentrations of multiple chemicals at different
13 receptor locations can be attributed to specific sources by setting up source groups for
14 each model run and identifying contributions from a given source within that group.
15 These refined models improve upon the screening models for cumulative
16 assessments by including dry and wet deposition algorithms, thus producing estimates
17 that can be used to assess multiple pathways (by providing deposition estimates rather
18 than being limited to inhalation). However, they still do not account for chemical
19 reactions because chemicals are essentially assessed one at a time and then results
20 are combined. However, some models do account for changing concentrations for an
21 individual chemical overtime by incorporating exponential decay. A general comparison
22 of the capabilities of screening and refined models for cumulative risk assessments is
23 offered in Text Box 3-23.
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1
2
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8
9
10
11
12
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16
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18
19
20
21
22
23
Model Capabilities for Cumulative Air Analyses
(Text Box 3-23)
Scope
Multiple
chemicals
Multiple
sources
Multiple
pathways
Screening Model
Refined Model
One at a time Yes, combined, and as
(individual runs) scaled to particulates
One at a time [ Yes, many of different
(individual runs) \ types, simultaneously
No, just provides I Yes, because also
estimates for air estimates deposition
Multiple time No, only 1-hour Yes, 1-hourto annual
periods
Source
attribution at
receptors
Changes
over time
Chemical
interactions
averages
No
No
No
averages
Yes, from the grouped
sources contributing to
pollutants at those points
Some cover attenuation
(for individual chemicals)
Not for metals and
organics at sites
(only ozone, acid rain)
Realistic No, conservative Yes, as constrained by
predictions concentrations relevant data availability
In general, steady-state
Gaussian models are not used for
areas beyond 50 km (30 mi)
because the steady-state
assumption does not hold. For
large study areas, dispersed
concentrations can be estimated
using models that can simulate
regional-scale, long-range
dispersion as well as local-scale,
short-range dispersion, e.g., the
non-steady-state Lagrangian puff
models such as CALPUFF (available at www.src.com/calpuff/ calpuffl .htmj. For areas
covering thousands of kilometers, Eulerian models such as the Community Multi-scale
Air Quality (CMAQ) modeling system would be used (see
www.epa.gov/asmdnerl/models3/J. This model was designed to address overall air
quality considering multiple inputs, but it is very labor-and resource-intensive; the
amount of computer time needed is much longer than for steady-state Gaussian
models, so these models would probably not be appropriate for most site assessments.
As a note, CMAQ does address chemical reactions but these are only for ozone and
acid rain, not air toxics. The source code would have to be modified to add algorithms
for chemical processes for the contaminants of interest at a given site to account for
those potential interactions.
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1 Certain site studies might consider other point sources that could contribute to
2 cumulative air impacts, either as assessed by the project team or in a complementary
3 assessment. Some analyses have considered generic distances within which
4 dispersion is to be assessed; some recent studies have indicated a distance of 20 km
5 (12.5 mi); a generic radius of 80 km (50 mi) has historically been used in environmental
6 impact assessments. However, this potential impact radius should be determined from
7 setting-specific features (including meteorology, terrain, and nature of emissions) that
8 affect the area over which airborne releases will travel. The dispersion model itself can
9 be used to define an appropriate study distance, by identifying a target level and
10 determining at what distance that target would be reached. This could be some fraction
11 or percent of background (e.g., 10%) or of the initial release, considering associated
12 health effects.
13 3.5. SUMMARY COMPARISON AND SCREENING SUGGESTIONS
14 A general comparison of the exposure assessment process conducted for basic
15 health risk assessments and for cumulative exposure assessments is summarized in
16 Text Box 3-24.
17 As this summary shows, the basic topics and outcomes are the same. The
18 cumulative column simply highlights additional attention that would be paid to certain
19 features in explicitly considering cumulative risk issues. Cumulative risk assessments
20 evaluate aggregate exposures by multiple pathways, media, and routes over time, plus
21 combined exposures to multiple contaminants from multiple sources.
22 Practical suggestions that can be considered in conducting the exposure
23 assessment for cumulative health risk assessments at these sites are offered below,
24 with an emphasis on screening for grouped evaluation.
25
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Comparison of Exposure Assessment Processes (Text Box 3-24)
Basic Assessment Cumulative Assessment
What general question is being addressed?
How could people be exposed to chemicals, ] Similar, but emphasizing combined source
what would the amount of exposure be? | contaminants and cumulative exposures
What is evaluated?
...... 0 , . , . . . Emphasis on combined sources/re eases (sources may
ndividua Sources/re eases of chemicas ."I . , .. ., . v y
not be bcated in community)
Behavior o, Individua, charts in ,he
environment (transport/fate) i , , . . .
v K ' \ sets of chemicals
Concentrations of chemicals at points of Emphasis on sets of chemicals that coexist initially and
human contact those that move together
r, i u « , , .... Representative receptors as for the basic case, paying
People who represent current conditions P sensitive subgroups and unique exposure
and likely future land use activitjes (e g pep
Routes by which people could be exposed to | Emphasis on combined chemicals and routes over
each chemical \ time, considering sequencing
Amoun, o, each chemica, taKen in over time *"""
How are results used?
.- .. . .. . . .. . . ... . . .. I Estimated intakes are considered in groups to guide
Estimated intakes are linked with toxicity | ^ J J
information to assess potential harm j potentiaf;ea|th harm
3 * Implementing existing guidance, which identifies many cumulative risk issues, is
4 enhanced by more explicitly acknowledging joint evaluations and at least
5 qualitatively indicating the potential for interactions to define groupings.
6
7 * An initial conservative screening of relative risks can be conducted to identify the
8 sets of contaminant sources, receptor locations, and pathways to be analyzed in
9 detail. Focus on grouping the chemicals, affected media, and exposure points
10 that are expected to contribute to combined pathway exposures for those
11 receptors, considering media and time frames.
12
13 * Because relatively few major sources might account for most of the hazards
14 associated with a site, focus first on the main sources especially when resources
15 are constrained. However, following that initial focus iterate through the
16 assessment process to assure that cumulative exposure issues have been
17 appropriately considered.
18
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1 * In modeling chemical transport and fate, account for environmental
2 transformation overtime (including mixtures), and adapt transport/dispersion
3 models to account for multiple chemicals, e.g., scaling to source concentrations
4 for those chemicals moving together, and defining source attributions at multiple
5 receptor locations.
6
7 * In developing groupings for chemicals and exposure pathways, focus on the
8 potential for relatively high exposures to sensitive populations and possible
9 contribution to induction of health effects that already exist at relatively high
10 levels in the study population, in addition to those with high inherent hazard
11 (toxicity) in combination with the amount present; potential interactions with other
12 chemicals; and tendency to persist, bioaccumulate, and/or be transported
13 between environmental media.
14
15 * To screen potential vulnerable or susceptible subgroups into the enhanced
16 cumulative assessment process, pursue existing data such as indicator
17 information in demographic studies and health registries.
18
19 * Consider the total exposure context to evaluate whether contributions from site
20 contaminants combined with existing body burdens might exceed levels that are
21 expected to be safe. For stakeholders desiring a more explicit assessment of
22 total exposure, to cover chemicals not related to the site, indicate information
23 resources that can be used to guide such a complementary assessment.
24
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1 4. CUMULATIVE TOXICITY ASSESSMENT
2
3 This chapter provides detailed information on the cumulative toxicity assessment
4 issues that are described in Chapter 2. The goals of Chapter 4 are to define cumulative
5 toxicity assessment (Section 4.1), summarize existing U.S. EPA guidance for
6 conducting toxicity assessments, including chemical mixtures risk assessments (Section
7 4.2), and then expand those ideas to include cumulative risk issues. These additional
8 issues include multiple route exposures at various time frames (Section 4.7), the value
9 of pharmacokinetic information in evaluating internal co-exposures (Section 4.3),
10 consideration of secondary and tertiary effects (Section 4.5), and the impact of chemical
11 interactions on cumulative risk (Section 4.6). A flow chart is presented in Section 4.4 for
12 the purpose of facilitating and organizing the risk assessor's effort to evaluate toxicity
13 groups for cumulative toxicity risk assessment. The goals of the approach presented in
14 this chapter are to provide a way to group chemicals by their potential for joint toxic
15 action as a refined classification of the cumulative exposure groups (developed in
16 Chapter 3) and then to provide cumulative risk assessment methods for addressing
17 multiple toxic effects, multiple exposure routes, and toxicological interactions for
18 chemical mixtures. The result is the identification of chemical groups (and single
19 chemicals) that should be evaluated for a particular population, including vulnerable
20 subpopulations.
21 This chapter presents a number of approaches, some of which can be easily
22 implemented with existing data and published methods and some of which would be
23 resource intensive in terms of data collection and analysis. They are all shown here in
24 the interest of advancing the field of cumulative risk assessment and for the purpose of
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1 providing the Agency with readily available, scientifically sound cumulative risk
2 assessment methods.
3 4.1. DEFINING CUMULATIVE TOXICITY ASSESSMENT
4 Toxicity assessments that support cumulative health risk assessments evaluate a
5 population's potential to develop adverse health effects from exposures to multiple
6 chemicals through multiple routes of exposure over time. As discussed in Chapter 2
7 (see Figure 2-1), cumulative risk assessment emphasizes a community focus where the
8 population may be exposed to multiple stressors, potentially from multiple sources.
9 Thus, information developed in the initial assessment phase regarding the population
10 profile is important to the ensuing toxicity assessment, including considerations related
11 to vulnerability (i.e., susceptibility/sensitivity, differential exposure, differential
12 preparedness, and differential ability to recover). In addition, such assessments may
13 need to consider the potential for multiple health effects to occur and for joint toxic
14 action from multiple route exposures to chemical mixtures. Timing and intensity of
15 exposures to different chemicals may need to be evaluated, including the evaluation of
16 internal co-occurrence of multiple chemicals and toxicological interactions in the target
17 tissue(s).
18 4.2. U.S. EPA TOXICITY ASSESSMENT GUIDANCE
19 The general methods the Agency uses for toxicity assessment are detailed in a
20 number of risk assessment guidelines and guidance documents, as illustrated in Text
21 Box 4-1. The Agency Program Offices use these various documents to conduct
22 assessments and also to develop additional guidance and tools specific to their
23 respective media and sites. Information regarding toxicity assessment and many other
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
aspects of risk assessment can be found within the U.S. EPA's Web site
(www.epa.gov). For example, to supplement its primary guidance for site assessments
(U.S. EPA, 1989a), Superfund provides a set of tables to be used as templates for
conducting hazard index calculations (online at
http://www.epa.gov/oswer/riskassessment/ragsd/tables.htm).
Most of the documents providing risk assessment guidance (see Text Box 4-1)
focus on specific health endpoints such as cancer, mutagenicity, reproductive and
developmental effects, and neurotoxicity. These documents can be used in a
cumulative toxicity assessment to
evaluate their respective health
endpoints; the resulting information can
then be combined using guidance that
deals with cumulative risk issues such as
the Supplementary Guidance for
Conducting Health Risk Assessment of
Chemical Mixture (U.S. EPA, 2000a) or
the Methodology for Assessing Health
Risks Associated with Multiple Pathways
of Exposure to Combustor Emissions
(U.S. EPA, 1998a). Guidance also is
available for evaluating toxicological
mechanisms of action, including those
related to cumulative risk for pesticide
Selected Information Guides for Toxicity
Assessment (Text Box 4-1)
Risk Assessment Guidelines of 1986, including
chemical mixtures, mutagenicity, cancer, exposure
assessment, developmental effects (U.S. EPA,
1986, 1987)
Risk Assessment Guidance for Superfund
(U.S. EPA, 1989a)
Guidelines for Developmental Toxicity Risk
Assessment (U.S. EPA, 1991)
Reproductive Toxicity Risk Assessment Guidelines
(U.S. EPA, 1996a)
Guidelines for Neurotoxicity Risk Assessment (U.S.
EPA, 1998b)
Guidelines for Ecological Risk Assessment (U.S.
EPA, 1998c)
Supplementary Guidance for Conducting Health
Risk Assessment of Chemical Mixtures (U.S. EPA,
2000a)
Guidance on Cumulative Risk Assessment of
Pesticide Chemicals That Have a Common
Mechanism of Toxicity (U.S. EPA, 2002c)
Guidelines for Carcinogen Risk Assessment (U.S.
EPA, 2005f)
Supplemental Guidance for Assessing
Susceptibility from Early-Life Exposure to
Carcinogens (U.S. EPA, 2005g)
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1 exposures (U.S. EPA, 2002c) and for mechanisms of carcinogenicity (U.S. EPA, 2005f).
2 The assessment of vulnerable subpopulations is also addressed by Superfund in their
3 site assessment guidance (1989a) and specifically for children in a supplemental
4 guidance to the 2005 carcinogen risk assessment guidelines (U.S. EPA, 2005g). In
5 summary, there are a number of Agency resources that describe methods and
6 approaches that can be used to address various aspects of cumulative toxicity
7 assessments for community-based cumulative risk assessments.
8 4.2.1. U.S. EPA Practices for Evaluating Chemical Mixtures. The U.S. EPA
9 evaluates risks from exposure to chemical mixtures using peer-reviewed Guidelines
10 (U.S. EPA, 1986, 2000a) that identify both component-based and whole mixtures
11 methods (Figure 4-1). The selection of a method (e.g., Hazard Index, Relative Potency
12 Factors) depends on the availability of information on toxicological joint action and
13 chemical composition of the mixture. The simplest component-based methods utilize
14 single chemical exposure and dose response information to form a mixtures
15 assessment and are useful in comparing mixtures containing the same chemicals but in
16 various concentrations and proportions. Component-based methods include those
17 based on assumptions of response addition (toxicologic independence) and dose
18 addition (toxicologic similarity). These methods, however, do not directly address
19 interaction effects among components (i.e., effects greater than or less than those
20 observed under a definition of additivity). To address the latter concern, the Interaction-
21 Based Hazard Index method may be applied, using information on binary (pairwise)
22 interactions among chemicals in a mixture to modify its Hazard Index (see Section 4.6.2
23 for details on this method). The main toxicologic considerations for the component-
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
C Mixture
if Concern
Mixture
RfD/C;
Slope
Factor
Assess Data Quality
adequate
inadequate
Only Qualitative Assessment
SufficientlyX
Similar
Mixture /
Group of
Similar
Mixtures
/ ~~\ / ~\/ \
fToxicologically^ |^oxicologically^| ( |nteractjons ]
I Similar J I Independent J I J
Comparative
Potency
Environmental
Transformation
*
Hazard
Index
Relative
Potency
Factors
Response
Addition
Interactions
Hazard
Index
Compare and Identify Preferred Risk Assessment,
Integrate Summary with Uncertainty Discussion
FIGURE 4-1
Approach for Assessing Mixtures Based on the Available Data (U.S. EPA, 2000a)
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4-5
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1 based risk assessment methods used by U.S. EPA are then toxicologic independence,
2 toxicologic similarity, and pairwise interaction.
3 Whole mixture methods (e.g., mixtures reference doses, environmental
4 transformations) account for unidentified chemicals in a complex mixture and inherently
5 incorporate joint toxic action among chemicals. Dose response assessments based on
6 tests of whole mixtures or on epidemiological data determine combined effects
7 empirically. Examples of these (U.S. EPA, 2005c) include (1) Reference Doses on
8 commercial PCB mixtures (Aroclors 1016 and 1254) based on primate data and (2) a
9 cancer slope factor for coke oven emissions based on human occupational exposures.
10 Drinking water disinfection by-products represent a complex mixture for which
11 epidemiological data suggest potential health risks (U.S. EPA, 2003f). A U.S. EPA
12 study, called the 4-Lab project, is currently underway to toxicologically and chemically
13 characterize this complex mixture to produce data on reproductive and developmental
14 effects in rats exposed to concentrations of this complex mixture for use in risk
15 assessment (Simmons et al., 2002).
16 The usefulness to a cumulative risk assessment of toxicologic data on a whole
17 mixture depends strongly on how similar the studied mixture is to the environmental
18 mixture of concern (U.S. EPA, 2000a). The fundamental requirement for what is called
19 "sufficient similarity" is that the complex mixture being considered as a surrogate have
20 roughly the same major chemical components in approximately the same proportions as
21 the environmental complex mixture to be evaluated. Any additional information on
22 toxicologic similarity, i.e., data on similar health effects and dose-response relationships
23 for the two complex mixtures or their common components, may also be useful in
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1 establishing similarity. The U.S. EPA's mixtures risk guidance discusses several issues
2 with determining toxicologic similarity of two complex mixtures. For example, either the
3 Reference Dose (RfD) or cancer potency for a complex mixture can be determined by
4 treating the mixture as if it were a single substance and using the dose-response data
5 on that substance in the same fashion that single chemical dose-response data are
6 used. The main concern is that the mixture composition (relative proportions of the
7 component chemicals) remains fairly constant.
8 Cumulative risk assessments add layers of complexity to evaluation of the
9 complex mixture. For example, oral, dermal, and inhalation exposures may occur in the
10 same population over varying timeframes. Although a mixture risk assessment can be
11 conducted for each route of concern, methods for incorporating multiple route
12 exposures into a mixture evaluation are being developed. Unfortunately, multi-route
13 exposures to a complex mixture cannot be addressed by treating the mixture as a single
14 substance. The combination of route-specific whole mixture dose-response data for two
15 different exposure routes is complicated because of potential interactions between the
16 two routes for some components and because the relative contributions of some
17 components to the mixture toxicity can be different for the two routes.
18 Multi-route dose-response methods seem promising with use of mixture
19 component data. One method is to estimate internal doses using pharmacokinetic
20 modeling for each chemical separately for each route of exposure and combine these to
21 represent a combined internal blood or target organ tissue dose (Teuschler et al., 2004;
22 U.S. EPA, 2003g). Providing the effect of concern is not a portal of entry effect (e.g.,
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1 lung tumors for inhalation exposure), the combined internal dose can be used in the
2 toxicity assessment.
3 For this report, component based methods based on dose addition and response
4 addition are stressed as initial approaches for evaluating cumulative toxicity, with
5 modifications to accommodate multiple effects, multiple routes, and toxicologic
6 interactions. Dose addition and response addition are fundamentally different methods,
7 based on different assumptions of the toxicity. The two additivity assumptions are
8 briefly described in the following text. Extensive discussion of these mixture methods is
9 given in the Agency's mixture risk assessment guidance (U.S. EPA, 2000a).
10 Dose addition sums the doses of the components in a mixture after they have
11 been scaled for toxic potency relative to each other. The predicted mixture
12 toxicity is determined from this summed dose. Dose addition requires the
13 component chemicals to be toxicologically similar, i.e., to share a common toxic
14 mode of action (MOA). When dose addition is applied using an index chemical
15 to estimate risk, then the mixture components are required to have similarly
16 shaped dose-response curves for the endpoint being evaluated.
17
18 Response addition first estimates the probabilistic risk of observing a toxic
19 response for each chemical component in the mixture. Then, the component
20 risks are summed to estimate total risk from exposure to the mixture, assuming
21 independence of toxic action (i.e., the toxicity of one chemical in the body does
22 not affect the toxicity of another chemical). This can be thought of as an
23 organism receiving two (or more) independent insults to the body, so the risks
24 are added under the statistical law of independent events.
25
26 4.2.1.1. Dose Addition Superfund site assessments have applied dose
27 addition in the form of a Hazard Index (HI) to evaluate sites for indications of health risk
28 (U.S. EPA, 1989a). The HI is calculated as the sum of Hazard Quotients (HQs) for the
29 chemical components of the mixture. (Note the HI is not dependent on using an index
30 chemical to assess risk, so the components are not required to have similarly shaped
31 dose-response curves.) An HQ is typically calculated as the ratio of a chemical's
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1 exposure level to its safe or allowable level, such that values larger than 1 are of
2 concern. For a group of n chemicals in a mixture and using the RfD as a safe,
3 allowable level, the HI for oral exposure is calculated:
5 where:
6 E, = exposure level of the /th chemical
7 RfD/ = Reference dose of the /th chemical
8 A similar index for inhalation exposure uses the Reference Concentration (RfC) for the
9 allowable level. The HI is usually calculated for groups of chemicals whose effects are
10 observed in a common target organ. The HI is interpreted similarly to the HQ, i.e., the
1 1 more HI exceeds 1 , the greater is the concern for mixture toxicity. Note that the HI
12 provides an indication of risk but is not an explicit risk estimate.
13 To estimate actual risk, a slightly different approach based on dose addition uses
14 Relative Potency Factors (RPFs) for the dose scaling. Because the total dose of the
15 chemicals in the mixture is of concern, the chemical components of a mixture are scaled
16 for relative toxicity to an index chemical and summed to produce a total index chemical
17 equivalent dose. In this method, the total index chemical equivalent dose is evaluated
18 using the index chemical's dose response curve to estimate risk (see Section 4.7.1 .2 for
19 details). Note that the toxicity equivalence factors (TEFs), developed for dioxin
20 assessment, are a special case of the RPF approach (U.S. EPA, 1989b).
21 As an expression of dose addition, the formula for HI has three important
22 uncertainties (U.S. EPA, 2000a). These include:
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1 1) The assumption of common MOA might not apply because only commonality of
2 the target organ is considered.
3 2) The use of a safe level, such as a lower bound on the toxicity threshold, might
4 not be an accurate measure of toxic potency. Weak toxicity data usually result in
5 a lower safe level because of larger uncertainty factors or use of lower
6 confidence bounds on dose.
7 3) The use of RfDs as safe levels may result in an overestimate of the degree of
8 concern because the RfD is based on one critical or most sensitive effect. Thus,
9 when a chemical causes multiple effects and needs to be included in more than
10 one HI calculation, the general use of its RfD is problematic. A solution is to
11 generate Target organ Toxicity Doses (TTD) (derived for each target organ of
12 concern using RfD methodology) for use in target organ specific HI calculations
13 (Mumtaz et al., 1997; U.S. EPA, 2000a).
14 Appropriate interpretation of the HI requires fairly detailed understanding of the
15 individual chemical's dose-response curves, the nature and commonality of the toxic
16 effects, and the quantitative relationship between the effect of concern and the critical
17 effect.
18 4.2.1.2. Response Addition Toxic effects described by the proportion of
19 exposed animals showing toxicity are often determined for mixtures using response
20 addition. For example, the probabilistic risk of cancer in a given dose group is typically
21 estimated by the proportion of responders in that group. One can then estimate total
22 cancer risk from a mixture by summing the individual cancer risks for the carcinogens in
23 the mixture (U.S. EPA, 1989a). For a two chemical mixture, the mixture risk (Rm) is the
24 sum of the risks for chemical 1 (r?) and chemical 2 (r2) minus the probability that the
25 toxic event from exposure to chemical 1 would overlap in time with the toxic event from
26 exposure to chemical 2, as expressed in the following equation:
27 Rm=r1+r2-(r1xr2) (4-2)
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1 Risks are appropriately aggregated for cancers across various target organs because
2 the result is interpreted as the risk of any cancer, and the cancers from each chemical
3 component are considered to be independent events in the body.
4 The applicability of both dose addition and response addition can be evaluated
5 by appropriate toxicity testing that produces dose-response data for the whole mixture
6 and its component chemicals. Any use of the additivity formulas to obtain estimates of
7 mixture toxicity extrapolated beyond the range of actual mixture data should be
8 accompanied by a description of the evidence supporting the additivity assumptions,
9 i.e., commonality of toxicity for dose addition and toxicologic independence for response
10 addition.
11 4.3. TOXICOLOGY OF INTERNAL CO-OCCURRENCE
12 This section communicates the importance of understanding tissue dosimetry of
13 compounds, as opposed to understanding the human exposure to them in the
14 environment. Toxicity is a function of the contact between a contaminant chemical and
15 its biological receptor, located in target tissues. Because of the complex nature of
16 biochemical and physicochemical factors governing chemical disposition in the body,
17 measures of environmental contact are insufficient to completely describe internal
18 disposition of chemicals in the human body and the temporal description of the toxic
19 sequella, including events that may modify the internal dosimetry of subsequently
20 encountered contaminants. At present, there is no Agency guidance on best practices
21 of this type of activity, though several related efforts are underway.
22 Toxicity assessment involves understanding and mathematically describing the
23 relationship between exposure (dose) and effect (response). This relationship may be
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1 quantified at several levels of specificity (Figure 4-2). At its most fundamental level, the
2 end result may only be hazard identification, the ability to link an exposure with an
3 adverse outcome, where the data are insufficient to inform an understanding of the
4 dose-response relationship. The next level of detail involves knowledge of the
5 concentration encountered in the environment, or in the cases of most toxicity studies,
6 the administered (not the internal) dose. Increasing the level of sophistication requires
7 knowledge of the internal dose of the parent compound and is the first level at which
8 consideration of pharmacokinetic principles must be employed. The final two levels of
9 complexity require solid understanding of pharmacokinetic conditions and allows the
10 internal dose to be translated first to concentrations of the parent compound in the
11 target tissues and ultimately to concentrations of the toxicologically active chemical
12 species (parent or metabolite) in the target tissue. This final level of specificity requires
13 knowledge of whether the compound is toxic in its parent form or as a metabolite. Thus,
14 doses, and specifically internal doses, may be considered at different levels of
15 specificity, and each is useful and differentially resource-intensive.
16 Because of the compound-specific nature of their disposition in and elimination
17 from the body, not every compound contained in the same contacted environmental
18 medium will remain in the tissues of the body for the same duration. Thus, for one
19 chemical a given exposure may result in prolonged retention and protracted tissue
20 exposure whereas a different compound encountered in the same environmental
21 medium may be quickly eliminated following exposure. The toxicity analysis should
22 summarize information demonstrating the biological longevity of contaminants to
23 determine potential overlap of tissue concentrations (Figure 4-3, also discussed from an
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1 Compound
> Toxicity
_ . Environmental
2 Compound-* Concentration
Toxicity
3 Compound
Environmental_
Concentration
Internal Dose
(Parent)
Toxicity
Environmental
4 Compound-* concentration'
Internal Dose
(Parent) ~
Tissue Dose
(Parent)
Toxicity
i
2
5 Compound
Environmental
Concentration
Internal Dose
(Parent)
Tissue Dose
Toxicity
(Active Chemical Species)
4
5
6
FIGURE 4-2
Level of Specificity for Dose-response Relationships
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Whole
Body
Cr(lll)
Cr(VI)
Tritium
Dose
Absorption
n+n=°-5%
Urine
Feces
Dose
Metabolism toCr(lll)
Absorption
Dose
Absorption and Incorporation
3H - body water
3H - organically bound
10
i
100
I
1000
I
10000 hours
i
0.42
4.2
42
420 days
FIGURE 4-3
Human Residence Time for Selected Contaminants
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1 exposure perspective as Figure 3-13 in Chapter 3), again focusing on doses or
2 exposures most similar to the anticipated environmental exposure. Compounds
3 encountered at the same time from different media and through different routes may
4 have similar or markedly different internal exposure profiles, depending on the
5 compound. It is important to relate either of these situations to the potential for
6 overlapping internal dose as each defines a concurrent exposure. Information on the
7 tissue dosimetry of single chemical exposures and information identifying sensitive
8 tissues/organs and interaction with key biochemical machinery (whether related to
9 metabolism/excretion or cellular function) should be combined to allow a more complete
10 evaluation of interactions among mixture components leading to changes in internal
11 exposure duration. Thus, there are advantages of evaluating exposures at the tissue
12 level rather than at the level of the environmental contact.
13 Biological effects can continue even after the chemical is removed from the
14 system. Persisting biological and/or biochemical effects can have multiple effects
15 including those based on chemical distribution and tissue effects. These effects can
16 relate to subsequent exposures
17 to the same chemical, or other
18 chemicals, depending upon the 6
19 extent to which multiple
20 chemicals interact with the same
21 biochemical machinery. For
22 example, exposure may induce,
23
24
or increase the liver's content of
an enzyme (Figure 4-4, also
FIGURE 4-4
Conceptual Illustration of Persistence of Mixture Components
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4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
discussed from an exposure perspective as Figure 3-14 in Chapter 3). This can result
in increased bioactivation and detoxication potential when that enzyme is responsible
for the metabolism of additional encountered compounds (Figure 4-5). In this example
(top panel), chemical A induces the expression and subsequent metabolic capacity of
the enzyme responsible for metabolizing (here, hydroxylating) not only chemical A, but
chemical B as well. With the increase in metabolic capacity (lower panel), increased
metabolism may result in a higher toxic potential when metabolism results in a
bioactivation process or lower toxic potential when metabolism represents a
detoxication process. However, enzyme induction does not always increase chemical
metabolism in vivo (Kedderis, 1997; Lipscomb, 2003, 2004). When metabolic capacity
of the liver already surpasses the
rate at which a chemical may be
delivered to the liver via hepatic
blood flow (a condition known as
flow-limited metabolism), further
increases in metabolic capacity,
e.g., through enzyme induction,
will not increase the rate or extent
of chemical metabolism. The
A-OH
Enzyme
Enzyme Induction
A, B
Increased Metabolism
A A-OH
Increased Metabolism
B B-OH
Increased
Detoxification
or Bioactivation
FIGURE 4-5
Conceptual Illustration of Effects of Metabolism on Toxicity
extent and duration of persistent
biological effects should be determined, and its impact on the toxicity of other
compounds must be investigated on a compound by compound basis.
The timing of compound exposure and the duration of biological effects must be
carefully considered. One well known initiation-promotion chemical interaction occurs
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1 when the prior events associated with the toxicity of benzo[a]pyrene (DMA damage)
2 persist beyond the chemical's residence time on the body. These effects are
3 transformed into tumors by the subsequent exposure to a second compound, TPA (see
4 Text Box 3-10). When the sequence of the exposure is reversed, tumors are not
5 produced, given the short biological residence time of TPA (compared to B[a]P), and the
6 short biological persistence of TPA's effects. Another example of the biological effects
7 persisting beyond chemical residence time is provided by studies from Mehendale and
8 colleagues (Mehendale, 1995; Soni et al., 1999). Their results demonstrate that low
9 levels of tissue damage can result in stimulations of cellular repair, which are
10 themselves protective against subsequent chemical exposure and insult occurring
11 during the time of increased repair. Co-exposure to agents that inhibit repair capacity
12 (e.g., chlordecone) potentiates the toxicity of the original compounds at least during the
13 time that the biological effect (inhibition or repair) persists. This information should be
14 summarized and considered as the toxicity assessment proceeds through the
15 evaluation of chemical interactions.
16 4.4. CHEMICAL MIXTURES GROUPING AND TOXICITY ASSESSMENT SCHEME
17 The object of grouping chemicals for toxicity assessment is to take advantage of
18 established chemical mixtures risk assessment approaches that rely on groups made
19 up of individual chemicals that act through a common toxic mode of action or,
20 conversely, are toxicologically independent of one another (while sharing a common
21 toxic endpoint). In cumulative risk assessment, the initial four exposure categories
22 group chemicals by exposures in the same or different media and at the same or
23 different point in time (see Section 3.5.2.2). In this chapter, we begin with those rough
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1 exposure groupings and further evaluate them to form revised groups based on
2 toxicological similarity. A systematic approach is suggested to evaluate these groups
3 using cumulative risk assessment methods.
4 Grouping chemicals by the potential for co-occurrence and joint toxic action is a
5 key simplifying concept for the conduct of cumulative risk assessments. Chemical
6 components of mixtures can be screened for inclusion in a cumulative risk assessment
7 using the elements of component-based methods. Figures 4-6a, 4-6b, and 4-6c outline
8 a three-step process for classifying chemicals into groups suitable for analysis and then
9 applying the methods shown in Figure 4-1. These three steps are:
10 1) Figure 4-6a (same as Text Box 3-9) - Classify all chemicals of concern
11 into initial groups by their potential to occur in the same or different
12 media and at the same or different time. (See Chapter 3 for details on
13 exposure assessment; Section 3.3.2.2 for information on exposure
14 grouping.)
15
16 2) Figure 4-6b - Divide these exposure/time groups further into
17 subgroups in which chemicals are thought to cause toxicity by the
18 same mode of action or affect the same target organ. Include all target
19 organs or effects for which positive evidence exists of adverse health
20 effects. An initial step here is to collect toxicologic and
21 pharmacokinetic data on each of the individual chemicals to be
22 considered in the risk assessment. Factors to consider in forming
23 these toxicity groups include pharmacokinetic parameters, persistence
24 of the chemicals in the body, and the formation of metabolites.
25
26 3) Figure 4-6c - Assess the toxic potential of the chemicals/whole
27 mixtures of concern using methods in Figure 4-1 from U.S. EPA
28 Guidance (U.S. EPA, 2000a). A flow chart is shown to apply
29 component based or whole mixture risk methods to the groups formed
30 in Steps 1 and 2.
31 4.4.1. Chemical Groupings by Common Effects. The groupings developed in the
32 exposure analysis (Figure 4-6a) categorize multiple chemicals into groups comprised
33 roughly of exposures in the same or different media at the same or different exposure
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1
2
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7
Chemical Groupings by
Co-occurrence in Media/Time
Time
Same
Different
Media
Same
Group 1
Group 2
Different
Group 3
Group 4
FIGURE 4-6a
Chemical Grouping by Co-occurrence in Media and Time
Because of
Exposure
Group
Consider
These
Factors to
Form
Toxicity
Groups
Exposure Groups
Same Media;
Same Time
Similar effects
or metabolites
Same Media;
Different Time
Similar effects or
metabolites; Body
burden;
Persistence of
effects
Different Media;
Same Time
Similar effects or
metabolites;
Pharmacokinetics;
Multi-route
exposures
Different Media;
Different Time
Similar effects or
metabolites; Body
burden,
Pharmacokinetics;
Persistence of effects;
Multi-route exposures
Target Organ Specific Toxicity Groups
Kidney
Liver
.
.
.
Lung
Group 1,1
Group 1,2
.
.
.
Group 1,n
Group 2,1
Group 2, 2
.
.
.
Group 2,n
Group 3,1
Group 3,2
.
.
.
Group 3,n
Group 4,1
Group 4, 2
.
.
.
Group 4,n
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
FIGURE 4-6b
Chemical Groupings by Common Target Organs and Effects. Each exposure
group is subdivided based on commonality or overlap of toxic effects, metabolic
pathways, or tissue concentrations. Chemicals must be retained for assessment if
information exists on their toxicologic interactions.
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4
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Component or
Whole Mixtures
Data for Toxicity
Group(s)?
Yes
Continue with Group(s)
i
Apply Component Mixture Risk Assessment
Methods to Toxicity Group(s)
Apply Whole
Mixture Risk
Assessment
Methods
to Toxicity
Group(s)
Evaluate Multiple Effects
Add Single
Chemicals
toCRA
Evaluate Multiple Route Exposures
Evaluate Interaction Effects
Screen out Group(s)
from CRA
Conduct CRA for Single
Chemicals and Group(s)
FIGURE 4-6c
Grouping Chemicals for Cumulative Risk Assessment. The mixture risk methods are
applied to each group, with "concern" judged by the appropriate screening value (e.g.,
mixture RfD for whole mixture oral exposure). Groups can be screened out only if both
whole mixture and component methods indicate no concern.
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23
time (see Section 3.3.2.2.). Note that many exposure groups could be formed when
multiple exposure media and timeframes are found to be important to the assessment.
Figure 4-6b shows that for each media/time
combination, the occurring chemicals are
grouped by common target organ or effect,
which does not necessarily imply common toxic
mechanism or mode of action. Because the
exposure scenarios vary with media and time,
factors relating to exposure routes and fate
within the body are then considered to further
refine the subgroups for the toxicity assessment
(see Figure 4-6b). Through consultations
among exposure analysts and toxicity analysts,
Target Organ Toxicity Doses
(Text Box 4-2)
The Agency's IRIS database generally
derives an oral RfD or an inhalation RfC
based on a single critical effect for a single
chemical. Thus, cumulative toxicity
assessments using secondary effects require
the development of additional dose response
information beyond readily available Agency
values. U.S. EPA (2000a) suggests the
development of Target Organ Toxicity Doses
(TTDs) for use in these situations. TTDs are
developed for secondary effects using the
same methodology as applied in the
derivation of an RfD (Mumtaz et al., 1997).
TTDs can then be used in Hazard Index
calculations instead of using an RfD to
represent a safe level for all target organs.
The alternative is to use the IRIS RfD
regardless of target organ, resulting in a
likely overestimation of the HI. To date,
there is not an analogous Agency alternative
value for an RfC.
several different groupings can be developed based on available exposure and toxicity
data. In addition, most chemicals are likely to end up in several different groups
because they can exist in more than a single medium, and they cause more than one
toxic effect in different target organs. (Text Box 4-2 discusses the availability of Agency
toxicity information beyond IRIS values for use in the cumulative toxicity assessment.)
An example of the grouping process can be seen using the information shown in
Figures 4-7 and 4-8. In Figure 4-7, several organ systems are represented (i.e., the
nervous, renal, cardiac, developmental, respiratory systems), with specific target organs
indicated in the second row. The third and fourth rows list chemicals causing primary or
secondary effects in those systems, respectively (see Tables B-1 and B-3 of Appendix
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1
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19
Organ
System
Specific
Target
Organ
Primary
Effects
Secondary
Effects
Nervous
System
Brain
Hg, PCB,
TCE
As, CCI4,
Hg, Ni,
DCA, TCE
Renal/Urinary
System (Kidney)
Spinal
cord
CCI4,
Hg, TCE
Cd, Hg,
Ni, TCE,
BDCM, U
Cd, U,
CrVI,
Hg,
TCE
Cardiac
System
Developmental Respiratory
System | System
Developing
fetus
Ni, As,
TCE
TCE,
BDCM
PCB
Cd, Cr,
Hg
CrVI,
Hg, Ni,
DCA,
TCE
CrVI
Crlll,
CrVI,
Hg, Ni
Sources:
Municipal Waste Combustor: Hg, Cd
Fish Consumption: Hg, PCB
Drinking Water Disinfection By-Products (DBPs): BDCM, DCA
Source Water Contaminants: TCE, Ni, As, CCI4, Cr
Contaminated Groundwater: U
Temporary Combustor for Site Remediation: Cd, Cr, Ni
As = Arsenic (inorganic)
BDCM= Bromodichloromethane
Cd = Cadmium
CCI4 = Carbon tetrachloride
Cr III = Chromium III (insoluble salts)
CrVI = Chromium VI
DCA = Dichloroacetic Acid
Hg = Mercury (based on mercuric chloride)
Ni = Nickel (soluble salts)
PCB = Polychlorinated Biphenyls (Arochlor 1016)
TCE = Trichloroethylene
U = Uranium (soluble salts)
FIGURE 4-7
Information on Primary and Secondary Effects Linked with Hypothetical Exposure Sources to
Show Example Chemical Groups
(see Appendix B, Tables B-1 and B-3 for chemical information)
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17
Exposure
Group:
Exposure
Scenarios
Exposure Groups
Same Media;
Same Time
Air: Daily
Exposure to
Municipal Waste
Combustor
Emissions
Air: Daily
Inhalation
Exposure to
Disinfection By-
products via
Showering
Same Media;
Different Time:
Drinking Water:
Acute Accidental
Exposure to
Source Water
Contaminants
Drinking Water:
Exposure to
Uranium
Contaminated
Ground Water,
Years Later
Different Media;
Same Time
Drinking Water:
Daily Exposure to
Disinfection By-
products via
Ingestion and
Showering
Fish: Daily
Exposures via
Local Fish
Consumption
Different Media;
Different Time
Air: Short Term
Exposure to
Emissions from
Temporary
Combustor
Drinking Water:
Acute Accidental
Exposure to Source
Water
Contaminants,
Months Later
Target Organ Specific Toxicity Groups
Kidney
Brain
Fetus
Heart
Lung
Hg, Cd, BDCM
Hg, DCA
Hg, BDCM, DCA
Hg, Cd
Hg
Ni, TCE, U, Cr
TCE, As, Ni, CCI4
TCE, Ni, Cr
TCE, Ni, As, Cr
Ni, Cr
Hg, BDCM
Hg, DCA, PCB
Hg, BDCM, DCA,
PCB
Hg
Hg
Cd, Ni, TCE, Cr
TCE, As, Ni, CCI4
TCE, Ni, Cr
Cd, TCE, Ni, As.Cr
Ni, Cr
FIGURE 4-8
Example Chemical Groupings for Toxicity Assessment
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1 B for chemical toxicity information). A primary effect is the adverse effect observed at
2 the lowest dose on the dose-response relationship developed for each adverse effect
3 noted from single chemical exposures. Secondary effects can be thought of in several
4 ways, as effects mediated by chemical metabolites, as effects that follow from chemical
5 insult but do not result in adversity (i.e., enzyme induction), or as adverse effects that
6 occur at doses higher than those producing the critical effect. Following these rows is a
7 list of six hypothetical exposure sources under consideration for a cumulative risk
8 assessment and a list of the associated contaminants to which the population is
9 exposed. This information is then used to form initial toxicity groups in Figure 4-8,
10 which begins by setting up hypothetical exposure scenarios for each combination of
11 same/different media and same/different time. The target organ specific toxicity groups
12 in Figure 4-8 are developed by distributing the chemicals associated with the
13 hypothetical exposure sources (Figure 4-7) into the five bottom rows that designate
14 specific target organs, according to the combinations of these sources shown in the
15 media/time exposure scenarios. In this way, contaminants that are expected to co-
16 occur in media and time are grouped by common target organ for analysis. For
17 example, in the first column, the population is exposed via inhalation to municipal waste
18 combustion emissions and drinking water disinfection by-products (DBP) through
19 showering, so the chemicals associated with these two sources are grouped by
20 common target organ.
21 4.4.2. Refinement of Toxicity Groups. Once these initial groups are formed, then
22 several other factors need to be accounted for before the groups are subjected to a risk
23 assessment procedure. At this point, the chemicals within each group do not
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1 necessarily act by the same toxic mechanism or mode of action and have not been
2 considered yet in terms of whether the exposure levels are within ranges that may
3 cause toxicity, additive joint toxic action, or toxicological interactions. These groups
4 must be refined using considerations of appropriate exposure routes, timing of
5 exposures and effects, persistence of chemicals within the body, and the potential for
6 joint toxic action. This refinement results in final chemical groupings that are ready for
7 analysis using chemical mixture risk assessment methods. The following issues should
8 be considered:
9 Are the chemicals in the toxicity groups appropriate, given the exposure routes
10 and health effects of concern?
11 Example: For the Same Media/Same Time exposure scenario, DCA is a non-
12 volatile DBP that would not volatilize, but would be found in aerosol (water
13 particles) during showering. Because of the relatively low level of exposure via
14 inhaled aerosols during showering, it could be removed from the toxicity groups.
15 Also, BDCM is known to cause renal effects via inhalation, but the toxicity data
16 on fetal loss are from oral exposures, with no developmental data available for
17 inhalation exposures; thus, because of the potential for a large inhalation
18 exposure to BDCM during showering and because fetal loss is a severe effect, it
19 would be reasonable to retain BDCM in the "fetus" grouping, but this uncertainty
20 must be discussed in the risk characterization.
21 Do data exist on toxicological interactions between chemicals in the groups that
22 would raise concerns for increased (or decreased) toxicity from the joint
23 exposure?
24 Example: Data exist that show a synergistic interaction effect in the brain for
25 joint exposures to TCE and CCU (ATSDR, 2003a). This relationship is only
26 documented for this one toxic effect. It is reasonable, however, to keep both
27 chemicals listed within all toxicity groups when the exposure scenario indicates
28 they will co-occur. Thus, in Figure 4-8, both TCE and CCU would be added to
29 all toxicity groups under exposure scenarios involving the contaminated ground
30 water source.
31 Are there metabolites that should be added to the groups and, if so, should the
32 parent compound be retained or removed?
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1 Example: Although this exposure scenario is not shown in Figure 4-8, suppose
2 a same media/same time scenario involves co-exposures to the DBP, DCA, and
3 the source water contaminant, TCE. Because DCA is a metabolite of TCE in the
4 body and both chemicals are known to cause effects in the brain, exposures to
5 both chemicals could result in elevated levels of DCA for consideration in the
6 risk assessment. If the risk analyst cannot determine whether TCE would still be
7 present or completely metabolized. It may be reasonable to also retain TCE in
8 the risk assessment, but this uncertainty must be noted in the risk
9 characterization discussion.
10 When the population is exposed to sources at different times, do the chemicals
11 from the first exposure remain in the body long enough to be of concern when
12 the second exposure occurs?
13 Example: The potential for toxic interactions of cadmium and TCE on the
14 cardiovascular system may be based on direct interactions in the heart itself, and
15 by additional, indirect, effects of cadmium and TCE on kidney function related to
16 blood pressure regulation. Both TCE and cadmium are readily absorbed into the
17 body. TCE is eliminated from the body with a half-life measured in hours,
18 whereas cadmium is eliminated from the body with a half-life measured in
19 decades; thus an earlier exposure to cadmium may result in persistent body
20 burdens, and internal co-exposure with TCE in tissues. The tissue
21 concentrations and the effects of cadmium in the heart and kidney may persist
22 beyond the initial exposure period, making these organs more susceptible to the
23 injury produced by TCE.
24 When the population is exposed to sources at different times, do the health
25 effects resulting from the first exposure last long enough to be of concern when
26 the second effect from the subsequent exposure occurs?
27 Example: As shown in Text Box 3-10, benzo[a]pyrene (BaP) and
28 tris(2-ethylhexyl) phosphate (TPA) are an initiator/promoter pair. TPA does not
29 have a tumorigenic effect in mouse skin assays, but when it is applied after
30 initiation with BaP tumorigenic activity is greatly enhanced (Verma et al., 1985).
31 Figure 4-9 illustrates a few of the changes (not comprehensive) that would be
32 made in Figure 4-8 based on the points raised in this section. Considerations of body
33 burden, pharmacokinetics, exposure route, persistence of effects, metabolites, and
34 multi-route exposures may be used to alter and refine the toxicity groups. When the
35 groups are finalized then the risk assessor can move forward to conducting the
36 cumulative toxicity assessment.
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17
Exposure Group
Exposure
Scenarios
Exposure Groups
Same Media; Same Time
Air: Daily Exposure to
Municipal Waste
Combustor Emissions
Air: Daily Inhalation
Exposure to Disinfection
By-Products via
Showering
Same Media; Different
Time:
Drinking Water: Acute
Accidental Exposure to
Source Water
Contaminants
Drinking Water:
Exposure to Uranium
Contaminated Ground
Water, Years Later
Different Media; Same
Time
Drinking Water: Daily
Exposure to Disinfection
By-Products via Ingestion
and Showering
Fish: Daily Exposures via
Local Fish Consumption
Different Media; Different
Time
Air: Short Term Exposure to
Emissions from Temporary
Combustor
Drinking Water: Acute
Accidental Exposure to
Source Water Contaminants,
Months Later
Target Organ Specific Toxicity Groups
Kidney
Brain
Fetus
Heart
Lung
Hg, Cd, BDCM
Hg*
Hg, BDCM*
Hg, Cd
Hg
Ni, TCE, U, Cr,
CCI4**
TCE, As, Ni,CCI4,
DCA***
TCE, Ni, Cr,
CCI4**, DCA***
TCE, Ni, As, Cr,
CCI4**
Ni, Cr
Hg, BDCM
Hg, DCA, PCB
Hg, BDCM, DCA,
PCB
Hg
Hg
Cd, Ni, TCE, Cr,
CCI4**
TCE, As, Ni, CCI4,
DCA***
TCE, Ni, Cr, CCI4**,
DCA***
Cd, TCE, Ni, As,Cr,
CCI4**
Ni, Cr
*DCA removed because it is not a volatile compound; inhalation exposures are not a concern.
**CCI4 added to account for potential interaction effects between CCI4 and TCE.
***DCA added as a metabolite of TCE.
FIGURE 4-9
Examples of Toxicity Group Refinements
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1 4.4.3. Cumulative Toxicity Assessment Scheme. After the joint exposure and target
2 organ groups are determined, the toxicity assessment for each group follows the
3 schematic shown in Figure 4-6c. This flow chart begins in the same way as Figure 4-1,
4 the chemical mixtures guidance flow chart, in that the risk analyst examines the
5 available data for toxicity information on the whole mixture and on the mixture
6 components. For the toxicity groups in Figure 4-8, it is not likely that toxicity data would
7 be available for those specific chemical combinations, so the risk analyst would follow
8 the flow chart in the direction of component data. If data are available for each of the
9 single chemicals in a toxicity group, then the single chemical hazard quotients and, if
10 applicable, cancer risks are calculated. If calculations show any HQ >1 or cancer risk
11 >10~6, then that single chemical is designated to remain in the cumulative toxicity
12 assessment, and it is not removed from the toxicity group. The next step is to apply the
13 chemical mixture risk assessment methods (flow chart in Figure 4-1) to each toxicity
14 group, using the hazard index (Section 4.2.1), response addition (Section 4.2.1) or RPF
15 (Section 4.7.1.2) approaches as appropriate, according to the judgments made
16 regarding toxicologic similarity of the component chemicals (see U.S. EPA, 2000a, for
17 details on applying these methods). Finally, additional quantitative methods may be
18 undertaken to evaluate multiple effects (Section 4.5), toxicologic interactions (Section
19 4.6) and multiple route exposures (Section 4.7). If quantitative data are not available to
20 conduct the analysis, but qualitative toxicity information exists, then some discussion of
21 these issues may be possible. If none of these mixtures assessments raises concern
22 for population health risks, then the toxicity group may be screened out of the
23 cumulative toxicity assessment. Otherwise, the risk analyst retains both the toxicity
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18
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20
21
22
group(s) and the single chemicals with elevated HQs or cancer risks and finalizes the
risk assessment, including a complete risk characterization (Chapter 5).
When data on the toxicity group as a whole mixture are available, the risk
assessment can use that information to estimate health risks for the toxicity group.
Also, within the toxicity group, there may be a complex mixture with a chemical
composition that is not fully characterized (e.g., complex disinfection by-product
mixtures typically contain ~50% of unidentified total organic halide material). Toxicity
may be estimated for the whole mixture
(see procedure in Text Box 4-3) and
compared with environmental exposure
levels. For example, a Reference Dose
can be calculated for the whole mixture
(RfDm) as shown for the general case
and compared to the IRIS value for
Araclor 1016 in Figure 4-10. The
Arachlor 1016 RfDm represents that
particular PCB mixture and could be
used in the cumulative toxicity
Procedure for Estimating Whole Mixture Toxicity
Values (Text Box 4-3)
1) Collect and Evaluate Data
Epidemiology/human data preferred, supporting
toxicology data
2) Evaluate Stability within a Mixture
Variability in components and their relative
proportions
3) Assess Sufficient Similarity Across Mixtures
(if applicable)
Similarity across mixtures' components and
relative proportions
Similar toxicity of two mixtures or of common
components
Common sources or produced by similar
process
4) Conduct Dose-Response Assessment
Use same procedures as for single chemicals
(e.g., RfD, slope factors)
5) Characterize Uncertainties
Relevance of health effects data to
environmental exposures
Stability of the mixture and environmental fate
(U.S. EPA, 2000a).
assessment as a surrogate value for the PCB exposure via fish consumption with the
relevant toxicity groups for effects in the brain and fetus. Returning to Figure 4-6c, if the
whole mixture toxicity is shown to be of concern, then it needs to remain in the
cumulative toxicity assessment.
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17
General Case (U.S. EPA, 2000c)
, LOAEL or BMDL
UF
m
where:
NOAEL/LOAEL = No/Lowest-Observed-
Adverse-Effect Level
BMDL = Lower 95% confidence limit on an X%
Effective Dose (e.g., ED10)
UFm = Uncertainty Factors for the mixture
(e.g., interspecies, intraspecies,
exposure duration, NOAEL to
LOAEL, data base deficiencies)
NOAEL, LOAEL or BMDL from experimental
toxicity data on the complex mixture dose-
response. Uncertainty factors are derived using
expert judgment, as is the case for single
chemicals. The uncertainty characterization
should include the relevance of the experimental
mixture from which the RfDm is derived to the
chemical composition of environmental mixtures.
Aroclor 1016 (U.S. EPA, 2005c)
lE-5 =
where:
NOAEL= 0.007 mglkgld
UFm = 100
NOAEL = Reduced birth weight in monkey
reproductive study
UFm = 3 for rhesus monkey to human
extrapolation
3 for infants as a sensitive
subpopulation
3 for subchronic to chronic
exposure duration
3 for missing 2 generation repro &
adult male repro studies
(i.e., 100 = 3x3x3x3, rounded up)
Confidence in RfD is medium when PCB
mixtures in the environment do not match the
pattern of congeners found in Aroclor 1016; high
if the environrmental mixture is Aroclor 1016.
FIGURE 4-10
Complex Mixture Reference Dose
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1 4.4.4. Evaluating Subpopulations. Information on vulnerable subpopulations should
2 be collected and included in the cumulative risk assessment when such information is
3 available. An extensive treatment of how to incorporate such a risk assessment into the
4 cumulative toxicity assessment will not be undertaken in this report, but should be the
5 subject of future research. The Agricultural Health Study and other literature on mixture
6 exposures and potential susceptibilities related to environmental exposures (see
7 Chapter 1) will be useful for identifying vulnerable subpopulations of concern when
8 conducting a cumulative risk assessment. In the development of chemical groups for
9 evaluation at a site, the characteristics of the potentially exposed population should be
10 evaluated (Chapter 2). Chemical mixture risk estimates for vulnerable subpopulations
11 should be calculated separately from risk assessments on the general population and
12 presented in a separate section of the risk characterization.
13 4.5. EVALUATING MULTIPLE EFFECTS
14 The hazard identification phase of a cumulative risk assessment must be
15 broadened to include factors beyond those considered for single chemicals. An
16 important difference between cumulative risk assessment and traditional single-
17 chemical assessments is the number of health effects evaluated. The method
18 described in Figures 4-6a, 4-6b and 4-6c shows that the cumulative risk assessment
19 needs to include an evaluation of all adverse effects, as evidenced by available health
20 effects data (e.g., toxicology data, epidemiology studies, human clinical trials). These
21 effects may occur at doses or exposures higher than those causing the critical effect.
22 Furthermore, health effects data from toxicologic studies of chemical mixtures may
23 reveal a different set of effects, potentially in target organs other than those observed in
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1 toxicology studies of the mixture's components individually. Finally, the set of identified
2 effects must take into account the potential routes of exposure.
3 The application of the toxicity assessment to actual site exposures will often
4 require extrapolation beyond the range of the toxicity data. If external exposure levels
5 are used in the risk assessment, then inferences about multiple effects could be highly
6 uncertain. When data are available and resources permit a more extensive
7 investigation, considerations should be given to using internal chemical doses based on
8 pharmacokinetic and mechanistic information. For example, multiple organ systems
9 and functions, such as the endocrine system and immune function, require specific
10 attention since tissue dosimetry among the multiple organs/tissues components may
11 differ among themselves and with respect to chemical components of the mixture. In
12 such cases, a doubling of external exposure levels will not result in a doubling of the
13 corresponding tissue doses. Chemicals that affect organs or tissues that are parts of a
14 larger biological system should be considered as affecting the same target system. In
15 this way, the assessment of multiple effects can be simplified by grouping the effects.
16 4.5.1. A Quantitative Method for Evaluating Multiple Effects. One of the goals in a
17 cumulative toxicity assessment is to account for the joint impact of all of the major
18 health impacts from exposure to multiple stressors. The approach demonstrated in this
19 report involves a three step process: a dose-response model for multiple effects, hazard
20 calculations using both dose-addition (Hazard Index) and response-addition
21 approaches, and a comparison of the results. This approach would begin by analyzing
22 dose response relationships for each single chemical, incorporating all toxic effects in
23 the same modeling procedure. Various statistical models could be applied (e.g.,
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1 multivariate normal linear regression, ordinal categorical regression) to predict the
2 probability of observing an array of toxic effects for a given dose. For many chemicals,
3 the available data on multiple effects differ across effects as well as across chemicals in
4 terms of completeness, range of doses covered, and level of detail, making multivariate
5 approaches difficult. In this report a simpler categorical regression model based on
6 toxicologic judgment will be used to illustrate estimating the probability of a certain level
7 of (non-specific) response, given exposure to a single chemical. From the modeling
8 results, a risk estimate for the exposure of interest can be made, and a benchmark dose
9 (BMD) can be estimated (e.g., a 5% effective dose or ED0s). To apply response
10 addition, the individual chemical risk estimates must be summed across chemicals to
11 calculate the mixture risk. To apply dose addition, an HI will be calculated using the
12 single chemical BMD estimates to provide an indication of risk for the mixture. These
13 results can then be compared in the risk characterization step (see Chapter 5) to
14 evaluate the potential health impacts for the site of interest.
15 Ordinal categorical regression is a statistical modeling procedure that allows for a
16 dose-response assessment of several toxicologic effects at once. The use of a
17 categorical regression procedure to express the risk of adverse health effects for
18 toxicological data was first proposed by Hertzberg and Miller (1985) and Hertzberg
19 (1989) and then demonstrated with several chemicals (Guth et al., 1991; Farland and
20 Dourson, 1992; Rao et al., 1993; Dourson et al., 1997; Teuschleret al., 1999; Strickland
21 and Guth, 2002).
22 In this procedure, toxicity data, regardless of the type of effect, are interpreted
23 using toxicological judgment in terms of pathological staging. Toxic effects, which may
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1 include both quantal and continuous data, are classified into ordered categories of total
2 toxic severity (e.g., categories 1-4 refer to none, mild, moderately adverse, and severe
3 effects, respectively). The model reflects a regression of dose on the category of effect,
4 yielding the probability that a given dose will result in a level or category of response
5 (e.g., the probability of observing a level 3 adverse effect, given dose). The U.S. EPA
6 software, CATREG, is useful for conducting this procedure (U.S. EPA, 2000c,d). In
7 addition, CATREG has the ability to incorporate other factors in the analysis, including
8 duration, study effects, species, and censored data (Guth, 1996; Guth et al., 1991,
9 1997). Thus, models may be developed to describe dose-risk relationships for a variety
10 of exposure scenarios.
11 In Teuschler et al. (1999), categorical regression analysis was used to model the
12 relationship between the logarithm of human equivalent doses and category of
13 cholinesterase inhibition for each of five pesticides. Table 4-1 shows an example using
14 three ordered categories of toxic severity for cholinesterase data (Dourson et al., 1997).
15 The toxic response (or its absence) was related to the explanatory variables, dose and
16 duration, by using a cumulative logistic function, and P was defined as the probability of
17 observing a response of a certain severity or a lessor response. The logistic function
18 used to express the relationship between P and the explanatory variables is given
19 below:
20 P,S*i= ** (4-3)
1 - exp(a, + jB1x1 + /32x2 )
21 where:
22 PJ = the probability of observing an effect of severity i or less,
23 S = the severity of the effect,
24 i = the severity category 1, 2, or 3,
25
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TABLE 4-1
Example Severity Assignments for Cholinesterase Inhibition Data*
Severity
Grade
Frank
Effects
Adverse
Effects
Non-
Adverse
Effects
No Effects
Site
Cholinergic effects
Cholinergic effects
Whole Body
Brain, whole blood or red
blood cell (RBC)
acetylcholinesterase
Cholinergic effects
Cholinergic effects
Nervous system
Plasma, whole blood or
RBC acetylcholinesterase
All
Effect
Severe abdominal pain, nausea and/or
vomiting, diarrhea
Seizures, severe disorientation or
confusion, excitation
Mortality
Inhibition (e.g., of 20% or greater)
Mild: Muscular weakness or twitching
Mild: Blurred vision and/or watery eyes,
pinpoint pupils, excess salivation,
sweating or clamminess
Hyperactivity or altered patterns of
locomotion
Inhibition (e.g., observed, but less than
20%)
No effect
2
3
*Adapted from Dourson et al. (1997)
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1 oti = an unknown intercept parameter associated with severity i,
2 Pi = an unknown slope parameter associated with the dose,
3 xi = the dose of the chemical,
4 £2 = an unknown slope parameter associated with the duration of exposure,
5 x2 = the duration of the exposure to the chemical.
6
7 Using Equation 4-3 with such data, the dose-response relationship for multiple effects
8 can be given as the probabilities of toxic effects for a given duration and dose (e.g., the
9 probability of an adverse effect for a 1-day exposure at 0.1 mg/kg/day), and BMDL
10 estimates can be determined (e.g., lower bound on the dose causing a 5% chance of a
11 non-adverse effect). Results of the categorical regression equation can then be used in
12 response addition and the HI to present a range of potential health risk for the exposure
13 of interest. In particular, using Equation 4-1 (from Section 4.2.1) for the HI, the RfD for
14 each chemical can be replaced by the BMDL for multiple effects divided by an
15 uncertainty factor (e.g., UF=100) to account for inter- and intra- species differences.
16 The equation would then be:
17 HI (effects) = V
BMDLj
'UF,
(4-4)
J
18 A probabilistic mixtures risk estimate could also be calculated for multiple effects using
19 the categorical regression results. Based on Equation 4-2, for ordered severity
20 categories of 1 = no effects, 2 = not adverse effects, 3 = adverse effects, 4 = frank
21 effects), response addition under categorical regression for a specific exposure of
22 interest is calculated:
23 Rm(effects) = 1-f\P,(severity < 2) (4-5)
i=1
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1 4.5.2. Interpretation. These two methods for dose-response assessment of multiple
2 health effects yield very different types of answers. The Hl(effects) is expressed as a
3 risk indicator and the Rm(effects) is expressed as a probabilistic risk estimate. A group
4 of chemicals should be screened in as part of a cumulative risk assessment when either
5 the value of an HI is greater than or equal to some pre-determined level (e.g., 0.5) or a
6 response addition risk estimate is greater than or equal to an acceptable risk level (e.g.,
7 1 x 10~6). In either case, when estimates approach or exceed these "cut off" values,
8 toxicologic judgment is needed to evaluate the chemicals and data used in the analysis
9 and to determine the level of concern for the analysis. For a cumulative risk
10 assessment screening exercise, if either "cut off" value is met or exceeded, then those
11 chemicals should be kept in the cumulative risk assessment. The factors considered
12 when evaluating dose and response addition in mixture risk assessments also apply
13 here but only in a rough sense: whether the collection of effects seem to be
14 toxicologically similar across the set of chemicals or seems to be independent,
15 particularly at the exposure levels under consideration. As described in the U.S. EPA
16 (2000a) mixture guidance, these formulas give similar results when component
17 exposures are low.
18 4.6. EVALUATING INTERACTION EFFECTS
19 Toxicologic interactions are defined in U.S. EPA (2000a) as any toxic responses
20 that are greater than or less than what is observed under an assumption of additivity.
21 The term additivity is used when the effect of the combination of chemicals can be
22 estimated directly from the sum of the scaled exposure levels (dose addition) or of the
23 responses (response addition) of the individual components. Many terms are used to
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1 represent various kinds of interaction effects (e.g., inhibition, antagonism, masking).
2 The most common and general of these refer to effects that are greater than additive
3 (i.e., synergistic) or less than additive (i.e., antagonistic).
4 The detection of interaction effects varies from toxicologic judgment to statistical
5 determinations. For cumulative risk assessment, interactions information should be
6 collected from the toxicologic and epidemiologic literature and used to inform the
7 grouping process. U.S. EPA has two collections of bibliographic summaries of
8 interaction studies that are available to the public: the Integral Search System (Arcos et
9 al., 1988) and the MIXTOX database (Marnicio et al., 1991). ATSDR has also
10 published a number of interaction profiles for common environmental contaminants
11 (Pohl et al., 2003). For example, in Table 4-2, the non-additive interactions are shown
12 for four metals: arsenic, cadmium, chromium, and lead (ATSDR, 2004). As Table 4-2
13 shows, even when interactions data exist, the situation is complicated because the
14 direction of interaction can be different for different effects or for changes in the
15 sequence of exposure. For metals, toxicologic interactions are more troublesome
16 because environmental conditions (e.g., pH) can alter the speciation and bioavailability
17 of the metals. At a minimum, when evidence of synergistic interaction is found for two
18 or more chemicals within a group (formed using Figure 4-6b) those chemicals should be
19 included in the cumulative risk assessment. A further quantitative evaluation may be
20 conducted using the interaction-based HI (see Section 4.6.2 and Chapter 5).
21 4.6.1. Toxicology of Interactions. A mixture can consist of chemicals that cause a
22 unique toxicologic expression that was not anticipated from the toxicity of the individual
23 compounds; the toxicodynamic process of one compound influences that of another
24
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TABLE 4-2
Joint Toxicity: Non-additive Effects of Metal Pairs on Systems/Organs
Using Oral Exposure
Effect of
Metall
on Metals
Arsenic
Cadmium
Chromium
Lead
Not
Additive*
Higher
Lower
Higher
Lower
Higher
Lower
Higher
Lower
Arsenic
Blood
Skin
Kidney
Neurological
Kidney
Blood
Cadmium
Blood
Kidney
Male
reproductive
Male
reproductive
Chromium
Kidney
Lead
Neurological
Blood
Kidney
Neurological
Male
reproductive
Blood
Kidney
4
5
* Higher = Effects are greater than expected under additivity
Lower = Effects are less than expected under additivity
Source: ATSDR (2004)
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1 (e.g., one compound causes toxicity and a second compound slows the process of
2 cellular repair). The toxicity of chemical mixtures is dependent upon the interactions of
3 mixture components at either toxicokinetic (TK) or toxicodynamic (TD) processes, thus,
4 interactions at either level may result in mixtures interactions. TK processes govern
5 tissue distribution of compounds and include both passive and active processes.
6 Toxicodynamics includes the effects or events that are dependent upon the contact
7 between the toxic chemical species and the biomolecules responsible for the effect.
8 Interactions at the TK level occur when tissue dosimetry is altered due to gross tissue
9 alteration or chemicals interact at the same metabolic enzyme.
10 In addition to separating interactions according to TK or TD, toxicologic
11 interaction among compounds may be direct or indirect. Examples of direct interaction
12 include those demonstrated by compounds altering the same biochemical pathway or
13 cell type or organ/tissue that is directly related to the toxic effect of the compound.
14 Examples of indirect interaction include chemicals that may alter the internal
15 dosimetry/metabolism of other compounds (e.g., enzyme induction, glutathione
16 depletion) and thus exert an indirect effect on their toxicity. Examples of direct
17 interaction include competition for key metabolizing enzymes, receptor binding sites and
18 lipid peroxidation leading to membrane damage and radical formation. Some of these
19 interactions will depend on the severity of the effect produced. If the effect of the first
20 compound only results in a slight functional decrement and is recovered quickly or is
21 compensated by the tissue, then such an effect, whether direct or indirect, may not be
22 sufficient to serve as the basis for an assumption of interaction. Knowledge that a given
23 effect may be reversible or compensated for by the cell must be coupled with
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1 information on the dose-response and temporal characterization of the reversibility.
2 This applies also to cellular/biochemical systems which are redundant and may be
3 directly or indirectly related to toxic effects (e.g., at what point glutathione depletions
4 lead to susceptibility).
5 Information on acute toxicity should be evaluated carefully. The manifestation of
6 acute toxicity (toxicity evident in close temporal proximity to the exposure) generally
7 requires chemical exposure levels that are greater than those required to produce
8 delayed effects. Further, doses sufficient to produce acute toxicity bring a higher
9 likelihood that fundamental biochemistry can be perturbed to produce TK and/or TD
10 interactions among compounds. Interactions observed with acute toxicity, however, are
11 generally poor indicators of interaction at lower exposure levels. Tumor production is a
12 multi-step process, and interactions may be several, ranging from the classic initiation-
13 promotion type interaction, to adduct formation and inhibition or repair capacity. For
14 compounds thought to interact in the tumorigenic process, a rich data set is required to
15 substantiate an interaction. However, when compounds are tumorigenic, regardless of
16 the mechanism, placing them in the same group is warranted. For compounds with a
17 tumorigenic mode of action defined to the point that a non-linear, or threshold-like,
18 dose-response relationship can be defended, the severity of the underlying effect (e.g.,
19 cytotoxicity and cellular regeneration) must be considered. For compounds that must
20 be metabolized to be tumorigenic, TK interactions at the enzyme level are an important
21 aspect and should be evaluated.
22 4.6.2. A Quantitative Method for Evaluating Interaction Effects. To account for
23 chemical interactions in a site assessment, the U.S. EPA recommends applying the
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1 Interaction-based Hazard Index (HIINT) to component data (U.S. EPA, 2000a). The
2 main assumption for the HI|NT is that interactions in a mixture can be adequately
3 represented as departures from dose addition (Hertzberg et al., 1999). The method
4 follows an obvious approach: begin with the dose-additive HI (Equation 4-1) and then
5 modify its calculation to reflect the interaction results, using plausible assumptions to fill
6 in the data gaps. Because toxicologic interactions have been mostly studied with binary
7 mixtures, the HI|NT includes information only on binary interactions; an assumption is
8 then that higher order interactions are relatively minor compared to binary interactions.
9 Noting that the first summation shown is the additive HI and the second summation
10 shown is the modification for interactions, the formula for the HI|NT is:
19
11 HlINT=^HQ^fJkM'^ (4-6)
1=1 k^j
12 where:
13 HI|NT = HI modified by binary interactions data,
14 HQj = hazard quotient for chemical j (unitless, e.g., daily intake/RfD),
15 fjk = toxic hazard of the kth chemical relative to the total hazard from all
16 chemicals potentially interacting with chemical j (thus k cannot
17 equal j). To calculate, the formula is:
18
(4-7)
20 Mjk = interaction magnitude, the influence of chemical k on the toxicity of
21 chemical j. To calculate, estimate from binary data or use default
22 value = 5
23
24 Bjk = score for the weight of evidence that chemical k will influence the
25 toxicity of chemical j (see U.S. EPA 2000a for numerical scores).
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1 gjk = degree to which chemicals k and j are present in equitoxic
2 amounts. To calculate, the formula is:
9 k =
(HQj+HQk)/2
5
6 The current weight-of-evidence (WOE) classification and scores are given in Table 4-3
7 (U.S. EPA, 2000a). This scheme does not focus specifically on the types of data
8 available to support a WOE determination but on the interpretation of the data made by
9 an analyst or a group of analysts. The binary WOE factor Bjk reflects the strength of
10 evidence that chemical k will influence the toxicity of chemical j, and that the influence
11 will be relevant to human health risk assessment. In general, the more extrapolation
12 required, the weaker the evidence is. For example, if the available interaction data were
13 from in vitro studies with effect measures not directly related to the toxicity of concern,
14 or represented a different exposure route or duration, then the WOE score would be
15 low. ATSDR has a similar but more structured scoring rule. The factor need not be the
16 same for the influence of chemical j on the toxicity of chemical k; i.e., Bjk * Bkj. The
17 weight-of-evidence determination begins with a classification of the available
18 information, followed by a conversion of that classification into a numerical weight.
19 This formula assumes a constant magnitude of interaction (M=5) and a limited
20 influence of mixture composition (i.e., dose ratio of the two chemicals). Both these
21 properties are likely to depend on the actual component exposure level and effect under
22 consideration. The toxicology assessment is then more useful to the risk
23 characterization if the evidence for toxicologic interactions can be discussed in the
24 context of the likely exposure ranges and array of effects of concern.
25
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TABLE 4-3
Default Weighting Factors for the Modified Weight of Evidence
Category
1
II
III
IV
Description
The interaction has been shown to be
relevant to human health effects and
the direction of the interaction is
unequivocal.
The direction of the interaction has
been demonstrated in vivo in an
appropriate animal model, and the
relevance to potential human health
effects is likely.
An interaction in a particular direction
is plausible, but the evidence
supporting the interaction and its
relevance to human health effects is
weak.
The assumption of additivity has been
demonstrated or must be accepted.
Direction
Greater than
Additive
1.0
0.75
0.50
0.0
Less than
Additive
-1.0
-0.5
0.0
0.0
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1 4.7. EVALUATING MULTIPLE ROUTE EXPOSURES
2 A cumulative risk assessment should consider exposure to the population from
3 multiple routes and pathways. Measures or estimates of internal doses may provide an
improved basis both for estimating risks posed by chemical mixtures that occur through
multiple exposure routes. To date, regulatory risk methods have only been published
for simpler and more common approaches that use external exposure levels.
Assessments of multiple route
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
exposures can be complicated because
of a lack of toxicity data for all exposure
routes of interest. If data on only one
route are available, then the risk
analyst must decide if it is appropriate
to conduct a route to route
extrapolation of the data. Such
extrapolations can be problematic
because of biological differences
among routes in toxic responses or
pharmacokinetic processes. The 2005
cancer guidelines recommend route-to-
Agency Uses of Route To Route Extrapolations
U.S. EPA (2003h) Workshop Report on Inhalation
Risk Assessment (Text Box 4-4)
Office of Solid Waste: only does such extrapolations when
there are findings that indicate it is appropriate. When it is
performed, the approach is similar to that used to aggregate
exposures.
Office of Air Quality Planning and Standards: treats
cancer and non-cancer extrapolations differently. For
cancer, in lieu of an inhalation unit risk (IUR) from the
hierarchy of sources, an IUR may be derived from an oral
value (using a rough breathing rate/body weight
calculation), with recognition of added uncertainty. No such
rough extrapolation is done to create RfCs. Because the
Clean Air Act list of hazardous air pollutants is heavily
weighted by respiratory toxicants, such rough non-cancer
route extrapolations are generally not performed because of
the high probability of missing target toxicity.
Office of Pesticide Programs: performs route-to-route
extrapolations with no distinction between cancer and non-
cancer endpoints. Absorption via the inhalation route (in
mg/kg/day) is considered to be equal to oral absorption. Air
concentration estimates for human exposure are converted
from a concentration (mg/m3) to an average daily dose
expressed as mg/kg/day so that exposure can be compared
directly to oral NOAEL and LOAEL values.
route extrapolations only on a case-by-case basis as supported by available data.
There seems to be general agreement in the literature that the most appropriate way to
extrapolate across routes is to employ a physiologically based pharmacokinetic model.
However, both qualitative assessments and application of simple quantitative methods
of route extrapolation are used as needed when data are lacking. Text Box 4-4
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1 describes the uses of route to route extrapolation by several program offices, as
2 presented in a 2003 U.S. EPA workshop report on inhalation risk assessment (U.S.
3 EPA, 2003h).
4 4.7.1. Quantitative Approaches to Evaluating Multiple Route Exposures to
5 Mixtures
6
7 4.7.1.1. Summing Across Routes and Pathways EPA's Risk Assessment
8 Guidance for Superfund (1989a) instructs risk assessors to sum HQs (Equation 4-1)
9 and cancer risks (Equation 4-2) across exposure routes and exposure pathways,
10 providing there is evidence of combined exposure pathways to identifiable individuals or
11 groups of individuals who would consistently face a reasonable maximal exposure.
12 U.S. EPA (1999b) guidance on preparing Records of Decision for Superfund site
13 assessments provides further information on this method. (See details of this procedure
14 in Section 5.2.1.) Although there is no discussion of summing across exposure routes
15 and pathways in the U.S. EPA (1986, 2000a) health risk assessment guidance
16 documents for mixtures, U.S. EPA (1989a, 1999b) establishes this approach as a policy
17 with the purpose of accounting for any reasonable risk from multiple route and pathway
18 exposures. U.S. EPA (1999b) provides a template for these calculations in the form of
19 pre-formatted tables and also shows examples on its Web site (e.g.,
20 http://www.epa.qov/oswer/riskassessment/raqsd/tara.htm). For the purpose of this
21 report, one recommended approach to account for multiple route exposures is to apply
22 these procedures to the target organ groups developed in Figure 4-9. Further
23 discussion of this approach is given in Section 5.2.1 in terms of a Cumulative Hazard
24 Index, along with guidance on its interpretation.
25
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1
4.7.1.2. Summing of Route-Specific Relative Potency Factors A second
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
approach is to estimate risks for each group and exposure route using an RPF mixtures
risk assessment
approach (U.S. EPA,
2000a) and then sum
the risks to yield a total
risk for that group by all
routes. The RPF
approach is a general
methodology for
applying dose addition to
mixtures of chemicals
that produce toxicity by
the same MOA. Text
RPF Formulas for Risk Estimation of a Two Chemical Mixture (Text Box 4-5)
where:
hmix(di,d2) = mixture hazard or risk from joint exposure to doses d-i of
chemical 1 and d2 of chemical 2 (dose units not specified,
must be consistent for all chemicals)
= dose-response function of the index chemical for the
response(s) common to chemical 1 and the other chemicals
= potency of chemical 2 relative to that of chemical 1
f-i(*
RPF2
Let potj be the potency estimate for chemical i. Then
RPF2 = pot2 / pot-i
For cancer risk, potj is often given by the slope factor of risk per unit of dose.
Note that if the inverse of the effective dose (e.g., 1/ED10) is used for the
potency, then RPF is the chemical 1 to chemical 2 ratio of the ED values:
RPF2 = ED101/ED102
This mixture hazard formula uses the mixture dose given as the equivalent dose
of the index chemical. Let ICED be the index chemical equivalent dose based
on relative potency estimates (dose units consistent with d-i and d2). Then,
ICED = d1 + (RPF/ d2)
and the mixture hazard formula is
hmix(di,d2) =
Example: With dioxins, the index chemical is 2,3,7,8-TCDD. For the mixture
assessment, the combined doses of all the dioxins are converted into the
equivalent dose of 2,3,7,8-TCDD, and the mixture risk is then determined from
the dose-response data for 2,3,7,8-TCDD.
Box 4-5 shows the mathematical formulas used to develop RPF-based risk estimates,
and Figure 4-11 illustrates the process followed. To summarize the procedure, doses of
mixture components are scaled by their potency relative to a well-studied component of
the chemical mixture (referred to as the index chemical) using scaling factors called
RPFs. The product of each mixture component's dose and its RPF is considered to be
its equivalent dose in units of the index chemical. These dose equivalents of all the
mixture components are summed to express the total mixture dose in terms of an Index
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Concentration
Chemical Al
(Index
Chemical)
Concentration
Chemical A2
Concentration
Chemical A3
X RPFA1 =
(Note:RPFA1= 1)
XRPF
A2
XRPF
A3
Index
Chemical
Concentration
Al
Index
Chemical
Equivalent
Concentration
ofA2
_ .
Index
Chemical
Equivalent
Concentration
of A3
f
Sum index chemical
'equivalent concentration
to estimate total
mixtures exposure in
units of the
index chemical
FIGURE 4-11
Schematic for Relative Potency Factor Approach
1
Index Chemical
Dose-Response
Mixture
Risk
Equivalent
Concentration
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1 Chemical Equivalent Dose (ICED).1 The risk posed by the mixture is then quantified by
2 comparing the mixture's ICED to the dose-response assessment of the index chemical.
3 To implement this approach, the index chemical must have an adequate toxicologic
4 dose-response data set. U.S. EPA (2000a) characterized the RPF methodology as a
5 generalized form of the toxicity equivalence factor (TEF) methodology that has been
6 used to assess risks. This approach is similar to the Toxicity Equivalents (TEQ) method
7 used for dioxins (U.S. EPA, 1989b) but requires a less strict interpretation of the toxicity
8 data. Thus, it is applicable to a larger group of chemical classes than the TEQ method.
9 Figure 4-12 illustrates the proposed approach that combines the principles of
10 dose addition and response addition into one method to assess mixtures risk for
11 multiple route exposures within a group (e.g., as defined using Figure 4-9). (Using two
12 exposure routes, inhalation and oral, Figure 4-12 illustrates how the approach estimates
13 risk from exposure to the mixture.) Within a target organ group, an index chemical (a
14 mixture component with high quality dose-response data that acts (or is judged to act)
15 through the same MOA as the other members of the group for the route of concern) is
16 selected, and ICED is calculated using the RPF approach (U.S. EPA, 2000a). (Note the
17 text here will only refer to an ICED. However, for clarity in Figure 4-12, the ICED refers
18 to the oral route of exposure, and the ICEC (Index Chemical Equivalent Concentration)
19 refers to the inhalation route of exposure.) The ICED is an important concept,
20 employed at two levels:
1 The ICED has the same mathematical interpretation as the dioxin toxicity equivalents (TEQ). TEQ
refers to the quantification of dioxin concentrations based on the congeners' equivalent 2,3,7,8-TCDD
toxicity (U.S. EPA, 1989b). ICED is applied to mixtures other than dioxins.
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Oral
ICED, Index
Chemical Al
DoseAl*!
Oral
ICED for
Chemical A2 =
DoseA2*RPFA2
Oral
ICED for
Chemical A3 =
DoseA3*RPFA3
Dose
Addition for Oral
Inhalation ICEC
for Chemical Al
= ConcAl*RPFAl
Inhalation ICEC
for Chemical A2
= ConcA2*RPFA2
Inhalation ICEC,
Index Chemical A3
= ConcA3*l
Dose
Addition for Inhalation
ICED, Oral
Al Dose
Response
ICED, Oral
A3 Dose
Response
ICEC, Inhalation
ICEC, Inhalation
Response Addition for
Group A Mixture Risk
Risk for Oral
Evaluated at
Group A ICED
Risk for Inhalation
Evaluated at
Group A ICEC
Total Mixture
Risk as Sum of
Risks for Oral
and Inhalation
FIGURE 4-12
Combining Grouped RPF Estimates Across Exposure Routes
(Source: U.S. EPA, 2000e)
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1 (1) Component ICED - refers to the ICED for an individual chemical
2 (2) Group ICED - refers to the ICED for all chemicals within the group and route,
3 formed by summing the component ICEDs.
4 The RPF approach has been proposed for characterizing health risks associated
5 with mixtures of chemicals that are toxicologically similar (U.S. EPA, 2000a). To
6 develop an RPF-based risk estimate for a class of chemicals, good toxicologic data are
7 needed for at least one component of the mixture (referred to as the index chemical).
8 Scientific judgment and analysis of available data are used to assess the relative
9 toxicityof the other individual components in the mixture. The component ICEDs are
10 then summed within the group to generate a route-specific ICED. The risk posed by the
11 group and route of interest can be estimated using the route-specific dose- response
12 information for the index chemical. For each exposure route, the RPF approach uses
13 dose-addition to estimate risk for the toxicologic outcome common across the group.
14 An assumption is made that the route-specific risks are independent of each other (i.e.,
15 the toxicity caused by one route does not influence the toxicity caused by the other
16 route). This condition meets the criteria required to apply response addition; the route-
17 specific risk estimates are added to yield a risk estimate for the mixture group.
18 Quantitative uncertainty analyses of this approach are complicated by the general lack
19 of multi-route toxicity studies. It is then important during the toxicity assessment to
20 identify any studies or dose-response data on the multi-route mixture exposure that can
21 support this RPF approach.
22 4.7.2. Internal Dose Estimates. A third quantitative approach to handling mixtures
23 assessments for multi-route exposures is to estimate a total internal dose for use in risk
24 estimation. In 2003, U.S. EPA completed a report showing that a multi-route mixtures
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1 risk assessment can be conducted based on internal dose estimates developed in both
2 test animals and humans for toxicants that do not cause portal of entry effects
3 (Teuschler et al., 2004; U.S. EPA, 2003b). This approach is mentioned here for
4 completeness but is resource intensive.
5 U.S. EPA (2003b) combines exposure modeling results, PBPK modeling results,
6 and the RPF mixtures risk assessment approach. Human internal doses (e.g., blood,
7 tissue, and organ concentrations) were estimated using PBPK models, accounting for
8 external exposures from multiple routes (as dictated by the exposure scenario) and
9 human PK processes. Hypothetical RPFs were developed for a subset of chemicals
10 based on test animal data. Although the application of a full PBPK model was
11 recognized as the preferred approach to estimating rodent internal doses (i.e., blood
12 concentrations), for the example data used in the report, administered doses were
13 assumed to be 100% bioavailable to the rat. The rodent toxic effects were assumed to
14 be constant between internal and external exposures and were used to evaluate the
15 human dose-response relationship. The use of internal dose measures (i.e., blood
16 concentrations in both humans and rodents), both for developing the RPFs based on
17 rodent data and for indicating human multi-route exposure, provides a consistent basis
18 for extrapolating across species. However, it should be noted that these approaches
19 are inappropriate for use with toxicants that elicit responses at points of contact with the
20 body (e.g., skin, intestinal tract, and nasopharyngeal, bronchial and lung epithelia).
21 4.8. SUMMARY RECOMMENDATIONS
22 The toxicity assessment step includes the evaluation of all available and relevant
23 toxicity data, with the goal of simplifying the multiple chemicals, exposures, and effects.
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1 The approach presented here focuses on the identification of common characteristics
2 so that these multiples can be consolidated into a manageable number of groups.
3 Because the primary risk methods invoke dose addition or response addition, the
4 grouping processes focus on assumptions of toxic similarity or toxic independence,
5 respectively. As the chemicals, pathways, and effects are grouped, it is critical to
6 include a discussion of the evidence supporting those key assumptions. Any decisions
7 to exclude chemicals or exposure pathways from the cumulative risk assessment must
8 be supported by toxicity arguments that are highly relevant to the estimated exposures.
9 When such information is weak, the chemicals and pathways should be retained in the
10 assessment.
11
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Elements of Risk Characterization (Text Box 5-1)
* Quality of and confidence in the available data;
* Uncertainty analysis;
* Justification of defaults or assumptions;
* Related research recommendations;
* Contentious issues and extent of scientific consensus
* Effect of reasonable alternative assumptions on
conclusions and estimates;
* Highlights of reasonable plausible ranges;
* Reasonable alternative models; and
* Perspectives through analogy.
(U.S. EPA, 2000f)
1 5. CUMULATIVE RISK CHARACTERIZATION
2
3
4 The last phase of cumulative
5 risk assessment, risk
6 characterization, assembles all the
7 information from the analysis phase
8 and interprets the results in the
9 context of the problem (s)
10 formulated in the planning and
11 scoping phase. As described in
12 Agency guidance (U.S. EPA, 2000f), risk characterization should include two products,
13 an integrative analysis, which can be fairly technical, and a risk characterization
14 summary that emphasizes recommendations and uncertainties. Text Box 5-1 describes
15 some important elements of a risk characterization that are useful to consider in a
16 cumulative risk assessment. As presented in Chapter 1, cumulative risk assessment
17 includes all aspects of the traditional risk assessment paradigm (i.e., hazard
18 identification, dose-response, exposure assessment, risk characterization). However,
19 these concepts must be integrated and expanded beyond the elements included for
20 both single chemical and mixture risk assessments to account for the complexity of
21 cumulative risk (U.S. EPA, 2000a, 2003a). In this document, cumulative risk
22 assessments potentially include multiple chemicals, multiple exposure routes and
23 pathways, multiple toxic effects over various time frames, joint exposure response
24 relationships, and population based risk estimates. Figure 5-1 illustrates these
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Total Combined
Exposures from
Multiple Routes
or Pathways
Subsistence
Fisherman
Family
Elderly,
Cancer
Child,
Asthma
Pregnant
Woman,
Spontaneous
Abortion
m
Child,
Adult IQ
Cancer Deficit
Rural Resident,
Neurotoxicity
Total Exposure
Duration for Multiple
Time Frames
FIGURE 5-1
Total Dose
Of Multiple
Chemicals
More Risk
Consideration of Multiples in Cumulative Risk Analysis
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1 concepts using a three-dimensional diagram in which the darker shaded bars represent
2 higher risk. The vertical axis represents increasing exposures from multiple pathways
3 and routes. The axis coming forward on the page represents increasing exposure
4 duration for multiple time frames. The horizontal axis represents increases in total dose
5 from multiple chemical exposures. The shaded bars show the potential for multiple
6 effects of combined exposures, multiple chemicals and exposure duration for the
7 following vulnerable subpopulations:
8 Pregnant woman - Spontaneous abortions from short-term, multiple route
9 exposures to low doses of multiple drinking water disinfection by-products
10 (Waller etal., 1998)
11 Rural resident - Neurological effects from chronic multiple route exposures to
12 organophosphorous pesticides used in agriculture (U.S. EPA, 2002a)
13 Subsistence fisherman family - Cancer in adults exposed chronically via
14 ingestion offish containing PCBs (U.S. EPA, 1996b); IQ deficits in children
15 exposure in utero to methyl mercury via fish consumption (U.S. EPA, 1997e)
16 Elderly - a potential combination of high exposure and high vulnerability is shown
17 by a susceptible population (e.g., the elderly) that may be more vulnerable to a
18 health effect (e.g., cancer) from chronic, multiple route exposures to high doses
19 of multiple chemicals (U.S. EPA, 2003a)
20 Child - asthma from short term inhalation exposures to high levels of particulate
21 matter in the air (U.S. EPA, 2004e)
22 Thus, the cumulative risk characterization must consider multiple risk factors as
23 identified in the initial planning and scoping phase.
24 The risk characterization phase is critical to the interpretation and
25 communication of the cumulative risk assessment process and results. In the
26 usual risk characterization, the major scientific evidence and "bottom-line" results
27 from hazard identification, dose-response assessment, and exposure
28 assessment are evaluated and integrated into an overall conclusion about risk,
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1 along with clear descriptions of the limitations and uncertainties (NRC, 1983,
2 1994). In cumulative risk
3 assessments, these same steps
4 are included but, because of the
5 multiples described above, the
6 evaluations are more complicated,
7 making it more difficult to identify
8 and understand the implications of
9 the assessment results. Text Box
10 5-2 shows an example of this
11 complexity. Successfully
12 communicating the uncertainties
13 can then be a major challenge.
14 The development of the risk
15 assessment is typically an iterative
16 process, where information from
17 each process step is reconsidered
18 from the perspective of the
19 information generated during the
20 other steps. The analyst evaluates
21 the collective information,
22 identifying information gaps,
Example: Site Closure vs. Public Access (Text Box 5-2)
Consider a site with soil contamination where the decision
alternatives are open public access and full closure (clay cap and
fence). The risk assessment is then to address the public access
scenario, where unacceptable risk would suggest the need for site
closure. The complications discussed here include population-
dependent exposure characteristics, for example the population
near the site may include adults and children with quite different
exposures. For this case, children are assumed to be exposed
predominantly by direct contact with soil (dermal and ingestion) ar
adults primarily by inhalation of dust. Both subgroups might also t
exposed by ingestion at lower concentration levels, mainly of
groundwaterthat is contaminated from gradual migration through
the soil.
Complexities to Consider when Determining Risk:
Different proportions of chemicals in inhaled dust compared
with ingested groundwater, leading to different critical effects
and different toxicologic interactions
Different toxic sensitivities of adults versus children
Time-varying combined exposure from soil and groundwater
that reflects multiple routes as well as timeframes
The integrative analysis should evaluate the relative impact of eac
of these complexities on the cumulative risk estimates. Any joint
contributions to risk should be quantified to the extent possible
based on available information.
Risk Characterization Summary:
Usual elements of the risk characterization (summary of likely
health endpoints, identification of key chemicals)
Comparison of adult risk with child risk for all routes combined
and over different exposure routes and timeframes
Quality of the exposure estimate from combining across route
Quality of the toxicity information for children and adults
Confidence in summary estimate of cumulative risks.
Other descriptions that might be required for this example site
include a comparison of the risk for average exposure vs. high-em
exposure (for adult and for child) and the ranking of the most
influential factors driving the risk estimates (a quantitative sensitivi
analysis if possible).
23 uncertainties at the interfaces between different process steps, and the appropriateness
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1 of the different levels of analysis across the steps of the risk assessment. For example,
2 combining dose-response and exposure data that are in different units forces the use of
3 assumptions or new data gathering.
4 An important iteration is the comparison of the analysis results with the goals set
5 out in the problem formulation stage. Once again, the description of uncertainties plays
6 a pivotal role, in this case to help determine whether these goals have been met. If the
7 results do not sufficiently address the goals, an iteration through one or more of the
8 previous steps might be indicated, including the initial scoping and problem formulation.
9 An important aspect of cumulative risk assessment is the process of identifying
10 and defining geographic areas, groups of chemical, biological and physical agents, and
11 exposure scenarios that are judged to either require or not require further analysis.
12 These decisions about the conduct of the assessment expand further to take into
13 account appropriate groupings of chemical agents using exposure information (Chapter
14 3) and judgments regarding similarity of toxic effects and the potential for interactions
15 (Chapter 4). Broader elements should also be addressed in the risk characterization:
16 appropriateness of the analytic selected scope, choice of agents for analysis, choice of
17 exposure scenarios, criteria for grouping chemicals, and identification of appropriate
18 populations for analysis. At the end of this process, the analyst identifies the types of
19 effects that might occur, quantifies their likelihood in different populations, and quantifies
20 the uncertainties in these estimates. Any effects or risks that cannot be quantified are
21 to be described qualitatively, along with suggestions for the kind of information required
22 for quantitative characterization. The principles and guidance offered in the Policy for
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1 Risk Characterization (U.S. EPA, 1995b) and Science and Judgment in Risk
2 Assessment (NRC, 1994) are applicable to characterizing cumulative risks.
3 Various individuals and groups may be significantly impacted by the results of the
4 risk characterization. As discussed earlier, potential stakeholders might be represented
5 by industry scientists and decision-makers, local government representatives, local
6 residents, citizen action groups, national environmental advocacy groups, and national
7 industry advocacy groups. Some issues with which they may be concerned include the
8 number of people exposed, the range of uncertainty around the exposure and health
9 risk estimates, the critical variables driving the assessment, the existence of data gaps,
10 the bottom-line conclusion, and whether the risk characterization supports a regulatory
11 decision. The economic and social ramifications of cumulative risk assessments require
12 that the risk characterization communicate the results clearly, highlighting the important
13 issues and uncertainties and exploring their implications for different audiences. The
14 risk characterization should focus on transparency in the logic that leads to decisions
15 regarding the inclusion or exclusion of specific exposure pathways, specific chemical
16 classes or groups of agents, and specific risk characterization approaches. The
17 consistency and reasonableness of the assumptions used to group chemicals for use in
18 risk assessment procedures also need to be evaluated. As discussed in the mixtures
19 risk guidance (U.S. EPA, 2000a), any quantitative or qualitative risk estimates must be
20 accompanied by the discussion of uncertainties and assumptions.
21 These obligations of risk characterization apply to all risk assessments
22 conducted by U.S. EPA. Issues unique to, or more complex in, cumulative risk
23 characterization are discussed in the following sections.
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1 5.1. SPECIAL CONCERNS WITH CUMULATIVE RISK CHARACTERIZATION
2 The EPA guidance documents on risk characterization all present lists of issues
3 or questions that should be addressed in the risk characterization step. As mentioned
4 above, the expansion to cumulative risk adds certain complexities, which change the
5 questions to be addressed. These lists usually include three major areas:
6 What is the simplest description that captures all the critical information?
7 How are the specific technical aspects addressed? and
8 What are the policy and technical choices or alternatives for the cumulative
9 assessment?
10 There are issues that are usually inappropriate for a cumulative risk characterization:
11 identifying a single key, supporting toxicity study; addressing only one critical effect; and
12 deriving a single benchmark risk value with which to judge safety of exposures. The
13 following list of questions may be used to guide the analyst in developing a cumulative
14 risk characterization. It covers most of the issues in the risk characterization handbook
15 (U.S. EPA, 2000f, Chapter 3) and is grouped according to the characteristics that differ
16 most with cumulative risk. (Several of the methods discussed are in Chapters 3 and 4.)
17 To Address Multiples:
18 Is there a focus, e.g., an effect caused by a single chemical by one pathway, that
19 dominates the risk? If no single key factor dominates, then what is the best
20 presentation of the array of possible combinations of factors?
21 How do composite evaluations compare with multivariate measures? How much
22 detail and accuracy is lost when combining across effects, such as with ordinal
23 regression? How well supported are the number of assumptions and default
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1 parameters that are used, and how can that strength of support be reflected in the
2 quantitative risk characterization?
3 How does the use of surrogates affect the overall uncertainties? How does
4 relying on an index chemical to represent the group increase the uncertainties
5 surrounding the contributions of the other chemicals?
6 Grouping chemicals, pathways, and effects structures and simplifies the
7 assessment. Are there alternative ways of grouping these factors? Are any factors
8 double-counted by the grouping process?
9 To Address Interactions:
10 Can the interaction magnitude be estimated for those chemical-pathway
11 combinations of most importance? How many interactions cannot be quantified? Can
12 all identified interactions at least be described for the direction of the interaction, i.e., do
13 they increase or decrease the risk?
14 To Address Populations of Concern:
15 How consistent are the risk estimates with those health effects of most concern
16 to the stakeholders as determined in the planning and scoping step? If a health effect
17 was the trigger or impetus for the cumulative risk assessment, is that effect adequately
18 addressed in the risk characterization?
19 To Address Time Dependencies:
20 What is the likelihood that the mixture composition or exposure pathways will
21 change over the timeframe being addressed? Can the impact of that change be
22 quantified in terms of a change in risk?
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1 How likely is it that the subpopulations of most concern will change location and
2 thus, change their risks over the timeframe being addressed?
3 Will any of the alternative remediation options change the mixture composition
4 (not just the total dose)? Is that change reflected in the way the expected reduction in
5 risk is calculated?
6 To Address Consistency of Information:
7 How well do the exposure levels in the dose-response data match the estimated
8 exposure ranges?
9 How much extrapolation is required for the risk estimates? How dependent is the
10 extrapolation on default values?
11 Are there inconsistencies among the data? Do some exposure or toxicity units
12 need conversion in order to allow combined exposure or joint toxicity to be estimated?
13 How different are the exposure and toxicity measures in terms of level of understanding,
14 level of accuracy, and detail? How much information is lost when reducing all the
15 measures to the lowest common level so that grouping and composite analysis can be
16 performed?
17 To Address Context:
18 How can the risk characterization for this site or situation be compared with risk
19 characterizations for other similar sites or situations? How can multivariate site
20 descriptions and risk evaluations be compared to determine whether sites are similar to
21 each other?
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1 5.2. EXAMPLE EVALUATIONS OF QUANTITATIVE APPROACHES TO
2 CUMULATIVE RISK CHARACTERIZATION
O
4 Much of the process of cumulative risk assessment involves information sharing,
5 planning discussions, and qualitative or judgment based decisions. As with all U.S.
6 EPA risk assessments, there is also the potential for quantification of exposure and risk.
7 Because cumulative risk assessment includes many factors, some of which vary over
8 time, the ideal risk calculations would utilize supporting measurements and studies that
9 usually do not exist. For example, Section 4.7.1 presents a modified relative potency
10 factor (RPF) approach for exposure to mixtures by multiple pathways. The RPF
11 approach requires information demonstrating that the chemicals included in the
12 calculation have similar toxicologic modes of action. Such information is not always
13 available on all chemicals of concern. Some of the quantitative approaches presented
14 in Chapter 4 are examined here in terms of feasibility and impact on the risk
15 assessment.
16 5.2.1. Example Cumulative Risk Characterization: Cumulative Hazard Index. As
17 an alternative to the RPF approach of Chapter 4, the integration of multiple chemical
18 exposures along multiple pathways can be quantitatively represented in a simple
19 fashion by the cumulative hazard index (CHI). The common dose-additive hazard index
20 (HI) combines multichemical exposures by summing the component exposure levels
21 after each has been scaled by division by that chemical's reference dose (RfD, for
22 ingestion) or reference concentration (RfC, for inhalation). (See Section 4.2.1 for a
23 complete description of the dose-additive HI.) The CHI is defined here to be similar to
24 the basic Superfund cumulative HI. The Superfund guidance first recommends
25 calculating each chemical's exposure for each completed pathway and then converting
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1 each into a pathway-specific, or more properly, a route-specific hazard quotient (HQ) in
2 the usual way. EPA's Risk Assessment Guidance for Superfund (1989a) instructs risk
3 assessors to sum HQs (Equation 5-1 ) across exposure routes and exposure pathways,
4 providing there is evidence of combined exposure pathways to identifiable individuals or
5 groups of individuals who would consistently face a reasonable maximal exposure. For
6 each chemical, the pathway HQs are summed to give the risk characterization reflecting
7 that chemical's total exposure to the individual or population, and expressed as a total
8 HQ across exposure routes with those routes explicitly stated. The CHI is then the sum
9 of these totals across chemicals.
10 5.2.1.1. Calculation Steps The CHI calculation that follows is based on the
11 Superfund guidance (U.S. EPA, 1999b).
12 This equation solves for pathway-specific HQ for chemical j:
13
14 where:
15 k = one of the pathways
16 Ejk = exposure for that pathway and
17 RVjk = the risk-based toxicity value for pathway k, such as the RfD for the water
18 pathway or the RfC for the air pathway.
19 This equation solves for total HQ for chemical j across m pathways:
m
20 HQJ=^HQJk (5-2)
k=1
21 The CHI across pathways and chemicals is then the sum across chemicals of the total
22 HQs:
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(5-3)
2 where n is the number of chemicals in the assessment. Not all chemicals need to be
3 present in a given pathway, and a given chemical need not be present in all pathways.
4 This latter condition means that in Equation 5-2, some terms might be zero.
5 5.2.1.2. Interpretation The numerical value of CHI is an index of concern in
6 the same vein as the common dose-additive HI used for mixture risk characterization.
7 The numerical value should not be interpreted as a risk number. For example, although
8 a higher CHI value indicates more concern for possible health effects, CHI=8 does not
9 necessarily indicate a site hazard that is 4 times worse than if CHI=2. The purpose of
10 the CHI is to express the degree of concern over possible toxic effects from onsite
11 exposure.
12 As with the mixture HI, the value of 1 could be used as the decision point for
13 determining whether further assessment or remedial action is warranted. When CHI>1,
14 the quality of the CHI should be examined. (Issues with CHI<1 are discussed below.)
15 The exposure assessment should be evaluated to determine any changes if more
16 details are available, such as information suggesting co-exposure by multiple pathways.
17 The dose-response assessment should be reviewed, particularly the assumptions of
18 similarity and no interaction (see Section 5.2.1.3), along with the other assumptions
19 described in the U.S. EPA mixture guidance (U.S. EPA, 2000a). As with the mixture HI,
20 if CHI is only slightly greater than 1 (say, CHI=3) then the uncertainties in the
21 methodology might exceed the numerical precision of the index. If CHI greatly exceeds
22 1, then there might be significant concern for health effects and the exposures should
23 be further evaluated for possible remedial action.
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1 When CHI<1, the indication is that no significant hazard exists by the chemicals
2 and pathways addressed. The key assumption to be checked is "no interaction." If any
3 indication of synergy exists from the supporting toxicity studies, then the pathways
4 involving those interacting chemicals should be evaluated in more detail. The second
5 check to be made is of the uncertainties, in particular the missing information (see
6 Section 5.3 for more details and suggestions).
7 Note that because the CHI involves simple sums, the summation can proceed in
8 either order:
9 either first sum across pathways for each chemical and then across chemicals
10 (Superfund's approach, given above in Equations 5-2 and 5-3) or
11 first sum across chemicals to get a pathway specific HI and then sum His across
12 pathways.
13 The first sequence of summing gives an index of total risk per chemical and thus
14 identifies which chemicals are posing the highest hazard or risk. That approach might
15 be useful in predicting the toxic effects that are most likely or of highest severity, keying
16 on the critical effects of those chemicals.
17 The second sequence gives an index of total risk per pathway, which might
18 assist in determining the preferred remediation approach. That approach might suggest
19 focusing on treating or mitigating the high risk pathway, without paying much attention
20 to the specific contaminants in that pathway. The best approach might be to perform
21 both intermediate calculations and present both the highest risk chemicals and highest
22 risk pathways to the decision makers. Previous experience by U.S. EPA in risk
23 assessments of Superfund waste sites indicates that in many cases risks will be
24 dominated by one or two chemicals and by one or two exposure pathways. These two
25 intermediate calculations will then help explain the extent of that dominance and provide
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1 support for further simplification or reduction in the scope of the cumulative risk
2 assessment.
3 This calculation is analogous to the cumulative risk approach used by the U.S.
4 EPA Office of Pesticide Programs (OPP). Although OPP uses margins of exposure
5 (MOEs) instead of HQs, once they are scaled by an uncertainty factor for species
6 differences, the total MOEs become nearly identical to the inverse of the total HQ. The
7 primary difference is in use of uncertainty factors. OPP considers whether there are
8 deficiencies in the database that apply to the chemicals as a group. The concern is tied
9 to the FQPA legislation that requires an additional safety factor when children's health is
10 an issue. If evidence indicates that another critical effect is produced by the identified
11 mechanism of toxicity at a dose significantly lower than those used in the risk approach,
12 then an additional database uncertainty factor is applied to the mixture assessment to
13 be protective for the young. OPP notes the importance of only applying an uncertainty
14 factor for database uncertainties once, i.e., either to a specific individual chemical or as
15 a group factor (U.S. EPA, 2002d).
16 5.2.1.3. Assumptions with CHI The risk characterization step should
17 address the assumptions in the CHI determination and the likely conditions under which
18 the approach would be reasonable and those under which it would be inappropriate.
19 Similar to the use of the mixture HI (U.S. EPA, 2000a), the CHI is useful for a screening
20 level risk assessment because it is fairly simple to determine once the exposures have
21 been estimated. The simple summation carries with it two assumptions:
22 There are no interactions across exposure pathways or chemicals in terms
23 of toxicity and
24
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1 There are no interactions across chemicals in terms of fate and transport
2 or in terms of single or multiroute uptake by the exposed individual.
3
4 The main weakness then seems to be this assumption of no interactions. By
5 drawing analogies to mixture risk procedures, one can define conditions under which
6 this exposure additivity, i.e., the lack of interaction, is plausible. The chemical
7 properties under which the HI for mixtures risk is plausible all relate to concepts of
8 functional or structural similarity. The counterparts for the CHI are:
9 Each of the chemicals incorporated into the CHI should be toxicologically
10 similar for all of the pathways included in its pathway HQ calculation and
11 should have no significant portal of entry effects (route-specific primary
12 toxicity). Similarity here can be indicated by the same toxic mode of
13 action, same primary target organs, or similar general type of toxic effect
14 (e.g., cancer, reproductive toxicity). (For further discussion of toxic
15 similarity, see Section 4.5). This property supports the combining of
16 exposures across pathways because for a given chemical, the same main
17 toxic effects occur for all pathways.
18
19 The chemicals grouped for a given pathway should be toxicologically
20 similar for that pathway according to the requirements for dose addition.
21 This property supports the combining of chemicals for a given pathway,
22 i.e., the pathway HI.
23
24 Perhaps most unique to cumulative risk assessment, the chemicals should
25 not affect each other's fate and transport, regardless of pathway.
26
27 Text Box 5-3 shows an example illustration.
28 5.2.2. Ordinal Regression Calculations for Multiple Effects and Pathways. One
29 complication of cumulative risk recognized in the Agency's Framework (U.S. EPA,
30 2003a) concerns the risk estimation and communication of multiple toxic effects. The
31 inclusion in the risk assessment of multiple stressors, pathways, exposure timeframes,
32 and subpopulations increases the likelihood of multiple effects of concern. One
33 approach is to separate the risk characterization into parts so that each part addresses
34 only one of the likely toxic effects. This approach would provide a fair amount of detail
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
that may be more difficult to
incorporate into a risk management
evaluation, partly because the
differing effects would need to be
ranked in order of public health
concern. An alternative is to
address the multiple effects directly
in a single composite measure as
described in Chapter 4.
5.2.2.1. Calculations
Two formulas are given in Chapter
4 (see Section 4.5.1) for describing
multiple effects and are restated
here, one based on the HI
(Equation 5-4) and one based on
response addition (Equation 5-5):
Hl(effects) =
Example: Site Safety (Text Box 5-3)
Consider the case where a goal is to be able to decide
with high confidence whether the site is safe as is. Then one
risk description could include an overly conservative (health
protective) estimate, perhaps one based on the high end
exposure estimates for each of the possible routes. If this
conservative risk estimate is considered to be within
acceptable levels, then any improved risk estimate is likely to
be lower, indicating high confidence of no health concern.
For risk characterization described by the CHI, then if CHI<1 ,
this screening level conclusion is there is no health concern.
This approach is similar to the screening calculation of a
Hazard Index that includes all chemicals, temporarily
ignoring the requirement of same target organ: if the
mixture's screening assessment gives Hl<1 , even when
including all target organs, then there is a conclusion of no
health concern because an improved and more appropriate
HI restricted to a specific target organ would be even lower
(U.S. EPA, 2001d). If CHI>1 , then additional evaluation is
recommended. Because the CHI is a conservative
overestimate of the hazard index, a value exceeding the
criterion does not imply the expectation of toxic effects but
only that a more detailed risk assessment is needed.
Note that for decisions on safety, the screening criterion
might be smaller, say CHI=0.5. Using a smaller index
criterion would assure more confidence that there is no
significant health concern. On the other hand, a smaller
criterion also increases the number of times the decision will
be to gather more information and perform a more detailed
risk assessment.
I
BMDLj
(5-4)
and
a
Rm (effects) = £ P, (severity > 2)
(5-5)
20 or more accurately as
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1 Rm (effects) = 1 - f] P, (severity < 2) (5-6)
1=1
2 where:
3 BMDL = Benchmark dose lower bound
4 UF = Uncertainty factor.
5 Equation 5-6 is the general form of Equation 4-2, response addition for only two
6 chemicals. As with the common response addition for mixtures, Equations 5-5 and 5-6
7 become essentially identical for low risks, say P\ <0.01. The representation in
8 Equation 5-6 might be easier to follow because its factors are the results of categorical
9 regression as given in Equation 4-3.
10 Details are provided in Chapter 4, but the basic concepts are fairly simple. In
11 both formulas, the underlying dose-response data, which include all effects of concern,
12 are first converted into dose-severity data by assigning each effect to a severity
13 category, where categories 3 and 4 represent toxic or lethal effects. In Equation 5-4,
14 the benchmark dose lower bound (BMDL) is derived from categorical regression on the
15 dose-severity data, and represents the dose associated with a fixed low probability of
16 toxicity, e.g., P(severity>2)=0.10. The BMDL is scaled to human terms by the
17 uncertainty factor so that the denominator is similar to the RfD and the formula
18 corresponds to the standard mixture HI formula.
19 The Hl(effects) calculated in Equation 5-4 could be used in the CHI calculation of
20 the pathway HI, and would then avoid the need to assume toxic similarity of the
21 chemicals in that pathway. Because all effects are included, the pathway HI and the
22 resulting CHI would also reflect all effects in the underlying dose-response data.
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1 In Equation 5-5, the first step is to convert the doses in the supporting toxicity
2 data into human equivalent doses. That converted set of dose-response data is then
3 modeled using categorical regression, as described above (and in Section 4.5.1). The
4 resulting regression formula is then used with the actual exposure estimates to generate
5 probabilities or risks of toxic effects (i.e., severity>2). The risk for the mixture is then
6 given by the sum of these chemical-specific risks. The mixture risk is not attached to
7 any particular toxic effect, as is the common single chemical benchmark risk, but
8 instead reflects all toxic effects in the underlying dose-response data and is then the risk
9 or probability of any toxicity. This risk addition approach is fairly easy to interpret for a
10 mixture of chemicals in one pathway or environmental medium, i.e., examining the
11 assumption of independent toxic action among the chemicals. For this regression on
12 overall severity, this assumption might be described as the toxicity of one chemical
13 having no effect on the toxicity of another chemical in the mixture, which is more
14 plausible if the component doses are all low. The combined mixture risk is then an
15 estimate of the probability of toxicity (any effect) from one or more of the chemicals.
16 The extension to cumulative risk in terms of a combination across pathways is not as
17 clear.
18 5.2.2.2. Assumptions with Multiroute Formulas for Multiple Effects The
19 calculation formulas for hazard or risk for multiple effects by multiple routes are similar
20 to their counterparts for simple mixtures, but the assumptions are less clear and more
21 difficult to evaluate. For Equation 5-4, the use of an HI implies the assumption of similar
22 toxicity across the chemicals. The regression on all effects makes the interpretation
23 more complex. Because the BMDL indicates a specific risk of toxicity, the HI represents
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1 an increasing concern as more chemicals approach or exceed their benchmark risk
2 level. The combining of multiple lower confidence bounds on the benchmark dose has
3 not been sufficiently investigated to allow a probabilistic interpretation in terms of a
4 confidence bound on the HI calculated in Equation 5-4.
5 Both of these approaches for addressing mixture risk for multiple effects are new
6 and have not been implemented in actual site assessments. One aspect related to
7 screening level assessments is the decision to base probabilistic risks on severity>2,
8 which means overt toxic effects. If a more conservative approach to the screening
9 assessment is indicated, then the calculations could be based instead on severity>1,
10 which would include definite effects that are not necessarily adverse. Further
11 exploration of the numerical properties of these approaches and scientific assumptions
12 with respect to transport and toxicity are encouraged.
13 5.2.3. Combination of Exposures of Different Time Frames. Risk estimates for
14 different time frames must consider the combined dose-duration influence on toxicity.
15 With complex aggregate exposures, the overlapping of exposures that have quite
16 different time courses is possible. An example is a low continuous exposure (say,
17 ambient air and drinking water) combined with intermittent exposure to industrial pulse
18 emissions, perhaps once a week at moderate to high levels. For acute exposure to
19 many chemicals, peak tissue concentration seems most appropriate as a predictor of
20 toxicity, i.e., accumulated dose or simple time-weighted averaging does not work
21 (Boyes et al., 2000). For longer exposure periods, simple cumulative dose (Haber's
22 rule) often does not work although a modified form does seem acceptable as a dose-
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1 duration metric. The combining of joint exposures over differing time frames then must
2 use the exposure metric appropriate to each exposure period.
3 The Agency and various scientists have published guidance, issue reports, and
4 research results on the impact of exposure duration on toxicity but so far only with
5 respect to single exposures for a fixed duration (Miller et al., 2000; Strickland and Guth,
6 2002; U.S. EPA, 1998d, 1999d, 2000c, 2004f; Zwart and Woutersen, 1988). The
7 complication with cumulative risk assessment is the potential overlap of exposures, the
8 durations of which differ. The combination exposures should be evaluated jointly, as
9 described in Chapters 3 and 4. When an exposure is short, less than a few days, then
10 the following steps are recommended:
11 Estimate the combined exposure during the short exposure period,
12 based on the combination of the short and longer exposures. For
13 example, a brief exposure to a hepatic toxicant might be combined with
14 a longer term exposure to another hepatic toxicant by summing their
15 exposure levels, to give a higher exposure level for the short duration.
16
17 Develop a risk characterization specific to this short exposure period,
18 focusing on those significant effects that do not persist beyond the
19 short exposure period.
20
21 Determine whether any effects from the short exposure are likely to
22 persist well into the longer exposure period. Those effects should be
23 incorporated into the description of likely toxicity for the longer period.
24 The persistent effects might be increased by the longer exposure and
25 might influence other effects caused by the longer exposure.
26
27 5.3. DESCRIPTION OF RESULTS
28 The risk characterization should include a summary or overview description of
29 health risk to the population of concern along with a second description that provides
30 more details. The goals defined in the problem formulation stage might dictate
31 additional descriptions or options.
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1 5.3.1. Risks for Population of Concern. The population of concern is one of the
2 items defined in the planning and scoping phase. The risk characterization for that
3 population is then a key result of the risk assessment and should at least include the
4 description of risk or expected toxicity for the average population exposure, along with
5 the size of the population. Because the assessment applies to the population as a
6 whole, this result can serve as a clear summary of the risk assessment. There is a
7 tendency, however, to describe such risks in simple, often one-dimensional terms. In a
8 cumulative risk assessment, however, complexity is expected. Because the setting
9 includes multiple chemicals with exposure potentially by multiple routes and time
10 frames, the number of health effects to be addressed can be quite high. For example,
11 even if one only described risks for the critical toxic effects, ignoring secondary effects
12 and joint toxicity, there can be different effects for each chemical, by each route, and for
13 each time frame of exposure. Moreover, the potential for several sensitive subgroups
14 means that the distribution of effects and severities to consider can be quite broad.
15 The cautionary advice most often given for cumulative risk characterizations is to
16 be clear and avoid oversimplification. With sufficient information, each of the parameter
17 combinations could be assessed separately, resulting in a distribution of risks that
18 covers the range of combinations of exposure and population subgroup. In many
19 cases, however, the information required for a complete quantitative risk
20 characterization of these combinations will be unavailable. At the least, the assessor
21 should provide a recommended risk estimate for the population, such as a central or
22 median risk estimate for the average individual, along with a risk estimate for the high
23 end of the population risk distribution. The high end risk characterization must clearly
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1 describe the assumed conditions leading to that high risk. Of particular importance is
2 the plausibility of the co-occurrence of the many factors related to the high-end risk. For
3 example, the risk of a given daily oral exposure might be highest for a child because of
4 the low body weight. The risk for an exercising adult (all else being equal) might be
5 highest because of the high daily drinking water intake. For a plausible high-end risk
6 estimate, the child body weight should be combined with the child daily intake and
7 similarly for the adult; it would be unrealistic to combine the two extremes: a low body
8 weight (e.g., the 10-kg child) with a high daily oral intake rate (e.g., the exercising adult).
9 The multiplicity of potential health effects in a diverse population raises another
10 complexity issue: the presentation or evaluation of the combination of different effects.
11 The traditional approach using a single critical effect avoids this issue so that the
12 population risk can be attached to one type of toxic endpoint, e.g., reproductive effects.
13 With cumulative risks, there may be several toxic effects of differing severity and with
14 different ways to measure or describe them, including some quantitative and some
15 judgmental. One approach described earlier (Chapter 4 and Section 5.1) relies on
16 converting the observed effects into a small set of severity categories, so that different
17 effects can be compared based on their toxic severity. Another approach is to simplify
18 the effects description by tying the risks to toxicity groups (see Chapter 4 and
19 Appendix B). In either case, the presentation of results must include a list of all effects
20 addressed by each risk measure, along with a discussion of the more likely effects.
21 Because of possible differences in exposure durations and treatability of the effects, the
22 discussion should also include any information on the persistence or reversibility of the
23 most likely effects.
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1 5.3.2. Risks for Population Subgroups. Specific population subgroups of main
2 concern might be identified in the planning and scoping stage. Some subgroups might
3 be linked to the trigger that led to the cumulative risk assessment although other
4 subgroups might also be of concern. For example, proposed siting of a chemical
5 manufacturing plant might be nearest to the population subgroup that initially raised the
6 issue, while emissions could disperse to cause wider-spread exposure. Those
7 subgroups identified in the scoping phase must be included in the risk characterization.
8 Results should be described in terms of the factors decided in the problem formulation
9 phase to ensure that the questions of central concern to the stakeholders have been
10 answered.
11 Several sensitive population subgroups might be identified during the exposure
12 and toxicity assessment steps. The risks to these subgroups should be described along
13 with estimates of the size of each subgroup, for completeness as well as improved
14 information for the risk managers. For example, remediation of organics in groundwater
15 by air stripping should be designed to avoid increasing risk to other sensitive subgroups,
16 such as nearby children living downwind.
17 5.3.3. Important Interaction Factors. The risk characterization will be used to decide
18 from among several risk management response alternatives, from recommended
19 changes in individual lifestyles of the affected population to official governmental action.
20 These responses often will involve changing one or more factors in the scenario. For
21 example, a remedial action could include moderate reduction of all exposures or
22 substantial reduction of some key exposures. Because the cumulative risk assessment
23 considers interactions (e.g., in transport and toxicity), those same interactions will affect
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1 the post-remediation risk assessment. Any remedial decisions will be enhanced if the
2 key interactions are identified and discussed in the risk characterization. Summaries
3 that only indicate the direction of potential interactions, i.e., greater or less than dose
4 addition (see Table 5-1), might still be useful for setting priorities or changing the degree
5 of conservatism used in the assessment.
6 One issue related to interactions, or at least to multiple sources contributing to
7 joint toxicity, is site-related (or source-related) exposure levels compared with
8 background exposure levels. Site contamination is often translated into the incremental
9 exposure, and thus incremental risk, i.e., the risk from the site exposure that exceeds
10 background. If background levels are comparable, and slightly toxic (e.g., above the
11 RfD for oral exposures), then the inclusion of background exposure into the cumulative
12 exposure estimate is appropriate as another source. When background exposure
13 contributes little to the cumulative risk, then separating the risks by background vs. the
14 site can add to the information needed for remedial action decisions.
15 5.4. DISCUSSION OF UNCERTAINTY
16 Clarity and transparency are requirements of cumulative risk assessments. For
17 risk descriptions, this relates to uncertainties and variabilities in the process and
18 calculations used to estimate the risks. Uncertainty refers to lack of knowledge, such as
19 unidentified chemicals in a groundwater sample or lack of data for modeling the
20 differences in toxicity between test animals and humans. Variability is used here to
21 denote known changes in certain important factors, changes that may or may not be
22 measured, and the impact of these changes on risk may not be quantified. Both
23 uncertainty and variability should be addressed quantitatively to the extent possible.
24
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TABLE 5-1
Joint Toxicity: Summary of Pairwise Toxic Interactions by Organ/System*
Metal
Interactions
Higher than
additive
Additive
Lower than
additive
Blood
As+Cd
As+Pb
Cd+Pb
Kidney
As+Cd
As+Cd
As+Cr
As+Pb
Cd+Pb
Neurologic
As+Pb
Cd+Pb
Male
Reproductive
Cd+Pb
As+Cd
Skin
Cr+As
Cardio-
vascular
As+Cr
Cd+Pb
2
3
4
*As=arsenic, Cd=cadmium, Cr=chromium, Pb=lead. All exposures are oral. This table
summarizes information in Table 4-2. (Data from ATSDR, 2004)
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1 When only qualitative characterizations are provided, their bases should be described
2 along with suggestions for ways to improve and quantify those characterizations.
3 As has been discussed in several previous U.S. EPA risk assessment guidance
4 reports, a critical part of the uncertainty analysis concerns the possible impact of
5 missing information. For example, if the risk assessment produces CHI<1, that might
6 not indicate safety if important information is not included. Instead, the CHI calculation
7 should be evaluated and quantified where possible for the likely change if the missing,
8 critical information were obtained. One example approach treats the possible impact on
9 a mixture risk estimate from unidentified chemicals in drinking water (U.S. EPA, 2003b).
10 Chemicals and exposure pathways that are not quantitatively included in the risk
11 assessment should be placed in a watch list, so that when sufficient information
12 becomes available, their contribution to the cumulative risk can be assessed.
13 5.4.1. Environmental Media Concentrations and Population Contact. The
14 exposure scenarios developed for a cumulative risk assessment involve multiple
15 chemicals and multiple environmental media. The concentrations of these chemicals in
16 various environmental media may be estimated through direct analytical measurement,
17 predictive modeling, or some combination of the two. The sensitivity and specificity of
18 different analyses used to measure the concentration of different chemicals or the same
19 chemicals in different media should be carefully evaluated. The quantitative uncertainty
20 of model predictions for concentrations of chemicals in different media may also vary.
21 When combining information on chemical concentrations in the characterization, clear
22 identification of the limits of the techniques used to estimate these concentrations is
23 necessary.
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1 Ingestion, inhalation, and dermal contact rate information may be developed from
2 several different sources. The U.S. EPA Exposure Factors Handbook (U.S. EPA,
3 1997c) recommends specific ingestion rates for foods such as vegetables and
4 freshwater fish, and drinking water. The relevance of the rates from these
5 recommended studies to the populations being evaluated should be examined. For
6 example, freshwater fish consumption rates among individuals in certain Native
7 American tribal groups may be greater than those in the general U.S. population (e.g.,
8 Peterson et al., 1995; Toy et al., 1995).
9 Finally, an exposure in a traditional risk assessment is often defined as an event
10 occurring in a specific place and at a specific time. In cumulative risk assessment, the
11 focus is on the population of concern, so that all relevant exposures are to be included.
12 The exposure event then might encompass several locations over a broad and varied
13 time period. These temporal and spatial aspects of cumulative risk analyses might then
14 require additional consideration as the dose-response data are integrated in the risk
15 characterization.
16 5.4.2. Dose-response Data. When determining groups of chemicals (as shown in
17 Figure 4-6b), the evaluation of component data includes steps that require consideration
18 of target organ specific data. Toxicity databases, such as the U.S. EPA IRIS database,
19 may provide toxicologic information only on a single critical effect (i.e., that effect
20 occurring at the lowest exposure level). Additional data such as those in the U.S. EPA
21 HEAST documents, ATSDR toxicological profiles and interaction profiles, or those
22 obtained from primary literature searches may be needed to identify additional effects
23 and target organs. Whether adequate dose-response data are available affects the
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1 grouping of chemicals and also the potential for estimating the joint toxicity of the
2 chemical combinations. When information on secondary effects is inadequate, the risk
3 characterization should address the impact of this uncertainty, particularly regarding
4 joint toxicity that may be underestimated for those secondary effects.
5 5.4.3. Multiplicity Issues with Exposures or Effects. The characterization of
6 complex exposures, even to a single chemical, might include well measured exposures
7 along with those that are conjectural or poorly understood. For example, concern might
8 exist for consequences of natural disasters (lightning induced fires, flooding) or
9 mechanical malfunction (e.g., intermittent emissions from an aging incinerator), neither
10 of which may have occurred at the site being assessed. One option is to present the
11 combined exposures and risks numerically for those aspects that can be quantified and
12 then describe the complete exposure and risks in qualitative terms, estimating the
13 impact on the risk estimate of the missing factors. In these situations, the analyst
14 should identify the source of the uncertainty, the available information to address it, and
15 the assumptions invoked in the risk analysis to compensate for the missing information.
16 5.4.4. Decision Steps in the Assessment Process. Throughout the analysis,
17 decisions will be made that influence the final conclusions of the assessment. Such
18 decisions may occur during planning and scoping and during the iterative analysis.
19 These decisions include the following:
20 the goal of the assessment
21 the spatial and temporal scope and scale of the analysis
22 the agents retained for analysis
23 the exposure scenarios considered
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1 the populations considered and
2 the choice of methods for evaluating risks posed under the selected
3 exposure scenarios.
4 The criteria used to make each of these decisions need to be clearly identified
5 and consistently applied. Although the criteria for planning, scoping, and problem
6 formulation are often determined early in the assessment process in consultation with
7 the stakeholders, these criteria must be clearly described in the risk characterization to
8 ensure transparency and clarity of the assessment's conclusions. When possible, a
9 sensitivity analysis should be performed to determine the relative impact of these
10 decisions on the resulting risk estimates. For example, if an exposure pathway is
11 screened out of the scope because the stakeholders desire focus on aspects under
12 local control, or because of the unlikelihood of obtaining adequate data for that pathway,
13 then the influence of ignoring that pathway should be described in the risk
14 characterization, even if merely to identify the direction of potential error (i.e., to
15 underestimate or overestimate the risk).
16 One approach to the evaluation of the decisions made during the assessment is
17 to determine the usefulness of the results, both in terms of addressing the issues laid
18 out in the scope, as well as providing information relevant to decisions about the
19 available remediation options (Figure 5-2). Suggested steps to follow when determining
20 the usefulness of the results include the following:
21 Evaluate compatibility of exposure, population, toxicity information.
22 - extrapolations (animal species, exposure route or duration, joint toxicity,
23 population susceptibility)
24 - measurement units (exposure or dose, toxic effects)
25 - omissions (pathways, chemicals, subpopulations, toxic effects)
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1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Planning-Scoping, Problem Formulation:
Cumulative Assessment Goals,
Risk Management Options
Analysis:
Exposure, Populations,
Toxicity
No
Extrapolations,
Simplifications,
and Omissions
Acceptable?^
Yes
Estimate Cumulative Risks and Uncertainties:
by Pathway, by Chemical or Group,
by Subpopulation,
by All Factors Combined
Can Scope or
Analysis be Refined?
Risk Estimates Sufficiently
Relevant and Accurate?
Conduct Qualitative Assessment Only,
Discuss All Cumulative Risk Elements,
Describe Data Gaps for Future Research
Document the Cumulative Risk Assessment
Process, Including Risk Estimates and
Uncertainty Discussion
FIGURE 5-2
Risk Characterization Decisions. Iteration to revisit the scope and analysis steps might resolve apparent incompatibilities
between the results and the available remediation options. Otherwise, a qualitative cumulative risk
assessment might be indicated.
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1 Evaluate health risk estimates and uncertainties.
2 - by subpopulation
3 - by pathway
4 - by chemical or chemical group
5 - for all factors combined.
6 Evaluate relevance and accuracy of risk estimates with respect to goals and risk
7 management alternatives identified in planning and scoping phase.
8 Identify next steps.
9 - revise analysis methods and seek new research information
10 - revisit planning and scoping steps
11 - consider qualitative assessment, including cumulative risk issues and
12 identification of needed data for cumulative risk.
13 5.5. SUMMARY RECOMMENDATIONS
14 5.5.1. Combined Characterization of Health Risk. Among the results in the
15 cumulative risk characterization should be the following:
16 Risk description for the main population of concern. The risks must
17 address those identified in the problem formulation phase as well as all
18 major exposure pathways and toxic effect groups.
19
20 Risk description for the high end risk groups or population subgroups.
21 These high end groups should reflect those with high single chemical
22 exposures as well as those with high exposure to interactive chemical
23 combinations. Subgroups of concern include those that are inherently
24 sensitive because of biological characteristics and those that are of
25 increased risk because of the cumulative aspects of risk, namely
26 toxicologic interactions. Such sensitivity might be related to physiologic
27 characteristics or exposure factors that could enhance the synergistic
28 activity of one or more chemicals. This latter group is unique to
29 cumulative risk assessment.
30
31 Summary of key uncertainties and suggestions for improvement.
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1 5.5.2. Interpretation of Results in Context of the Formulated Problem. Results
2 should highlight those risk estimates that address the issues identified in the problem
3 formulation step according to the consensus details of the planning and scoping step.
4 (See planning and scoping documents referred to in Chapter 1 for details.) The risk
5 assessment should contribute useful information to the risk management decisions. In
6 particular, the uncertainties should be linked to the stakeholder concerns and
7 interpreted in the context of the risk management options as well as the risk estimates
8 themselves. If the results do not seem to be compatible with the scope or are not
9 sufficiently accurate or detailed to be useful to the risk management decisions, then the
10 scoping and problem formulation steps should be revisited. For example, if the primary
11 concern is risks caused by contamination at the site, then a comparison is needed with
12 risks from exposures to background or off-site contamination.
13 5.5.3. Summary. The outcome of the risk characterization should provide a useful
14 integration of the data needed by the risk manager to make decisions regarding a
15 cumulative risk trigger. Results of the analysis may aid the risk manager in deciding the
16 extent of potential health risks from population, exposures and whether remedial action
17 is necessary. A cumulative risk characterization may include sensitive information such
18 as the number of people exposed, risk estimates for health endpoints of concern to the
19 community, uncertainties regarding the exposure and health risk estimates, and bottom-
20 line conclusions in support of a regulatory decision. Thus, results of the risk
21 characterization must be communicated clearly, with important issues and uncertainties
22 highlighted. Finally, the identification of data gaps, chemicals placed on a watch list,
23 and research needs that may improve the risk characterization should be articulated.
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1 6. REFERENCES
2
O
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1 ATSDR (Agency for Toxic Substances and Disease Registry). 1996. Toxicological
2 Profile for cis-, trans-1,2-Dichloroethene (update). U.S. Department of Health and
3 Human Services, Public Health Service. August. Available at
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5 ATSDR (Agency for Toxic Substances and Disease Registry). 1997a. Toxicological
6 Profile for Chloroform (update). U.S. Department of Health and Human Services, Public
7 Health Service. September. Available at http://www.atsdr.cdc.gov/toxprofiles/tp6.html.
8 ATSDR (Agency for Toxic Substances and Disease Registry). 1997b. Toxicological
9 Profile for Tetrachloroethylene (PERC). U.S. Department of Health and Human
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12 ATSDR (Agency for Toxic Substances and Disease Registry). 1997c. Toxicological
13 Profile for Trichloroethylene (TCE). U.S. Department of Health and Human Services,
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16 ATSDR (Agency for Toxic Substances and Disease Registry). 1997d. Toxicological
17 Profile for Vinyl Chloride (update). U.S. Department of Health and Human Services,
18 Public Health Service. September. Available at
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20 ATSDR (Agency for Toxic Substances and Disease Registry). 1999a. Toxicological
21 Profile for Lead. U.S. Department of Health and Human Services, Public Health
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23 ATSDR (Agency for Toxic Substances and Disease Registry). 1999b. Toxicological
24 Profile for Cadmium (Update). U.S. Department of Health and Human Services, Public
25 Health Service. July. Available at http://www.atsdr.cdc.gov/toxprofiles/tp5.html.
26 ATSDR (Agency for Toxic Substances and Disease Registry). 1999c. Toxicological
27 Profile for Mercury. U.S. Department of Health and Human Services, Public Health
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29 ATSDR (Agency for Toxic Substances and Disease Registry). 1999d. Toxicological
30 Profile for Uranium. U.S. Department of Health and Human Services, Public Health
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32 ATSDR (Agency for Toxic Substances and Disease Registry). 2000a. Toxicological
33 Profile for Arsenic (Update). U.S. Department of Health and Human Services, Public
34 Health Service. September. Available at http://www.atsdr.cdc.gov/toxprofiles/tp2.html.
35 ATSDR (Agency for Toxic Substances and Disease Registry). 2000b. Toxicological
36 Profile for Chromium (Update). U.S. Department of Health and Human Services, Public
37 Health Service. September. Available at http://www.atsdr.cdc.gov/toxprofiles/tp7.html.
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1 ATSDR (Agency for Toxic Substances and Disease Registry). 2001. Toxicological
2 Profile for 1,2-Dichloroethane. Update. U.S. Department of Health and Human
3 Services, Public Health Service, Atlanta, GA. Available at
4 http://www.atsdr.cdc.gov/toxprofiles/tp38.html.
5 ATSDR (Agency for Toxic Substances and Disease Registry). 2002a. Toxicological
6 Profile for Aldrin and Dieldrin. U.S. Department of Health and Human Services, Public
7 Health Service. September. Available at http://www.atsdr.cdc.gov/toxprofiles/tp1.html.
8 ATSDR (Agency for Toxic Substances and Disease Registry). 2002b. Toxicological
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32 Washington, DC. September. EPA/630/R-98/002.
33 U.S. EPA. 1987. The Risk Assessment Guidelines of 1986. U.S. Environmental
34 Protection Agency, Office of Health and Environmental Assessment, Washington, DC.
35 EPA/600/8-87/045.
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy 6-12
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1 U.S. EPA. 1989a. Risk Assessment Guidance for Superfund: Volume 1, Human Health
2 Evaluation Manual (Part A). U.S. Environmental Protection Agency, Office of
3 Emergency and Remedial Response, Washington, DC. EPA/540/1-89/002. (Also see
4 Parts B-D.)
5 U.S. EPA. 1989b. Interim Procedures for Estimating Risks Associated with Exposures
6 to Mixtures of Chlorinated Dibenzo-p-dioxins and -dibenzofurans (CDDs and CDFs) and
7 1989 Update. U.S. Environmental Protection Agency, Risk Assessment Forum,
8 Washington, DC. EPA/625/3-89/016.
9 U.S. EPA. 1991. Guidelines for Developmental Toxicity Risk Assessment. Federal
10 Register. 56(234):63798-63826.
11 U.S. EPA. 1992a. Guidelines for Exposure Assessment. U.S. Environmental
12 Protection Agency, Risk Assessment Forum, Washington, DC. EPA/600/Z-92/001.
13 U.S. EPA. 1992b. Screening Procedures for Estimating the Air Quality Impact of
14 Stationary Sources, Revised. Office of Air Quality Planning and Standards, Research
15 Triangle Park, NC. October. EPA/454/R-92/019.
16 U.S. EPA. 1994. Revised Interim Soil Lead Guidance for CERCLA Sites and RCRA
17 Corrective Action Facilities. U.S. Environmental Protection Agency, Office of Solid
18 Waste and Emergency Response, Washington, DC. OSWER Directive #9355.4-12.
19 U.S. EPA. 1995a. Profile of the Metal Mining Industry. U.S. Environmental Protection
20 Agency, Office of Compliance, Office of Enforcement and Compliance Assurance,
21 Washington, DC. September. EPA/310/R-95/008. Available at
22 http://www.epa.gov/compliance/resources/publications/assistance/sectors/notebooks/rn
23 etminsnpt1.pdf.
24 U.S. EPA. 1995b. Policy for Risk Characterization. Memorandum from Agency
25 Administrator Carol M. Browner, Washington, DC. March 21.
26 U.S. EPA. 1995c (et sequelae). Compilation of Air Pollutant Emission Factors. U.S.
27 Environmental Protection Agency, Office of Air Quality Planning and Standards.
28 EPA AP-42. Available at http://www.epa.gov/ttn/chief/ap42/.
29 U.S. EPA. 1996a. Soil Screening Guidance, Technical Background Document. U.S.
30 Environmental Protection Agency, Office of Solid Waste and Emergency Response,
31 Washington, DC. May. EPA/540/R-95/128. Available at
32 http://www.epa.gov/superfund/resources/soil/introtbd.htm.
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1 U.S. EPA. 1996b. PCBs: Cancer Dose-Response Assessment and Application to
2 Environmental Mixtures. U.S. Environmental Protection Agency, Office of Research
3 and Development, National Center for Environmental Assessment, Washington Office,
4 Washington, DC. EPA/600/P-96/001F.
5 U.S. EPA. 1997a. Guidance on Cumulative Risk Assessment, Part 1. Planning and
6 Scoping. U.S. Environmental Protection Agency, Science Policy Council, Washington,
7 DC. Attachment to memo dated July 3, 1997 from the Administrator, Carol Browner,
8 and Deputy Administrator, Fred Hansen, titled "Cumulative Risk Assessment Guidance-
9 Phase I Planning and Scoping." Available at
10 http://www.epa.gov/OSA/spc/2cumrisk.htm.
11 U.S. EPA. 1997b. Chemical and Radiation Leukemogenesis in Humans and Rodents
12 and the Value of Rodent Models for Assessing Risks of Lymphohematopoietic Cancers.
13 U.S. Environmental Protection Agency, Office of Research and Development, National
14 Center for Environmental Assessment, Washington, DC. May. EPA/600/R-97/090.
15 Available at http://www.epa.gov/ncea/pdfs/lympho.pdf.
16 U.S. EPA. 1997c. Exposure Factors Handbook-Volumes I, II, and III (General
17 Factors, Food Ingestion Factors, and Activity Factors). U.S. Environmental Protection
18 Agency, Office of Research and Development, National Center for Environmental
19 Assessment, Washington, DC. August. EPA/600/P-95/002Fa. Available at
20 http://www.epa.gov/ncea/pdfs/efh/front.pdf.
21 U.S. EPA. 1997d. Research on Risk Assessment Issues with Commercial Mixtures
22 Using Toxaphene as a Case Study. U.S. Environmental Protection Agency, National
23 Center for Environmental Assessment, Cincinnati, OH.
24 U.S. EPA. 1997e. Mercury Study Report to Congress. U.S. Environmental Protection
25 Agency, Office of Research and Development, Office of Air Quality, Planning &
26 Standards, Washington, DC. EPA/452/R-97/003.
27 U.S. EPA. 1998a. Methodology for Assessing Health Risks Associated with Multiple
28 Pathways of Exposure to Combustor Emissions. U.S. Environmental Protection
29 Agency, Office of Research and Development, National Center for Environmental
30 Assessment, Cincinnati, OH. December. EPA/600/R-98/137.
31 U.S. EPA. 1998b. Guidelines for Neurotoxicity Risk Assessment. Federal Register.
32 63(93): 26926-26954. EPA/630/R-95/001 F.
33 U.S. EPA. 1998c. Guidelines for Ecological Risk Assessment. Federal Register.
34 63(93): 26846-26924. EPA/630/R-95/002F.
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1 U.S. EPA. 1998d. C x T: Historical perspectives, current issues, and approaches. In:
2 Summary of the U.S. EPA Workshop on the Relationship Between Exposure Duration
3 and Toxicity. U.S. Environmental Protection Agency, National Center for Environmental
4 Assessment, Washington, DC. September. EPA/600/R-99/081.
5 U.S. EPA. 1998e. Handbook for Air Toxics Emission Inventory Development,
6 Volume I: Stationary Sources. U.S. Environmental Protection Agency, Office of Air
7 Quality Planning and Standards, Office of Air and Radiation, Washington, DC.
8 EPA/454/B-98/002.
9 U.S. EPA. 1999a. Guidance for Identifying Pesticide Chemicals and Other Substances
10 that Have a Common Mechanism of Toxicity. U.S. Environmental Protection Agency,
11 Office of Pesticide Programs, Washington, DC.
12 U.S. EPA. 1999b. A Guide to Preparing Superfund Proposed Plans, Records of
13 Decision, and Other Remedy Selection Decision Documents: 6.0: Writing the Record of
14 Decision. U.S. Environmental Protection Agency, Office of Solid Waste and Emergency
15 Response, Washington, DC. EPA/540/R-98/031.
16 U.S. EPA. 1999c. Sociodemographic Data Used for Identifying Potentially Highly
17 Exposed Populations. U.S. Environmental Protection Agency, National Center for
18 Environmental Assessment, Washington, DC. July. EPA/600/R-99/060. Summary
19 information (not the report) is available at
20 http://oaspub.epa.gov/eims/eimscomm.getfile7p download id=428679.
21 U.S. EPA. 1999d. Reregistration Eligibility Decision Facts for Chlorine Gas. U.S.
22 Environmental Protection Agency, Office of Prevention, Pesticides, and Toxic
23 Substances, Washington, DC. February. EPA/738/F-99/001. Available at
24 http://www.epa.gov/oppsrrd1/REDs/factsheets/4022fact.pdf.
25 U.S. EPA. 1999e. Guidance for Performing Aggregate Exposure and Risk
26 Assessments. U.S. Environmental Protection Agency, Office of Pesticide Programs,
27 Washington, DC. October. Available at http://www.pestlaw.eom/x/guide/1999/EPA-
28 19991029A.html.
29 U.S. EPA. 1999f. Screening Level Ecological Risk Assessment Protocol for Hazardous
30 Waste Combustion Facilities. Peer Review Draft. U.S. Environmental Protection
31 Agency, Office of Solid Waste and Emergency Response, Washington, DC. EPA/R6-
32 098/002A. November. Available at
33 http://www. epa. gov/epaoswer/hazwaste/com bust/ecorisk. htm.
34 U.S. EPA. 1999g. Frequently Asked Questions (FAQs) on the Adult Lead Model.
35 Technical Review Workgroup for Lead Guidance Document. U.S. Environmental
36 Protection Agency, Washington, DC. April.
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Does Not Constitute EPA Policy 6-15
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1 U.S. EPA. 1999h. Handbook for Criteria Pollutant Inventory Development: A
2 Beginner's Guide for Point and Area Sources. U.S. Environmental Protection Agency,
3 Office of Air Quality Planning and Standards, Office of Air and Radiation, Washington,
4 DC. September. EPA/454/R-99/037.
5 U.S. EPA. 1999i. Risk Assessment Guidance for Superfund (Volume 3, Part A:
6 Process for Conducting Probabilistic Risk Assessment). Draft. U.S. Environmental
7 Protection Agency, Office of Solid Waste and Emergency Response, Washington, DC.
8 December. Available at http://www.epa.gov/oswer/riskassessment/rags3adt/.
9 U.S. EPA. 2000a. Supplementary Guidance for Conducting Health Risk Assessment of
10 Chemical Mixtures. U.S. Environmental Protection Agency, Risk Assessment Forum,
11 Washington, DC. EPA/630/R-00/002. Available at
12 http://www.epa.gov/ncea/raf/pdfs/chem mix/chem mix 08 2001.pdf.
13 U.S. EPA. 2000b. Community Risk-Based Air Screening: A Case Study in Baltimore,
14 MD. Baltimore Community Environmental Partnership, Air Committee Technical
15 Report. U.S. Environmental Protection Agency, Office of Pollution Prevention and
16 Toxics, Washington, DC. April. EPA/744/R-00/005.
17 U.S. EPA. 2000c. CATREG Software Documentation. Office of Research and
18 Development, Washington, DC. EPA/600/R-98/053F.
19 U.S. EPA. 2000d. CATREG Software User Manual. Office of Research and
20 Development, Washington, DC. EPA/600/R-98/052F.
21 U.S. EPA. 2000e. Conducting a Risk Assessment of Mixtures of Disinfection By-
22 Products (DBPs) for Drinking Water Treatment Systems. U.S. Environmental Protection
23 Agency, Office of Research and Development, National Center for Environmental
24 Assessment, Cincinnati, OH. EPA/600/R-03/040.
25 U.S. EPA. 2000f. Science Policy Council Handbook: Risk Characterization. U.S.
26 Environmental Protection Agency, Science Policy Council, Washington, DC.
27 EPA/1 OO/B-00/002.
28 U.S. EPA. 2000g. Guidance for the Data Quality Objectives Process (QA/G-4). U.S.
29 Environmental Protection Agency, Washington, DC. Available at
30 http://www.epa.gov/guality/gs-docs/g4-final.pdf.
31 U.S. EPA. 2000h. Guidance for Data Quality Assessment: Practical Methods for Data
32 Analysis. U.S. Environmental Protection Agency, Office of Environmental Information,
33 Washington, DC. July. EPA/600/R-96/084. Available at
34 http://www.epa.gov/region10/www/offices/oea/epagag9.pdf.
35 U.S. EPA. 2001 a. General Principles for Performing Aggregate Exposure and Risk
36 Assessments. U.S. Environmental Protection Agency, Office of Pesticide Programs,
37 Washington, DC. Fax-On-Demand. Fax no. (202) 401-0527. Item no. 6043.
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1 U.S. EPA. 2001 b. Methylmercury Reference Dose. Integrated Risk Information
2 System. Available at http://www.epa.gov/iris/subst/0073.htm.
3 U.S. EPA. 2001 c. Trichloroethylene Health Risk Assessment: Synthesis and
4 Characterization, External Review Draft. U.S. Environmental Protection Agency, Office
5 of Research and Development, National Center for Environmental Assessment,
6 Washington, DC. August. EPA/600/P-01/002A. Available at
7 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=23249.
8 U.S. EPA. 2001 d. Risk Assessment Guidance for Superfund. Vol. I. Human Health
9 Evaluation Manual (Part D), Standardized Planning, Reporting, and Review of
10 Superfund Risk Assessments. U.S. Environmental Protection Agency, Office of Solid
11 Waste and Emergency Response, Washington, DC.
12 U.S. EPA. 2001 e. Guidance for Characterizing Background Chemicals in Soil at
13 Superfund Sites. External Review Draft. U.S. Environmental Protection Agency,
14 Washington, DC. June. EPA/540/R-01/003.
15 U.S. EPA. 2002a. Organophosphate Pesticides: Revised Cumulative Risk
16 Assessment. U.S. Environmental Protection Agency, Office of Pesticide Programs,
17 Washington, DC. Available at http://www.epa.gov/pesticides/cumulative/rra-op/.
18 U.S. EPA. 2002b. Region/ORD Workshop on Cumulative Risk Assessment.
19 November 4-8, 2002, Dallas, TX. Office of Science Policy, Washington, DC. Available
20 at http://www.epa.gov/osp/regions/cmrskrpt.pdf.
21 U.S. EPA. 2002c. Guidance on Cumulative Risk Assessment of Pesticide Chemicals
22 That Have a Common Mechanism of Toxicity. U.S. Environmental Protection Agency,
23 Office of Pesticide Programs, Washington, DC. Available at
24 http://www.epa.gov/oppfead1/trac/science/cumulative guidance.pdf.
25 U.S. EPA. 2002d. Ground Water and Drinking Water Technical Fact Sheet on
26 1,1-Dichloroethylene. U.S. Environmental Protection Agency, Office of Ground Water
27 and Drinking Water, Washington, DC. November. Available at
28 http://www.epa.goV/OGWDW/dwh/t-voc/11 -dichl.html.
29 U.S. EPA. 2002e. A Review of the Reference Dose and Reference Concentration
30 Processes. U.S. Environmental Protection Agency, Risk Assessment Forum,
31 Washington, DC. EPA/630/P-02/002F. Available at
32 http://epa.gov/iriswebp/iris/RFD FINALM l.pdf.
33 U.S. EPA. 2002f. Lessons Learned on Planning and Scoping of Environmental Risk
34 Assessment. Memorandum from Science Policy Council. January. Available at
35 http://www.epa.gov/osp/spc/llmemo.htm.
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1 U.S. EPA. 2002g. Region 9 Preliminary Remediation Goals Table 2002 Update.
2 Technical Memorandum (from Stanford Smucker, Regional Toxicologist, to PRG Table
3 Users). U.S. Environmental Protection Agency, Washington, DC. October. Available
4 at http://www.epa.gov/region09/waste/sfund/prg/files/02userguide.pdf.
5 U.S. EPA. 2002h. Guidance for Evaluating the Vapor Intrusion to Indoor Air Pathway
6 from Groundwater and Soils (subsurface vapor intrusion guidance). Draft. Federal
7 Register. 67(230):71169-71172. November 29. Available at
8 http://www.epa.gov/correctiveaction/eis/vapor.htm.
9 U.S. EPA. 2002i. Child-Specific Exposure Factors Handbook. Interim Report. U.S.
10 Environmental Protection Agency, National Center for Environmental Assessment,
11 Washington, DC. EPA/600/P-00/02b. Available at
12 http://cfpub.epa.gov/ncea/cfm/recordisplav.cfm?deid=55145.
13 U.S. EPA. 2003a. Framework for Cumulative Risk Assessment. U.S. Environmental
14 Protection Agency, Office of Research and Development, National Center for
15 Environmental Assessment, Washington, DC. EPA/600/P-02/001F. Available at
16 http://cfpub.epa.gov/ncea/cfm/recordisplav.cfm?deid=54944.
17 U.S. EPA. 2003b. The Feasibility of Performing Cumulative Risk Assessments for
18 Mixtures of Disinfection By-Products in Drinking Water. U.S. Environmental Protection
19 Agency, Office of Research and Development, National Center for Environmental
20 Assessment, Cincinnati, OH. EPA/600/R-03/051.
21 U.S. EPA. 2003c. Exposure and Human Health Reassessment of
22 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. National
23 Academy Sciences (NAS) Review Draft. U.S. Environmental Protection Agency,
24 Exposure Assessment and Risk Characterization Group, Washington, DC.
25 EPA/600/P-00/001Cb.
26 U.S. EPA. 2003d. Guideline on Air Quality Models, Appendix W of CFR Part 51, April.
27 Available at http://www.arb.ca.gov/toxics/harp/docs/40CFR APPW.pdf.
28 U.S. EPA. 2003e. Considerations in Risk Communication: A Digest of Risk
29 Communication as a Risk Management Tool. U.S. Environmental Protection Agency,
30 National Risk Management Research Laboratory, Cincinnati, OH. March.
31 EPA/625/R-02/004. Available at
32 http://www.epa.gov/ORD/NRMRL/Pubs/625r02004/625r02004.pdf.
33 U.S. EPA. 2003f. Developing Relative Potency Factors for Pesticide Mixtures:
34 Biostatistical Analyses of Joint Dose-Response. U.S. Environmental Protection Agency,
35 Office of Research and Development, National Center for Environmental Assessment,
36 Cincinnati, OH. EPA/600/R-03/052. Available at
37 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=66273.
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Does Not Constitute EPA Policy 6-18
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1 U.S. EPA. 2003g. Guidance for Developing Ecological Soil Screening Levels. Revised
2 February 2005. U.S. Environmental Protection Agency, Office of Solid Waste and
3 Emergency Response, Washington, DC. OSWER Directive 9285.7-55. Available at
4 http://www.epa.gov/ecotox/ecossl/pdf/ecossl guidance chapters.pdf.
5 U.S. EPA. 2003h. Region/ORD Workshop on Inhalation Risk Assessment: A
6 Superfund Focus: Summary Report. U.S. Environmental Protection Agency,
7 Washington, DC. September 9-12, 2003. Available at
8 http://intranet.epa.gov/ospintra/scienceportal/htm/complete.htmffinhale.
9 U.S. EPA. 2003i. Region 3 Risk-Based Concentrations (RBC) Tables. Technical
10 Background Document (from Jennifer Hubbard, Regional Toxicologist, to RBC Table
11 Users). U.S. Environmental Protection Agency, Washington, DC. October. Available
12 at http://www.epa.gov/reg3hwmd/risk/human/info/cover.pdf.
13 U.S. EPA. 2003J. User's Guide for Evaluating Subsurface Vapor Intrusion into
14 Buildings. Draft. Prepared by Environmental Quality Management under Contract
15 #68-W-01-058 to U.S. Environmental Protection Agency, Office of Emergency and
16 Remedial Response, Washington DC. June 19. Available at
17 http://www.epa.gov/superfund/programs/risk/airmodel/guide.pdf.
18 U.S. EPA. 2004a. Risk Assessment Guidance for Superfund Volume I: Human Health
19 Evaluation Manual (Part E, Supplemental Guidance for Dermal Risk Assessment).
20 U.S. Environmental Protection Agency, Office of Solid Waste and Emergency
21 Response, Washington, DC. EPA/540/R/99/005.
22 U.S. EPA. 2004b. Framework for Inorganic Metals Risk Assessment. U.S.
23 Environmental Protection Agency, Office of Research and Development, Risk
24 Assessment Forum, Washington, DC. EPA/630/P-04/068B.
25 U.S. EPA. 2004c. Air Screening Assessment for Cook County Illinois and Lake County
26 Indiana. Prepared by Argonne National Laboratory, Argonne, IL, in support of the
27 U.S. EPA Region V Cumulative Risk Initiative, for U.S. Environmental Protection
28 Agency, Office of Pollution Prevention and Toxics and Region V. (In press.)
29 U.S. EPA. 2004d. Human Exposure Measurements: National Human Exposure
30 Assessment Survey (NHEXAS). Office of Research and Development, National
31 Exposure Research Laboratory. Accessed March 2004. Available at
32 http://www.epa.gov/heasd/edrb/nhexas.htm.
33 U.S. EPA. 2004e. Air Quality Criteria for Particulate Matter. U.S. Environmental
34 Protection Agency, Office of Research and Development, National Center for
35 Environmental Assessment, Research Triangle Park, NC. EPA/600/P-99/002aF.
36 Available at http://cfpub.epa.gov/ncea/cfm/partmatt.cfm.
37 U.S. EPA. 2004f. Health-based Short-term Advisory Levels: Pilot Guide. National
38 Homeland Security Research Center, Cincinnati, OH.
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Does Not Constitute EPA Policy 6-19
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1 U.S. EPA. 2004g. Benchmark Dose Software. U.S. Environmental Protection Agency,
2 Washington, DC. Accessed February 18. Available at
3 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=20167.
4 U.S. EPA. 2005a. Wells G & H Fact Sheet. U.S. Environmental Protection Agency,
5 Region 1, Boston, MA. Available at
6 http://www.epa.gov/NE/superfund/sites/wellsgh/factsh.html.
7 U.S. EPA. 2005b. Region 9: Naturally Occurring Asbestos (NOA) in California. U.S.
8 Environmental Protection Agency, Region 9, San Francisco, CA. Available at
9 http://www.epa.gov/region09/toxic/noa/index.html.
10 U.S. EPA. 2005c. Integrated Risk Information System (IRIS). Accessed March 9,
11 2004. Available at http://epa.gov/iriswebp/iris/index.html.
12 U.S. EPA. 2005d. Human Health Risk Assessment Protocol for Hazardous Waste
13 Combustion Facilities, Final. U.S. Environmental Protection Agency, Office of Solid
14 Waste and Emergency Response (5305W), Washington, DC. EPA/520/R-05/006.
15 Available at http://www.epa.gov/epaoswer/hazwaste/combust/risk.htm.
16 U.S. EPA. 2005e. Human Health Medium-Specific Screening Levels. U.S.
17 Environmental Protection Agency, Region 6, Dallas, TX. November. Available at
18 http://www.epa.gov/earth1r6/6pd/rcra c/pd-n/r6screenbackground.pdf.
19 U.S. EPA. 2005f. Guidelines for Carcinogen Risk Assessment. U.S. Environmental
20 Protection Agency, Risk Assessment Forum, Washington, DC. EPA/630/P-03/001B.
21 U.S. EPA. 2005g. Supplemental Guidance for Assessing Susceptibility from Early-Life
22 Exposure to Carcinogens. U.S. Environmental Protection Agency, Risk Assessment
23 Forum, Washington, DC. EPA/630/R-03/003F.
24 U.S. EPA. 2005h. All-Ages Lead Model (AALM) Version 1.05 (External Review Draft).
25 U.S. Environmental Protection Agency, Washington, DC. EPA/600/C-05/013. Available
26 at http://cfpub.epa.gov/ncea/cfm/recordisplav.cfm?deid=139314.
27 Verma, A.K., G.T. Bryan and C.A. Reznikoff. 1985. Tumor promoter 12-0-
28 tetradecanoylphorbol-13-acetate receptors in normal human transitional epithelial cells.
29 Carcinogenesis. 6(3):427-432.
30 Waller, K., S.H. Swan, G. DeLorenze and B. Hopkins. 1998. Trihalomethanes in
31 drinking water and spontaneous abortion. Epidemiology. 9(2):134-140.
32 Walton, G. 1951. Survey of literature relating to infant methemoglobinemia due to
33 nitrate-contaminated water. Am. J. Public Health. 41:986-996 (cited in U.S. EPA,
34 2005c).
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1 Weischer, C.H., W. Kordel and D. Hochrainer. 1980. Effects of NICI2 and NiO in Wistar
2 rats after oral uptake and inhalation exposure, respectively. Zent Bakteriol. Mikrobiol.
3 Hyg. (B) 171:336-351 (cited in ATSDR, 2003b).
4 Yadrick, M.K., M.A. Kenney and E.A. Winterfeldt. 1989. Iron, copper, and zinc status:
5 Response to supplementation with zinc or zinc and iron in adult females. Am. J. Clin.
6 Nutr. 49:145-150 (cited in U.S. EPA, 2005c).
7 Zhang, J. and X. Li. 1987. Chromium pollution of soil and water in Jinzhou. J. Chinese
8 Prev. Med. 21:262-264 (cited in ATSDR, 2000b).
9 Zwart, A. and R.A. Woutersen. 1988. Acute inhalation toxicity of chlorine in rats and
10 mice: Time-concentration-mortality relationships and effects on respiration. J. Haz. Mat.
11 19:195-208.
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1 7. GLOSSARY
2
O
4 Significant terms used in this guidance document and in cumulative health risk
5 assessments are defined below. Definitions have been extended to include the
6 implications for cumulative risk assessment. Many general risk terms are not included
7 because standard definitions are readily available elsewhere. In particular, EPA and
8 ATSDR have developed extensive glossaries of risk assessment terms (available at
9 http://www.epa.gov/iris/gloss8.htm, http://oaspub.epa.gov/trs/ and
10 http://www.atsdr.cdc.gov/glossarv.html).
11
12 Absorbed dose. The concentration of a chemical inside the body, upon being taken in
13 through an absorption barrier, e.g., skin absorption, ingestion (see dose).
14
15 Acute toxicity. Adverse effect expressed within a short time (generally from minutes to
16 a day) following exposure to an agent (here, chemical). Most experimental acute
17 toxicity studies involve response to a single, large dose of an agent, although
18 occasionally to multiple exposures given within a short time period. EPA defines acute
19 exposure to be 24 hours or less.
20
21 Additivity. Concept that cumulative or joint risk can be represented by adding the
22 component information, commonly used for chemical doses or their toxic responses.
23 Additivity is the default assumption for evaluating health effects of multiple chemicals.
24 Specifically, an additive formula for the toxicity of multiple chemicals is some function of
25 a linear combination of the component exposures or toxic responses (such as a
26 weighted sum). Exposure can be represented by the external exposure level or the
27 internal dose, and toxic response can be represented by the frequency or probability of
28 toxicity or the measure of toxic effect. (The terms exposure and effect must be explicitly
29 defined for additivity to be meaningful for a given combination of chemicals.)
30
31 Agent. An environmental chemical that could cause harm to human health. (More
32 broadly interpreted, this term can include biological stressors such as anthrax and
33 physical stressors such as noise and heat as well as stressors causing impacts other
34 than toxicity. This guidance focuses on chemicals and human health effects.)
35
36 Aggregate exposure. The combined exposure of a receptor (individual or population)
37 to a single chemical. The chemical can originate from multiple sources and be present
38 in multiple media, and exposures can occur by different routes and over different time
39 periods. Under current Agency definitions, aggregate exposure does not translate to
40 cumulative risk because it addresses only one chemical; however, combining aggregate
41 exposures by addressing two or more chemicals would constitute a cumulative risk
42 assessment.
43
44 Antagonism. The process by which two or more chemicals together exert an effect
45 that is lower than would be predicted by simple addition, which is usually defined as
46 adding the doses or responses of the individual chemicals. For example, copper has
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1 been shown to protect against cadmium poisoning. Thus, depending on their levels
2 (compared with those at which this sparing effect is observed), ingesting both could
3 reduce the combined toxic response predicted from summing the individual responses.
4 Additivity must be clearly defined (e.g., dose or response addition) to appropriately
5 assess whether antagonism exists, and care must be taken to understand the dose-
6 response relationships. For example, if dose addition were applied when in fact the
7 chemicals were toxicologically independent (meaning response addition should be
8 applied), then the result would be lower than expected and could be misinterpreted as
9 antagonism.
10
11 Bioactivation. Process by which a chemical or its metabolite is biochemically
12 converted to a reactive intermediate. For example, chloroform is converted in the body
13 to the reactive intermediate phosgene (which was historically used as a chemical
14 weapon). In a mixture, one chemical can trigger the toxic effects of another by affecting
15 its bioactivation.
16
17 Biomolecule. Any molecule synthesized by an organism, e.g., an enzyme or other
18 protein.
19
20 Chemical antagonism. The process by which two or more chemicals undergo a
21 chemical reaction to produce a different chemical, which has a lower toxic effect than
22 that predicted from adding the toxic responses of the original chemicals; this toxic effect
23 might also qualitatively differ from those of the original chemicals (see antagonism).
24
25 Chemical exposure class. A group of chemicals that are physically and chemically
26 similar, primarily in chemical structure and potential for environmental transformation
27 and transport (as directly linked to potential exposure). For example, chlorinated
28 ethanes are considered a chemical exposure class because they are generated by the
29 same commercial process and have similar fate and transport characteristics so are
30 often found together in the environment.
31
32 Chemical mixture. Two or more chemicals that coexist (e.g., whether at a generating
33 source, dispersed in the environment, or inside a person) and could contribute to
34 combined toxicity; their actual identities or origins might or might not be known.
35 Examples include: (1) Aroclor 1254 (a commercial combination of PCB congeners) in
36 soil and (2) benzene and ethanol together in the body due to workplace exposures to
37 benzene followed by drinking beer at home. In parallel with the common risk
38 assessment term for single chemicals, this can also be referred to as the "mixture of
39 concern" (see whole mixture and complex mixture).
40
41 Chemical synergism. The process by which two or more chemicals undergo a
42 chemical reaction to produce a different chemical, which has a greater toxic effect than
43 that predicted from adding the toxic responses of the original chemicals; this toxic effect
44 might also qualitatively differ from those of the original chemicals (see synergism).
45
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1 Chemical toxicity class. A group of chemicals that are toxicologically similar, primarily
2 due to similarities in chemical structure and biologic activity. Such a group with similar
3 toxicities could also be a chemical exposure class, e.g., if they were produced by the
4 same commercial process and frequently coexist in the environment. Where the
5 composition of such a group is well controlled (e.g., by a standard generating process),
6 the mixture could be evaluated as a single chemical. Examples include dioxins,
7 coplanar (dioxin-like) polychlorinated biphenyls (PCBs), and ketones; these similar
8 groups of compounds can also interact toxicologically with chemicals outside their class.
9
10 Complex interaction. The interaction produced by three or more chemicals acting
11 together that cannot be described according to other interaction definitions. (For two
12 chemicals, see pair-wise interaction.)
13
14 Complex mixture. A mixture containing so many chemicals that any estimate of its
15 toxicity based on the toxicities of its components is too uncertain to be useful. The
16 chemical composition of this type of mixture could vary over time or with different
17 generating conditions. The various components of complex mixtures can be produced
18 as commercial products or they can be generated simultaneously as byproducts of a
19 process (e.g., diesel exhaust emissions), or they can coexist because of disposal
20 practices. To assess risks for complex mixtures, exposure and toxicity data for the
21 complete mixture are preferred (see whole mixture method).
22
23 Component(s). Single chemicals that make up a mixture. These could be further
24 classified by the type of toxicity they cause. For example, the individual toxicities of
25 dichloroethylene and acetone ingested together could be separately assessed, as well
26 as their potential for toxicologic interaction.
27
28 Component-based method. An approach for evaluating a mixture using exposure and
29 dose-response information for the individual chemicals in that mixture. This approach is
30 useful for comparing mixtures that contain the same chemicals but in differing
31 concentrations and proportions to determine whether they are similar mixtures. (See
32 whole mixture method for comparison.)
33
34 Contact. The connection between a receptor (person) and a chemical (e.g., in soil,
35 water, or air). Contact can be continuous (constant) or intermittent (e.g., only occurring
36 at discrete times during a day or season).
37
38 Critical effect. The toxic effect characterized by the lowest observed adverse effect
39 level (LOAEL), which represents the lowest dose at which any adverse effect is
40 observed regardless of its nature (e.g., severity) and serves as the basis of the toxicity
41 values used to assess noncancer effects (see reference dose, reference concentration,
42 and toxicity value).
43
44 Cumulative risk. The combined risk to a receptor (individual or population) from
45 exposures to multiple agents (here, chemicals) that can come from many sources and
46 exist in different media, and to which multiple exposures can be incurred over time to
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1 produce multiple effects. (Health risks are the focus of this guidance.) More than one
2 chemical must be involved for the risk to be considered cumulative.
o
4 Detoxify. Diminish or remove the toxicologic effect of a chemical, e.g., by metabolic or
5 chemical reaction with another (sometimes referred to as detoxicate).
6
1 Dose. The amount of a chemical that enters into the body (from being administered,
8 taken, or absorbed), usually expressed as milligrams of substance per kilogram of body
9 weight. If the exposure surface crossed is an absorption barrier, the dose is an
10 absorbed dose/uptake dose; otherwise it is an intake dose. The dose represents the
11 amount available for interaction, e.g., with other chemicals, metabolic processes or
12 biologically significant receptors.
13
14 Dose addition. The process by which the doses of individual chemicals in a mixture
15 are summed to represent an overall mixture dose. This approach assumes that the
16 chemicals are toxicologically similar, with each behaving as a concentration or dilution
17 of an index chemical in that mixture (effectively as a senior or junior clone). The mixture
18 dose is estimated by summing equivalent doses of the individual chemicals, which are
19 determined by scaling the toxic potency of each to that of the index chemical (see index
20 chemical and hazard index).
21
22 Effect. The health endpoint resulting from the chemical exposure(s), which can be
23 estimated or observed (such as increased liver enzyme levels, cardiac arrhythmia, or
24 cancer). Human health effects are typically estimated from effects observed in animal
25 toxicity studies, with various adjustment factors applied as appropriate.
26
27 Endpoint. An observable or measurable biological event; this can be an observed
28 effect or a chemical concentration (e.g., of a metabolite in a target tissue) used as an
29 index of an exposure.
30
31 Exposure. The contact between a chemical and the outer boundary of an organism,
32 quantified as the amount available at the exchange boundaries (e.g., skin, lungs, or
33 gut). This contact can be intermittent or continuous. The total amount of exposure is
34 determined by multiplying the exposure time, frequency, and duration.
35
36 Exposure duration. The total length of time over which an exposure occurs, given in
37 years for chronic exposures. Unless time-weighted averaging can be justified, repeated
38 exposures should consider duration to be the time period from start to end of the
39 exposure. For example, if an individual contacts a chemical 10 minutes a day for
40 350 days a year over 8 years, the exposure duration is 8 years.
41
42 Exposure frequency. How often a receptor is exposed to a chemical over a year, for
43 chronic exposures. For example, if an individual contacts a chemical 10 minutes a day
44 for 350 days a year over 8 years, the exposure frequency is 350 days/year.
45
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1 Exposure pathway. The physical course a chemical takes from its source to a
2 receptor. If an exposure is occurring the exposure pathway is considered complete.
3 The elements of a complete pathway are (1) a chemical source (e.g., waste lagoon)
4 and mechanism of release (e.g., volatilization or leaching); (2) contaminant fate (such
5 as physical or chemical changes) and transport through the environment (e.g., air,
6 water, and soil); (3) an exposure point, or the location where the receptor comes in
7 contact with either the source itself or a medium carrying the chemical; and (4) an
8 exposure route.
9
10 Exposure route. The way a chemical gets inside an individual who comes in contact
11 with it, e.g., inhalation, ingestion, or dermal absorption.
12
13 Exposure time. How long a receptor is in intermittent or continuous contact with a
14 chemical over a day. For example, if an individual is in contact 10 minutes a day for
15 350 days a year over 8 years, the exposure time is 10 minutes/day.
16
17 Extrapolation. The process by which information is inferred to fill a gap in existing
18 data. Commonly used to estimate the response at a low dose, often well below the
19 range of the experimental data, or equitoxic doses across species. The better
20 approaches use biologically based mathematical models.
21
22 Hazard identification. The process of determining whether exposure to a given
23 chemical or mixture could cause harm (adverse health effects). It can also involve
24 qualitatively indicating the nature of the likely health effects.
25
26 Index chemical. The one chemical in a mixture against which the toxicities of the other
27 chemicals are normalized so equivalent doses can be calculated and summed to
28 represent the total dose of the mixture. Two key criteria are used to select an index
29 chemical: first, good toxicity data should exist (with a clearly defined dose-response
30 relationship), and second, it should represent the whole group well. To illustrate,
31 2,3,7,8-TCDD is the index chemical for dioxins because it has the best toxicity data and
32 is considered a good representative of this group of compounds; the concentrations of
33 the other dioxins are multiplied by their individual potencies relative to this isomer, then
34 summed as "2,3,7,8-TCDD equivalents" to arrive at the dose for the dioxin mixture.
35
36 Induction. The initiation or elicitation of a certain response, which can be beneficial or
37 adverse. The response can be evaluated across a wide scale, from the genetic and
38 cellular level to the tissue and whole-organism level. For example, at the genetic level
39 the activity of a regulatory protein can induce increased expression of a certain gene,
40 while at the molecular level the binding of a chemical to a biomolecule can induce an
41 enzyme to increase its reaction rate or initiate a series of biochemical reactions that can
42 ultimately result in an adverse health effect (such as kidney hyperplasia).
43
44 Inhibition. The process by which a chemical that is not itself toxic acts on another
45 chemical that is toxic and makes that chemical less toxic. (More broadly, this term
46 means the limitation or prevention of a certain response, which could be beneficial or
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1 adverse. For example, if the response is cell growth, one toxic chemical might inhibit
2 the growth of certain cells needed for a system to function properly, while another might
3 inhibit cell proliferation that would otherwise lead to tumor formation [e.g., a
4 chemotherapeutic agent]. For mixtures, this term is often used to describe beneficial
5 inhibition as indicated above.)
6
7 Interaction. Generally, the influence or action of one chemical on the behavior or effect
8 of another, which can be mutual or reciprocal. In the environment, interactions among
9 chemicals can alter their physicochemical forms and transport characteristics (e.g.,
10 increasing or decreasing mobility and bioavailability). Within the body, one chemical
11 can interact with another (or others) to cause toxicity, increase or decrease a response,
12 or completely change the response expected from the individual chemicals acting alone.
13 Both pharmacokinetics and pharmacodynamics could be altered by the interactions of
14 chemicals that can target different organs or organ functions and can result from
15 simultaneous or sequential exposures (so long as they are present at the same time
16 within the body, e.g., due to pharmacokinetic overlap). The Agency has defined toxic
17 interactions as being less or more than additive.
18
19 Interindividual variability. Differences among individuals within the same species,
20 e.g., differential susceptibility of humans to a given heath effect from exposure to a
21 given hazard, which can result from metabolic or other pharmacokinetic differences. To
22 illustrate for a physical hazard (ultraviolet radiation), one person might sunburn after
23 spending an hour outside, while another might not burn for several more hours, i.e., until
24 the exposure is much greater. Similar variability exists for exposures to chemicals and
25 within other species (see intraspecies variability).
26
27 Internal dose. The dose of a chemical inside the body. Depending on the nature of
28 the data, this can be expressed as (1) the total absorbed dose of the original chemical
29 (also referred to as the parent compound), (2) the concentration of the parent
30 compound in target tissues, (3) the total amount of the toxicologically active metabolite,
31 or (4) the concentration of the toxicologically active chemical species in the target
32 tissues.
33
34 Interspecies variability. Differences between different species (e.g., between rats and
35 mice, or between rats and humans). A factor of 10 is often applied to account for these
36 differences in deriving a standard toxicity value to estimate human health effects from
37 animal studies, as indicated by the appropriate scientific data.
38
39 Intraspecies variability. Differences within a single species (e.g., among rats or
40 among mice, but not between rats and mice). A factor of 10 is often applied to account
41 for these differences in deriving a standard toxicity value to estimate human health
42 effects as indicated by the appropriate scientific data (see interindividual variability).
43
44 Joint toxicity. The toxic outcome resulting from the interaction of a set of two or more
45 chemicals. This outcome can be lower than, equal to, or greater than that predicted by
46 adding the doses or responses of the component chemicals acting alone.
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1 No observed interaction. The negative outcome of a study of two or more chemicals,
2 which indicates that they do not interact at the levels studied, to alter either behavior or
3 effect. For example, considering toxic interactions, if two chemicals were administered
4 together or coexist within the body due to pharmacokinetic overlap (when exposure
5 timing differs), and if the effect produced does not differ from that expected by the two
6 chemicals acting alone (which could also be no effect), then no interaction would be
7 observed. (Note: this term was used to categorize study outcomes for EPA's Mixtox
8 data base.)
9
10 Parent compound. The original form of a chemical prior to its transformation in the
11 environment (e.g., by photolysis or microbial degradation) or its transformation within
12 the body (e.g., by metabolism).
13
14 Pharmacodynamics (PD). The study of the biochemical and physiological effects of
15 drugs and their mechanisms of action, or what they do to the body (see toxicodynamics
16 for the parallel study of toxic chemicals).
17
18 Pharmacokinetics (PK). The study of the absorption, distribution, metabolism, and
19 excretion of a drug in and from the body (see toxicodynamics for the parallel study of
20 toxic chemicals).
21
22 Physiologically based pharmacokinetic (PBPK) model. A mathematical model that
23 estimates the dose to a target tissue or organ by taking into account the rates of
24 absorption into the body, distribution among organs and systems, metabolism, and
25 elimination. It typically takes the form of compartments that represent organs and
26 tissues, linked by flow (e.g., blood) exchanges, with associated weights, volumes, flow
27 rates and fractions, partition coefficients, and metabolic constants based on
28 physiological studies. These mechanistic PBPK models translate exposure to tissue
29 concentrations, characterizing tissue dosimetry for different species, doses, and route
30 extrapolations. (Although PBPK models can offer insights into metabolic interactions for
31 mixtures, integrating multiple contaminants greatly increases the amount of data
32 needed for parameter estimates.)
33
34 Potentiation. The process by which a chemical that is not itself toxic acts on another
35 chemical that is toxic and makes that chemical more toxic. (More broadly, this term
36 means the enhancement of a certain response, which could be beneficial or adverse.
37 For mixtures, this term is often used to describe an enhanced adverse response, as
38 indicated above.)
39
40 Receptor. The individual or population group actually or potentially exposed to a
41 chemical (receptors can be real or hypothetical). For contaminated sites, various
42 receptors are typically hypothesized to evaluate potential risks under likely future uses,
43 to help guide risk management decisions. In cases where real people might be
44 incurring exposures (e.g., including cleanup workers), these should clearly be assessed.
45
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1 Reference concentration (RfC). An estimate (with uncertainty spanning perhaps an
2 order of magnitude) of a continuous inhalation exposure to the human population
3 (including sensitive subgroups) that is likely to be without an appreciable risk of
4 deleterious effects during a lifetime. It can be derived from a NOAEL, LOAEL, or
5 benchmark concentration, with uncertainty factors generally applied to reflect limitations
6 of the data used. Generally used in U.S. EPA's noncancer health assessments.
7
8 Reference dose (RfD). An estimate (with uncertainty spanning perhaps an order of
9 magnitude) of a daily oral exposure to the human population (including sensitive
10 subgroups) that is likely to be without an appreciable risk of deleterious effects during a
11 lifetime. It can be derived from a NOAEL, LOAEL, or benchmark dose, with uncertainty
12 factors generally applied to reflect limitations of the data used. Generally used in U.S.
13 EPA's noncancer health assessments.
14
15 Reference value (RfV). An estimate of an exposure for a given duration to the human
16 population (including susceptible subgroups) that is likely to be without an appreciable
17 risk of adverse health effects over a lifetime. It is derived from a BMDL, a NOAEL, a
18 LOAEL, or another suitable point of departure, with uncertainty/variability factors applied
19 to reflect limitations of the data used. [Durations include acute, short-term, subchronic,
20 and chronic and are defined individually in this glossary.] [Reference value is a term
21 proposed in the report A Review of the Reference Dose and Reference Concentration
22 Processes (U.S. EPA, 2002e), and is a generic term not specific to a given route of
23 exposure. U.S. EPA develops numerical toxicity values for the RfD and RfC only; no
24 numerical toxicity values are developed for the RfV.]
25
26 Response addition. The process by which the toxic response of each chemical in a
27 mixture is summed to represent an overall mixture response. This approach assumes
28 the chemicals are toxicologically independent, and the toxic response can be defined as
29 a rate, incidence, risk, or probability of effect. For mixtures, the response equals the
30 conditional sum of the toxic responses for individual chemicals as defined by the
31 formula for the sum of independent event probabilities. For two-chemical mixtures, this
32 means the incremental toxic effect from exposure to the first chemical is the same
33 whether the second chemical is present or not. (Response addition underlies the
34 standard process for estimating combined cancer risks by summing the cancer risks of
35 individual chemicals.)
36
37 Risk. The probability (for carcinogens) or potential (for noncarcinogens) that adverse
38 health effects to result from chemical exposures (see cumulative risk). (More broadly,
39 this term also covers other types of risks and other stressors, but the focus of this
40 guidance is the potential for harm to human health from exposures to multiple
41 chemicals.)
42
43 Similar components. Single chemicals that cause or are expected to cause the same
44 type biologic activity based on toxicity studies or chemical structure (e.g., as analogues,
45 reflecting the structure-activity relationship). In addition to similar characteristics in
46 terms of physiological processes and toxicity within the body, these chemicals would
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1 also be considered to have similar fate and transport characteristics in the environment.
2 Evidence of toxic similarity can include (1) similarly shaped dose-response curves,
3 (2) parallel log-probit or logit dose-response curves for quantal (presence-absence) data
4 on the number of animals (or people) exhibiting a specific response, and (3) the same
5 mechanism of action or toxic endpoint. Trichloroethylene and tetrachloroethylene are
6 examples of similar components.
7
8 Similar mixtures. Mixtures of similar chemicals although they might differ slightly from
9 one another (e.g., same chemicals but in slightly different proportions or the same
10 chemicals in nearly the same proportions but missing a few or have a few new ones).
11 Similar mixtures cause or are expected to cause the same type of biologic activity, and
12 they would act by the same modes of action or affect the same toxic endpoints. In
13 addition to similar characteristics in terms of physiological processes and toxicity within
14 the body, these chemicals would also be considered to have similar fate and transport
15 characteristics in the environment. Varying grades of gasoline (e.g., from regular to
16 super-premium) are examples of similar mixtures.
17
18 Simple mixture. A set of chemicals that is small enough for each individual chemical to
19 be identified, so the toxicity of the mixture can be characterized by combining the
20 toxicities and considering the interactions of the component chemicals. For example,
21 acetone, methylene chloride, and ethanol present together in water to which someone
22 could be exposed would comprise a simple mixture.
23
24 Slope factor. An upper bound, approximating a 95% confidence limit, on the increased
25 cancer risk from a lifetime exposure to an agent. This estimate, usually expressed in
26 units of proportion (of a population) affected per mg/kg-day, is generally reserved for
27 use in the low-dose region of the dose-response relationship, that is, for exposures
28 corresponding to risks less than 1 in 100.
29
30 Source. The location of the environmental chemical(s) being assessed (e.g., an
31 incinerator stack or waste lagoon), from which it is released and can subsequently be
32 transported through the environment.
33
34 Stressor. A chemical that could cause harm. More broadly, this term also covers
35 biological agents such as anthrax and physical agents such as noise and heat. The
36 umbrella definition provided in the Framework for Cumulative Risk (U.S. EPA, 2003a)
37 extends to any physical, chemical, or biological agent that can induce an adverse
38 response, e.g., a chemical, noise, loss of habitat, or lack of food or water.
39
40 Substrate. The substance to which another material attaches or upon which it acts, for
41 example an environmental chemical or biomolecule upon which an enzyme acts. This
42 can be a chemical that binds to the active site of an enzyme or other protein in the body.
43
44 Synergism. The process by which two or more chemicals together exert an effect that
45 is greater than would be predicted by simple addition, which is usually defined as
46 adding the doses or responses of individual components. For example, depending on
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1 their levels (compared with those at which the toxic interaction is observed), inhaling
2 both carbon tetrachloride and acetone could produce a more toxic liver response than
3 would be predicted from summing the individual responses. Additivity must be clearly
4 defined (e.g., dose or response addition) to appropriately assess whether synergism
5 exists; care must be taken to understand the dose-response relationships. For
6 example, if response addition were applied when in fact the chemicals were dose-
7 additive, then the result would be higher than expected and could be misinterpreted as
8 synergism.
9
10 Target Organ. The biological organ adversely affected by a given chemical or mixture.
11
12 Toxicity value. The standard value used to translate chemical exposures (doses) to
13 estimates of cancer risks or the potential for noncarcinogenic effects. The cancer or
14 noncancer toxicity value is specific to the chemical (or mixture), route of exposure, and
15 duration over which the exposure occurs. These values are typically derived from
16 animal studies, with adjustment factors applied to develop estimates for humans. For
17 the cancer endpoint the toxicity value is termed the slope factor, and for noncarcinogens
18 it is termed the reference concentration (RfC) for inhalation exposure and reference
19 dose (RfD) for oral exposure.
20
21 Toxicodynamics (TD). The sequence of events at the cellular and molecular levels
22 leading to a toxic response following exposure to a chemical. This involves the
23 processes underlying the effect severity, reversibility, recovery, and adaptive response.
24 (See the general term pharmacodynamics, which was developed for drug studies.
25 Although the TD term is often used in risk assessments of environmental chemicals,
26 pharmacodynamics could be a more appropriate term for certain chemicals, e.g.,
27 essential metals, depending on the exposure levels.)
28
29 Toxicokinetics (TK). The characterization and quantification of the time course of
30 absorption, distribution, and metabolism (or biotransformation) in the body and
31 elimination (or excretion) from the body of a chemical taken in. (See the general term
32 pharmacokinetics, which was developed for drug studies. Although the TK term is often
33 used in risk assessments of environmental chemicals, pharmacokinetics could be a
34 more appropriate term for certain chemicals, e.g., essential metals, depending on the
35 exposure levels.)
36
37 Toxicologic interaction class. A group of chemicals that are toxicologically similar in
38 terms of the direction of toxicologic interaction (synergism, antagonism, or additivity).
39 For any given interacting chemical, when paired with other members of this group the
40 direction of the interaction would be the same. This group can be defined as a
41 toxicologic interaction class only for specific toxic endpoints. Ketones and selenium
42 compounds are examples of interaction classes.
43
44 Trigger. A condition involving more than one chemical that catalyzes a cumulative risk
45 study, such as (1) multiple sources/releases, (2) measured or inferred chemical
46 concentrations, or (3) illness in a given population.
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1 Unable to assess. The effect of the chemical (mixture) cannot be classified, for
2 example due to lack of proper control groups; lack of statistical significance; or poor,
3 inconsistent, or inconclusive data in the available toxicity studies.
4
5 Uncertainty factor (UF). An adjustment factor applied to experimental data in deriving
6 toxicity values used to estimate health risks and the potential for noncancer effects.
7 These factors are applied to account for (1) variation in susceptibility among members
8 of the human population; (2) uncertainty in extrapolating animal data to humans;
9 (3) uncertainty in extrapolating from data obtained in a study with less-than-lifetime
10 exposure; (4) uncertainty in extrapolating from a lowest-observed-adverse-effect level
11 (LOAEL) instead of a no-observed-adverse-effect level (NOAEL); and (5) uncertainty
12 associated with extrapolation when the database is incomplete (which might be
13 addressed by a modifying factor).
14
15 Whole mixture. A mixture that is evaluated in its entirety, usually with exposure levels
16 for the entire mixture unadjusted for any differences among the toxic potencies of its
17 component chemicals. Some whole mixtures can be defined and are reproducible, e.g.,
18 where the process that created them is well understood. Other whole mixtures are
19 defined by groups of structurally similar chemicals that often co-occur. Examples
20 include total chromium and compounds and total petroleum (hydrocarbons). This term
21 is often applied to highly complex mixtures with components that cannot be fully
22 identified or reproducibly measured. Diesel exhaust, gasoline, and toxaphene are
23 specific examples.
24
25 Whole mixture method. An approach in which the whole mixture is treated as a single
26 entity, similar to the way single chemicals are assessed, and thus requires dose-
27 response information for the whole mixture. This approach is used for complex
28 mixtures, and it is best applied to mixtures with a composition that is constant over the
29 entire exposure period. It differs from the component-based method because the
30 toxicity information inherently reflects unidentified chemicals in the mixture as well as
31 any interactions that might be occurring among the chemicals. (See the component-
32 based method for comparison.)
33
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1 APPENDIX A
2 CUMULATIVE RISK TOOLBOX
4 This appendix identifies resources that can be used to address various elements
5 of cumulative risk assessments for specific situations and contaminated sites. Several
6 have been applied at sites being addressed by the U.S. Environmental Protection
7 Agency (U.S. EPA) and U.S. Department of Energy (DOE). Many of these resources
8 are also useful for other types of cumulative risk analyses, and tools from U.S. EPA
9 studies for several regulatory programs are also included here.
10 Many federal, state, academic, and professional organizations have developed
11 general risk assessment guidelines and tools for a variety of situations. While some
12 resources clearly consider multiple exposures to multiple chemicals, such as the
13 standard Risk Assessment Guidance for Superfund (U.S. EPA, 1989a), relatively few
14 are described as explicitly assessing cumulative risks by specifically addressing
15 groupings or joint toxicity, or by being population focused. The main body of this report
16 includes discussions of how more recent cumulative risk approaches can enhance the
17 traditional risk assessment approach. The toolbox of information resources presented
18 in this appendix includes many tools developed for general risk assessments that can
19 also be used or adapted for population specific cumulative risk assessments, or whose
20 underlying approaches offer insights for these assessments. This toolbox is not
21 intended to be comprehensive; the aim is simply to highlight those resources that could
22 be useful for cumulative health risk assessments. This appendix focuses on chronic
23 exposures, but some resources related to acute or subchronic exposures (such as
24 those developed for health and safety in the workplace) are also included.
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1 Resources that support planning, scoping, and problem formulation, including
2 stakeholder involvement, are identified in Section A.1. Those that support evaluations
3 of contaminant fate and transport and exposure, which range from summary data on
4 physicochemical constants to specific transport and exposure models, are highlighted in
5 Section A.2. Resources that support the toxicity evaluation are offered in Section A.3,
6 and those that support the characterization of risk and uncertainty and presentation of
7 results are highlighted in Section A.4. Several resources cover more than one of these
8 topics; where this is the case, they are generally listed within their main area of
9 emphasis. The information reproduced here is believed accurate as of the publication
10 date. The intent is to post these resources on U.S. EPA's Web site and update them
11 regularly.
12 A.1. RESOURCES FOR PLANNING, SCOPING, AND PROBLEM FORMULATION
13 Topics addressed during iterative planning, scoping, and problem formulation
14 include the purpose and scope of the assessment (which involves considering multiple
15 chemicals, exposures, effects, and population groups), the products needed, the data to
16 be collected and synthesized, the general assessment approach, and stakeholder
17 involvement. Cumulative risk assessments are complex because of the very large
18 number of potential combinations of chemicals and interactions inherent to
19 environmental settings.
20 During this initial and iterative phase of a cumulative assessment, a main focus is
21 on which chemicals present are most likely to interact and what the nature of those
22 interactions might be. The internet has emerged as a very valuable tool for stakeholder
23 involvement. It can be used to easily provide information about the project and
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1 associated scientific issues for a wide audience, which can be browsed on-line or
2 downloaded at the user's convenience. It can also be used to notify interested parties
3 of upcoming meetings or the availability of specific reports for the site. Project websites
4 and e-mails can also be used to effectively solicit and receive stakeholder inputs about
5 the project. Limited-access web sites can be also used to share and evaluate draft
6 information as it is developed.
7 The usefulness of internet-based approaches for stakeholder involvement is
8 described further below, and examples of specific tools are included in Table A-1. (Note
9 that most resources presented in this toolbox are available through the internet.)
10 1. Low cost to involve many stakeholders. Although fixed costs to build a website
11 can be somewhat high, the marginal cost to involve additional stakeholders is
12 nearly zero, so the internet can be cost-effective for projects with extensive
13 stakeholder participation. For example, a document can be posted on a website
14 very cheaply; in contrast, mailing would require postage, printing, and paper
15 costs with marginal costs that do not diminish significantly with additional users
16 (essentially free via the internet method). Receiving stakeholder inputs through
17 the web or e-mail can also save costs compared with paper-based approaches.
18
19 2. Wide geographical reach. Using a website and e-mail allows ready access to
20 information and opportunity for participation regardless of stakeholder location, in
21 contrast to traditional methods that typically focus on people nearby. This is
22 particularly important when travel to public meetings is restricted (e.g., due to
23 cost, schedule, or physical disabilities). This broad accessibility can increase
24 participation because additional people become aware of the project (e.g.,
25 through web searches). The use of e-mail can also be effective because
26 information can be delivered to a broad set of stakeholders at their desktops.
27
28 3. Availability. Information posted to a public website is available 24 hours a day, 7
29 days a week, and can be accessed at times convenient to the user - which can
30 also increase participation. (People without computers could access the internet
31 from libraries or other such facilities during regular hours.) Likewise, e-mails can
32 be opened at the user's convenience.
33
34 4. Extent of information. Large amounts of data and other information can be
35 provided via the internet, much more than would be reasonable by other means
36 (meetings and paper). Further, this information can be reviewed at whatever
37 level of detail and pace the user prefers.
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1 5. Immediacy. Information can be made available essentially immediately via the
2 internet. This can be especially useful for situations that might arise when the
3 level of concern is high (e.g., when wildfires or accidents cause acute releases).
4
5 6. Data interactivity. Websites can integrate the capabilities of many different
6 databases, geographic information systems (GISs), graphing, and other tools so
7 stakeholders can play with data and information in ways that would not be
8 possible under traditional methods (e.g., with hard copies). This can include
9 "clicking" on specific locations to identify multiple chemicals present there, or
10 searching to find all locations with a specific combination of chemicals (e.g.,
11 which could be known to interact).
12
13 7. Flexibility. Information shared vie the web or e-mail can be made available in
14 different types of electronic formats, which can facilitate use by multiple parties.
15 Also, websites and e-mail communications can be readily adapted to
16 accommodate new types of information as it is developed.
17
18 Selected resources that can be used to support planning, scoping, and problem
19 formulation for cumulative risk assessments, including stakeholder involvement, are
20 briefly described below. Selected information is also summarized in Table A-1 at the
21 end of this section.
22 Framework for Cumulative Risk Assessment (U.S. EPA). The framework
23 document released in spring 2003 identifies an umbrella structure for cumulative
24 risk assessments, identifies key issues, and defines common terms. It
25 summarizes basic elements of the cumulative risk assessment process and
26 presents a flexible structure for conducting cumulative risk assessments. Neither
27 a procedural guide nor a regulatory requirement, this framework is expected to
28 evolve over time. The document does not present protocols to address specific
29 risk issues; rather it provides good information about important aspects of
30 cumulative risk (U.S. EPA, 2003a). A main foundation of this guidance, the
31 report is available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=54944.
32
33 Planning and Scoping for Cumulative Risk Assessment (U.S. EPA).
34 Guidance was published in 1997 by the U.S. EPA Office of Science Policy,
35 Science Policy Council, which reflects the Agency's policy statement for planning
36 and scoping for cumulative risk assessments (U.S. EPA, 1997a). This guidance
37 presents ideas for broad-based approaches, including consideration of multiple
38 endpoints, sources, pathways and routes of exposure; community-based
39 decision making; flexibility in achieving goals; case-specific responses; a focus
40 on all environmental media; and holistic reduction of risk. This report is available
41 at http://www.epa.gov/OSA/spc/2cumrisk.htm. Lessons learned from cumulative
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1 risk case studies are captured in a companion technical memorandum (report)
2 (U.S. EPA, 2002f), available at http://www.epa.gov/osp/spc/llmemo.htm.
o
4 Environmental Justice Geographic Assessment Tool (U.S. EPA) and Similar
5 Ranking/Prioritization Tools. Designed jointly by the U.S. EPA Office of
6 Environmental Information and Office of Environmental Justice, this tool is a GIS-
7 based module to support front-end scoping of cumulative assessments. It
8 combines environmental, socioeconomic, and health indicators in statistical
9 tables, and it was initially developed to evaluate potential issues related to
10 environmental justice. Where a community-based approach is applied, this tool
11 can be helpful in identifying the risk problems to be assessed. (Although
12 presented here within the planning/problem formulation stage, this can also be a
13 used to support risk characterization.)
14
15 Site Conceptual Exposure Model (SCEM) Builder (DOE). The SCEM Builder
16 was developed by the DOE Office of Environmental Policy and Guidance in 1997
17 to support planning, scoping, and problem formulation for risk assessments at
18 contaminated sites, by providing a tool to build SCEMs. An SCEM is a visual
19 representation of scenarios that organizes information about sources of
20 contamination, release mechanisms, exposure pathways, and receptors for a site
21 and can be used to address data gaps. These conceptual models are often used
22 to develop data quality objectives (DQOs) and prioritize field sampling activities,
23 in order to help reduce uncertainty associated with risk characterization. Using
24 this tool, assessors can build SCEMs for a given site and modify variables to
25 refine the model, e.g., to reflect stakeholder inputs. This tool can also be used to
26 develop SCEMs for various "what-if" scenarios to help bound data uncertainties.
27 It is available at http://tis.eh.doe.gov/oepa/programs/scem.cfm.
28
29 Stakeholder Involvement (U.S. EPA, DOE). Several resources exist that
30 document the procedures and approaches implemented to support stakeholder
31 involvement activities in risk assessment projects. These range from national
32 policy guidance documents to site-specific reports that chronicle the approaches
33 taken by individual projects to solicit input from stakeholders and incorporate
34 their concerns and ideas into the analysis plan. Guidance from the U.S. EPA
35 Superfund and Environmental Justice programs (captured in Table A-1)
36 encourages community involvement and can be useful for cumulative risk
37 assessments at contaminated sites.
38
39 A number of stakeholder involvement examples exist that can offer insights for
40 cumulative risk assessment projects. Many are available for contaminated DOE
41 sites, where citizen advisory boards have been established to provide input
42 during planning and scoping and as assessments progress. The mission or
43 charter language prepared by these advisory boards can offer clues for other
44 projects. Such language typically includes general "rules of engagement"
45 (including respect for diverse opinions) as well as specific roles and
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1 responsibilities (notably with regard to providing advice and recommendations
2 instead of making management decisions for the project).
o
4 For example, a citizen's advisory board (CAB) was created to facilitate public
5 outreach for the DOE Savannah River Site. That CAB consists of 25 individuals
6 from South Carolina and Georgia chosen by an independent panel of citizens
7 from approximately 250 applicants that reflect the cultural diversity of the local
8 population. The CAB has considered itself a major component of the risk
9 assessment/management team for the site and maintains a website
10 (www.srs.gov/general/outreach/srs-cab) that offers ideas that can be useful for
11 similar programs at other sites.
12
13 A stakeholder advisory board has also been established at the DOE Hanford site
14 in Washington. Information on the Hanford Advisory Board (HAB) is available at
15 http://www.hanford.gov/public/boards/hab/. This Board created a calendar for
16 public involvement that lists upcoming meetings and other events at which input
17 from affected parties and stakeholders is encouraged. Nearly a decade ago, an
18 advisory group that included many stakeholders and a technical expert team
19 from the project considered an approach for a comprehensive impact
20 assessment for the Columbia River that flows next to the site; that effort is no
21 longer underway as defined at that time, but related information can be found on
22 the internet (e.g., see http://www.hanford.gov/docs/rl-96-16/). The DOE
23 management at Hanford has also put together a comment response tracking
24 system, as have other sites, to coordinate the issues identified by stakeholders
25 during the iterative planning and scoping phase and throughout the assessment
26 process (which at this site will last for decades), and to track follow-ups.
27
28 A stakeholder involvement program is under way for an ongoing sitewide
29 cumulative risk assessment and risk reduction project at the DOE Los Alamos
30 National Laboratory (LANL) in New Mexico. This approach has been developed
31 and is being implemented by the independent Risk Assessment Corporation
32 (RAC) team is under the Risk Analysis, Communication, Evaluation, and
33 Reduction (RACER) project. The primary objectives of this project are to
34 develop:
35
36 1. A process for extensive stakeholder involvement in the risk assessment and
37 decision-making processes for LANL.
38
39 2. A methodology to estimate contemporary (current) human health risks and
40 ecological impacts from LANL using available data on chemicals and
41 radionuclides measured in environmental media.
42
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1 3. A methodology to implement a comprehensive risk-informed decision
2 analysis framework, including a prospective risk and ecological impact
3 assessment and other quantitative and qualitative criteria, to guide long-term
4 management of risks and ecological impacts at LANL.
5
6 4. A consistent approach for efficiently compiling, using, and updating data to
7 support the risk assessment and decision-making processes.
8
9 Guidelines developed by RAC for involving stakeholders in this project are
10 included on the project website at
11 http://www.racteam.com/LANLRisk/Reports/Guidelines%20for%20lnvolvement%
12 2010-30.pdf. The RACER project is also involving local schools in science
13 projects, including to provide input to exposure scenarios. This input is also
14 being solicited in one-on-one meetings with others at various locations in the
15 community (businesses and homes).
16
17 A much earlier scientific educational partnership was established more than a
18 decade ago at the Weldon Spring site. Information about that Partners in
19 Education program can be found at http://web.em.doe.qov/wssrap/pie.html.
20 Every community will have its own priorities and levels of interest. More
21 examples are given in Table A-1.
22
23 Data Quality Objectives and Assessment (U.S. EPA). The Agency has
24 developed a series of documents that provide guidelines to help ensure that the
25 data collected are appropriate for their intended use (see Table A-1). These
26 documents outline a systematic planning process for developing performance
27 criteria for the collection, evaluation, and use of environmental data. This
28 process can be used to focus communication among interested parties and to
29 form the basis for selecting decision points for a risk assessment project. The
30 overall approach is called the DQO process, and it is detailed in Guidance for the
31 Data Quality Objectives Process (U.S. EPA, 2000g). The seven-step planning
32 approach to develop sampling designs for data collection is iterative and applies
33 to all scientific studies, but it is particularly useful for addressing problems that
34 have two clear alternatives. The final outcome of the DQO process is a design
35 for collecting data (including the number of samples, location of samples, and
36 collection method) that acknowledges the limits on the data collection and the
37 probabilities of making decision errors. Guidance can be found at
38 http://www.epa.qov/quality/qs-docs/q4-final.pdf.
39
40 The Agency has also developed Data Quality Assessment (DQA) guidance
41 (U.S. EPA, 2000h) that describes procedures to help ensure that data used in
42 risk assessments are appropriate for their intended use with respect to quality,
43 quantity, and type. Also provided are statistical and analytical tools that can be
44 used to review DQOs and sampling designs, review preliminary data, select
45 statistical tests to summarize and analyze data, verify the assumptions of the
46 statistical test, and perform appropriate calculations.
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TABLE A-1
Selected Resources for Planning, Scoping, and Problem Formulation
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Resources for Overall Planning, Scoping, and Problem Formulation
Framework for Cumulative Risk
Assessment (U.S. EPA)
http://cfpub.epa.gov/ncea/cfm/recordispl
ay.cfm?deid=54944
Provides a flexible framework for cumulative risk
assessments; identifies the basic elements of the process,
describes a number of technical and coordination issues,
and defines terms.
Defines general structure and components
of cumulative risk assessments; serves as
the foundation for this report.
Guidance on Cumulative Risk
Assessment - Part 1, Planning and
Scoping (U.S. EPA)
http://www.epa.gov/OSA/spc/2cumrisk.
htm
This guidance directs each office of U.S. EPA to take into
account cumulative risk issues in scoping and planning
major risk assessments and to consider a broader scope
that integrates multiple sources, effects, pathways,
stressors and populations for cumulative risk analyses in
all cases for which relevant data are available. It
describes general approaches and concepts for planning
and scoping for cumulative risk assessments.
Identifies four key steps for planning and
scoping: determine overall purpose and risk
management objectives for assessment;
determine the scope, problem statement,
participants, and resources; determine the
risk dimensions and technical elements that
may be evaluated; and formulate a
technical approach including a conceptual
model and an analysis plan for conducting
the assessment.
Lessons Learned on the Planning and
Scoping of Environmental Risk
Assessments (U.S. EPA)
http://www.epa.gov/osa/spc/pdfs/handb
ook.pdf
Provides early feedback to agency scientists and
managers regarding U.S. EPA's experiences with
planning and scoping as the first step in conducting
environmental assessments. It is intended to reinforce the
importance of formal planning and dialogue prior to
conducting complex cumulative assessments and to
provide case studies "lessons learned" for anyone
involved in planning an assessment.
Provides information and feedback from the
Part 1 planning guidance that offer insights
for designing and conducting cumulative
risk assessments.
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TABLE A-1 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Environmental Justice Geographic
Assessment Tool (U.S. EPA)
http://www.epa.gov/enviro/ej/
CIS-based module designed for front-end scoping of
cumulative assessments. Combines environmental,
socioeconomic, and health indicators in statistical tables.
Initially developed to evaluate potential environmental
justice (EJ) issues.
Allows interactive mapping and review of
regulated facilities, environmental
monitoring sites, bodies of water, land use,
community demographics,
streets/schools/hospitals. Can be adapted
or linked as a module to assess cumulative
risks for various communities (i.e., not
limited to EJ issues).
SCEM Builder Model (DOE)
http://tis.eh.doe.gov/oepa/programs/sce
m.cfm
Graphics tool designed to develop a site conceptual
exposure model for a contaminated site.
General graphics tool that can be used to
set up a conceptual model for the site, to
guide stakeholder inputs for a cumulative
risk assessment.
Risk Screening Environmental
Indicators (RSEI) (U.S. EPA)
http://www.epa.gov/opptintr/rsei/
Screening tool that compares toxic chemicals released to
the environment from industrial sources. Offers way to
examine rankings and trends and set priorities for further
action.
Allows data to be sorted by chemical,
media, and geographic area. Preliminary
analyses can identify situations of relatively
higher concern during scoping.
Resources for Stakeholder Involvement
Community Air Screening How To
Manual (U.S. EPA)
http://www.epa.gov/oppt/cahp/howto.ht
ml
Explains how to form a partnership, clarify goals, develop
a detailed local source inventory, use a risk-based
process to identify priorities, and develop options for risk
reduction. Developed by U.S. EPA's Office of Pollution
Prevention and Toxics based on the Baltimore, MD,
approach. (Expected to be published in spring 2004.)
Presents and explains a step-by-step
process a community can follow to: form a
partnership to access technical expertise,
identify and inventory local sources of air
pollutants, review these sources to identify
known hazards that might pose a health risk
to the community, and set priorities and
develop a plan for making improvements.
Covers only the air pathway.
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TABLE A-1 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Superfund Community Involvement
Handbook, Appendix on Community
Involvement Requirements (U.S. EPA)
http://www.epa.gov/superfund/action/co
mmunity/index.htm
Superfund guidance on suggested community
involvement structure, communications, and approach.
For contaminated Superfund sites, the lead agency
informs public of the availability of technical assistance
grants (TAG). TAG is a grant program that provides funds
for citizen groups to hire independent technical advisors to
help them understand/comment on technical decisions re:
Superfund cleanup actions.
Developed for U.S. EPA's Superfund
program, the information about community
involvement, including forming community
advisory groups (CAGs), is useful for
cumulative risk assessments at
contaminated sites.
Hanford Site, Hanford Advisory Board
(HAB), Public Involvement Resources
and Calendar (DOE site)
http://www.hanford.gov/orp/?page=5&p
arent=1
http://www.hanford.gov/public/calendar/
The HAB was set up to provide recommendations and
advice to DOE, U.S. EPA, and the Washington
Department of Ecology on a number of issues related to
cleanup of the Hanford site.
The HAB has developed mission language,
a meeting schedule/calendar, and other
information that can serve as examples for
other projects.
Los Alamos National Laboratory (LANL)
Risk Analysis, Communication,
Evaluation, and Reduction (RACER)
project (DOE site)
http://www.racteam.com/LANLRisk/Rep
orts/Guidelines%20for%20lnvolvement
%2010-30.pdf
The RACER project is founded on extensive stakeholder
involvement. Established by the RAC team, this project is
developing an open process for assessing cumulative
risks at LANL and for creating a decision analysis
framework for risk reduction, as well as an integrated
database (containing data from multiple collecting
organizations) to support data evaluations and trend
analyses, site risk assessments, and the overall decision-
making process for environmental management at LANL.
Stakeholder participation is actively sought, both open
progress meetings and one-on-one meetings are held (in
various settings), and the internet (project website and
e-mail) is also used to announce upcoming activities and
the availability of draft documents for stakeholder
comment, and to solicit inputs.
Insights for cumulative assessments can be
found in: RAC guidelines for stakeholder
involvement, open survey questions, plans
for soliciting (in various venues) and
summarizing inputs to guide the
assessment, and suggestions for pursuing
grants for ongoing stakeholder involvement
(aimed to be administered through an
independent group), as well as other plans
and products that can be found on the
project website.
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TABLE A-1 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Community Air Screening How To
Manual (U.S. EPA)
http://www.epa.gov/oppt/cahp/howto.ht
ml
Explains how to form a partnership, clarify goals, develop
a detailed local source inventory, use a risk-based
process to identify priorities, and develop options for risk
reduction. Developed by U.S. EPA's Office of Pollution
Prevention and Toxics based on the Baltimore, MD,
approach. (Expected to be published in spring 2004.)
Presents and explains a step-by-step
process a community can follow to: form a
partnership to access technical expertise,
identify and inventory local sources of air
pollutants, review these sources to identify
known hazards that might pose a health risk
to the community, and set priorities and
develop a plan for making improvements.
Covers only the air pathway.
Superfund Community Involvement
Handbook, Appendix on Community
Involvement Requirements (U.S. EPA)
http://www.epa.gov/superfund/action/co
mmunity/index.htm
Superfund guidance on suggested community
involvement structure, communications, and approach.
For contaminated Superfund sites, the lead agency
informs public of the availability of technical assistance
grants (TAG). TAG is a grant program that provides funds
for citizen groups to hire independent technical advisors to
help them understand/comment on technical decisions re:
Superfund cleanup actions.
Developed for U.S. EPA's Superfund
program, the information about community
involvement, including forming community
advisory groups (CAGs), is useful for
cumulative risk assessments at
contaminated sites.
Hanford Site, Hanford Advisory Board
(HAB), Public Involvement Resources
and Calendar (DOE site)
http://www.hanford.gov/orp/?page=5&p
arent=1
http://www.hanford.gov/public/calendar/
The HAB was set up to provide recommendations and
advice to DOE, U.S. EPA, and the Washington
Department of Ecology on a number of issues related to
cleanup of the Hanford site.
The HAB has developed mission language,
a meeting schedule/calendar, and other
information that can serve as examples for
other projects.
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TABLE A-1 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Los Alamos National Laboratory (LANL)
Risk Analysis, Communication,
Evaluation, and Reduction (RACER)
project (DOE site)
http://www.racteam.com/LANLRisk/Rep
orts/Guidelines%20for%20lnvolvement
%2010-30.pdf
The RACER project is founded on extensive stakeholder
involvement. Established by the RAC team, this project is
developing an open process for assessing cumulative
risks at LANL and for creating a decision analysis
framework for risk reduction, as well as an integrated
database (containing data from multiple collecting
organizations) to support data evaluations and trend
analyses, site risk assessments, and the overall decision-
making process for environmental management at LANL.
Stakeholder participation is actively sought, both open
progress meetings and one-on-one meetings are held (in
various settings), and the internet (project website and
e-mail) is also used to announce upcoming activities and
the availability of draft documents for stakeholder
comment, and to solicit inputs.
Insights for cumulative assessments can be
found in: RAC guidelines for stakeholder
involvement, open survey questions, plans
for soliciting (in various venues) and
summarizing inputs to guide the
assessment, and suggestions for pursuing
grants for ongoing stakeholder involvement
(aimed to be administered through an
independent group), as well as other plans
and products that can be found on the
project website.
Savannah River Site Citizen's Advisory
Board (CAB) (DOE site)
http://www.srs.gov/general/outreach/srs
-cab
The CAB provides advice and recommendations DOE,
U.S. EPA, and the South Carolina Department of Health
and Environmental Control on environmental remediation,
waste management and related issues. Meetings and
public comment sessions are held regularly and are open
to the public.
Recommendations and information on
workshops published on this website can
offer insights for similar projects.
Multnomah County Protocol for
Assessing Community Excellence in
Environmental Health (PACE-EH)
http://www.pace-eh.org
Pilot assessments performed in five neighborhoods of
Portland, Oregon, resulted from a community health
assessment team's efforts to prioritize environmental
health concerns.
Multipathway issues identified that can offer
insights for other studies include poor
indoor air quality (including mold and
mildew), exposure to lead-based paint, and
unsafe grounds.
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TABLE A-1 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Onondaga Lake Partnership (OLP)
website http://www.onlakepartners.org
Aim is to promote cooperation among government
agencies and others involved in managing environmental
issues of Onondaga Lake and the Onondaga Lake
watershed in Syracuse, New York. The website presents
information about pollutants, health risks, cleanup
projects, and opportunities for public involvement in this
complex cleanup project for a heavily polluted lake in a
major metropolitan area, with high level of public concern.
Similar to previous example, illustrates how
a variety of scientific information,
documents, program management
information, presentations, video clips,
image gallery, and an e-mail announcement
list can be shared for cumulative risk
assessment projects.
Depleted Uranium Hexafluoride
Management Information Network
(DOE project)
http://www.ead.anl.gov/uranium
Presents information for the DOE inventory of depleted
uranium hexafluoride (DUF6). Includes basic scientific
information on uranium, depleted uranium, and DUF6; the
DOE program for managing the DUF6 inventory; research
and development for beneficial uses of DU, and public
involvement opportunities. Environmental impact
statements (EISs) and other reports are included.
(Several hundred thousand visitors since 1997.) Used
comment response management system (CRMS), web-
enabled software which expedites responses to
government and public comments about this and other
EISs.
Similar to previous example, illustrates how
various reports, presentations, video clips,
image gallery, and an e-mail announcement
list can be shared for a cumulative risk
assessment project.
Resources for Guiding Data Quality
Guidance for the Data Quality
Objectives Process (QA/G-4) (U.S.
EPA) http://www.epa.gov/quality/qs-
docs/q4-final.pdf
Guidance on the data quality objectives (DQO) process, a
systematic planning process for environmental data
collection. Designed to help risk assessors ensure that
data are collected for a specific purpose. Includes
determination of chemicals to evaluate or test for, media
and locations of concern, and detection limits.
Developed for the recommended planning
process when environmental data are used
to select between two opposing conditions,
this general guidance is useful for
cumulative assessments. Focus is placed
on the cumulative risk questions to be
answered, while maintaining awareness of
appropriate statistical techniques that
should be considered to produce defensible
results.
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TABLE A-1 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Decision Error Feasibility Trials (DEFT)
Software (QA/G-4D) (U.S. EPA)
http://www.epa.gov/qualitv/qs-docs/q4d-
final.pdf
Computer-based software for determining the feasibility of
data quality objectives defined using the DQO process.
Enables statistical sample size planning and can be used
to estimate costs associated with obtaining a specific
precision in environmental data (such as how many
samples are required to determine whether environmental
concentrations are above or below background or risk-
based concentrations).
General analytical guidance can be applied
to multiple media and multiple
contaminants. This tool calculates the
appropriate number of environmental
samples required to statistically answer
whether soil or water concentrations are
above or below a risk-based level, which
could be adapted to grouped chemicals.
Guidance on Choosing a Sampling
Design for Environmental Data
Collection (QA/G-5S) (U.S. EPA)
http://www.epa.gov/quality/qs-docs/q5s-
final.pdf
Guidance on applying standard statistical sampling
designs (such as simple random sampling) and more
advanced sampling designs (such as ranked set
sampling, adaptive cluster sampling) to environmental
applications.
Can be useful to identify co-located
contaminants to support grouping for a
cumulative risk assessment at a
contaminated site or situation.
Guidance for Quality Assurance Project
Plans for Modeling (QA/G-5M) (U.S.
EPA) http://www.epa.gov/quality/qs-
docs/qSm-final.pdf
General guidance for developing quality assurance project
plans (QAPPs) for modeling projects.
Can be useful to cumulative risk
assessments, particularly where air or
groundwater models are needed to
extrapolate small data sets to the site or
community level.
Guidance on Environmental Data
Verification and Data Validation (QA/G-
8) (U.S. EPA)
http://www.epa.gov/quality/qs-docs/q8-
final.pdf
Guidance to help organizations verify and validate data.
Applying this to laboratory analytical data allows risk
assessors to understand uncertainties associated with
concentration measurements (which impact assessment
results).
Useful for determining appropriate data for
the chemicals to be evaluated in a
cumulative risk assessment; important to
results, especially when using conservative
screening approaches.
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TABLE A-1 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Guidance for Data Quality Assessment:
(DQA): Practical Methods for Data
Analysis (QA/G-9) (U.S. EPA)
http://www.epa.gov/qualitv/qs-docs/q9-
final.pdf
Describes procedures and methodologies for ensuring
sound data are used in the risk assessment. Provides
tools that can be used to review DQOs and sampling
design, review preliminary data, select statistical tests to
summarize and analyze data, verify the assumptions of
the statistical test, and perform calculations.
These tools can indicate differences in the
statistical robustness that might affect data
combinations for chemical
groupings/selection of representative
concentrations. For instance, if certain data
were collected according to DQOs
established with DEFT (see earlier entry)
while other data were collected under a
different program that required fewer
samples, then care must be taken when
combining those data.
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1 A.2. RESOURCES FOR ENVIRONMENTAL FATE AND TRANSPORT ANALYSES
2 Several tools that can be used to evaluate environmental fate and transport of
3 chemicals to support cumulative health risk assessments are highlighted below.
4 Selected information is summarized in Table A-2 at the end of this section.
5 ChemFinder Database (Private, via U.S. EPA). The ChemFinder database is
6 an online, U.S. EPA-linked search engine that provides access to information on
7 the chemical, physical, product, and biological properties of a large number of
8 chemicals. Developed by Cambridgesoft, this tool can be searched by common
9 name, brand name, Chemical Abstract Service (CAS) number, chemical formula,
10 or other designations, including chemical structure. ChemFinder searches
11 chemical information from a large pool of websites worldwide, including
12 government and multilateral agencies, universities, and private institutions. The
13 ChemFinder search engine is available for free use via the U.S. EPA Office of
14 Pesticide Programs at http://www.epa.gov/oppfead1/pmreg/pits/index.html and
15 can also be found at http://chemfinder.cambridgesoft.com/.
16
17 Risk Assessment Protocols for Hazardous Waste Combustion Facilities
18 (U.S. EPA). In 1998, U.S. EPA Region 6 identified the need for a guidance
19 document that consolidated information presented in earlier Agency documents
20 and in reports from state environmental agencies, to provide an integrated set of
21 procedures for conducting site-specific combustion risk assessments addressing
22 multiple sources and exposure scenarios. Two documents were prepared: the
23 Human Health Risk Assessment Protocol for Hazardous Waste Combustion
24 Facilities (HHRAP; U.S. EPA, 2005d), and the Screening Level Ecological Risk
25 Assessment Protocol for Hazardous Waste Combustion Facilities (SLERAP;
26 U.S. EPA, 1999f). The objectives of these documents were to (1) apply the best
27 available methods for evaluating risk to human health and the environment from
28 operations of hazardous waste combustion units, and (2) develop repeatable and
29 documented methods for consistency and equity in permitting decisions.
30
31 In addition to providing methodologies for evaluating multi-media, multi-pathway
32 risks, Volume II of the guidance contains information and data on the chemical,
33 physical, and environmental properties of many chemicals that can be used to
34 model environmental fate and transport and exposure. These data can also be
35 used to predict what chemicals are likely to behave similarly in the environment,
36 to support groupings for cumulative risk assessments.
37
38 Soil Screening Guidance (U.S. EPA). The Agency has developed an extensive
39 set of environmental and physical constants and parameters that can be used to
40 model the fate and transport of chemicals in soil and to develop risk-based soil
41 screening levels (SSLs) to protect human health (U.S. EPA, 1996a).
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1 The primary goal is to provide simple screening information and a method for
2 developing site-specific screening levels, so it also serves as a tool to support
3 exposure-based screening. The guidance includes both detailed models and
4 generic SSLs, which can be used to quickly (and conservatively) assess what
5 areas or pathways might not warrant a detailed assessment. Developed for use
6 at National Priorities List sites, the concepts can be extended to other sites and
7 situations. The guidance also includes tables of chemical-specific constants,
8 such as the organic carbon partition coefficient (Koc), the soil-water partition
9 coefficient (Kd), and water and air diffusivity constants (Di,w and Di,a), to support
10 the evaluation of fate and transport.
11
12 Background Determinations (U.S. EPA, Others). Concentrations that
13 appropriately represent "background" levels (naturally occurring or ambient) are
14 location-specific and help provide context for the fate and transport of site
15 chemicals. The Agency has prepared extensive guidance on various
16 approaches for characterizing background, as well as protocols for determining
17 whether a contaminated site's concentrations are statistically above background.
18 For example, see Guidance for Characterizing Background Chemicals in Soil at
19 Superfund Sites (U. S. E PA, 2001 e).
20
21 Data on background concentrations of inorganics (notably in soil) can be found in
22 several sources, and these data can provide an initial general context for site- or
23 community-specific risk analyses. The information sources include toxicological
24 profiles developed by the Agency for Toxic Substances and Disease Registry
25 (ATSDR) and reports from the U.S. Geological Survey and universities. Agency
26 sources include the Ecological Soil Screening Level Guidance (U.S. EPA,
27 2004e), which gives 50 state-specific ranges, and regional guidelines, and
28 "typical" values provided as technical background to risk-based screening levels
29 (U.S. EPA, 2002g, 2003i). The U.S. EPA Region 6 includes background
30 concentrations in its Human Health Medium-Specific Screening Levels document
31 (U.S. EPA, 2005e), and the associated database contains screening values and
32 the physical and chemical parameters that were used to derive those values.
33
34 Background data can also be found in state-specific documents, such as the
35 Texas Risk Reduction Program Guidelines (TCEQ, 1999), which include
36 background concentrations for the state. The Massachusetts Department of
37 Environmental Protection (MADEP) has published state-specific background
38 levels of PAHs and metals in soil
39 (http://www.tceq.state.tx.us/assets/public/remediation/trrp/350revisions.doc)
40 (MADEP, 2002). City or other location-specific resources can also be found (as
41 described in Chapter 3 of this report), such as the City of Chicago Department of
42 Environment values for "background" PAHs (CCDE, 2003), which have been
43 adopted by Illinois EPA as indicative of PAH concentrations in Chicago soil (see
44 http://www.epa.state.il.us/land/site-remediation/urban-area-pah-study.pdf).
45
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1 Vapor Intrusion (U.S. EPA, Others). Vapor intrusion can be an important
2 pathway when volatile organic chemicals in subsurface media (soil, groundwater,
3 and non-aqueous phase liquids) could migrate to air inside a building. Risks
4 from this pathway are often combined with other exposure pathways for indoor
5 air (e.g., inhalation of volatiles during showering) to quantify aggregate risks for
6 single chemicals (e.g., benzene) and cumulative risks for a group of chemicals
7 (e.g., chlorinated solvents).
8
9 This pathway has been evaluated using a model based on the allometric
10 equation given in Johnson and Ettinger (1991). That model is a one-dimensional
11 spreadsheet that estimates convective and diffusive transport of chemical vapors
12 to indoor air from sources near a building's perimeter. The model ignores
13 attenuating factors (e.g., biological degradation) and assumes an infinite source
14 over the exposure duration of the receptor (e.g., 25 years for a commercial or
15 industrial worker). A detailed description of the vapor intrusion model is provided
16 in draft Guidance for Evaluating the Vapor Intrusion to Indoor Air Pathway from
17 Groundwater and Soils (U.S. EPA, 2002h) and the draft User's Guide for
18 Evaluating Subsurface Vapor Intrusion into Buildings (U.S. EPA, 2003J).
19 Separate versions of the spreadsheet model are available for evaluating potential
20 source concentrations (e.g., soil gas or groundwater data).
21
22 Both screening-level and advanced versions of the models are available for
23 each. The screening-level version limits user inputs to the most sensitive
24 parameters and allows the user to define only a single soil stratum above the
25 source. The advanced version allows users to enter additional site-specific data
26 for soil and building parameters and incorporates up to three soil strata for which
27 soil properties can be varied. In February 2003, the U.S. EPA released Version
28 3.0 of the vapor intrusion model, which contained updated toxicity values and
29 other physical/chemical parameters. This model and associated guide are still
30 undergoing review. Certain state agencies (e.g., California) have modified that
31 model to include state-sanctioned toxicity values or other model parameters
32 (DTSC, 2003). Other organizations are also developing approaches (including
33 other federal agencies).
34 While the Johnson and Ettinger model is most widely recognized for vapor
35 intrusion, several states have adopted simple equations based on this
36 methodology to evaluate the indoor air pathway on a screening level. For
37 example, the Risk Evaluation/Corrective Action Program (RECAP) of the
38 Louisiana Department of Environmental Quality (LDEQ) has developed a set of
39 publicly available spreadsheets that contain equations and chemical-specific
40 information that can be used to predict conservative concentrations of VOCs in
41 indoor air for industrial and nonindustrial buildings constructed over groundwater
42 plumes. Chemical concentration values for multiple chemicals calculated by the
43 models could be combined to evaluate cumulative exposure.
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1 Fate and Transport/Risk Assessments (U.S. EPA, Others). For risk
2 assessments at contaminated sites, urban environments and other situations
3 potentially impacted by multiple sources or sources distant from the population of
4 concern, it is often necessary to simulate the behavior of multiple chemicals in
5 different environmental media. Hundreds of computer models have been
6 developed to model various aspects of horizontal and vertical contaminant fate
7 and transport in the environment. Some are very general and conceptual, while
8 others are quite specific to certain media characteristics and applications. The
9 use and applicability of individual models varies widely depending on the project
10 objectives and specificity required, so it is important for the model chosen to be
11 appropriate for the given site setting. For example, the Center for Subsurface
12 Modeling Support (CSMoS) within U.S. EPA's Office of Research and
13 Development (ORD) (located in Ada, Oklahoma) maintains an online database of
14 public groundwater and vadose zone fate and transport models. This database
15 is accessible at http://www.epa.qov/ada/csmos.html.
16
17 Other tools that support characterization and modeling of the movement and
18 behavior of chemicals in the environment include the U.S. EPA Soil Screening
19 Guidance (described above), as well as environmental data compiled by many
20 organizations for specific regions and conditions. Data of interest typically
21 include soil type (e.g., sand, loam, clay); drainage characteristics, hydraulic
22 conductivity, depth to groundwater, water quality parameters, organic carbon
23 content, and various other constants and coefficients.
24
25 Environmental data are also available through databases maintained by the U.S.
26 Geological Survey (USGS), state natural resources departments, colleges and
27 universities, U.S. Department of Agriculture (USDA) Natural Resources
28 Conservation Service (NRCS) field offices (offices in most county seats), USDA
29 soil surveys (available for most counties at NRCS offices and local libraries),
30 scientific textbooks and journals, internet resources, and professional
31 organizations. Other organizations have also developed groundwater models
32 that can be used for cumulative risk assessments (not available through the U.S.
33 EPA website), as indicated in Table A-2.
34
35
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TABLE A-2
Selected Resources for Evaluating Fate and Transport
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Soil Screening Guidance
(U.S. EPA)
http://www.epa.gov/superfun
d/resources/soil/introtbd.htm
Provides tools for developing screening levels for, and
conducting, risk assessments involving soil and
groundwater. Useful input parameters and technical
background for environmental models.
Standard constants, coefficients, and soil data
that can be useful to cumulative risk
assessments.
SESOIL (SEasonal SOIL
compartment model)
In the public domain,
although updated versions
are available from
RockWare, Inc.
http://www.rockware.com/
SESOIL is a one-dimensional vertical transport screening-
level model for the unsaturated (vadose) zone that can be
used to simulate the fate of contaminants in soil to support
site-specific cleanup objectives. Simulates natural
attenuation based on diffusion, adsorption, volatilization,
biodegradation, cation exchange, and hydrolysis. The
model can evaluate one chemical at a time; does not
predict interactions in environmental media.
Results can indicate how far a contaminant
plume will migrate; predicted concentrations can
be compared to media-specific standards and
can be used to estimate single-chemical risks
based on standard default exposure parameters,
locations, and times. The location- and time-
specific predictions for single chemicals can be
overlain to support grouping decisions for a
cumulative assessment.
AT123D
(Analytical Transient 1-, 2-,
and 3-Dimensional
simulation of waste transport
in the aquifer system)
http://www.scisoftware.com/
Generalized three-dimensional groundwater transport and
fate model. Transport and fate processes simulated
include advection, dispersion, adsorption and biological
decay. The model can evaluate one chemical at a time;
does not predict interactions in environmental media.
As above.
Summers model
http://www.seview.com/
Screening level leachate program that estimates
groundwater concentrations based on mixing. Simulates
dilution of soil in groundwater. The model can evaluate one
chemical at a time; does not predict interactions in
environmental media.
As above.
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TABLE A-2 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Draft guidance and user's
guide for evaluating vapor
intrusion into buildings (U.S.
EPA);
LDEQ spreadsheets to
screen vapor intrusion
pathway
Provides a model to estimate convective and diffusive
transport of chemical vapors to indoor air. Could offer
insights where indoor air exposures are a concern.
(Currently under review.) LDEQ provides set of equations
that enable screening of the vapor intrusion pathway.
Model output can be used to support cumulative
risk assessments, as concentrations of multiple
chemicals can be evaluated simultaneously.
(The following models are available for download from the CSMoS website, http://www.epa.gov/ada/csmos/models.html.)
2DFATMIC and 3DFATMIC
Simulates subsurface flow, transport, and fate of
contaminants that are undergoing chemical and/or
biological transformations. Applicable to transient
conditions in both saturated and unsaturated zones.
model can evaluate one chemical at a time; does not
predict interactions in environmental media.
The
Results can indicate how far a contaminant plume
will migrate; predicted concentrations can be
compared to media-specific standards and can be
used to estimate single-chemical risks based on
standard default exposure parameters, locations,
and times. The location- and time-specific
predictions for single chemicals can be overlain to
support grouping decisions for a cumulative
assessment.
BIOCHLOR
Screening model that simulates remediation by natural
attenuation of dissolved solvents at sites with chlorinated
solvents. Can be used to simulate solute transport without
decay and solute transport with biodegradation modeled as
a sequential first-order process within one or two different
reaction zones. The model can evaluate one chemical at a
time; does not predict interactions in environmental media.
As above
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TABLE A-2 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
BIOPLUME II and
BIOPLUME III
Two-dimensional contaminant transport under the influence
of oxygen-limited biodegradation (BIOPLUME II) and under
the influence of oxygen, nitrate, iron, sulfate, and
methanogenic biodegradation (BIOPLUME III). Models
advection, dispersion, sorption, biodegradation (aerobic
and anaerobic) and reaeration (BIOPLUME II) and through
instantaneous, first order, zero order, or Monod kinetics
(BIOPLUME III). BIOPLUME III was developed primarily for
the modeling of natural attenuation of organic contaminants
in groundwater; it is particularly useful at petroleum-
contaminated sites. The model can evaluate one chemical
at a time; does not predict interactions in environmental
media.
As above
BIOSCREEN
Screening-level groundwater transport model that simulates
natural attenuation of dissolved-phase hydrocarbons.
Based on the Domenico analytical contaminant transport
model and can simulate natural attenuation based on
advection, dispersion, adsorption and biological decay.
Estimates plume migration to evaluate risk at specific
locations and times. The model can evaluate one chemical
at a time; does not predict interactions in environmental
media.
As above
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TABLE A-2 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
(The following models are available for download from the CSMoS website, http://www.epa.aov/ada/csmos/models.html, except as indicated.)
CHEMFLO
Simulates one-dimensional water and chemical movement
in the vadose zone. Models advection, dispersion, first-
order decay and linear sorption. The model can evaluate
one chemical at a time; it does not predict interactions in
environmental media.
Results can indicate how far a contaminant plume
will migrate; predicted concentrations can be
compared to media-specific standards and can be
used to estimate single-chemical risks based on
standard default exposure parameters, locations,
and times. The location- and time-specific
predictions for single chemicals can be overlain to
support grouping decisions for a cumulative
assessment.
GEOEAS
Enables geostatistical analysis of spatially correlated data.
Can perform basic statistics, scatter plots/linear and
nonlinear estimation (kriging). The model can evaluate one
chemical at a time; it does not predict interactions in
environmental media.
As above.
GEOPACK
Enables geostatistical analysis of spatially correlated data.
Can perform basic statistics, variography, linear and
nonlinear estimation (kriging). The model can evaluate one
chemical at a time; it does not predict interactions in
environmental media.
As above.
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TABLE A-2 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
HSSM
Can simulate: light non-aqueous phase liquid (LNAPL)
flow and transport of a chemical constituent of the LNAPL
from the ground surface to the water table; radial spreading
of the LNAPL phase at the water table; and dissolution and
aquifer transport of the chemical. One-dimensional in the
vadose zone, radial in the capillary fringe, two-dimensional
vertically averaged analytical solution of the advection-
dispersion equation in the saturated zone. The model can
evaluate one chemical at a time; it does not predict
interactions in environmental media.
As above.
Visual MODFLOW (available
for a fee from the developer)
and MODFLOW
(U.S. Geological Survey),
many iterations/updates;
most recent is MODFLOW-
2000
One of the most accessible and widely used models
available. Numerically solves the three-dimensional
ground-water flow equation for a porous medium by using a
finite-difference method. Visual MODFLOW output is
graphic, including two- and three-dimensional maps;
designed to model flow, can evaluate one chemical at a
time (information input by user); it does not predict
interactions in environmental media.
As above.
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TABLE A-2 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
(The first three models below are available for download from the CSMoS website, http://www. epa. gov/ada/csmos/models. html.)
PESTAN
Vadose zone modeling of the transport of organic
pesticides. Models advection, dispersion, first-order decay
and linear sorption. The model can evaluate one chemical
at a time; it does not predict interactions in environmental
media.
Results can indicate how far a contaminant plume
will migrate; predicted concentrations can be
compared to media-specific standards and can be
used to estimate single-chemical risks based on
standard default exposure parameters, locations,
and times. The location- and time-specific
predictions for single chemicals can be overlain to
support grouping decisions for a cumulative
assessment.
Soil Transport and Fate
(STF) Database
Database providing information concerning the behavior of
organic and a few inorganic chemicals in the soil
environment. Focus is on one chemical at a time;
interactions not addressed.
General-use tool can be used to evaluate
environmental contaminants for cumulative risk
assessments.
UTCHEM
Three-dimensional model that simulates non-aqueous
phase liquid (NAPL) movement in the subsurface. Can
address: multiple phases; dissolution and/or mobilization
by non-dilute remedial fluids; chemical and microbiological
transformations; and changes in fluid properties as a site is
remediated.
General-use tool can be used to evaluate
environmental contaminants for cumulative risk
assessments. Interesting for cumulative risk
because NAPL is commonly a complex mixture
itself and can be present in multiple phases, which
are assessed by the model.
MT3D (links to MODFLOW)
http://www.ess.co.at/ECOSI
M/MANUAL/mt3d.html
Three-dimensional transport model for simulating
advection, dispersion, and chemical reactions in
groundwater systems; assumes first-order decay. Can
address one chemical at a time.
Chemical reaction can be addressed with a loss
term (information on chemical must be input by
user) but degradation product not tracked.
Heavily dependent on extensive characterization
of site setting (can be hard to get sufficient data
for all parameters needed).
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TABLE A-2 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
SWIFTIII (private)
Three-dimensional flow (transient and steady state) and
solute transport (advection, dispersion, sorption and decay)
in fractured porous media; uses finite difference method;
addresses chemical reactions with second-order decay;
also models radionuclides.
Similar to above, but can address more than one
chemical: parent plus degradation product(s)
(chain of two). (As above, user must input
information about each chemical.)
MULKOM codes, including
TMVOC (and predecessor
T2VOC)
(DOE/Lawrence Berkeley
Laboratory, http://www-
esd.lbl.gov/TOUGH2
Three-dimensional, three-phase flow of water, air, and
volatile organic compounds in saturated and unsaturated
zone to support remediation (e.g., soil vapor extraction).
TMVOC can address more than one volatile organic (e.g.,
to model a spill of fuel hydrocarbons or solvents).
Similar to above, but can address a mixture of
volatile organic compounds. Like the others
models, depends heavily on extensive site setting
characterization (hard to get data needed for all
parameters, for results to be meaningful).
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1 A.3. RESOURCES FOR EXPOSURE ANALYSES
2 Many exposure models are well suited to assessing multiple exposures to
3 multiple chemicals at contaminated sites and other multimedia situations, although this
4 is generally performed by combining predictions for individual chemicals. Tools range
5 from relatively straightforward screening models to comprehensive multimedia, multiple-
6 pathway exposure models, as summarized below and in Table A-3 at the end of this
7 section. Certain models presented here also support other portions of the risk
8 assessment process. For example, the model for subsurface vapor migration soil
9 (Johnson and Ettinger, 1991) is commonly considered an environmental fate and
10 transport tool, but it can also serve as a multimedia exposure assessment resource
11 because it considers both soil and groundwater inputs to predict concentrations in
12 indoor air. Several supporting documents are also available that provide exposure
13 factors, their bases, and receptor parameters that are used in various exposure models.
14 Exposure Factors (U.S. EPA). Risk assessments rely on exposure models to
15 represent various environmental and receptor-specific factors that can affect
16 exposures to chemicals. For example, exposure factors cover exposure
17 duration, time involved in certain activities, body weight and surface area, intake
18 rates (e.g., inhalation, ingestion of food, soil, water), and many others parameters
19 needed to estimate representative risks. The Agency has summarized extensive
20 data in a set of exposure factor handbooks based on many studies, which
21 consider statistical and relative contributions of many potential sources of human
22 exposures to chemicals in air, drinking water, vapor, food, and soil. These
23 handbooks include:
24
25 Exposure Factors Handbook, Volume I - General Factors (U.S. EPA, 1997c),
26 see www.epa.gov/ncea/pdfs/efh/front.pdf.
27 Exposure Factors Handbook, Volume II - Food Ingestion Factors (U.S. EPA,
28 1997c), see www.epa.gov/ncea/pdfs/efh/front.pdf.
29 Exposure Factors Handbook, Volume III - Activity Factors (U.S. EPA, 1997c),
30 see www.epa.gov/ncea/pdfs/efh/front.pdf.
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1 Child-Specific Exposure Factors Handbook (Interim Report) (U.S. EPA,
2 20021), see http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=55145.
3 Sociodemographic Data Used for Identifying Potentially Highly Exposed
4 Populations (U.S. EPA, 1999c), see
5 http://oaspub.epa.gov/eims/eimscomm.getfile7p download id=428679.
6 Fact Finder CD-ROM searches data from the Exposure Factors Handbook
1 and Sociodemographic Data Used for Identifying Potentially Highly Exposed
8 Populations (referenced above), see
9 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=23650.
10
11 3MRA Model (U.S. EPA). The 3MRA model is a multimedia, multipathway,
12 multireceptor exposure and risk assessment model being developed by the Agency
13 to assess releases from land-based waste management units. After simulating
14 releases from disposal units, modules model fate and transport through the
15 environment, estimate exposure to receptors, and calculates distributions of risks to
16 receptors. This screening-level model is intended to be applied on a site-specific
17 basis to generate risk-based standards (considering exit levels, e.g., to exit from
18 specific regulations). Risks are assessed at individual sites to provide input to a
19 representation a national distribution of risks. The national distribution of risks is the
20 basis for determining waste stream constituent concentrations that meet regulatory
21 criteria established to be protective of human health and ecological receptors (as
22 determined by U.S. EPA policy). To establish national regulatory limits, site-based
23 risk results are combined to evaluate national risk (i.e., to determine the percentage
24 of nationwide receptors that are protected at various levels). For example, from this
25 information a limit might be established to ensure protection of 95% of all receptors
26 within 2 miles of a waste management unit at all sites across the nation. The 3MRA
27 methodology uses a Monte Carlo scheme to quantify uncertainty (e.g., from natural
28 variability or based on selection of representative sites). The resulting national
29 criteria would represent threshold waste concentrations not considered hazardous
30 (and not requiring Subtitle C disposal). The model is available at
31 http://www.epa.gov/ceampubl/mmedia/3mra/.
32
33 Exposure and Fate Assessment Screening (E-FAST) Tool (U.S. EPA). This
34 computer-based model can provide screening-level estimates of general
35 population, consumer, and environmental exposures to concentrations of
36 chemicals released to air, surface water, landfills, and from consumer products.
37 Potential inhalation, dermal and ingestion doses resulting from these releases
38 are estimated. Modeled concentrations and doses are designed to reasonably
39 overestimate exposures for use in screening-level assessments. The model is
40 available from http://www.epa.gov/opptintr/exposure/docs/efast.htm.
41
42 Lead Exposure (U.S. EPA). The traditional reference dose approach used to
43 estimate health risks does not apply to lead because most human health effects
44 data are based on blood lead concentrations rather than external dose. Blood
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1 lead concentration is an integrated measure of internal dose, reflecting total
2 exposure from all sources (e.g., both site-related and background sources for
3 Superfund sites) (ATSDR, 1999a). Both U.S. EPA and the California EPA
4 Department of Toxic Substances Control (CalEPA DISC) have developed
5 models to estimate blood lead concentrations from exposures to lead from
6 various media, including soil, water, air, and food. The U.S. EPA tool for
7 evaluating lead risks (the All Ages Lead Model) (U.S. EPA, 2005h) predicts lead
8 concentrations in body tissue and organs for a hypothetical individual based on a
9 simulated lifetime of lead exposure, and then extrapolates to a population of
10 similarly exposed individuals.
11
12 The Agency has also developed a set of models for evaluating lead exposures
13 and risks for non-residential adults. The models and supporting literature,
14 methodologies, and technical information for these analyses are available at
15 http://www.epa.gov/superfund/programs/lead/products.htm. Documents on the
16 website include descriptions of how bioavailability and uptake factors for the adult
17 lead model were determined. Examples of useful support documents also
18 available from U.S. EPA include Revised Interim Soil Lead Guidance for
19 CERCLA Sites and RCRA Corrective Action Facilities (U.S. EPA, 1994) and
20 Frequently Asked Questions on the Adult Lead Model (U.S. EPA, 1999g).
21
22 The National Human Exposure Assessment Survey (NHEXAS) (U.S. EPA).
23 NHEXAS was developed by U.S. EPA's Office of Research and Development
24 (ORD) in the early 1990s to provide critical information about multipathway,
25 multimedia population exposure distribution to chemical classes. The first phase
26 consisted of three pilot studies with the objectives of: evaluating the feasibility of
27 NHEXAS concepts, methods, and approaches for the conduct of future
28 population-based exposure studies; evaluating the utility of NHEXAS data for
29 improved risk assessment and management decisions; testing the hypothesis
30 that the distributions of exposure given by modeling and extant data do not differ
31 from the measurement-based distributions of exposure; defining the distribution
32 of multipathway human exposures for a relatively large geographic area; and
33 stimulating exposure research and forging strong working relationships between
34 government and nongovernment scientists. The NHEXAS web site is located at
35 http://www.epa.gov/nerl/research/nhexas/nhexas.htm. NHEXAS data are
36 available in the Human Exposure Database System (HEDS) at
37 http://www.epa.gov/heds/.
38
39 Hotspots Analysis and Reporting Program (HARP) Tool (California Air
40 Resources Board, CARB). The State of California's Air Toxics "Hot Spots"
41 program requires stationary air emission sources within the state to report the
42 types and quantities of certain substances routinely release into the air. The
43 recent HARP software package is designed to create and manage facility
44 emissions inventory databases; prioritize facilities; model atmospheric dispersion
45 of chemicals from one or multiple facilities using U.S. EPA models ISCST3 and
46 BPIP; calculate cancer and noncancer (acute and chronic) health impacts using
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1 guidance developed by CalEPA (in 2003); use point estimates or data
2 distributions of exposures to calculate inhalation and multipathway risks; perform
3 stochastic health risk analyses; calculate potential health effects for individual
4 receptors, population exposures, cumulative impacts for one or multiple facilities
5 and one or multiple pollutants, and potential health effects using ground-level
6 concentrations; and present results as tables and isopleth maps. The results can
7 be printed, added to word processing documents, or input to a Geographic
8 Information Systems (CIS) program. The HARP model can be downloaded from
9 http://www.arb.ca. gov/toxics/harp/downloads.htm#2.
10
11 Dietary Exposure Potential Model (DEPM) (U.S. EPA). The DEPM estimates
12 dietary exposure to multiple chemicals based on data from several national,
13 government-sponsored food intake surveys and chemical residue monitoring
14 programs. The DEPM includes recipes developed specifically for exposure
15 analyses that link consumption survey data for prepared foods to the chemical
16 residue information, which is normally reported for raw food ingredients, to
17 estimate daily dietary exposure. Consumption in the model is based on 11 food
18 groups containing approximately 800 exposure core food types, established from
19 over 6500 common food items. The summary databases are aggregated in a
20 way that allows the analyst to select appropriate demographic factors, such
21 age/sex groups, geographical regions, ethnic groups and economic status. The
22 model also includes modules for evaluating chemical exposures from residues,
23 soil, and tap water. The model is available from U.S. EPA's National Exposure
24 Research Laboratory (NERL) at http://www.epa.gov/nerlcwww/depm.htm.
25
26 Health Registries (Centers for Disease Control and Prevention, CDC;
27 Others). Several organizations maintain databases that contain information on
28 the frequencies and types of diseases and other health-related information, such
29 as on cancer, asthma, and birth defects, and blood lead levels. This information
30 can be evaluated in concert with modeled or measured chemical exposure data
31 to correlate potential influences of multiple exposures and to calibrate risk
32 models. For example, the CDC maintains a national registry of cancer cases,
33 including cancer type and target tissue, as well as demographic and location
34 information.
35
36 Many states have established cancer and other disease registries to monitor
37 trends over time; determine patterns in various populations; guide planning and
38 evaluation of control programs; help set priorities for allocating health resources;
39 advance clinical, epidemiologic, and health services research; and provide
40 information for a national database of cancer incidence. The National Cancer
41 Registry is searchable online http://www.cdc.gov/cancer/natlcancerdata.htm.
42 The CDC website also contains links to various state registries. Other resources
43 that can be useful for identifying populations at potential risk include the
44 U.S. Census Bureau (http://www.census.gov/), state and local government health
45 departments, and other health organizations. An additional useful resource is the
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1 report Sociodemographic Data Used for Identifying Potentially Highly Exposed
2 Populations (U. S. E PA, 1999c).
o
4 National Occupational Research Agenda (NORA) (National Institute for
5 Occupational Safety and Health, NIOSH). Within NIOSH, NORA has identified
6 a number of research areas for mixed occupational exposures, with an aim to
7 protect individuals in the workplace from exposures to multiple chemicals. The
8 mixed exposures team website
9 (http://www2a.cdc.gov/nora/noratopictemp.asp?rscharea=me) provides links to
10 current and past studies, as well as information on how to join a listserv group to
11 discuss topics related to mixed exposures. Scientific knowledge developed
12 through this effort can offer insights for assessing combined the effects of
13 chemicals at contaminated sites, occupational settings and other scenarios
14 involving multiple chemicals.
15
16 Tool for the Reduction and Assessment of Chemical and Other Impacts
17 (TRACI) (U.S. EPA). TRACI is an impact assessment tool for assessing multiple
18 chemical impact and resource-use categories to analyze various study designs.
19 Impacts that can be modeled include: ozone depletion; global warming;
20 acidification; eutrophication; photochemical smog; cancer risk and noncancer
21 health effects; human health criteria; ecotoxicity; fossil fuel use; land use; and
22 water use. The program includes quantitative data on human carcinogenicity
23 and noncarcinogenicity (based on human toxicity potentials), acidification, smog
24 formation, and eutrophication. The model uses a probabilistic approach to
25 determine spatial scale(s) for other impact categories such as acidification, smog
26 formation, eutrophication, and land use. Information is available at
27 http://www.epa.aov/ordntrnt/ORD/NRMRL/pubs/600r02052/600r02052.htm .
28
29 Technology Transfer Network, TTN (U.S. EPA). This is an on-line information
30 resource for tools to support air pathway analyses. The TTN maintains a
31 Clearinghouse for Inventories and Emission Factors (CHIEF) website
32 (http://www.epa.gov/ttn/chief/) that contains links to many of the relevant
33 documents on methods and data for constructing emissions inventories available
34 for download, including the Handbook for Criteria Pollutant Inventory
35 Development: A Beginner's Guide for Point and Area Sources (U.S. EPA,
36 1999h); Handbook for Air Toxics Emission Inventory Development, Volume I:
37 Stationary Sources (U.S. EPA, 1998e); and Compilation of Air Pollutant Emission
38 Factors (U.S. EPA, 1995c et seq.). U.S. EPA also maintains a Support Center
39 for Regulatory Air Models (SCRAM) website (http://www.epa.qov/ttn/scram/),
40 which provides information on codes described in the Guideline on Air Quality
41 Models (U.S. EPA, 2003d), and includes downloadable models and guidance.
42 Information from TTN is included in the discussion of the air pathway in
43 Section 4.4 of this report.
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TABLE A-3
Selected Resources for Evaluating Exposure
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Exposure Factors
Guidance (U.S. EPA)
general:
http://www.epa.gov/ncea/
pdfs/efh/front.pdf
child:
http://cfpub.epa.gov/ncea/
cfm/recordisplay.cfm?deid
=55145
Provides extensive values and underlying bases for many
factors that affect exposures. Examples include exposure
duration, frequency, surface area, inhalation rates per activity
level and age/gender, as well as ingestion rates, including for
incidental soil ingestion and by food type, based on age and
gender. Because children are often more heavily exposed to
environmental toxicants than adults, U.S. EPA also published
the Child-Specific Exposure Factors Handbook is to provide a
summary of the available and up-to-date statistical data on
various factors assessing children exposures.
Excellent compendium of values for
exposure parameters that can be
reviewed to determine those most
appropriate for a given site/setting (for
both adults and children). Can be
used to assess multiple pathways and
activities/intake rates associated with
multiple chemicals.
Sociodemographic Data
Used for Identifying
Potentially Highly
Exposed Populations
(U.S. EPA)
http://cfpub.epa.gov/ncea/
cfm/recordisplay.cfm?deid
=22562
Fact Finder searches and returns data from the
Sociodemographic Data Used for Identifying Potentially Highly
Exposed Populations document. These data assist assessors
in identifying and enumerating potentially highly exposed
populations. Due to unique social and demographic
characteristics, various segments of the population may
experience exposures different from those of the general
population, which in many cases could be higher. It is helpful
for risk or exposure assessors evaluating a diverse population
to first identify and then characterize certain groups within the
general population who could be at risk for greater
contaminant exposures (and related effects).
This document presents data relating
to factors which potentially impact an
individual or group's exposure to
environmental contaminants based on
various activity patterns, different
microenvironments, and other Socio-
demographic data such as age,
gender, race and economic status.
Populations potentially more exposed
to multiple chemicals of concern,
relative to the general population, is
also addressed in this database.
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TABLE A-3 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
3MRA(U.S. EPA)
http://www.epa.gov/ceam
publ/mmedia/3mra/index.
htm
(CEAM)
Developed for screening-level assessment of potential human
and ecological health risks from chronic exposures to
chemicals released from land-based waste management units
containing listed waste streams. Site-based and intended for
national-scale application to generate risk-based standards
(e.g., levels to exit from hazardous waste regulation),
evaluates human and ecological receptors, and captures
uncertainty and variability in risk estimates. (Ecological
exposure and risk focuses on population effects related to key
species within habitats found in the proximity of sites.)
Can quantify exposure via multiple
pathways after a simulated release.
Human receptors include adult/child
residents, home gardeners, beef and
dairy farmers, and recreational fishers.
Pathways include inhalation of
outdoor air and indoor air during
showering, ingestion of drinking water,
and ingestion of farming products and
fish.
E-FAST (U.S. EPA)
http://www.epa.gov/opptin
tr/exposure/docs/efast. ht
m
Provides screening-level estimates for general population,
consumer, and environmental exposures to concentrations of
chemicals released to air, surface water, landfills, and from
consumer products. Modeled estimates of concentrations and
doses are designed to reasonably overestimate exposures, for
use in screening-level assessments.
Default exposure parameters are
available, but site-specific values are
recommended to be used. Can
predict exposure concentrations for
comparison to media-specific
standards.
All Ages Lead Model
(U.S. EPA):
http://cfpub.epa.gov/ncea/
cfm/recordisplay.cfm?deid
=139314
Predicts lead concentrations in body tissue and organs for a
hypothetical individual based on a simulated lifetime of lead
exposure, and then extrapolates to a population of similarly
exposed individuals.
Useful for evaluating the impact of
possible sources of lead in a specific
human setting where there is a
concern for potential or real exposures
to lead. The results can be correlated
with risks from other contaminants, if
interactions with lead are known to
occur.
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TABLE A-3 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
CALTOX Model
(CalEPA)
Spreadsheet-based model that relates the concentration of a
chemical in soil to the risk of an adverse health effect for a
person living or working on or near a site. Determines
chemical concentration in the exposure media of breathing
zone air, drinking water, food, and soil that people inhale,
ingest and contact dermally, and uses the standard equations
found in U.S. EPA RAGS (U.S. EPA, 1989a) to estimate
exposure and risk.
Can be used to assess multiple
exposures; has tended to be more for
research than practical applications.
Defaults are available but site-specific
values are recommended. Can
predict exposure concentrations that
can be compared to media-specific
standards and used to estimate
single-chemical risks.
Dietary Exposure
Potential Model (DPEM)
(U.S. EPA)
http://www.epa.gov/nerlcw
ww/depm.htm
The DEPM estimates dietary exposures to multiple chemicals
based on data from several national, government-sponsored
food intake surveys and chemical residue monitoring
programs.
Can be used to assess exposures to
multiple chemicals by ingestion of
food and tap water, including as
potential context for ambient
exposures in the area of a site.
Disease registries
(multiple organizations,
including CDC:)
http://www.cdc.gov/cancer
/natlcancerdata. htm
A number of databases exist for cancer and other health-
related information, such as asthma and birth defects.
Data could be used to indicate key
community health concerns or for
exploratory investigation of certain
diseases that might increase the
vulnerability of certain people exposed
to chemicals from a contaminated site.
However, the links to diseases from
environmental exposures or directly to
environmental pollutants as a causal
or contributing factor is not usually
clear.
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TABLE A-3 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Tool for the Reduction
and Assessment of
Chemical and Other
Impacts (TRACI) (U.S.
EPA)
http://www.epa.gov/ordntr
nt/ORD/NRMRL/pubs/600
r02052/600r02052.htm
TRACI is an impact assessment tool for evaluating multiple
chemical impact and resource-use categories so various study
designs can be analyzed.
Can be used to model and compare
exposures to multiple chemicals and
health risks associated with different
projects. For example, can
graphically analyze the reduction in
risk projected from one
implementation design versus
another.
NORA Mixed Exposures
Team (NIOSH)
http://www2a.cdc.gov/nor
a/noratopictemp.asp?rsch
area=me
Provides technical and support information on projects
involving mixed exposures in the workplace. Research
reflected on the website could provide insights for cumulative
risk assessment projects.
Information resource for mixtures in
the workplace; can offer insights for
cumulative assessments at
contaminated sites.
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1 A.4. RESOURCES FOR TOXICITY ANALYSES
2 Resources that can be used to support toxicity analyses for cumulative risk
3 assessments are highlighted below and summarized in Table A-4. Topics include:
4 (1) development of toxicity factors, including for whole mixtures; (2) identification of
5 toxicity criteria for similar or surrogate compounds or mixtures to represent a mixture or
6 its components; and (3) joint toxicity of the components of a mixture.
7 Integrated Risk Information System, IRIS (U.S. EPA). The IRIS database is a
8 key source of information on chronic toxicity, including standard toxicity values
9 (reference doses and concentrations), cancer slope factors, and corresponding
10 risk-based concentrations. These values have undergone thorough Agency
11 review and represent expert Agency consensus, and they are widely used within
12 the United States and by other countries. Toxicity values and target tissue
13 information included in IRIS summaries can be used in a cumulative risk
14 assessment to identify chemicals that primarily or secondarily affect similar target
15 tissues or systems. Chemical interactions other than addition are not quantifiable
16 using toxicity criteria from IRIS; however, information in the accompanying study
17 summaries can be used to qualitatively assess the nature and magnitude of
18 certain interactions, and the primary literature can be further pursued for
19 additional information. Toxicity criteria are presented in a way that supports
20 addition (the default approach) to estimate risks and the potential noncancer
21 effects of chemicals. This information is available at http://www.epa.qov/iris/.
22
23 Toxicological Profiles and Interaction Profiles (ATSDR). The ATSDR, within
24 the U.S. Centers for Disease Control and Prevention (CDC), has developed
25 toxicological profiles for many individual chemicals that summarize information
26 about sources and uses as well as key data from the scientific literature
27 regarding toxicity and behavior and levels in the environment. These profiles can
28 be valuable for cumulative risk assessments because they describe in detail the
29 effects of the given chemical, as well as its primary environmental and metabolic
30 transformation products, on specific target organs and biological functions. In
31 addition, where possible, the toxicological profiles discuss known interactions of
32 the topic chemical with other chemicals. These profiles are available at
33 http://www.atsdr.cdc.gov/toxpro2.html.
34
35 The ATSDR has also developed a mixtures program and has drafted a guidance
36 manual that presents an assessment approach, and perhaps more importantly
37 has drafted nine interaction profiles for seven specific chemical combinations and
38 two general mixtures. The specific chemical combinations are: (1) arsenic,
39 cadmium, chromium, and lead; (2) benzene, toluene, ethylbenzene, and xylene;
40 (3) lead, manganese, zinc, and copper; (4) cyanide, fluoride, nitrate, and
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1 uranium; (5) cesium, cobalt, PCBs, strontium, and trichloroethylene;
2 (6) 1,1,1-trichloroethane, 1,1-dichloroethane, trichloroethylene, and
3 tetrachloroethylene; and (7) arsenic, hydrazine, jet fuels, strontium-90, and
4 trichloroethylene. These interaction profiles evaluate data on the toxicology of
5 the whole mixture where available, and where not available data are evaluated
6 for the joint toxicity of chemicals in the mixture (often as pairs). These drafts are
7 available at http://www.atsdr.cdc.gov/iphome.html.
8
9 Supplementary Guidance for Conducting Health Risk Assessment of
10 Chemical Mixtures (U.S. EPA). This guidance published in summer 2000
11 updates the Agency's 1986 guidelines for chemical mixtures (U.S. EPA, 2000a).
12 It describes approaches that depend on the type, nature, and quality of available
13 data. The report includes equations, definitions, discussions of toxicologic
14 interactions and pharmacokinetic models, and approaches for assessing whole
15 mixtures, surrogate mixtures, and individual mixture components. The whole-
16 mixture discussion includes the whole-mixture reference dose (RfD) and
17 concentration (RfC) and slope factors; comparative potency; and environmental
18 transformations. The component discussion includes the hazard index (HI);
19 interaction-based HI; relative potency factors (RPF); and response addition.
20 Toxicity criteria are presented for several common product mixtures, such as
21 polychlorinated biphenyls (PCBs). This guidance is available at
22 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=20533.
23
24 Database for Airborne Workplace Chemicals (Institut de Recherche Robert-
25 Sauve en Sante et en Securite du Travail, IRSST). This health and safety
26 research institute in Quebec, Canada, has developed a database that covers a
27 large number of chemicals commonly found in the workplace, and also found at
28 many contaminated sites. This database contains information on occupational
29 standards, chemical-specific health effects, target organs (and chemical-specific
30 groupings), toxicokinetics, effect levels, and mode of action where available. The
31 database also includes a calculation tool that allows up to 10 chemicals to be
32 assessed at a time, comparing the concentration of interest to the occupational
33 standard (many are similar to ours) to produce a sum of ratios, using an additivity
34 default (IRRST, 2003).
35
36 Relative Potency Factors for Pesticide Mixtures, Biostatistical Analyses of
37 Joint Dose Response (U.S. EPA). In response to requirements of the Food
38 Quality Protection Act of 1996, U.S. EPA recently published a technical report
39 that presents research and methodologies for developing relative potency factors
40 by which cumulative risks from exposures to mixtures such as organophosphate
41 pesticides, dioxins, and PCBs can be assessed (U.S. EPA, 2003f). The
42 document presents three scenarios for which biostatistical methods for toxicity
43 assessment can be accomplished, including use of dose addition in simple cases
44 where common modes of toxicity are present, integration of dose and response
45 addition for cases where toxicities are independent, and joint dose-response
46 modeling for cases where the mode of action is uncertain. The report, published
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1 by NCEA in coordination with OPP, is available at
2 http://cfpub.epa. gov/ncea/cfm/recordisplav.cfm?deid=66273.
o
4 Cumulative Risk of Pesticides with Common Toxic Mechanism (U.S. EPA).
5 In response to the Food Quality Protection Act, the U.S. EPA Office of Pesticide
6 Programs (OPP) recently released an assessment of the risks associated with
7 cumulative exposures to various formulations of organophosphate (OP)
8 pesticides (U.S. EPA, 2002a). This report updated the preliminary assessment
9 released a year earlier. For this assessment, the Agency evaluated potential
10 exposures to 30 OPs, including via food, drinking water and residential uses, and
11 applied methodologies to account for variability in exposures based on age,
12 seasonal, and geographic factors. The cumulative risk assessment report is
13 available at http://www.epa.gov/pesticides/cumulative/rra-op/.
14
15 Dose Addition for Cumulative Risks from Exposures to Multiple Chemicals
16 (U.S. EPA). As part of the response to the Food Quality Protection Act of 1996,
17 which requires consideration of cumulative risk from exposures to multiple
18 chemicals that have a common mechanism of toxicity, NCEA published a paper
19 describing three dose addition-based techniques that can be used to estimate
20 cumulative risk (Chen et al., 2001). The three methods include the hazard index
21 (HI), point-of-departure index (PODI), and toxicity equivalence factor (TEF), all of
22 which are based on estimates of a point of departure (as the effective dose for a
23 10 percent response, or ED10) and reference doses of individual chemicals. A
24 formal statistical procedure is also proposed to estimate cumulative risk by fitting
25 the dose-response model of the mixture under dose addition and estimating
26 relative potency between two chemicals from that model.
27
28 Long-Range Research Initiative, LRI (American Chemistry Council, ACC).
29 Through its LRI program, the ACC sponsors scientific research aimed at better
30 understanding the potential impacts of chemicals on human health and the
31 environment, including wildlife (ACS, 2003). Cumulative risk is a priority
32 research area within the LRI program, and studies are ongoing. Reports and
33 papers prepared from this research can provide insights for cumulative risk
34 assessments at contaminated sites. Research topics include improved methods
35 for understanding toxicodynamics, applications of physiologically-based
36 pharmacokinetic (PBPK) models to predict target tissue dose and response, and
37 exposure assessment of mixtures. The LRI holds a conference each year at
38 which ongoing and completed research is presented. The summary report of the
39 recent annual conference, with abstracts of research projects presented, can be
40 found at http://www.uslri.com/.
41
42 Chemical Mixtures Toxicology Studies (Netherlands, TNO). International
43 research is currently underway to improve the understanding of potential risks of
44 chemical mixtures with different modes of action. For example, a team led by Dr.
45 John Groten of the TNO Nutrition and Food Research Institute of the Netherlands
46 is researching the use of mechanistic models to describe interactions between
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1 mixture components expected to act by different modes of action. In an ongoing
2 pilot study (funded by ACC/LRI), the TNO team is using PBPK models to assess
3 possible toxicokinetic interactions between compounds in an applied mixture,
4 and comparing them to empirical dose-response modeling of observed
5 pathological changes in liver, blood and kidney. The aim is to apply the method
6 developed to other chemical mixtures. Other studies have developed and
7 applied statistical experiments combining multivariate data analysis and modeling
8 in in vitro and in vivo studies on various chemical mixtures such as petroleum
9 hydrocarbons, aldehydes, food contaminants, industrial solvents, and mycotoxins
10 (Feronetal., 1998).
11
12 Scientific Studies on Toxicology/Mixtures (National Institute of Environmental
13 Health Sciences, NIEHS). Research areas of the NIEHS, within the National
14 Institutes of Health (NIH), U.S. Department of Health and Human Services (DHHS),
15 include toxicology, mixtures, and environmental health. The Institute sponsors the
16 National Toxicology Program (NTP), which coordinates toxicological testing
17 programs; strengthens the science base in toxicology; develops and validates
18 improved testing methods; and provides information about potentially toxic
19 chemicals to health regulatory and research agencies, scientific and medical
20 communities, and the public. Fact sheets and reports on chemicals and related
21 risks, and data and findings from NTP-related studies are available at
22 http://www.niehs.nih.gov/. This website also links to other research projects and
23 programs within the organizationand summaries of past and ongoing studies that
24 can provide insights for cumulative risk assessments at contaminated sites. A
25 search engine on the website can be used to identify research and tools for specific
26 applications, including those related to cumulative risk. NIEHS also publishes
27 Environmental Health Perspectives, a monthly journal that often summarizes
28 research papers relevant to chemical mixtures, and some issues and supplements
29 have been entirely dedicated to mixtures. Also, NIH maintains the National Library
30 of Medicine Toxic Substances Data Bank and other valuable databases and
31 biomedical links.
32
33 Toxic Substances Research Initiative, TSRI (Health Canada). The Canadian
34 environmental health department (Health Canada) has developed a program called
35 the Toxic Substances Research Initiative (TSRI). The primary focus of this initiative
36 is assessment of cumulative effects to human and ecological receptors. To date,
37 TSRI has spent more $7 million to fund 23 research projects in this priority research
38 area. Resulting technical reports and other publications are available at
39 http://www.hc-sc.ac.ca/ahc-asc/media/nr-cp/2000/2000 69bk2 e.html. One
40 example research study is the evaluation of the pharmacokinetics and cumulative
41 health effects of mixtures of disinfection byproducts, led by Dr. Kannan Krishnan of
42 the University of Montreal.
43
44 Toxicity Values for Diesel Particulate Matter (DPM) Mixture (California EPA).
45 Risks of whole mixtures are evaluated using toxicity criteria developed for that
46 mixture where data are available. In 1998, the CalEPA Office of Environmental
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Health Hazard Assessment (OEHHA)
completed a 10-year human health
assessment of the mix of chemicals in
diesel exhaust. From the results the
California Air Resources Board
(GARB) identified diesel particulate
matter (DPM) exhaust as a toxic air
contaminant (TAG) that poses a threat
to human health. This exhaust results
from combustion of diesel fuel in
internal combustion engines. Its
composition varies based on engine
type, operating conditions, fuel
composition, lubricating oil, and
whether an emission control system is
present. The DPM exhaust is a
complex mixture of thousands of fine
particles, commonly known as soot;
this contains 47 compounds classified
by U.S. EPA as hazardous air
pollutants (HAPs) and by GARB as
TACs. These compounds include
many known or suspected
carcinogens, such as benzene,
arsenic, formaldehyde, and nickel.
The GARB evaluation exhaust takes
into account its individual
components; chemicals commonly
found in diesel exhaust are shown in
Text Box A-1.
The report prepared from the GARB
assessment Proposed Identification of
Diesel Exhaust as a Toxic Air
Contaminant was formally reviewed
and approved by a scientific review
panel. The panel deemed data from
human epidemiological studies of
occupationally exposed populations to
be applicable for quantitative risk
assessment. After considering the
results of the meta-analysis of human
studies, as well as the detailed
analysis of railroad workers, the panel
developed a unit risk estimate expressed in terms of diesel particulates, which
was then used to derive an inhalation slope factor of 1.1 (mg/kg-day)"1. This type
Toxic Air Contaminants in Diesel Exhaust*
(Text Box A-1)
Acetaldehyde
Acrolein
Aluminum
Ammonia
Aniline
Antimony compounds
Arsenic
Barium
Benzene
Beryllium compounds
Biphenyl
Bis [2-ethylhexyl]phthalate
Bromine
1,3-Butadiene
Cadmium
Chlorinated dioxins
Chlorine
Chlorobenzene
Chromium
Cobalt compounds
Copper
Cresol
Cyanide compounds
Dibenzofuran
Dibutylphthalate
Ethyl benzene
Formaldehyde
Hexane
Lead compounds
Manganese compounds
Mercury compounds
Methanol
Methyl ethyl ketone
Naphthalene
Nickel compounds
4-Nitrobiphenyl
Phenol
Phosphorus
Polycyclic aromatic hydrocarbons
Propionaldehyde
Selenium compounds
Silver
Styrene
Sulfuric acid
Toluene
Xylene isomers and mixtures
Zinc
These have either been identified in diesel exhaust
or are presumed to be in the exhaust based on
observed chemical reactions and/or their presence
in the fuel or oil. Additional information at
http://cfpub.epa.gov/ncea/cfm/recordisplav.cfm7deid
=29060.
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1 of approach might offer useful insights not only for assessments involving diesel
2 exhaust but also for assessments at sites with other chemical mixtures.
o
4 Toxicity/Risk Technical Resource (U.S. EPA National Center for
5 Environmental Assessment, NCEA). As a major research center within the
6 U.S. EPA Office of Research and Development (ORD), NCEA serves as the
7 Agency's national resource for human health and ecological risk assessment.
8 The Center conducts risk assessments as well as research to improve the state-
9 of-the-science, and also provides guidance and technical support to risk
10 assessors. This organization manages and is responsible for updating the
11 content of the IRIS database (U.S. EPA, 2005c). Risk assessors can contact
12 NCEA for help regarding provisional values when toxicity values are not available
13 in IRIS. Information available online at http://cfpub.epa.gov/ncea/ can offer
14 useful insights for cumulative risk assessments. Ongoing research is being
15 conducted by NCEA in the development of PBPK models for use in risk
16 assessments, the evaluation of different risk assessment approaches, the
17 modified hazard index approach for chemical mixtures assessments, and the
18 significance of indirect exposure pathways and quantitative models of variability
19 for assessing uncertainty.
20
21 Statistical/Computer Tools in Development (Universities, Research
22 Institutes). Statistically based methods and computer tools that can model
23 interactions and effects associated with multiple chemicals are being developed.
24 A main area of study involves applying physiologically based pharmacokinetic/
25 pharmacodynamic (PB-PK/PD) models to chemical mixtures. Many researchers
26 are working in this area (e.g., M. Anderson, K. Krishnan, and R. Yang), and
27 advances continue to be made. An example of a computer-based approach for
28 predicting toxicological interactions of chemical mixtures is reaction network
29 modeling, which has been to model complex chemical processes in petroleum
30 engineering. For this effort, reaction network modeling incorporates various
31 statistical methods (including Monte Carlo-type analysis) to predict chemical
32 reaction rates, products, and outcomes. A molecular-based model (BioMOL) is
33 in development, which uses this reaction network modeling approach to predict
34 effects of chemicals in complex biological systems (Liao et al., 2002).
35 BMDS (U.S. EPA). This software was developed by U.S. EPA to perform fitting
36 of mathematical models to toxicological dose-response data for a particular toxic
37 effect (U.S. EPA, 1995c). The user evaluates the results to select a benchmark
38 dose (BMD) that is associated with a predetermined benchmark response
39 (BMR), such as a10% increase in the incidence of a particular lesion or a 10%
40 decrease in body weight gain. A goal of the BMD approach is to define a starting
41 point of departure for the computation of a reference value (RfD or RfC) or slope
42 factor that is more independent of study design than the traditional method that
43 uses a single experimental dose, such as the no-observed-adverse-effect level
44 (NOAEL). The hazard index uses RfDs or RfCs in a dose addition formula to
45 scale the exposure levels in a mixture, producing an indicator of the extent of
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1 concern for toxicity. The BMD values used with dose addition could allow
2 estimation of a BMD for the mixture, allowing the mixture dose to be interpreted
3 in terms of the risk of a particular effect.
4 CatReg (U.S. EPA). This categorical regression tool was developed by U.S.
5 EPA to conduct meta-analyses of toxicological data, i.e., to analyze data or
6 results from multiple studies including to assess different severity levels. The
7 tool is a customized software package that runs under S-PLUS (MathSoft, Inc.),
8 and a free version written in R is under development. Additional context is
9 offered as follows (from U.S. EPA, 2000c): "Meta-analysis becomes valuable
10 when individual experiments are too narrow to address broad concerns. For
11 example, in acute inhalation risk assessment, it is important to investigate the
12 combined effects of concentration and duration of exposure but few published
13 experiments vary both the concentration and the duration of exposure. By
14 combining information from multiple studies, the contribution of both
15 concentration and duration to toxicity can be estimated. Moreover, the combined
16 analysis allows the analyst to investigate variation among experiments, an
17 important benchmark for the level of model uncertainty." For cumulative health
18 risk assessments, CatReg can be applied to evaluate grouped chemicals
19 considering multiple effects and multiple routes. Also, during the validation of
20 CatReg, Sciences International (under contract to NCEA) developed three acute
21 values; that product was submitted for consideration in adding to the IRIS
22 database. Therefore, this tool can also be used to support toxicity values.
23
24 Risk-Based Screening Levels (U.S. EPA). Risk-based screening criteria have
25 been developed for environmental media (including soil, drinking water, and air)
26 by several organizations. For example, U.S. EPA Regions 3, 6, and 9 have
27 developed risk-based concentrations (RBCs), medium-specific screening levels
28 (MSSLs), and preliminary remediation goals (PRGs), respectively. These
29 screening values are based on very conservative default assumptions for
30 exposure and environmental parameters and incorporate toxicity values for
31 cancer and non-cancer effects from IRIS, PPRTV, and the old Health Effects
32 Assessment Summary Tables (HEAST), which have not been updated since
33 1997. Information for the MSSLs is presented in technical guidance (U.S. EPA,
34 2005e) and can be found at http://www.epa.gov/earth1 r6/6pd/rcra c/pd-
35 n/r6screenbackground. pdf. The PRGs developed from the guidance (U.S. EPA,
36 2002g) can be found at
37 http://www.epa.gov/region09/waste/sfund/prg/files/02userguide.pdf. The RBCs
38 are described in a technical memorandum (U.S. EPA, 2003i) and can be found at
39 http://www.epa.gov/reg3hwmd/risk/human/info/cover.htm. These screening
40 criteria can be used to narrow the focus of the assessment to those chemicals of
41 potential concern likely to contribute the most to overall risks associated with the
42 site. However, the screening values do not reflect site-specific exposure routes
43 and are of limited usefulness for site-specific cumulative risk assessments
44 because they do not consider relevant setting and exposure information.
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TABLE A-4
Selected Resources for Evaluating Joint Toxicity
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Integrated Risk Information
System (IRIS) (U.S. EPA)
http://www.epa.gov/iris
An electronic database containing information on human
health effects that may result from exposure to various
chemicals in the environment. Describes toxic effects, dose
concentrations, and reference inhalation dose
concentrations for oral and inhalation exposures of over 500
chemicals. Good resource for identifying individual
toxicological effects for an extensive list of chemicals.
Combined with specific exposure information, the data in
IRIS can be used for characterization of the health risks of a
given chemical in a given situation and provide toxic effects
of a particular chemical within a chemical mixture.
Toxicity values and target organ information
included in IRIS summaries can be used in
cumulative risk assessments to identify
chemicals that primarily or secondarily affect
similar target tissues or systems. Chemical
interactions other than addition are not
quantifiable using these toxicity criteria;
however, the nature(s) and magnitudes of some
interactions could be predicted. Toxicity criteria
are calibrated such that health effects and
cancer risks can be readily summed where
effects are assumed to be additive.
Technical resource
(U.S. EPA)
http://www.epa.gov/ncea
NCEA is a technical resource for many topics relevant to
cumulative assessments. These U.S. EPA scientists
provide guidance and support to risk assessors across a
broad scope of assessment issues, including cumulative
health risk.
Serves as the source of provisional toxicity
values (where standard toxicity values are not
available) and related data.
Interaction profiles (draft)
(ATSDR)
http://www.atsdr.cdc.gov/ipho
me.html
These interaction profiles summarize available toxicity data
for mixtures and assesses joint toxicity. Drafts exist for nine
combinations (see accompanying text). Information
includes critical effect levels and directions of interactions
with confidence indicators by organ/system, and also
includes representative chemicals
Useful for assessing cumulative risks when
exposures involve chemicals covered in the
profiles. Good resource for finding specific
toxicity data organized by organ/system to
determine at what levels joint toxicity could be
exerted among chemical sets without having to
search in the primary literature. Some
secondary effects information is included.
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TABLE A-4 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Supplementary Guidance for
Conducting Health Risk
Assessment of Chemical
Mixtures (U.S. EPA)
http://cfpub.epa.gov/ncea/cfm
/record isplay.cfm?deid=2053
3
This guidance presents approaches for assessing risks of
mixtures, as dictated by the nature and quality of available
data (e.g., for mixtures, surrogate mixtures, or individual
mixture components). Provides formulas, definitions, and
discussions of toxic interactions and pharmacokinetic
models. (Does not address exposures, just toxicity.)
Presents more detailed information on
considerations and calculational approaches for
assessing mixtures, going beyond the
summaries included in Chapters 5 and 6 of this
report.
TOXNET, other databases
(NIH)
http://toxnet.nlm.nih.gov/cgi-
bin/sis/htmlgen?HSDB
NIH sponsors many databases for toxicology and
environmental health, including TOXNET and Haz-Map
(hazardous chemicals and occupational disease), and
MEDLINE links to biomedical journals.
Useful source of single-chemical information,
will also reflect emerging data relevant to
cumulative risks as they are developed.
Chemical database
(IRSST)
http://www.irsst.qc.ca/fr/
100015.html
outil
Database for airborne chemicals in the workplace that
includes the Canadian occupational standards (many are
the same as U.S. standards) and identifies target organs,
effect levels from toxicity studies, and, where available,
mode of action information; includes a sum-of-ratios tool to
assess airborne chemicals compared to standards, for up to
10 at a time. (The database is in French; it is currently
being translated to English.)
Good source of useful inhalation toxicity
information for a large number of chemicals.
The tool can be used to organize chemicals by
target organ/effect and levels can be ratioed to
a reference level (occupational standard), with
an option for calculating a sum of ratios for
10 chemicals at a time (assumes additivity) for a
combined estimate.
Revised Cumulative Risk
Assessment of Pesticides
That Have a Common
Mechanism of Toxicity (U.S.
EPA)
http://www.epa.gov/pesticides
/cumulative/rra-op
Identifies methods, review toxicities, develop relative
potency factors and present risks associated with
cumulative exposures to organophosphate pesticides.
Document reviewed toxicity, product, and exposure data for
30 organophosphate and presented detailed findings on
cumulative risks.
One of the first comprehensive risk
assessments addressing cumulative risk; offers
good insights for multipathway assessments.
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TABLE A-4 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Studies within Long-Range
Research Initiative (LRI)
(ACC)
http://www.uslri.org/
Industry-funded scientific program includes a cumulative risk
focus area. Ongoing research in this area is addressing
assessment methods and toxicity studies for mixtures.
Research results could offer insights for
cumulative risk assessments at contaminated
sites.
BMDS (U.S. EPA)
http://cfpub.epa.gov/ncea/cfm
/record isplay.cfm?deid=2016
7
BMDS is designed to fit mathematical models to dose-
response data so that the results allow selection of a
benchmark dose (BMD) that is associated with a
predetermined benchmark response (BMR), such as a 10%
increase in the incidence of a particular lesion or a 10%
decrease in body weight gain. General guidance is
available. Technical guidance document for BMDS is
available online (external review draft). Periodic revision.
BMD values used with dose addition could allow
estimation of a BMD for the mixture. For toxicity
endpoints usually described by virtually safe
levels (RfDs and RfCs), this approach would
provide a risk-based dose associated with risk
of a particular effect.
CatReg (U.S. EPA)
http://cfpub.epa.gov/ncea/cfm
/record isplay.cfm?deid=1816
2
Categorical regression model developed for meta-analysis
of toxicology data. Still in development, this could be useful
for evaluating different types of data in evaluating potential
cumulative health risks.
CatReg can be used to evaluate multiple effects
within a chemical grouping (e.g., as grouped by
target organ or system) and can also be used
as a tool to support the health effect estimate
(e.g., hazard index) from multiple-route
exposures.
Risk-based screening levels
(see text, can be found
through:
http://www.epa.gov/region09/
waste/sfund/prg/,
http://www.epa.gov/reg3hwm
d/risk/eco, and
http://epa.gov/earth1 r6/6pd/rc
ra c/pd-n/screen.htm
Screening criteria for environmental media (soil, drinking
water, and air) based on specified risk levels, based on
conservative assumptions and extant toxicity values (some
are outdated); developed by various U.S. EPA regions,
offices, and other organizations. For example, U.S. EPA
Regions 3, 6, and 9 have developed risk-based
concentrations (RBCs), medium-specific screening levels
(MSSLs), and preliminary remediation goals (PRGs),
respectively.
Not designed for cumulative risk assessment,
because they are chemical-specific and not
based on specific pathways or target organs.
However, they could be useful for narrowing the
assessment focus (e.g., during data evaluation)
to those chemicals most likely to contribute to
overall risks at a site.
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1 A.5. RESOURCES TO CHARACTERIZE RISK AND UNCERTAINTY AND PRESENT
2 RESULTS
O
4 Many assumptions are made when assessing human health risks of multiple
5 chemicals from environmental exposures. Thus, it is important for the risk results and
6 associated uncertainties to be well characterized and clearly presented so this
7 information can be appropriately interpreted to guide sound decisions. This can involve
8 graphical illustrations of statistical and spatial information, as highlighted below.
9 Selected tools to support this final phase of the cumulative risk assessment are
10 summarized in Table A-5.
11 Spatial Analysis and Decision Assistance (SADA) (U.S. EPA and
12 U.S. Nuclear Regulatory Commission, NRC). The NRC joined U.S. EPA to
13 support a very useful integrated software package to support human and
14 ecological cumulative risk assessments, working with the University of
15 Tennessee. The human health module of this tool includes the equations from
16 the standard Superfund guidance (U.S. EPA, 1989a) and contains flexible land
17 use scenarios and exposure pathways. These can be combined as indicated to
18 represent overall exposure for the representative receptors evaluated. The input
19 data for these pathways can be tailored to reflect site-specific conditions;
20 interactions are not considered. This tool emphasizes the spatial distribution of
21 contaminant data, and modules cover visualization, geospatial analysis,
22 statistical analysis, sampling design, and decision analysis. Outputs can be
23 tabular or graphical, and can be used to identify where risk results exceeds a
24 target value. Many SADA capabilities are also covered by the Fully Integrated
25 Environmental Location Decision Support (FIELDS) system, which is coordinated
26 through U.S. EPA Region 5 and accessible from ArcView. The SADA tool is
27 available at http://www.tiem.utk.edu/~sada/.
28
29 Probabilistic Resources (U.S. EPA, Others). Risk assessments commonly
30 present human health risks as single-point estimates (e.g., 1 x 10~5), following
31 U.S. EPA's basic risk assessment guidance for contaminated sites (U.S. EPA,
32 1989a). Such estimates provide little information about the underlying
33 uncertainty or variability. The uncertainty typically spans at least an order of
34 magnitude and often much more. Monte Carlo simulation offers one way of
35 considering uncertainty and variability, as it relies on multiple descriptors using
36 statistical techniques to calculate a quantity repeatedly with inputs selected
37 randomly from a reasonable population of values (U.S. EPA, 1999i). Results
38 approximate a full range of reasonably possible outcomes and are typically
39 plotted as graphs (e.g., frequency distributions) or tabulated. However, this
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1 approach has several limitations, which affect its acceptance as a preferred
2 assessment method. Limitations include: difficulty in distinguishing between
3 variability and uncertainty; use of exposure parameters developed from short-
4 term studies for long-term exposure; and sensitivity of the tails of the
5 distributions, which can be of greatest interest, to input distributions.
6 Nevertheless, Monte Carlo simulation approaches offer one way to represent
7 uncertainty and variability in the risk results.
8
9 RESRAD (DOE Argonne National Laboratory). The original RESidual
10 RADioactivity code was designed to evaluate radiological risks and develop
11 radiological cleanup levels. It can cover 14 combined exposure pathways and is
12 used by DOE for radioactively contaminated sites and by NRC for dose
13 evaluations to support decommissioning and waste disposal requests.
14 Subsequent additions to the family of codes include RESRAD-CHEM (which
15 calculates risks and hazard indices across 9 exposure pathways and includes a
16 database of chemical properties, transfer factors, and toxicity values for about
17 150 chemicals), RESRAD-BASELINE (which covers both radionuclides and
18 chemicals and uses measured concentrations as input), and RESRAD-OFFSITE
19 (with includes a two-dimensional dispersion groundwater model and the
20 CAP-88PC air dispersion model). Outputs can be tabular and graphic, and the
21 code includes a Monte Carlo module for probabilistic analyses. The code
22 incorporates transformation over time for radioactive decay, but like many others
23 it does not address environmental transformation of chemicals or interactions.
24
25 Regional Air Modeling Initiative (RAIMI) (U.S. EPA). The Regional Air
26 Modeling Initiative (RAIMI) approach developed by U.S. EPA Region 6 is GIS-
27 based and looks at multiple sources across U.S. EPA programs. This tool was
28 developed by Region 6 and uses multiple emissions data sources to assess
29 community-level inhalation impact by evaluating an unlimited number of
30 stationary and mobile air toxics sources. It utilizes both air and risk modeling
31 components. RAIMI also supports source attribution analyses, so individual
32 sources can be for targeted reductions rather than simply revealing areas of
33 concern. Initial findings indicate that a small number of sources may be
34 responsible for the majority of impact. Such models aim to become useful
35 beyond Region 6, as U.S. EPA moves to risk-based approaches across all
36 programs. In the RAIMI approach, cumulative information does not necessarily
37 take into account the effect of complex mixtures, as additivity is assumed. At a
38 July 2003 meeting of the Advisory Board, several potential applications of this
39 tool were identified, including using the RAIMI dataset in conjunction with the
40 cumulative risk framework; predicting future risk, or the impact of past regulation;
41 or integrating data sources. The tool is already being used to identify useful
42 databases and emissions inventories. The model has been submitted to the U.S.
43 EPA's Council for Regulatory Environmental Modeling (CREM) for validation.
44 The tool currently focuses on one medium (air) so it would need to link with other
45 modules to address other sources of risk (such as from community drinking water
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1 or food residues) for a full cumulative assessment. Information is available at
2 http://www.epa.gov/earth1 r6/6pd/rcra c/raimi/raimi.htm.
o
4 Cumulative Risk Index Analysis (U.S. EPA). The Cumulative Risk Index
5 Analysis (CRIA) System is a multi-purpose environmental assessment tool based
6 on CIS technology from U.S. EPA Region 6. This CIS-based screening system
7 uses data from major government databases and inputs from technical and
8 regulatory professionals to mathematically transform information relevant to
9 cumulative risk to visual forms such as CIS maps and tables. The system has
10 been used to assess and display human health, ecological, socio-economic and
11 regulatory risk information. The framework developed for implementing CRIA is
12 available from the U.S. EPA website at
13 http://www.epa.gov/osp/presentations/cumrisk/carney.pdf. Region 6 has
14 conducted over 6,500 cumulative risk assessments in environmental justice
15 communities using its Comparative Cumulative Risk System.
16
17 Other GIS Tools (Private). Several government agencies and private
18 companies have developed GIS programs to simultaneously assess exposures
19 of multiple chemicals by a single receptor. For example, ESRI, Inc., has
20 developed the screening-level risk assessment module RISKMOD for its ArcView
21 platform; this tool calculates cumulative risks from multiple contaminants. For
22 carcinogens, risk is calculated for each exposure pathway by summing the
23 individual lifetime excess cancer risks for each chemical associated with that
24 pathway. For non-carcinogens, the hazard quotients for each exposure pathway
25 can be summed to produce a hazard index for that pathway (Naranjo et al.,
26 2000). A case study illustrating how RISKMOD was applied to assess risks for a
27 Bolivian mine site is available at
28 http://gis.esri.com/librarv/userconf/procOO/professional/papers/PAP480/p480.htm.
29
30 Cumulative Adjustment of Protective Concentration Levels (PCLs) (Texas,
31 TCEQ). PCLs are a set of toxicity-based screening criteria developed by TCEQ
32 for use in risk assessments of sites in the state. Whereas the individual PCLs
33 were derived for evaluation of risks from individual chemicals, the TCEQ has
34 developed an equation for downward adjustment of the PCLs for use when
35 evaluating risks where at least 10 carcinogenic or noncarcinogenic chemicals of
36 concern (COC) are present for a specific exposure pathway. The adjustments
37 result in reduced PCLs for individual chemicals based on the ratio of the
38 measured concentration of each COC to its PCL. If the sum of these ratios
39 exceeds a predetermined value (here, 10), adjusted PCL values may be
40 necessary for some COCs to ensure that state risk reduction rule mandates are
41 met (i.e., cumulative cancer risks for multiple carcinogenic COCs cannot exceed
42 1 x 10~4, and the hazard index for multiple noncarcinogenic COCs cannot exceed
43 10). The COCs to be adjusted are determined based on a decision process
44 outlined in the Cumulative Adjustment guidance document (TCEQ, 2002). The
45 adjustment process is a simplistic budgeting exercise in which the risk assessor
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1 is able to choose the PCLs to be lowered and the magnitude of the reduction.
2 The guidance document is available at http://www.tceq.state.tx.us/.
o
4 Framework for Risk Analysis in Multimedia Environmental Systems
5 (FRAMES) (U.S. EPA). The U.S. EPA has developed an integrated software
6 system with support from Pacific Northwest National Laboratory, to conduct
7 screening-level assessments of health and ecological risks for hazardous waste
8 identification rule (HWIR) chemicals from land-based waste management units.
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TABLE A-5
Selected Resources for Characterizing Risk and Uncertainty and Presenting Results
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
SADA (Spatial Analysis and Decision
Assistance) (DOE, NRC, UT)
http://www.tiem.utk.edu/~sada/
Integrated set of software with flexible land use
scenarios and exposure pathways to assess health
risks. The tool emphasizes spatial distribution of
contaminant data; modules cover visualization,
geospatial analysis, statistical analysis, sampling
design, and decision analysis. Outputs can be
tabular or graphical. (Also covers ecological risks,
aims to support integrated decisions.)
Useful for cumulative risk assessments;
can combine pathways to assess overall
exposures and summed risks/hazard
indices for receptors of interest. Input
data can reflect site-specific conditions;
interactions are not considered.
RESRAD (RESidual RADioactivity) (DOE-
ANL)
http://www.ead.anl.gov/resrad
(family of codes, including RESRAD-
CHEM and BASELINE for chemicals)
The original code was designed to guide radiological
cleanup criteria for contaminated sites and assess
doses and risks from residual radionuclides. Sister
codes cover chemical contaminants to support a
combined evaluation of risks and hazard indices at
sites with radionuclides and chemicals. Includes a
screening groundwater model, links to an air
dispersion model, and includes a probabilistic
module. Outputs are graphics and tables.
Useful for cumulative assessments at
radioactively and chemically
contaminated sites; can assess
sensitivity, covers natural radioactive
decay (but not environmental
transformation) to address changes over
time; produces risk and hazard indices
summed across multiple contaminants
and pathways; does not address
interactions.
Monte Carlo Analysis-Based Resources
(U.S. EPA, others)
Statistical methods for addressing uncertainty and
variability in estimating health risks by developing
multiple descriptors to calculate a quantity repeatedly
with randomly selected scenarios for each
calculation. Most useful for single-point risk
estimates; can be a useful as a presentation tool
because graphics show range of scenarios and
outputs.
Combining approximations for multiple
sources of potential risk (e.g.,
environmental and lifestyle risk) can be
complicated. Could be used to evaluate
cumulative risks by combining results for
individual exposures that consider
variability and uncertainty.
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TABLE A-5 cont.
Resource and Access
Purpose and Scope
Cumulative Risk Remarks
Regional Air Impact Modeling Initiative
(RAIMI) (U.S. EPA)
http://cfpub2.epa.gov/crem/
crem report.cfm?deid=74913
Risk-based prioritization tool developed by Region 6
to support regional risk-based prioritization at a
community-level resolution, from exposures to
multiple airborne contaminants from multiple sources
via multiple exposure pathways. Designed to support
cross-program analyses. Includes Risk-MAP, to
estimate health risks from exposures to chemical
emissions over large areas.
Assesses multiple contaminants and
multiple sources for U.S. EPA programs,
for air contaminants. Designed to
consider source-specific and
contaminant-specific contributions to
cumulative exposures associated with the
air pathway.
Cumulative Risk Index Analysis (CRIA)
(U.S. EPA)
http://www.epa.gov/osp/presentations/
cumrisk/carney.pdf
Analyze and present cumulative risks spatially and
statistically using a CIS-based tool designed by U.S.
EPA Region 6. Useful for projects where quality
toxicity, geographical, and exposure data exist.
Useful for cumulative impacts analysis in National
Environmental Policy Act (NEPA) projects, including
ecological stressors and sources of pollutants
impacting humans.
Designed specifically for spatial
presentation of cumulative risks. Can
compare human health and ecological
risks. 90 environmental criteria are in
use, with 45 used to identify multimedia
inspection targets. Also considers
cultural resource concerns and sensitive
subpopulations.
Environmental Load Profile (U.S. EPA)
http://www.epa.gov/region02/community/
ej/guidelines.htm#step4
Compares indicators of well-being with statewide-
derived benchmarks. A screening-level tool
developed by U.S. EPA Region 2, as a companion to
the Environmental Justice Demographic Screening
Tool.
Similar to RAIMI and CRIA above but
considers only Toxics Release Inventory
(TRI) emissions, air toxics, and facility
density, in screening mode. A more
detailed investigation fora community's
burden should be conducted at the local
level.
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1 APPENDIX B
2 TOXICITY INFORMATION TO SUPPORT GROUPINGS
3
4 This appendix illustrates how toxicity data can be organized to support screening
5 and grouping for cumulative risk assessments. Information presented here can be used
6 in conjunction with the toxicity considerations presented in Chapter 4 and more detailed
7 chemical-specific information when available (e.g., resources listed in Appendix A).
8 B.1. EXAMPLE TOXICITY MATRICES FOR SELECTED CHEMICALS
9 The primary toxicological effects for a set of example chemicals often
10 encountered at a contaminated site are summarized in this appendix to illustrate how
11 this information can be used to support grouping for an evaluation of joint toxicity and
12 potential interactions. These chemicals were selected for study to support a site-
is specific integrated risk evaluation (at the U.S. Department of Energy's Hanford site).
14 This primary toxicity information can be used to help group the chemicals by common
15 target organ or system, by common mode of action, or by potential for interaction
16 considering common metabolites or metabolic pathways. Primary effects for oral
17 exposures are provided in Table B-1, and those for inhalation exposures are
is summarized in Table B-2. The toxicity values presented in Tables B-1 and B-2 are from
19 U.S. EPA's IRIS database, current to November 2005. The reference doses and lowest
20 secondary toxicological effect levels for these study chemicals are compared in
21 Table B-3.
22 To simplify the presentation of information, the tables are presented together
23 after the references for this appendix. A glossary of toxicity terms to support the
24 grouping of chemicals by effects is presented following these tables.
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1 B.2. SUPPORTING INFORMATION ON TOXICOLOGICAL CONCEPTS
2 Information used to derive the primary toxicity values - oral reference doses
3 (RfDs) and inhalation reference concentrations (RfCs) - are provided in Section B.2.1.
4 These primary data are also compared to the data describing effects that are
5 considered secondary (occurring at higher doses than the primary or critical effect) in
6 Section B.2.2.
7 B.2.1. Derivation of Primary Toxicity Factors. As described in EPA's document
8 A Review of the Reference Dose and Reference Concentration Processes (U.S. EPA,
9 2002e), the critical effect used in dose-response assessments is currently associated
10 with the lowest no-observed-adverse-effect level (NOAEL), and various uncertainty
11 factors are applied to the dose at this critical-effect level to derive the RfD or RfC. An
12 experimental exposure level is selected from the critical-effect study that represents the
13 highest level tested in which no adverse effect was demonstrated. This NOAEL is the
14 key data point obtained from the study of the dose-response relationship and has
15 traditionally served as the primary basis for evaluating potential human health risks.
16 This approach is based on the assumption that if the critical toxic effect is prevented,
17 then all toxic effects are prevented. A chemical can elicit more than one toxic effect,
is even in one test animal, or in tests of the same or different duration (acute, subchronic,
19 and chronic exposure studies). In general, NOAELs for these effects will differ. In
20 addition, this approach assumes that the sequence of various health effects with
21 increasing exposure for a particular chemical is maintained across species (U.S. EPA,
22 2002e).
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i A more recent approach used to derive RfDs and RfCs is the benchmark dose
2 (BMD) method. Use of the NOAEL in determining RfDs and RfCs has long been
3 recognized as having limitations in that it (1) is limited to one of the doses in the study
4 and is dependent on study design; (2) does not account for variability in the estimate of
5 the dose-response; (3) does not account for the slope of the dose-response curve; and
6 (4) cannot be applied when there is no NOAEL, except through application of an
7 uncertainty factor (U.S. EPA, 2004g). A goal of the BMD approach is to define a
8 starting point-of-departure for the computation of a reference value (RfD or RfC) or
9 slope factor that is more independent of study design. Use of BMD methods involves
10 fitting mathematical models to dose-response data and using the different results to
11 select a BMD that is associated with a predetermined benchmark response, such as a
12 10% increase in the incidence of a particular lesion or a 10% decrease in body weight
13 gain, which would be termed the BMDio (U.S. EPA, 2004g). Note that for the study
14 chemicals, the primary RfD for beryllium and the primary RfC for chromium VI
15 (particulates) are both based on this newer BMD approach, as opposed to the standard
16 NOAEL/LOAEL approach used to derive toxicity data for the other chemicals.
17 B.2.2. Comparison of Primary and Lowest Secondary Effects. The primary and
is lowest secondary effects and respective concentrations (i.e., RfDs and
19 LOAELs/NOAELs) are given for each chemical for the oral pathway in Table B-3. The
20 secondary effects data were selected as the lowest doses from the entire set of studies
21 discussed in the sections on subchronic and chronic levels of significant exposure in the
22 toxicological profiles prepared by the Agency for Toxic Substances and Disease
23 Registry (ATSDRJ. Human and animal studies were evaluated separately.
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i As shown in this table, the lowest doses yielding secondary effects are higher
2 than the respective RfDs for all the study chemicals. This is to be expected because
3 RfDs are set to be protective of the lowest adverse effects, or critical effects. For all but
4 three chemicals, the RfDs are lower than both the lowest NOAEL and LOAEL values for
5 secondary effects from human and animal studies.
6 The three chemicals where RfDs could overlap NOAELs are trivalent chromium,
7 nickel, and zinc. For trivalent chromium, nickel, and zinc, some of the lowest NOAEL
8 values for secondary effects are below the RfD, but none of the LOAEL values for
9 secondary effects are below the RfD. The RfD for trivalent chromium is 1.5 mg/kg-day,
10 while the lowest animal NOAEL is a lower value of 0.46 mg/kg-day. However, the
11 lowest animal LOAEL (5 mg/kg-day) is above the RfD. The RfD for nickel is
12 0.02 mg/kg-day and the lowest human NOAEL is also 0.02 mg/kg-day. No human
13 LOAEL was reported for nickel, but the lowest animal NOAEL (0.97 mg/kg-day) is
14 above the RfD. The RfD for zinc is 0.3 mg/kg-day, while the lowest human NOAEL is
15 0.06 mg/kg-day, a lower value. However, the lowest human (0.71 mg/kg-day) and
16 animal LOAELs (0.5 mg/kg-day) are both higher than the RfD. These overlaps can be
17 viewed as indications of the quantitiative uncertainties when using LOAELs and
is NOAELs.
19 All secondary adverse effects identified in the collection of human and animal
20 studies reported in the ATSDR toxicological profiles for the 15 study chemicals occur at
21 concentrations above the RfDs (all LOAELs were above the RfDs). Thus, although
22 some actual LOAELs for secondary effects may be lower than the LOAEL for the
23 primary effect (as discussed in Section B.2.3), the series of modifying and other
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i uncertainty factors applied during the RfD derivation process ensured that the RfD
2 based on a critical effect is at least below other available LOAELs. The levels resulting
3 in secondary effects would not typically be seen on contaminated sites, as the lowest
4 LOAELs for secondary effects are generally several orders of magnitude higher than the
5 RfDs. This fact is a testament to the necessity for uncertainty and other modifying
6 factors during RfD development, given the findings noted in Section B.2. Because
7 hazard indices estimated for contaminated sites are often less than 10, these effects
8 would not generally be expected to occur, except in cases of high concentrations (e.g.,
9 following a major release, for which acute or short-term exposure levels would be
10 relevant rather than chronic values), multiple routes of exposure, or where interactions
11 occur. Thus, although effect-specific RfDs can be derived for data-rich chemicals,
12 which would yield useful information for a cumulative risk assessment involving
13 chemical mixtures, such an approach might not be needed. Obviously, obtaining
14 secondary effects data for less-studied compounds would be more difficult but would
15 give a fuller picture of the array of toxic effects exerted by each chemical. Another
16 example of what a secondary effect analysis might find is discussed below.
17 B.2.3. Secondary Effects Findings: Case Study Chemicals. Although the
is discussion above notes that the RfDs based on primary effects appear protective of all
19 effects for the example chemicals studied, it should be noted that the RfD or RfC is
20 protective partly because of the use of uncertainty and/or modifying factors. Except for a
21 few cases where no or minimal UFs are used (e.g., when chronic human toxicity data
22 are available), part of the magnitude of UFs is to account for equitoxic dose
23 extrapolation or scaling, and part is to be protective in the face of quantitative
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i uncertainty. Thus, uncertainty and modifying factors serve multiple purposes. Some
2 secondary effects might occur at concentrations lower than the primary NOAEL or
3 LOAEL, but because of study difficulties might have not been selected as the critical
4 study. Consequently, one purpose of the UFs not often recognized is to provide some
5 assurance that the RfD or RfC is protective of secondary effects.
6 The secondary effects summary for the study chemicals discussed below is
7 abstracted from the ATSDR toxicological profiles and includes some examples of
8 LOAELs for secondary effects that are lower than the primary effect LOAEL. These are
9 the types of secondary effects that should be prioritized in a cumulative health
10 assessment, as they would be the first to be manifested upon cumulative source or
11 cumulative pathway exposure in addition to the primary effects. This is not a
12 comprehensive review of all LOAELs for the study chemicals where a LOAEL is below
13 the primary effect LOAEL, but rather a cross-section of considerations. Highlights are
14 as follows:
15 A human oral arsenic study found nervous system effects including
16 fatigue, headaches, dizziness, insomnia, and numbness at a secondary
17 effect LOAEL of 5 x 10"3 mg/kg-day (below the primary effect LOAEL of
is 1.4 x 10~2 mg/kg-day). Dermal effects of oral exposure have been
19 documented at LOAELs below the LOAEL from the key study for the same
20 dermal primary effect in at least three studies. Two recent studies found
21 cardiovascular effects at a LOAEL below the dermal-based primary effect
22 LOAEL; increased cerebrovascular disease and cerebral infarction were
23 indicated at a LOAEL of 2 x 10~3 mg/kg-day in a 1997 study. Palpitations,
24 chest discomfort, and cyanosis of the extremities were indicated in a 1994
25 study that also documented dermal effects at 5 x 10~3 mg/kg-day.
26 Increased serum bilirubin has also been observed at a lower LOAEL than
27 the primary effect; however, the biological significance of this endpoint
28 alone may be questionable.
29
30 A human inhalation study of beryllium found increased T-cell activity and
31 chronic beryllium disease at a reported LOAEL of 5.2 x 10~4 mg/m3 (below
32 the primary effect LOAEL of 5.5 x 10"4 mg/m3). Although this is
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i mathematically slightly lower than the study selected as the critical study
2 in the IRIS file derivation of the RfC, the difference is not significant, as the
3 primary effect basis for the RfC was also a human (more recent 1996)
4 occupational study of chronic beryllium disease.
5
6 Mercury has been reported in at least six developmental studies and
7 seven neurological studies to result in adverse effects below the primary
8 effect-based LOAEL of 0.633 mg/kg-day. Four studies found impacts to
9 the kidneys at LOAELs below the primary effect-based LOAEL as well.
10
11 For nickel, 15 studies found effects below the primary effect-based LOAEL
12 of 50 mg/kg-day. A handful of the studies also found effects below the
13 NOAEL of 5 mg/kg-day. Specifically, 1993, 1999, and 2000 studies
14 (captured in the 2003 update to the ATSDR toxicological profile) indicate
15 reproductive impacts in animals below the primary NOAEL.
16
17 For trichloroethylene, only one study had a LOAEL below the basis for the
is primary effect underlying NCEA's recommended provisional value.
19 Increased fetal heart abnormalities were noted in offspring below the
20 LOAEL upon which the primary effect (cellular disruption) was based.
21 U.S. EPA (2001 c) evaluated this study in choosing its primary effect basis.
22
23 Uranium studies found secondary effects at LOAELs below that which the
24 oral RfD was based. Specifically, endocrine effects and cellular hepatic
25 and kidney changes were observed in one study. Other minor renal
26 effects were also noted at lower LOAELs than that used to develop the
27 oral RfD.
28
29 Cancer data are also given in the ATSDR toxicological profiles. For example,
30 human lung cancer and skin cancer due to arsenic exposure were also reported at
31 LOAELs below the noncancer primary effect LOAEL; however, cancer risks are typically
32 evaluated separately from the noncancer hazards so this would be accounted for in a
33 cancer risk assessment.
34 Thus, the full body of available literature and resulting toxicity factors, NOAELs
35 and LOAELs need to be considered and evaluated when performing a cumulative risk
36 assessment to ensure that the risk assessment takes into account all possible
37 significant effects and their respective effect levels. While the primary RfDs and RfCs
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i are considered protective and are often based on the effect seen at the lowest chemical
2 concentration or dose, the secondary effects discussed above should be prioritized and
3 considered in a cumulative health assessment, as they would be the first to be
4 manifested upon cumulative source or cumulative pathway exposure in addition to the
5 primary effects.
6 B.3. GLOSSARY OF TOXICOLOGICAL EFFECTS
7
8 Abdominal pain See Pain. Indicates effect is seen in the abdominal region.
9 Abnormality Unusual function or irregularity.
10 Abnormal electromyographic findings See Abnormality. In this effect, measurements
11 indicating that the electrical voltage generated by body muscles is irregular.
12 Abnormal nerve conduction See Abnormality. Indicates the effect is manifested in
13 nerve conduction.
14 Abortion The premature expulsion from the uterus of the products of conception of
15 the embryo or of a nonviable fetus. Natural abortions are typically called miscarriages.
16 Aborted or stillborn fetuses See Abortion, Stillbirth.
17 Absorption alterations See Alterations. Indicates effect is seen in gastrointestinal
is tract absorption.
19 Acinar cell necrosis and metaplasia in pancreas See Necrosis and Metaplasia.
20 Indicates effects are seen in the acinar cells of the pancreas.
21 Adenocarcinoma A form of cancer that involves cells from the lining of the walls of
22 many different organs of the body.
23 Adenoma A benign epithelial tumor in which the cells form recognizable glandular
24 structures or in which the cells are clearly derived from glandular epithelium.
25 Adhesions Fibrous bands or structures by which parts abnormally adhere.
26 Adnexal changes Alterations in appendages. For example, in gynecology the
27 adnexa are the appendages of the uterus, namely the ovaries, Fallopian tubes and
28 ligaments that hold the uterus in place.
29 Albuminuria The presence of protein in the urine, principally albumin, generally
30 indicating disease.
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i Alkaline phosphatase An enzyme that catalyses the cleavage of inorganic phosphate
2 non-specifically from a wide variety of phosphate esters and having a high (greater than
3 8) pH optimum.
4 Alopecia Baldness, absence of the hair from skin areas where it normally is present.
5 ALT activity changes Changes in a liver enzyme that plays a role in protein
6 metabolism; see also AST. Elevated serum levels of ALT are a sign of liver damage
7 from disease or drugs. Synonym: serum glutamic pyruvic transaminase.
8 Alterations Changes, such as increase or decrease.
9 Altered sperm chromatin structure See Alterations. Indicates effect seen in the
10 chromatin structure of sperm.
11 Alveolar proteinosis A very rare disease in which a phospholipid is widely distributed
12 in cells and accumulates in the alveolar spaces in the lung. In some cases the
13 underlying cause is unknown. In others it may relate to an infection or an immune
14 system dysfunction. The net effect is a progressive interference in the ability of the lung
15 (alveoli) to exchange oxygen and carbon dioxide. Symptoms include cough, weight
16 loss, fatigue, shortness of breath and nail abnormalities (clubbing).
17 Anemia Too few red blood cells in the bloodstream, resulting in insufficient oxygen
is supply to tissues and organs.
19 Anisokaryosis Cells or cell nuclei that vary considerably in size.
20 Anorexia The uncontrolled lack or loss of the appetite for food.
21 Arterial insufficiency Failure of arteries to function adequately, resulting in insufficient
22 oxygen supply to cells, tissues, or organs.
23 Arterial [oxygen] tension The pressure of the blood within an artery, the arterial
24 pressure. Also called the intra-arterial pressure.
25 Arterial thickening Increase in the thickness of the arterial walls, resulting in impaired
26 function and restricted flow.
27 Arterial thickening in pancreas See Arterial thickening. Indicates effect is seen in the
28 pancreas.
29 Arterial thickening in stomach and intestines See Arterial thickening. Indicates effect
30 is seen in the stomach and intestines.
31 Ascites An effusion and accumulation of serous fluid in the abdominal cavity.
32 Synonyms: abdominal dropsy, peritoneal dropsy, hydroperitonia, hydrops abdominis.
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i AST activity changes Changes in a liver enzyme that plays a role in protein
2 metabolism; see also ALT. Elevated serum levels of AST are a sign of liver damage
3 from disease or drugs. Synonym: serum glutamic oxaloacetic transaminase.
4 Astroglial hypertrophy See Astrogliosis.
5 Astrogliosis Hypertrophy of the astroglia, usually in response to injury. Astroglia
6 (astrocytes) are the largest and most numerous neuroglial cells in the brain and spinal
7 cord. They regulate the extracellular ionic and chemical environment, and "reactive
8 astrocytes" (along with microglia) respond to injury.
9 Ataxia Failure of muscular coordination, irregularity of muscular action.
10 Atelectasis A term used to describe partial or complete collapse of the lung, usually
11 due to an obstruction of a bronchus (with mucus plug, infection or cancer). Symptoms
12 of atelectasis include low-grade fever, dry cough, chest pains and mild shortness of
13 breath.
14 Atrophy A wasting away, a diminution in the size of a cell, tissue, organ or part.
15 Autoimmune glomerulonephritis A condition in which an individual's immune system
16 starts reacting against his or her own tissues, causing diseases such as
17 glomerulonephritis (inflammation of the cluster of blood vessels at the beginning of the
is kidney tubule where unconcentrated urine is formed by filtration of the blood).
19 Autonomic dysfunction See Dysfunction. Indicates effect is seen in the autonomic
20 nervous system (Neurons that are not under conscious control, comprising two
21 antagonistic components, the sympathetic and parasympathetic nervous systems. The
22 autonomic nervous system regulates key functions including the activity of the cardiac
23 (heart) muscle, smooth muscles (e.g., of the gut), and glands. The autonomic nervous
24 system has two divisions: 1. The sympathetic nervous system that accelerates the heart
25 rate, constricts blood vessels, and raises blood pressure. 2. The parasym pathetic
26 nervous system slows the heart rate, increases intestinal and gland activity, and relaxes
27 sphincter muscles.
28 Azotemia A higher than normal blood level of urea or other nitrogen containing
29 compounds in the blood. The hallmark test is the serum BUN (blood urea nitrogen)
30 level. Usually caused by the inability of the kidney to excrete these compounds.
31 Basal cell carcinoma See Carcinoma. Indicates effects is seen in the relatively
32 undifferentiated cells in an epithelial sheet that give rise to more specialized cells act as
33 stem cells.
34 Behavioral changes See Alterations. Indicates effect is seen on normal or usual
35 behavior.
36 Bile duct enlargement/proliferation See Enlargement, Proliferation. Indicates effect is
37 seen in bile ducts.
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i Blackfoot disease Syndrome characterized by a progressive loss of circulation in the
2 hands and feet, leading ultimately to necrosis and gangrene.
3 Blastogenesis Multiplication or increase by gemmation or budding.
4 Blastogenic activity See Blastogenesis.
5 Bleeding in the gut See Hemorrhage. Indicates effect is seen in the gut.
6 Blood phosphate A salt of phosphoric acid present in blood or blood serum, the clear
7 liquid that separates from blood on clotting.
8 Body weight alterations See Alterations. Indicates effect is manifested as a change
9 in body weight. See also Weight gain, Weight loss.
10 Body weight gain See Weight gain. Indicates effect is for whole body weight.
11 Body weight loss See Weight loss. Indicates effect is for whole body weight.
12 Bone accretion The growing together of bones.
13 Bone marrow retention alterations See Retention alterations. Indicates effect is
14 manifested in the bone marrow.
15 Brain cell degeneration See Degeneration. Indicates effect is manifested in brain
16 cells.
17 Brain, reduced number of myelinated fibers Fewer neural connections within the
is brain.
19 Bronchiectasis Persistent and progressive dilation of bronchi or bronchioles as a
20 consequence of inflammatory disease (lung infections), obstruction (tumor) or
21 congenital abnormality (for example cystic fibrosis). Symptoms include fetid breath and
22 paroxysmal (spastic) coughing, with the expectoration of mucopurulent matter. It may
23 affect the bronchioles uniformly (cylindric bronchiectasis) or occur in irregular pockets
24 (sacculated bronchiectasis) or the dilated bronchi may have terminal bulbous
25 enlargements (fusiform bronchiectasis).
26 Bronchitis Inflammation of one or more bronchi, usually secondary to infection.
27 Bronchopneumonia/bronchiopneumonia Inflammation of the lungs that usually
28 begins in the terminal bronchioles. These become clogged with a mucopurulent
29 exudate forming consolidated patches in adjacent lobules. The disease is frequently
30 secondary in character, following infections of the upper respiratory tract, specific
31 infectious fevers and debilitating diseases. In infants and debilitated persons of any age
32 it may occur as a primary affection. Synonyms: bronchial pneumonia, bronchoalveolitis,
33 bronchopneumonitis, lobular pneumonia.
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i Carcinoma A malignant new growth that arises from epithelium, found in skin or,
2 more commonly, the lining of body organs, for example: breast, prostate, lung, stomach
3 or bowel. Carcinomas tend to infiltrate into adjacent tissue and spread (metastasize) to
4 distant organs, for example: to bone, liver, lung or the brain.
5 Cardiac inotropy See Inotropy. Indicates effect is seen in the cardiac muscles.
6 Casts (in urine) White blood cell casts indicate pyelonephritis, but they are not
7 always present in the urine.
8 Cell-mediated cytotoxicity See Cytotoxicity. Indicates cells convey effect.
9 Cell-mediated immune response Immune response that involves effector T
10 lymphocytes and not the production of humoral antibody. Responsible for delayed
11 hypersensitivity and in defense against viral infection and intracellular protozoan
12 parasites.
13 Cellular degeneration/changes See Degeneration. Indicates effect is seen within
14 cells.
15 Central lobe necrosis See Necrosis. Indicates effect is seen in the central lobe of the
16 liver.
17 Centrilobular necrosis See Central lobe necrosis.
is Cerebral infarction Infarction of brain tissue.
19 Cerebrovascular disease A general term which encompasses a variety of diseases
20 which affect (via the occlusive effects of atherosclerosis) the arteries which supply the
21 brain.
22 Chronic conjunctivitis See Conjunctivitis.
23 Cirrhosis Liver disease characterized pathologically by loss of the normal
24 microscopic lobular architecture, with fibrosis and nodular regeneration. The term is
25 sometimes used to refer to chronic interstitial inflammation of any organ.
26 Cloudy swelling in kidneys See Inflammation. Indicates effect is seen in kidneys.
27 Confusion Disturbed orientation in regard to time, place or person, sometimes
28 accompanied by disordered consciousness.
29 Congenital malformations Abnormal formation of a structure evident at birth
30 Conjunctivitis Inflammation of the conjunctiva, generally consisting of conjunctival
31 hyperemia associated with a discharge.
32 Contractility Capacity for becoming short in response to a suitable stimulus.
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i Cough A rapid expulsion of air from the lungs typically in order to clear the lung
2 airways of fluids, mucus, or material.
3 Cramps See Pain. Indicates effect is seen in abdomen.
4 Cyanosis A bluish discoloration, applied especially to such discoloration of skin and
5 mucous membranes due to excessive concentration of reduced hemoglobin in the
6 blood.
7 Cysts Any closed cavity or sac that is lined by epithelium often contains liquid or
8 semi-solid material.
9 Cytomegaly A condition or disease characterized by abnormally enlarged cells.
10 Cytotoxicity The quality of being poisonous, or toxic, to individual cells.
11 Damage See Injury.
12 Death See Survival.
13 Decline in conditioned responses Reduced frequency of learned behaviors in
14 response to triggering stimulus.
15 Decrease in Hb and H values Lowered hemoglobin content, resulting in reduced
16 oxygen carrying capacity and possible anoxia. Hemoglobin is the Four subunit globular
17 oxygen carrying protein of vertebrates and some invertebrates. There are two alpha
is and two beta chains (very similar to myoglobin) in adult humans, the heme moiety (an
19 iron-containing substituted porphyrin) is firmly held in a nonpolar crevice in each peptide
20 chain.
21 Decreased alkaline phosphatase See alkaline phosphatase.
22 Decreased arterial tension See arterial tension. Reduction in the pressure of blood
23 within an artery.
24 Decreased avoidance response Reduction in learned ability to respond to a cue that
25 is instrumental in avoiding a noxious experience.
26 Decreased blood or serum phosphate levels See blood phosphate and serum
27 phosphate.
28 Decreased cardiac contractility See contractility. Indicates effect is seen in the
29 cardiac muscles.
30 Decreased caudal ossification See Ossification. Indicates effect is seen at a position
31 more toward the cauda or tail of an organism.
32 Decreased corpuscular volume See Anemia. Indicates reduced volume of red blood
33 cells.
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i Decreased DMA in brain areas Reduction in genetic material in the brain.
2 Decreased fetal body weight See Weight Loss. Indicates decrease is in the fetus.
3 Decreased immunoglobulins Reduction in the specific protein substances that are
4 produced by plasma cells to aid in fighting infection. Some immunoglobulins (gamma
5 globulin) take part in various immune responses of the body to bacteria or foreign
6 substances (allergens, tumor or transplanted tissue). Examples include IgG, IgM, IgA,
7 IgD and IgE.
8 Decreased macrophage activity Reduction in the function of macrophages, which are
9 relatively long lived phagocytic cell of mammalian tissues, derived from blood monocyte.
10 Macrophages from different sites have distinctly different properties. Macrophages play
11 an important role in killing of some bacteria, protozoa and tumor cells, release
12 substances that stimulate other cells of the immune system and are involved in antigen
13 presentation.
14 Decreased pulmonary bactericidal activity Reduction in the body's defense
15 mechanisms to kill bacteria in the lungs.
16 Decreased response rate for learned behaviors Increased time to respond to
17 triggering stimuli. See also Decline in Conditioned Responses.
is Decreased tactile-kinesthetic function Reduction of the tactile the sense of touch or
19 pressure by which muscular motion, weight, position, are perceived.
20 Decreased T-cell activity See T-cell.
21 Decreased sperm count Decrease in the number of sperm in the ejaculate (when
22 given as the number of sperm per milliliter it is more accurately known as the sperm
23 concentration or sperm density).
24 Decreased survival See Survival.
25 Decreased vasoreactivity Reduction in the blood vessels' ability to change caliber in
26 response to stimulus, thus affecting blood flow.
27 Degeneration Reduced size or function of a cell, tissue, organ, or part.
28 Dehydration Excessive loss of body water.
29 Delayed ossification Indicates a delay in the formation of bone or of a bony
30 substance, the conversion of fibrous tissue or of cartilage into bone or a bony
31 substance. See also Reduced Ossification.
32 Demyelination See Myelin degeneration.
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i Depigmentation See Pigmentation changes. The removal or loss of pigment,
2 especially melanin.
3 Depression A lowering or decrease of functional activity. Also a mental state of
4 depressed mood characterized by feelings of sadness, despair and discouragement.
5 Depression ranges from normal feelings of the blues through dysthymia to major
6 depression.
7 Dermal effects Effects on the skin.
8 Dermatitis Inflammation of the skin.
9 Desquamation of tubular cells The shedding or exfoliation of epithelial elements of
10 the renal tubules.
11 Diabetes mellitus Relative or absolute lack of insulin leading to uncontrolled
12 carbohydrate metabolism. In juvenile onset diabetes (that may be an autoimmune
13 response to pancreatic cells) the insulin deficiency tends to be almost total, whereas in
14 adult onset diabetes there seems to be no immunological component but an association
15 with obesity.
16 Diarrhea A morbidly frequent and profuse discharge of loose or fluid evacuations
17 from the intestines, without tenesmus; a purging or looseness of the bowels; a flux.
is Diffuse erythematous and scaly rash Redness and scaling of the skin produced by
19 congestion of the capillaries, which may result from a variety of causes.
20 Diffuse palmar or plantar hyperkeratosis See Hyperkeratosis. Indicates effect is
21 seen on palms of hands and soles of feet, and is widespread in nature.
22 Diffuse pigmentation See Pigmentation. Indicates pigmentation is widespread.
23 Dilation Expanded in internal diameter.
24 Disorientation See Confusion.
25 Distribution alterations Changes in distribution.
26 Diuresis Increased excretion of urine. Can be due to metabolic conditions such as
27 diabetes, where the increased glucose level in the blood causes water to be lost in the
28 urine. Can also be produced specifically by diuretic drugs that increase sodium and
29 water loss from the kidney.
30 DOPAC (Dopachrome oxidoreductase) Decarboxylates and converts dopachrome to
31 5,6-dihydroxyindole.
32 Dysfunction Failure to function normally.
33 Dyspepsia Difficult or painful digestion, indigestion.
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i Edema The presence of abnormally large amounts of fluid in the intercellular tissue
2 spaces of the body, usually applied to demonstrable accumulation of excessive fluid in
3 the subcutaneous tissues. Edema may be localized, due to venous or lymphatic
4 obstruction or to increased vascular permeability or it may be systemic due to heart
5 failure or renal disease. Collections of edemous fluid are designated according to the
6 site, for example ascites (peritoneal cavity), hydrothorax (pleural cavity) and
7 hydropericardium (pericardial sac). Massive generalized edema is called anasarca.
8 Embryolethality See Abortion, Stillbirth.
9 Emaciation Excessive leanness; a wasted condition of the body.
10 Emesis Vomiting, an act of vomiting. Also used as a word termination, as in
11 hematemesis.
12 Emphysema A pathological accumulation of air in tissues or organs, applied
13 especially to such a condition of the lungs.
14 Encephaloceles Hernia of the brain; infarction of brain tissue.
15 Enhanced inflammatory response Increased sensitivity to tissue injury causing an
16 inflammatory response, which is a part of innate immunity. Inflammation occurs when
17 tissues are injured by viruses, bacteria, trauma, chemicals, heat, cold or any other
is harmful stimulus. Chemicals including bradykinin, histamine, serotonin and others are
19 released by specialized cells. These chemicals attract tissue macrophages and white
20 blood cells to localize in an area to engulf (phagocytize) and destroy foreign
21 substances. A byproduct of this activity is the formation of pus, which is a combination
22 of white blood cells, bacteria, and foreign debris.
23 Enlarged nuclei Increase in size of the cellular nucleus.
24 Enlarged nuclei of tubular cells See Enlarged nuclei. Indicates cells affected are
25 kidney tubular cells.
26 Enlargement Increased size. See also Weight gain.
27 Enzyme activity stimulation See Increased enzyme activity.
28 Enzyme inhibition - Arrest or restraint of a enzyme process(es).
29 Eosinophilia - The formation and accumulation of an abnormally large number of
30 eosinophils in the blood.
31 Epitaxis (epitasis) The period of violence in a fever or disease; paroxysm.
32 Epithelial degeneration See Degeneration. Indicates effect is manifested in the
33 epithelium.
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i Epithelial degradation See Epithelial degeneration.
2 Eroded luminal epithelium in the stomach See Degeneration. Indicates effect is seen
3 in the luminal epithelium of the stomach.
4 Erythroid hyperplasia of bone marrow See Hyperplasia. Indicates effect is seen in
5 erythrocytes of the bone marrow.
6 Exencephaly See Terata. Condition in which the brain is located outside of the skull.
7 This condition is usually found in embryos as an early stage of anencephaly. As an
8 exencephalic pregnancy progresses, the neural tissue gradually degenerates. It is
9 unusual to find an infant carried to term with this condition because the defect is
10 incompatible with survival.
11 Excretion reduction A decline in production of waste products. See also Abnormal
12 Retention. May include reduced urinary output.
13 Eye defects in fetus See Terata. Indicates malformation of the fetal eye.
14 Fatigue Weakness.
15 Fatty changes See Fatty infiltration.
16 Fatty infiltration Accumulation of fatty acids as triglycerides in the liver. Focal fatty
17 infiltration may mimic neoplastic or other low-density parenchymal lesions, including
is abscesses and hemangiomas. Fatty liver has also been associated with diabetes,
19 obesity, use of corticosteroids and other drugs (including chemotherapy), Cushing's
20 disease, total parenteral nutrition, starvation, hyperlipidemia, pregnancy, cystic fibrosis,
21 Reye's syndrome, malignancy, jejunoileal bypass, and other causes.
22 Fertility The capacity to conceive or induce conception and thus generate offspring.
23 Fetotoxicity Toxicity manifested in the fetus.
24 Fibrosis The formation of fibrous tissue, fibroid or fibrous degeneration.
25 Focal necrosis See Necrosis. Indicates effect is seen in localized area.
26 Folliculitis Inflammation of a follicle or follicles, used ordinarily in reference to hair
27 follicles, but sometimes in relation to follicles of other kinds.
28 Functional denervation Reduced capacity of existing neurons resulting in effective
29 disfunction at the neural termination.
30 Functional impairment Reduction of normal function in a cell, organ, tissue, or part.
31 Gangrene Death of tissue, usually in considerable mass and generally associated
32 with loss of vascular (nutritive) supply and followed by bacterial invasion and
33 putrefaction.
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i Gasping The act of opening the mouth convulsively to catch the breath; a labored
2 respiration; a painful catching of the breath.
3 Gastrointestinal hemorrhage See Hemorrhage. Indicates effect is seen in the
4 gastrointestinal tract.
5 Gastrointestinal irritation See Irritation. Indicates effect is seen in the gastrointestinal
6 tract.
7 Genitourinary defects See Terata. Indicates malformation occurring in the
8 (urogenital) genital and urinary organs.
9 Glucosuria - A condition in which glucose is discharged in the urine; diabetes mellitus.
10 Glycogen level changes Alterations in levels of the branched polymer of D glucose,
11 which serves as the major short-term storage polymer of animal cells and is particularly
12 abundant in the liver and to a lesser extent in muscle.
13 Granule cell loss Reduction in number of granule cells, a type of neuron, in the
14 cerebellum.
15 Granuloma Chronic inflammatory lesion characterized by large numbers of cells of
16 various types (macrophages, lymphocytes, fibroblasts, giant cells), some degrading and
17 some repairing the tissues.
is Granulomata See Granuloma.
19 Gross gastrointestinal lesions See Lesions. Indicates widespread effect is seen in
20 the gastrointestinal tract.
21 Gross physical abnormalities See Terata. Indicates fetal malformations are
22 significant and relate to the basic components of the body. See also Skeletal
23 Malformations, Increases in Skeletal Variations.
24 Headache See Pain. Indicates effect is seen in the head or sinuses.
25 Heart abnormalities in fetus See Terata. Indicates malformations affecting the heart.
26 Heart disease Common condition where vessels (arteries) that carry blood to the
27 heart muscle become narrowed with fatty deposits. The heart then cannot get the
28 oxygen and other nutrients it needs. A complete blockage of one of these vessels may
29 result in a heart attack.
30 Hematemesis The vomiting of blood.
31 Hemolysis Disruption of the integrity of the red cell membrane causing release of
32 hemoglobin.
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i Hemoperitoneum Intraabdominal bleeding, accompanied by abdominal pain. The
2 liver or spleen may increase in size. If the bleeding is severe enough, the blood
3 pressure and hematocrit may fall.
4 Hemorrhage Bleeding. The escape of blood from the vessels. Small hemorrhages
5 are classified according to size as petechiae (very small), purpura (up to 1 cm) and
6 ecchymoses (larger). The massive accumulation of blood within a tissue is called a
7 hematoma.
8 Hemosiderin deposits Deposits of a mammalian iron storage protein (related to
9 ferritin but less abundant).
10 Hemosiderin deposits in hepatic macrophages See Hemosiderin deposits. Indicates
11 effect is seen in liver macrophages, which are relatively long-lived phagocytic cells of
12 mammalian tissues, derived from blood monocytes.
13 Hemosiderin deposits in liver See Hemosiderin deposits. Indicates effect is seen in
14 liver.
15 Hemosiderin deposits in kidney See Hemosiderin deposits. Indicates effect is seen
16 in kidney.
17 Hepatoma Carcinoma derived from liver cells. Also known as hepatocarcinoma or
is hepatocellular carcinoma.
19 Hepatomegaly Enlargement of the liver.
20 Hepatotoxicity Toxicity manifested in the liver.
21 Histopathological changes Microscopic changes in diseased tissues.
22 Histopathological changes in heart tissue See Histopathological changes. Indicates
23 effect is manifested in heart tissue.
24 Histopathological changes in lungs See Histopathological changes. Indicates effect
25 is manifested in lung tissue.
26 Humoral immune response Immune responses mediated by antibodies.
27 Hypalgesia Decreased pain response.
28 Hyperemia An excess amount of blood in an organ. Active hyperemia is increased
29 blood supply to an organ, usually for physiologic reasons (exercise). Passive
30 hyperemia is engorgement of an organ with venous blood, usually the result of
31 inadequate circulation (heart failure).
32 Hyperkeratosis Hypertrophy of the corneous layer of the skin, or any of various
33 conditions marked by hyperkeratosis.
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i Hyperkeratosis of foot See Hyperkeratosis. Indicates effect is seen in the feet.
2 Hyperpigmentation Darkening of the skin. See also Pigmentation.
3 Hyperplasia The abnormal multiplication or increase in the number of normal cells in
4 normal arrangement in a tissue.
5 Hypertension Persistently high arterial blood pressure. Hypertension may have no
6 known cause (essential or idiopathic hypertension) or be associated with other primary
7 diseases (secondary hypertension). This condition is considered a risk factor for the
8 development of heart disease, peripheral vascular disease, stroke and kidney disease.
9 Hypertrophy The enlargement or overgrowth of an organ or part due to an increase
10 in size of its constituent cells.
11 Hypertrophy of pancreas islet cells See Hypertrophy. Indicates effect is seen on the
12 cells of the Islets of Langerhans (or islet cells) within the pancreas.
13 Hypoplasia The incomplete development or underdevelopment of an organ or tissue.
14 Hypopigmentation A condition caused by a deficiency in melanin formation or a loss
15 of pre-existing melanin or melanocytes. It can be complete or partial and may result
16 from trauma, inflammation, and certain infections.
17 Hypothermia - A low body temperature, as that due to exposure in cold weather or a
is state of low temperature of the body induced as a means of decreasing metabolism of
19 tissues and thereby the need for oxygen, as used in various surgical procedures,
20 especially on the heart or in an excised organ being preserved for transplantation.
21 Impaired lymphocytic/leukocytic function See impairment. Indicates effect is seen in
22 the normal function of lymphocytes and leukocytes.
23 Impaired peripheral vision Reduction in visual capacity, particularly in the periphery
24 of the normal field of vision.
25 Impaired liver mitochondrial respiration - See Impairment. Indicates effect is seen in the
26 respiration of the liver mitochondria.
27 Impaired renal mitochondrial respiration - See Impairment. Indicates effect is seen in
28 the respiration of the kidney mitochondria.
29 Impairment Reduction in normal function.
30 Increased cerebral infarction Infarction (an area of tissue death due to a local lack of
31 oxygen) of brain tissue.
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i Increased cerebrovascular disease Increase in any of a variety of diseases which
2 affect (via the occlusive effects of atherosclerosis) the arteries which supply the brain.
3 May lead to stroke.
4 Increased DOPAC concentration See DOPAC, increased enzyme activity, and
5 increased enzyme levels.
6 Increased enzyme activity Metabolic increase via stimulation of enzyme systems.
7 Increased enzyme levels See Increased enzyme activity. Higher measurable
8 circulating or tissue enzymes.
9 Increased glycogen see Glycogen level changes.
10 Increased heart weight See Organ weight gain. Indicates effect is manifested in the
11 heart tissue.
12 Increased kidney weight See Organ weight gain. Indicates effect is manifested in the
13 kidney tissue.
14 Increased leukocyte count An abnormal accumulation of white blood cells.
15 Increased liver weight See Organ weight gain. Indicates effect is manifested in the
16 liver tissue.
17 Increased lung weight See Organ weight gain. Indicates effect is manifested in the
is lung tissue.
19 Increased MCH See MCH, increased enzyme activity, and increased enzyme levels.
20 Increased resorptions The loss of substance through physiologic or pathologic
21 means, such as loss of dentin and cementum of a tooth or of the alveolar process of the
22 mandible or maxilla. In a reproductive context, implies embryos are not carried to term
23 but are instead absorbed into the uterine wall. See also Fertility, Reduced Birth Rate,
24 and Reduced Litter Size, as increased resorptions are related to pregnancy outcome.
25 Increased response to sheep red blood cells Heightened sensitivity to immune
26 challenge.
27 Increased serum enzyme levels See Increased enzyme levels. Indicates effect is
28 manifested in circulating serum enzymes.
29 Increased SCOT See SCOT, increased enzyme activity, and increased enzyme
30 levels.
31 Increased skeletal variations See Terata. See also Gross physical abnormalities.
32 Increased stillbirth See Stillbirth.
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i Increased urea See urea. Indicates a higher than normal excretion of urea in urine.
2 Increased vasopasticity Enhanced constriction of blood vessels.
3 Inflammation A localized protective response elicited by injury or destruction of
4 tissues, which serves to destroy, dilute or wall off (sequester) both the injurious agent
5 and the injured tissue. Histologically, it involves a complex series of events, including
6 dilatation of arterioles, capillaries and venules, with increased permeability and blood
7 flow, exudation of fluids, including plasma proteins and leukocytic migration into the
8 inflammatory focus.
9 Infiltration The diffusion or accumulation in a tissue or cells of substances not normal
10 to it or in amounts of the normal. Also, the material so accumulated. See Macrophage
11 infiltration.
12 Inotropy Muscular contractions.
13 Interstitial bronchiole pneumonia See Bronchiopneumonia. Indicates effect is seen in
14 the interspaces of the lung tissue.
15 Interstitial lung disease A heterogeneous group of noninfectious, nonmalignant
16 disorders of the lower respiratory tract, affecting primarily the alveolar wall structures but
17 also often involving the small airways and blood vessels of the lung parenchyma.
is "interstitial" refers to the fact that the interstitium of the alveolar walls is thickened,
19 usually by fibrosis. This group of diseases is usually inflammatory.
20 Intraepidermal carcinoma See Carcinoma. Indicates effect is seen within the
21 epidermis.
22 Intromission Insertion; introduction.
23 Initial body weight loss See Weight loss.
24 Injury Result of assault by an external force, organic or physiologic dysfunction, or a
25 pathogen.
26 Intestinal hyperemia See Hyperemia. Congestion of the blood in the intestines.
27 Irritation of the eyes See Irritation. Indicates effect is seen in the eye.
28 Irritation Local inflammation of cutaneous or mucosal surfaces.
29 Ischemic heart disease Disease of the heart characterized by a low oxygen state
30 usually due to obstruction of the arterial blood supply or inadequate blood flow leading
31 to hypoxia in the tissue.
32 Karyomegaly - The condition of a cells nucleus being abnormally enlarged (i.e., for
33 reasons other than it being polyploid).
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i Keratosis A skin lesion that is abnormally sensitive to the effects of ultraviolet light
2 (sunlight). Thought to be a precancerous skin lesion that is more common in the fair-
3 skinned or elderly individual. Usually a discrete slightly raised, red or pink lesion
4 located on a sun-exposed surface. Texture may appear as rough, gritty or scaly.
5 Labored breathing See Gasping.
6 Lesions Any pathological or traumatic discontinuity of tissue or loss of function of a
7 part.
8 Lassitude Weakness, exhaustion.
9 Leukocytosis - A term used to describe an abnormal elevation on the white blood cell
10 count. Elevated counts can be seen in cases of inflammation and infection.
11 Leukoderma An acquired disorder that selectively destroys (or that results in the
12 selective disappearance) of some or all melanocytes residing in the interfollicular
13 epidermis and occasionally in the follicle as well. The mechanism(s) by which the
14 melanocytes are lost (or by which melanocytes are made to disappear) may be multiple
15 but are not yet identified unequivocally.
16 Leukopenia Abnormal decrease in the number of white blood cells.
17 Lethal Dose 50 The amount, or dosage, of a toxin necessary to kill 50% of the
is experimental subjects.
19 Leydig cell tumor The most common nongerminal tumor of the testis, derived from
20 the leydig cells. It is rarely malignant. This tumor appears among 1-3% of testicular
21 tumors and although they may be seen in children, the median age of appearance is 60
22 years. They are sometimes seen in women as ovarian tumors. Clinically, symptoms
23 are usually related to the endocrine abnormalities induced by this tumor.
24 Lipid peroxidation Peroxidase-catalyzed oxidation of lipids using hydrogen peroxide
25 as an electron acceptor.
26 Loss of circulation Reduced oxygen supply to cells, organs, or parts.
27 Loss of dexterity Decrease in readiness and grace in physical activity; decrease in
28 skill and ease in using the hands.
29 Lung irritation See Irritation. Indicates effect is manifested in the lung.
30 Lymphoma Malignant tumor of lymphoblasts derived from B lymphocytes.
31 Lysosomal inclusions Accumulations of the undigested substrate within cells caused
32 by an enzyme deficiency.
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i MCH (Mch4 proteaseAn) An enzyme. An aspartate-specific cysteine protease
2 containing two fadd-like domains.
3 Macrocytic anemia See Anemia. Indicates the effect is caused by enlarged red
4 blood cells.
5 Macrophage infiltration See Infiltration. Indicates effect is an accumulation of
6 macrophages.
7 Melanoderma Abnormal blackness of skin.
8 Melanosis A disorder caused by a disturbance in melanin pigmentation; melanism.
9 Melena Bloody or dark black or tarry bowel movements.
10 Memory loss Disturbances in registering an impression, in the retention of an
11 acquired impression or in the recall of an impression.
12 Mental sluggishness Delayed reactions or fatigue arising in consequence of mental
13 effort.
14 Metabolism alterations See Alterations. Indicates the effect is manifested in
15 metabolic processes; may reflect and increase or decrease in metabolism.
16 Metaplasia The change in the type of adult cells in a tissue to a form that is not
17 formal for that tissue.
is Methemoglobinemia The presence of methemoglobin in the blood, resulting in
19 cyanosis. A small amount of methemoglobin is present in the blood normally, but injury
20 or toxic agents convert a larger proportion of hemoglobin into methemoglobin, which
21 does not function reversibly as an oxygen carrier.
22 Microgranuloma See Granuloma. Indicates the effect is small, little.
23 Mineralization Production of bone minerals from collagen, important in the
24 progressive growth and development of normally calcifying bone, cartilage, tendon,
25 dentin, and cementum among vertebrate tissues. Collagen represents the principal
26 organic component in such tissues and it strictly mediates the nucleation, growth, and
27 development of the mineral, a calcium phosphate salt (apatite). The interaction
28 between collagen and mineral leads to a composite tissue having improved strength
29 and biomechanical properties different from those of either component separately
30 considered. Conversely, changes in collagen content, assembly, or aggregation could
31 have profound effects on mineralization and subsequently on the nature of tissue
32 integrity and mechanical behavior.
33 Miscarriage See Abortion.
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i Mitochondria! Respiration Impairment See Impairment. Indicates reduction in the
2 energy produced in the mitochondria, which are specialized membrane structures within
3 a cell that provide energy for a cell by the addition of substances acted upon by
4 enzymes
5 Mortality See Survival.
6 Motility Ability of the spermatozoa to move by flagellate swimming.
7 Muscular hypertrophy see Hypertrophy.
8 Myelin degeneration See Degeneration. Indicates the effect is seen in the material
9 making up the myelin sheath of nerve axons.
10 Narcosis State of unconsciousness.
11 Nausea An unpleasant sensation, vaguely referred to the epigastrium and abdomen
12 and often culminating in vomiting. See Also Dyspepsia, Emesis, Vomiting.
13 Necrosis Death of a tissue.
14 Nephrosis A type of nephritis that is characterized by low serum albumin, large
15 amount of protein in the urine and swelling (edema). Swelling, weight gain, high blood
16 pressure and anorexia are key features. Nephrotic syndrome can be seen with a
17 number of illness that cause damage to the kidney glomerulus. Examples include
is diabetes, hereditary disorders, lupus, multiple myeloma, amyloidosis,
19 glomerulonephritis, minimal change disease and membranous glomerulonephritis.
20 Nephrotoxicity Toxicity to the kidney.
21 Nerve conduction Neural transport of an electronic impulse.
22 Neuropathy A general term denoting functional disturbances and/or pathological
23 changes in the peripheral nervous system. If the involvement is in one nerve it is called
24 mononeuropathy, in several nerves, mononeuropathy multiplex, if diffuse and bilateral,
25 polyneuropathy. The etiology may be known for example arsenical neuropathy, diabetic
26 neuropathy, ischemic neuropathy, traumatic neuropathy) or unknown. Encephalopathy
27 and myelopathy are corresponding terms relating to involvement of the brain and spinal
28 cord, respectively. The term is also used to designate noninflammatory lesions in the
29 peripheral nervous system, in contrast to inflammatory lesions (neuritis).
30 Neonatal survival See Perinatal mortality.
31 Nonspecific brain injury See Injury. Indicates effect is seen in the brain, but specific
32 etiology or precise effect is unknown.
33 Nonspecific hepatotoxicity See Hepatotoxicity.
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i Not specified Not otherwise specified. No additional information is immediately
2 available.
3 Numbness Lacking sensation.
4 Oliguria Secretion of a diminished amount of urine in relation to the fluid intake.
5 Ossification - The formation of bone or of a bony substance, the conversion of fibrous
6 tissue or of cartilage into bone or a bony substance.
7 Organ Weight Gain Increase in the mass of an organ. May indicate injury to the
8 organ or increase in organ function in response to a stimulus.
9 Ossification the formation of bone or of a bony substance, the conversion of fibrous
10 tissue or of cartilage into bone or a bony substance. See Delayed ossification; Reduced
11 ossification.
12 Osteomalacia - A condition marked by softening of the bones (due to impaired
13 mineralization, with excess accumulation of osteoid), with pain, tenderness, muscular
14 weakness, anorexia and loss of weight, resulting from deficiency of vitamin D and
15 calcium.
16 Osteoporosis A reduction in the amount of bone mass, leading to fractures after
17 minimal trauma.
is Pain Sensation of discomfort, distress, or agony.
19 Pale skin Skin lacking freshness or ruddiness; a sickly whiteness; lack of color or
20 luster; wanness.
21 Palmar and plantar keratosis See Keratosis. Indicates effect is seen on palms of
22 hands and soles of feet.
23 Palpitations Irregular and violent heartbeats.
24 Pancreatitis Acute or chronic inflammation of the pancreas, which may be
25 asymptomatic or symptomatic and which is due to autodigestion of a pancreatic tissue
26 by its own enzymes.
27 Paresthesia Paralysis.
28 Perforation A hole made through a part or substance.
29 Periocular edema See Edema. Indicates effect is seen around the eyes.
30 Perinatal mortality Mortality occurring in the period shortly before and after birth, (in
31 humans defined as beginning with completion of the twentieth to twenty eighth week of
32 gestation and ending 7 to 28 days after birth); see also Stillbirth, Abortion, Mortality.
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i Peripheral nervous system impairment See Impairment. Indicates effect is seen in
2 the nerves of the PNS, which connect the central nervous system (CMS) with sensory
3 organs, other organs, muscles, blood vessels, and glands.
4 Peripheral Pertaining to or situated at or near the periphery, situated away from a
5 center or central structure.
6 Persistent extensive hyperkeratosis See Hyperkeratosis. Indicates condition is
7 widespread and difficult to treat.
8 Pharyngitis Inflammation of the pharynx.
9 Pheochromocytoma A tumor of the adrenal gland, which produces catecholamines
10 (noradrenaline and adrenaline). Although the tumor is usually benign it produces
11 hypertension, pounding headaches, tachycardia, palpitations, apprehension, facial
12 flushing, nausea and vomiting.
13 Pigmentation Coloration, especially abnormally increased coloration, by melanin.
14 Pigmentation changes Increase or decrease in pigment, especially melanin.
15 Pigmentation in hepatic macrophages See Pigmentation. Indicates effect is seen in
16 the liver macrophages, which are relatively long-lived phagocytic cells derived from
17 blood monocytes.
is Pneumonia Inflammation of the lungs with consolidation.
19 Pneumonitis Inflammation of the lung secondary to viral or bacterial infection.
20 Portal hypertension Any increase in the portal vein (in the liver) pressure due to
21 anatomic or functional obstruction (for example alcoholic cirrhosis) to blood flow in the
22 portal venous system. Indicators of portal hypertension are: esophageal varices,
23 hemorrhoids, enlarged veins on the anterior abdominal wall (caput Medusae) and
24 ascites.
25 Possible vascular complications See Vascular complications.
26 Production Creation of a product.
27 Proliferation Increase in numbers; the reproduction or multiplication of similar forms,
28 especially of cells and morbid cysts.
29 Prostration Absolute exhaustion.
30 Proteinuria Too much protein in the urine. This may be a sign of kidney damage.
31 Pulmonary vasculitis See Vasculitis. Indicates effect is seen in the respiratory tract.
32 Rales Abnormal breathing sounds heard through a stethoscope.
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i Raynaud's disease Paroxysmal (i.e., occurring in spasms or seizures) bilateral
2 cyanosis of the digits due to arterial or arteriolar contraction.
3 RBC functional impairment See Impairment. Indicates failure of the red blood cells to
4 function, primarily resulting in poor oxygen distribution.
5 Reduced birth rate Fewer live births than expected. See also Stillbirth, Increased
6 resorptions, Abortion, and Reduced fertility.
7 Reduced growth rate Failure to gain weight normally. See also Weight gain, Weight
8 loss.
9 Reduced clavicle Also called the collar bone, it articulates with the shoulder on one
10 end (at the acromion process of the scapula) and the sternum (breast bone) on the
11 other.
12 Reduced fertility See Fertility. Failure to conceive normally.
13 Reduced fine motor performance See Impairment. Indicates effect is noted in fine
14 motor skills.
15 Reduced glycogen Reduction in the polysaccharide occurring especially in the liver
16 and muscle, where it is stored as a sugar-supply reserve, capable of complete
17 conversion to glucose when needed. See also Glycogen level changes.
is Reduced heart rate Depressed heart rate.
19 Reduced litter size See Reduced birth rate.
20 Reduced lung function See Impairment. Indicates effect is seen on pulmonary
21 function.
22 Reduced nerve conduction See Impairment. Indicates effect is seen in nerve
23 conduction.
24 Reduced ossification Indicates a reduction in the formation of bone or of a bony
25 substance, the conversion of fibrous tissue or of cartilage into bone or a bony
26 substance. See also Delayed Ossification.
27 Reduced short-term memory See Memory Loss. Indicates effect is manifested in
28 short-term retention.
29 Reduced sperm motility See Motility. See also Fertility. Indicates effect is seen in
30 sperm.
31 Reduced sperm production See Production. See also Fertility. Indicates effect is
32 seen in sperm.
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i Reduced urinary output Lower volume (whether due to excretion reduction or
2 concentration of wastes) of urine production. See also Excretion Reduction.
3 Respiratory tract inflammation See Inflammation. Indicates effect is seen in the
4 respiratory tract.
5 Resorption The loss of substance through physiologic or pathologic means.
6 Respiratory tract injury See Injury. Indicates effect is seen in the respiratory tract.
7 Retention alterations Changes in the persistent keeping within the body of matters
8 normally excreted; thus, decreased excretion is also increased retention. See also
9 Excretion Reduction.
10 Reticulin sclerosis See Sclerosis. Indicates effect is seen in the reticulin, the
11 constituent protein of reticulin fibers found in extracellular matrix.
12 Rhinitis Inflammation of the mucous membrane of the nose.
13 Rhinorrhea The free discharge of a thin nasal mucus.
14 Rickets A condition caused by deficiency of vitamin D, especially in infancy and
15 childhood, with disturbance of normal ossification. The disease is marked by bending
16 and distortion of the bones under muscular action, by the formation of nodular
17 enlargements on the ends and sides of the bones, by delayed closure of the fontanelles,
is pain in the muscles and sweating of the head.
19 Scaling Dry patches of skin resembling fish scales. See also Dermatitis.
20 Scaling of skin See Scaling.
21 Sciatic and optic nerve injury See Injury. Indicates effect is seen in the sciatic (hip
22 region) and optic (eye) nerves.
23 Sclerosis An induration or hardening, especially hardening of a part from
24 inflammation and in diseases of the interstitial substance. The term is used chiefly for
25 such a hardening of the nervous system due to hyperplasia of the connective tissue or
26 to designate hardening of the blood vessels.
27 Seizures Attacks of cerebral origin consisting of sudden and transitory abnormal
28 phenomena of a motor, sensory, autonomic or psychic nature resulting from transient
29 dysfunction of the brain.
30 Serum phosphate See blood phosphate.
31 SCOT An enzyme produced by the liver. Elevated levels of SCOT in the blood
32 indicate a liver problem.
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i Skeletal defects See Terata. Indicates skeletal malformation, may be a considered a
2 (see also) Gross Physical Abnormality.
3 Skin inflammation See Dermatitis.
4 Sleep disorders Disturbances of usual sleep patterns or behaviors.
5 Spasm of digital arteries A sudden but transitory constriction of the arteries of the
6 digits (e.g., one of the terminal divisions of a limb appendage, such as a finger or toe).
7 Squamous cell carcinoma See Carcinoma. Indicates effect is seen in the flat thin
8 cells found in the outer layer of the skin.
9 Stillbirth Delivery of a dead fetus. See also Abortion.
10 Stomach adhesions See Adhesions. Indicates effect is seen in the stomach.
11 Survival Living or continuing living. Decreased survival is increased mortality,
12 increased death rate.
13 Swelling of the eyes See Edema. Indicates effect is seen in or near the eyes.
14 T-cell A class of lymphocytes, so called because they are derived from the thymus
15 and have been through thymic processing. Involved primarily in controlling cell-
16 mediated immune reactions and in the control of B-cell development. The T-cells
17 coordinate the immune system by secreting lymphokine hormones.
is Terata Malformation in an embryo; birth defect.
19 Testicular degeneration or atrophy See Degeneration, Atrophy. Indicates effect is
20 seen in the testicles.
21 Thin and dilated coronary arteries See Thinning, Dilation. Indicates effect is seen in
22 coronary arteries.
23 Thinning Reduced thickness, as of vessel walls.
24 Thrombosis The formation, development or presence of a thrombus.
25 Tingling of hands and feet Detection of a feeling in extremities indicated.
26 Tonsilitis Inflammation of the tonsil.
27 Toxic nephrosis Toxicity or destruction observed in kidney cells. See also
28 Nephrotoxicity.
29 Tremors An involuntary trembling or quivering.
30 Trembling See Tremors.
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i Tubular degeneration See Degeneration. Indicates effect is seen in kidney tubules.
2 Ulcer A local defect or excavation, of the surface of an organ or tissue, which is
3 produced by the sloughing of inflammatory necrotic tissue.
4 Ulceration See Ulcer. The formation or development of an ulcer.
5 Ulcerative cecitis Inflammation of the cecum, a blind pouch-like commencement of
6 the colon in the right lower quadrant of the abdomen at the end of the small intestine.
7 The appendix is a diverticulum that extends off the cecum.
8 Urea The final nitrogenous excretion product of many organisms.
9 Vacuolization Formation into, or multiplication of, vacuoles.
10 Vacuolization of fasciculata cells in adrenal cortex See Vacuolization. Indicates
11 effect is seen on the fasciculata cells in adrenal cortex, the outer portion of the fatty
12 acids that inhibit inflammation in allergic responses.
13 Vacuolization of pancreas islet cells See Vacuolization. Indicates effect is seen on
14 the cells of the Islets of Langerhans (or islet cells) within the pancreas.
15 Vascular complications Complications pertaining to blood vessels or indicative of a
16 copious blood supply.
17 Vasculitis Inflammation of a vessel.
is Vesiculation The state of containing vesicles, or the process by which vesicles are
19 formed. A vesicle is a closed membrane shell, derived from membranes either by a
20 physiological process (budding) or mechanically by sonication.
21 Viability The quality or state of being viable; specifically, the capacity of living after
22 birth.
23 Vibration sensation Detection of a feeling of oscillation.
24 Vomiting See Emesis. See also Nausea, Dyspepsia.
25 Wart formation Formation of a benign tumor of basal cell of skin, the result of the
26 infection of a single cell with wart virus (Papilloma virus). Virus is undetectable in basal
27 layer, but proliferates in keratinizing cells of outer layers.
28 Weight gain Increase in body mass.
29 Weight loss Decrease in body mass.
30
31
32 Note: These definitions have been adapted from the following sources:
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i The On-line Medical Dictionary (c) Academic Medical Publishing & CancerWEB
2 1997-98. Available at
3 http://www.betterhealth.vic.gov.au/bhcv2/bhcsite.nsf/pages/bhc medicaldictionary?open
4 document. Accessed July-September 2001. Distributed by CancerWEB under license
5 from Academic Medical Publishing.
6
7 The New Lexicon: Webster's Dictionary of the English Language. 1989 edition.
8 Lexicon Publications, Inc., New York, NY.
9
10 ATSDR (Agency for Toxic Substances and Disease Registry). 2000a. Toxicological
11 Profile for Arsenic (Update). September.
12
13 E-Doc (Electronic Doctor) Index of Medical Terminology, (c) E-Doc 1998-99. Available
14 at http://www.edoc.co.za/.
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TABLE B-1
Primary Effects from Oral Exposures3
Chemical
Arsenic (inorganic)
(As)
Beryllium (Be)
Bromodichloro-
methane (BDCM)
Cadmium (Cd)
Carbon tetrachloride
(CCI4)
Chromium III
(insoluble salts) (Crlll)
Chromium VI
(Cr VI)
Dichloroacetic Acid
(DCA)
Mercury (based on
mercuric chloride) (Hg)
Primary
System/Organ
Affected
Skin, cardiovascular
system
Gastrointestinal
system
Kidney,
Developing fetus
Kidney
Liver
Liver, spleen
No observed effect
Reproductive
system, Developing
fetus, Liver, Brain
Kidney
Primary Noncancer Effect
Hyperpigmentation, keratosis,
possible vascular complications
Small intestinal lesions
Renal cytomegaly
Proteinuria
Lesions (mild centrilobular
vacuolization, increased serum
sorbitol dehydrogenase activity)
Decreased organ weights
No observed effect
Lesions in the testes, cerebrum,
cerebellum, liver
Autoimmune glomerulonephritis
Primary Effect
LOAEL
(mg/kg-day)
0.014
Not established
(benchmark dose is
0.46)b
17.9
Not established
(NOAEL is 0.005
[water], 0.01 [food])
7.1
Not established
(NOAEL is 1 ,468)
Not established
(NOAEL is 2.5)
12.5
0.317
Oral RfD
(mg/kg-day)
0.0003
0.002
0.02
0.0005 (water)
0.001 (food)
0.0007
1.5
0.003
0.004
0.0003
Oral RfD Combined
Uncertainty
Factor/Modifying
Factor
3
300
1,000
10
1,000
900
1,000
3,000
1,000
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TABLE B-1 cont.
Chemical
Nickel (soluble salts)
(Ni)
Nitrate (NO3)
Nitrite (NO2)
Polychlorinated
Biphenyls (PCBs)
(Arochlor1016)
Trichloroethylene3
(TCE)
Uranium (soluble
salts) (U)
Zinc (Zn)
Primary
System/Organ
Affected
Kidney, liver, spleen
Blood
Blood
Reproductive
system, Brain
Liver, kidney, and
developing fetus
Kidney
Blood
Primary Noncancer Effect
Decreased body and organ
weights
Methemoglobinemia
Methemoglobinemia
Reduced birth weights
Disruption of cellular processes
through multiple metabolites and
mechanisms in liver, kidney, fetus
Initial body weight loss, moderate
nephrotoxicity
47% decrease in erythocyte
superoxide dismutase
concentration (adult females after
10-week exposure)
Primary Effect
LOAEL
(mg/kg-day)
50
1.8-3.2
11-20 ppm
0.028
1.0
2.8
0.91
Oral RfD
(mg/kg-day)
0.02
1.6
0.1
0.00007
0.0003
0.003
0.3
Oral RfD Combined
Uncertainty
Factor/Modifying
Factor
300
1
10
100
3,000
1,000
3
2
o
J
4
5
6
7
a Source: U.S. EPA (2005c). The exception is the RfD fortrichloroethylene, taken from U.S. EPA (2001 c).
b The benchmark dose is a BMD10 value, i.e., the dose at the 95% confidence limit of the dose-response model corresponding to a 10% increase
in incidence of these effects compared with controls.
Acronyms and abbreviations are defined as follows: LOAEL = lowest-observed-adverse-effect level; mg/kg-day = milligram per kilogram body
weight per day; NOAEL = no-observed-adverse-effect level; RfD = reference dose.
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-34
-------
TABLE B-2
Primary Effects from Inhalation Exposures3
Chemical
Arsenic (inorganic)
Beryllium
Cadmium
Chromium III
(insoluble salts)
Chromium VI
(dissolved aerosols,
chromic acid mists)
Chromium VI
(particulates)
Copper
Mercury
Nickel (soluble salts)
Nitrate
Primary System/
Organ Affected
Not established
Lung
Not established
Not established
Respiratory system
Respiratory system
Not established
Central nervous
system
Not established
Not established
Primary Noncancer Effect
No observed effect
Beryllium sensitization,
progression to chronic
beryllium disease
No observed effect
No observed effect
Atrophy of the nasal
septum
Lactate dehydrogenase in
bronchoalveolar lavage
fluid, indicating
inflammation and injury
No observed effect
Hand tremor, increases in
memory disturbance
No observed effect
No observed effect
LOAEL for Primary Effect
(mg/m3)
Not established
0.0002
Not established
Not established
0.000714
Not established
(benchmark dose is
0.034)b
Not established
0.009
Not established
Not established
Inhalation RfC
(mg/m3)
Not established
0.00002
Not established
Not established
0.000008
0.0001
Not established
0.0003
Not established
Not established
Inhalation RfC
Combined
Uncertainty Factor/
Modifying Factor
Not established
10
Not established
Not established
90
300
Not established
30
Not established
Not established
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-35
-------
TABLE B-2 cont.
Chemical
Nitrite
Trichloroethylene3
Uranium (soluble
salts)
Zinc
Primary System/
Organ Affected
Not established
Central nervous
system, liver, and
endocrine system
Not established
Not established
Primary Noncancer Effect
No observed effect
Adverse effects on central
nervous system
No observed effect
No observed effect
LOAEL for Primary Effect
(mg/m3)
Not established
38
Not established
Not established
Inhalation RfC
(mg/m3)
Not established
0.04
Not established
Not established
Inhalation RfC
Combined
Uncertainty Factor/
Modifying Factor
Not established
1,000
Not established
Not established
2
3
4
5
6
7
a Source: U.S. EPA (2005c). The exception is the RfC fortrichloroethylene, taken from U.S. EPA (2001 c).
b The benchmark dose is a BMD10 value, i.e., the dose at the 95% confidence limit of the dose-response model corresponding to a 10% increase
in incidence of these effects compared with controls.
Acronyms and abbreviations are defined as follows: LOAEL = lowest-observed-adverse-effect level. In some cases this reflects an adjusted value
(e.g., for beryllium, the study LOAEL was adjusted to account for inhalation rate and days exposed); mg/m3 = milligram per cubic meter (air); RfC =
reference concentration.
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-36
-------
TABLE B-3
Comparison of Selected Secondary Effect Levels to Reference Doses for Oral Exposures3
Chemical
Arsenic
(inorganic)
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.0003
0.0004
0.0004
0.0008
0.025
0.8
Ratio
to RfD
1
1.3
1.3
2.7
83
2670
Study Basis
NOAEL of 0.0008 mg/kg-day;
LOAEL of 0.014 mg/kg-day;
human study; UF 3; MF 1
(inorganic)
Chronic drinking water study,
continuous exposure
(inorganic)
Chronic drinking water study;
continuous exposure
(pentavalent arsenic)
Chronic drinking water study
(test compound not reported)
Rat gavage study (7 months)
(arsenic solution)
Dog oral study (26 weeks)
(trivalent)
Organ/System Effect
Skin - hyperpigmentation, keratosis;
possible vascular complications
Skin - lesions; abnormal nerve
conduction
Skin - pigmentation changes,
hyperkeratosis; Gl system -
nausea, diarrhea
Skin - hyperpigmentation,
hyperkeratosis
No increased embryonic effects;
infrequent slight expansion of
ventricles of the cerebrum, renal
pelvis, urinary bladder
Liver - mild increase in serum
ALT/AST
Reference
U.S. EPA, 2005c
Cebrian etal., 1983
(cited in U.S. EPA,
2005c and ATSDR,
2000a)
Cebrian etal., 1983
(cited in ATSDR,
2000a)
Foyetal., 1992
(cited in ATSDR,
2000a)
Nadeenko et al.
1978 (cited in U.S.
EPA, 2005c and
ATSDR, 2000a)
Neigerand Osweiler,
1989 (cited in
ATSDR, 2000a)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-37
-------
TABLE B-3 cont.
Chemical
Beryllium
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.002
Not
reported
Not
reported
0.7
0.7
12
Ratio
to RfD
1
NA
NA
350
350
6,000
Study Basis
BMD10 of 0.46 mg/kg-day;
dog oral study; in food;
UF 300; MF 1 (sulfate
tetrahydrate)
NA
NA
Rat oral study; in water
(3 years) (sulfate)
Rat oral study; drinking water
(91 days) (sulfate)
Dog oral study; in food
(172 weeks) (sulfate)
Organ/System Effect
Multiple target organs; small
intestinal lesions.
NA
NA
Various organ systems (e.g.,
cardiovascular, endocrine, hepatic,
renal, respiratory)
Whole body - no effects
Gl system - ulcerative, inflammatory
lesions; hematopoetic system -
erythroid
hypoplasia of bone marrow;
whole body - weight loss, increased
mortality
Reference
U.S. EPA, 2005c
NA
NA
Schroederand
Mitchener, 1975
(cited in ATSDR,
2002c)
Freundt and Ibrahim,
1990 (cited in
ATSDR, 2002c)
Morgareidge et al.,
1976 (cited in
ATSDR, 2002c)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-38
-------
TABLE B-3 cont.
Chemical
Cadmium
Cadmium
Type of
Level
RfD-
water
RfD-
food
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.0005
0.001
0.0021
0.0078
0.0081
0.001
Ratio
toRfD
1
1
2.1
7.8
16
2
Study Basis
NOAEL of 0.005 mg/kg-day
(water); human study; UF 10;
MF1
NOAEL of 0.01 mg/kg-day
(food); human study; UF 10;
MF1
Chronic lifetime exposure in
food (test compound not
reported)
Chronic oral study (25 years)
(inorganic)
Rat chronic oral study
(5 months);
in water (chloride)
Rat chronic oral study
(18 months);
in water (acetate)
Organ/System Effect
Kidney - proteinuria (note:
supporting data have been derived
from many animal and human
studies, renal effects, proteinuria,
and calcium pharmacokinetic
parameters)
Kidney - proteinuria (note:
supporting data have been derived
from many animal and human
studies, renal effects, proteinuria,
and calcium pharmacokinetic
parameters)
Kidney- no effects
Kidney - renal tubule interstitial
lesions
Whole body - no effects
Cardiovascular system-
hypertension;
increase in systolic blood pressure
Reference
Data from U.S. EPA,
2005d (effect type
note from RAIS,
1991)
Data from U.S. EPA,
2005c (effect type
note from RAIS,
1991)
Nogawaetal., 1989
(cited in ATSDR,
1 999b)
Shiwen etal., 1990
(cited in ATSDR,
1 999b)
Perry etal., 1989
(cited in ATSDR,
1 999b)
Koppetal., 1982
(cited in ATSDR,
1 999b)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-39
-------
TABLE B-3 cont.
Chemical
Carbon
tetrachloride
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.0007
Not
reported
Not
reported
1.0
10
Ratio
to RfD
1
NA
NA
1,430
14,300
Study Basis
NOAEL of 0.71 mg/kg-day;
LOAEL of 7.1 mg/kg-day; rat
gavage study (12 weeks);
UF 1,000; MF1
NA
NA
Rat gavage study (12 weeks)
Rat gavage study (12 weeks)
Organ/System Effect
Liver- lesions (mild centrilobular
vacuolization and increases in
serum sorbitol
dehydrogenase activity)
NA
NA
Liver- substantially elevated sorbitol
dehydrogenase; mild centrilobular
vacuolization
Liver- substantially elevated sorbitol
dehydrogenase; mild centrilobular
vacuolization
Reference
U.S. EPA, 2005c
NA
NA
Bruckner et al., 1986
(cited in ATSDR,
2003a)
Bruckner et al., 1986
(cited in ATSDR,
2003a)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-40
-------
TABLE B-3 cont.
Chemical
Chromium III
(insoluble
salts)
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
1.5
Not
reported
Not
reported
0.46
5.0
Ratio
to RfD
1
NA
NA
0.31
3.3
Study Basis
NOAEL of 1 ,468 mg/kg-day;
rat chronic oral study;
UF100; MF 10 (chronic
oxide)
NA
NA
Rat chronic drinking water
study
(2-3 years) (trivalent)
Mouse drinking water study
(12 weeks) (trivalent)
Organ/System Effect
Liver and spleen - decreased organ
weights
NA
NA
Cardiovascular system, liver,
kidney, whole body - no effects
Reproductive system - increased
testes, decreased preputial gland
weights; decreased number of
implantations and viable fetuses;
increased ovarian, decreased
uterine weights; whole body -
decrease in body weight gain
Reference
U.S. EPA, 2005c
NA
NA
Schroederet al.,
1965 (cited in
ATSDR, 2000b)
Elbetieha and
AI-Hamood, 1997
(cited in ATSDR,
2000b)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-41
-------
TABLE B-3 cont.
Chemical
Chromium VI
Chromium VI
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.003
Not
reported
0.57
1.1
3.5
Ratio
to RfD
1
NA
190
367
1170
Study Basis
NOAEL of 2.5 mg/kg-day; rat
chronic drinking water study
(1 year); UF 300; MF 3
(potassium chromate)
NA
Unspecified environmental
exposure (hexavalent)
Mouse oral study, in food
(9 weeks) (hexavalent)
Mouse oral study, in food
(9 weeks) (hexavalent)
Organ/System Effect
No effects
NA
Gl system - oral ulcers, diarrhea,
vomiting abdominal pain;
hematopoetic system -
leukocytosis, immature neutrophils
Liver - cytoplasmic vacuolization of
hepatocytes
Liver - cytoplasmic vacuolization of
hepatocytes
Reference
U.S. EPA, 2005c
NA
Zhang and Li, 1987
(cited in ATSDR,
2000b)
NTP, 1996 (cited in
ATSDR, 2000b)
NTP, 1996 (cited in
ATSDR, 2000b)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-42
-------
TABLE B-3 cont.
Chemical
Mercury
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.0003
0.0005
0.0012
0.05
0.05
Ratio
to RfD
1
1.67
4
167
167
Study Basis
LOAEL of 0.317 mg/kg-day;
rat study; UF 1,000; MF 1
(mercuric chloride)
Oral study (methylmercury)
Oral study, food
(methylmercuric chloride)
Rat oral study, food (52 days)
(methylmercuric chloride)
Monkey oral study, water
(328-907 days)
(methylmercury hydroxide)
Organ/System Effect
Kidney- autoimmune
glomerulonephritis; assumes the
oral absorption of divalent mercury
is 7% and absorption from
subcutaneous exposure is 100%
Developmental - no effects
Developmental -
delayed walking, abnormal motor
scores
Developmental - increased
incidence of eye defects in fetuses
Developmental - impaired visual
recognition memory in offspring
Reference
U.S. EPA, 2005c
Myers etal., 1997
(cited in ATSDR,
1999c)
Cox etal., 1989
(cited in ATSDR,
1999c)
Khera and
Tabacova, 1973
(cited in ATSDR,
1999c)
Gunderson et al.,
1 988 (cited in
ATSDR, 1999c)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-43
-------
TABLE B-3 cont.
Chemical
Nickel
(soluble
salts)
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.02
0.02
Not
reported
0.97
0.23
Ratio
to RfD
1
1
NA
48
12
Study Basis
NOAEL of 5 mg/kg-day;
LOAEL of 50 mg/kg-day; rat
study;
in food; UF 300; MF 1
Oral study; water (178 days)
(sulfate)
NA
Rat oral study; water (28
days) (chloride)
Rat oral study; water (28
days) (chloride)
Organ/System Effect
Multiple target organs;
changes in body and organ weights
Dermal - no effects
NA
Hematopoetic system - no effects;
liver - no effects
Whole body - decreased body
weight gain;
metabolic system effects
Reference
U.S. EPA, 2005c
Santucci etal., 1994
(cited in ATSDR,
2003b)
NA
Weischeretal., 1980
(cited in ATSDR,
2003b)
Weischeretal., 1980
(cited in ATSDR,
2003b)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-44
-------
TABLE B-3 cont.
Chemical
Nitrate
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
1.6
3.7
3.2
20
60
Ratio
to RfD
1
2.3
2
12
38
Study Basis
NOAEL of 1 .6 mg/kg-day;
human study; LOAEL of 1 .8-
3.2 mg/kg-day; (infants,
drinking water in formula);
UF1; MF1
Oral study, 1- to 6-month-old
infants; nitrate in formula
Oral study, 8-day to 5-month-
old infants; nitrate in formula
Oral rat drinking water study
(2 years) (sodium nitrite)
Rat oral study, drinking water
(2 years) (sodium nitrite)
Organ/System Effect
Hematopoetic system -
methemoglobinemia
Hematopoetic system -
no methemoglobinemia clinical
signs
Hematopoetic system -
cyanosis, methemoglobinemia
Respiratory system -
dilated bronchi, fibrosis,
emphysema
Lung - dilated bronchi, fibrosis and
emphysema,
Circulatory/cardiovascular system -
fibrosis, degenerative foci
Reference
U.S. EPA, 2005c
Simon etal., 1964
(cited in U.S. EPA,
2005c)
Bosch etal., 1950
(cited in U.S. EPA,
2005c)
Shuval and Gruener,
1972 (cited in
U.S. EPA, 2005c)
Shuval and Gruener,
1972 (cited in RAIS,
1995)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-45
-------
TABLE B-3 cont.
Chemical
Nitrite
Trichloro-
ethylene
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.1
1.0
Not
reported
0.0003
Not
reported
Not
reported
18
0.18
Ratio
to RfD
1
10
NA
1
NA
NA
60,000
600
Study Basis
NOEL of 1 .0 mg/kg-day;
LOAEL of 1.1-2.0 mg/kg-day;
human study;
UF1; MF 10 (from nitrate)
Oral study, infants, nitrate in
formula
NA
LOAEL of 1 .0 mg/kg-day;
subchronic mice and rats
studies (liver effects);
UF 3000
NA
NA
Mouse drinking water study
(6 months)
Rat drinking water study,
gestational (3 months)
Organ/System Effect
Hematopoetic system -
methemoglobinemia
Hematopoetic system -
methemoglobinemia above 10%
NA
Various effects - liver; kidney;
developing fetus
NA
NA
Gl - gas pockets in the intestinal
coating;
blood in the intestines
Developmental -
increased fetal heart abnormalities
Reference
U.S. EPA, 2005c
Walton, 1951 (cited
in U.S. EPA, 2005c)
NA
U.S. EPA, 2001 c
NA
NA
Tucker etal., 1982
(cited in ATSDR,
1997c)
Dawson etal., 1993
(cited in ATSDR,
1997c)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-46
-------
TABLE B-3 cont.
Chemical
Uranium
(soluble
salts)
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.003
Not
reported
Not
reported
0.06
0.05
Ratio
to RfD
1
NA
NA
20
17
Study Basis
LOAEL of 2.8 mg/kg-day,
rabbit dietary study;
UF 1,000; MF1 (30 days)
(uranyl nitrate hexahydrate;
soluble salt)
NA
NA
Rat drinking water study
(91 days) (uranyl nitrate
hexahydrate)
Rabbit drinking water study
(91 days) (uranyl nitrate
hexahydrate)
Organ/System Effect
Kidney - moderate nephrotoxicity;
whole body - initial body weight loss
NA
NA
Endocrine system - multi-focal
reduction of follicularsize; increased
epithelial height in thyroid;
decreased amount and density of
colloid in males only
Kidney - anisokaryosis, nuclear
vesiculation
Reference
U.S. EPA, 2005c
NA
NA
Oilman etal., 1998a
(cited in ATSDR,
1 999d)
Oilman etal., 1998b
(cited in ATSDR,
1 999d)
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-47
-------
TABLE B-3 cont.
Chemical
Zinc
Type of
Level
RfD
Lowest
human
NOAEL
Lowest
human
LOAEL
Lowest
human
LOAEL
Lowest
animal
NOAEL
Lowest
animal
LOAEL
Value
(mg/kg-
day)
0.3
0.06
0.71
0.71
3.5
0.5
Ratio
to RfD
1
0.2
2.4
2.4
12
1.7
Study Basis
LOAEL of 1 .0 mg/kg-day;
human dietary supplement
study; UF 3; MF 1
Dietary supplement study
(1 1 weeks) (aspartate)
Dietary supplement study
(12 weeks) (gluconate)
Dietary supplement study
(6 weeks) (gluconate)
Rat gavage study; in water
(20 months) (chloride)
Mouse oral study, in water
(60 days) (acetate)
Organ/System Effect
Hematopoetic system -
47% decreased ESOD concentration
(in adult females after 10-week
exposure)
Developmental - no effects
Liver- decreased serum
HDL-cholesterolb
Hematopoetic system -
decreased ESOD activity
Reproductive effects -
decreased live pups per litter
Nervous system -
increase in latency in inhibitory
avoidance test
Reference
Yadricketal., 1989
(cited in U.S. EPA,
2005c)
Kynast and Saling,
1 986 (cited in
ATSDR, 2003c)
Black etal., 1988
(cited in ATSDR,
2003c)
Fischer etal., 1984
(cited in ATSDR,
2003c)
Khan etal. ,2001
(cited in ATSDR,
2003c)
De Oliveira et al.,
2001 (cited in
ATSDR, 2003c)
1 This table presents information for 15 chemicals selected for study at a contaminated site. The form of the chemical or compound used in the
2 toxicity study that served as the basis for the indicated level is given in parentheses; where not listed here, the chemical itself was identified as the
3 test chemical. Selected acronyms are defined as follows; others (e.g., agency acronyms) are included in the notation at the front of this report.
4 ALT/AST = alanine aminotransferase/aspartate aminotransferase; BMD10 = benchmark dose, at the 95% confidence limit of the dose-response
5 model corresponding to a 10% increase in incidence of the effect compared with the control; ESOD = erythocyte superoxide dismutase; Gl =
6 gastrointestinal system; HDL = high-density lipid; LOAEL = lowest-observed-adverse-effect level; MF = modifying factor; mg/kg-day = milligram per
7 kilogram per day; NA = not available/not applicable; NOAEL = no observed adverse effect level; RfD = reference dose; UF = uncertainty factor.
8 b Low levels of low-density lipoprotein (LDL) cholesterol put a person at a high risk of heart disease. Taken from The American Heart Association
9 "What are Healthy Levels of Cholesterol?" See http://www.americanheart.org/presenter.ihtml?identifier=183.
Review Draft: Do Not Cite or Quote
Does Not Constitute EPA Policy
B-48
------- |