Ecological Risk Assessment - Part 1 pdf

Second Edition

Ecological
Risk Assessment

ß 2006 by Taylor & Francis Group, LLC.


ß 2006 by Taylor & Francis Group, LLC.


Second Edition

Ecological
Risk Assessment
Editor and Principal Author

Glenn W. Suter II
Contributing Authors
Lawrence W. Barnthouse
Steven M. Bartell
Susan M. Cormier
Donald Mackay
Neil Mackay
Susan B. Norton

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Library of Congress Cataloging-in-Publication Data
Ecological risk assessment / edited by Glenn W. Suter II. -- 2nd ed.
p. cm.
Includes bibliographical references and index.
ISBN 1-56670-634-3

1. Ecological risk assessment. I. Suter, Glenn W.
QH541.15.R57E25 2006
333.95’14--dc22
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2006049394


Dedication
To my parents,
Glenn W. Suter and Kathleen T. Suter
We are products of our heredity and environment,
and parents provide all of one and most of the other.

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ß 2006 by Taylor & Francis Group, LLC.


Preface to the Second Edition
The primary purpose of preparing this edition is to provide an update. In the 14 years since
the first edition was published, ecological risk assessment has gone from being a marginal
activity to being a relatively mature practice. There are now standard frameworks and
guidance documents in the United States and several other countries. Ecological risk assessment is applied to the regulation of chemicals, the remediation of contaminated sites, the

importation of exotic organisms, the management of watersheds, and other environmental
management problems. Courses in ecological risk assessment have been taught at several
universities. As a result, there is a much larger literature to draw on, including many case
studies. This is reflected both in the citation of ecological risk assessments published in the
open literature and in the use of more figures drawn from real assessments. Hence, the reader
will notice a greater diversity in the graphical style, resulting from the many sources from
which figures have been drawn so as to give a flavor of the diverse practice of ecological risk
assessment.
The second edition also provides an opportunity for a new organization of the material
that is more logically consistent. In particular, whereas the first edition had separate chapters
for types of ecological risk assessments (i.e., predictive, retrospective, regional, surveillance,
and exotic organisms), this edition presents a unitary process of ecological risk assessment
that is applicable to various problems, scales, and mandates. All risk assessments are about
the future consequences of decisions. Those that were described in the first edition as
retrospective, following EPA terminology, are simply risk assessments that must begin with
an analysis of the current consequences of past actions in order to predict future consequences
(Chapter 1).
Since 1992, ecological risk assessment has become sufficiently important to acquire critics
and opponents. Some criticisms deal with aspects of the technical practice. Ecological
risk assessment is often criticized for being based on inadequate data and models, for not
addressing large-scale spatial dynamics, and for using conservatism to compensate for those
inadequacies (DeMott et al. 2004; Landis 2005; Tannenbaum 2005a). Other critics are
opposed to ecological risk assessment per se (Pagel and O’Brien 1996; Lackey 1997;
O’Brien 2000; Bella 2002). These criticisms arise from a misperception of the nature and
purpose of risk assessment. In particular, risk assessment is technical support for decision
making under uncertainty, but the critics hold risk assessment responsible for the
decision itself. If decision makers listen to fishermen, loggers, chemical manufacturers, or
utility companies more than to environmental advocates, critics say it is the fault of risk
assessment. If risk assessments are limited by regulatory context to considering only one
alternative, they say that also is the fault of risk assessment. If decisions are based on

balancing of costs and benefits, it is again the fault of risk assessment. If the best available
science does not address all of the important complexities of the system, they say that risk
assessors who use that science are to blame. Similarly, risk assessors are blamed when holistic
properties, endocrine disruptors, regional properties, or other favorite concerns are not
addressed. Some of this criticism arises from an opposition to technology, science, and even
rationality, but more generally it is based on anger that the environment is not being
adequately protected. One partial solution is to avoid the phrase ‘‘risk-based decision making.’’ Environmental decisions are, at best, ‘‘risk-informed.’’ They are based on risk information plus economic considerations, technical feasibility, public pressures, political pressures,

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and the personal biases of the decision makers. Another partial solution is to be fastidious in
quantifying, or at least describing, uncertainties and limitations of our assessments.
Some things have not changed since the first edition. The emphasis is still on providing
clear, scientifically sound, and unbiased technical advice to environmental decision makers.
Although other examples are included in this edition, the focus is still on risks from chemicals
or chemical mixtures, indicating that most ecological risk assessments are concerned with
these issues.
The text is still aimed at practitioners and advanced students with at least a basic knowledge of biology, chemistry, mathematics, and statistics. It does not assume any familiarity
with ecological risk assessment or risk assessment in general. A glossary is provided, because
terms from risk assessment, ecology, toxicology, and other disciplines are used.
As with the first edition, I have written most of the book myself in order to provide a
common voice and a common vision of the topic. This is a service to the reader as well as an
opportunity for me to share my particular vision of what ecological risk assessment is and
what it could be. However, for some major topics, the readers would be ill-served by my
meager expertise. Fortunately, Larry Barnthouse, Steve Bartell, and Don Mackay agreed to
participate in this edition as they did in the first. I believe they are the preeminent experts in
the application of population modeling, ecosystem modeling, and chemical transport and fate
modeling, for the assessment of ecotoxicological effects. Fortunately, they have similar
pragmatic approaches to mine.

The preface to the first edition described it as a manifesto. The program of that manifesto
was that ecological assessors must become more rigorous in their methods and practices in
order to be taken as seriously as human health and engineering risk assessors. That program
is no longer needed. Ecological risk assessments are at least as rigorous as human
health assessments and in some ways, particularly in the use of probabilistic analysis,
ecological assessments are more advanced. As a result, ecological risks are more often the
basis for environmental regulatory and management decisions. However, ecologically driven
decisions are still far less common than health-driven decisions. To a certain extent, this is
inevitable, because humans are making the decisions based on the concerns of other humans,
the public. However, we can make progress in protecting the nonhuman environment by
greater integration of ecological risk assessment with concerns for human health and welfare.
Hence, the greatest challenge in the coming years is to estimate and communicate ecological
risks in a way that makes people care.
Glenn Suter
Cincinnati, Ohio

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Acknowledgments
I gratefully acknowledge the innumerable environmental scientists who contributed to this
text. Those who are cited are thereby acknowledged, although you are probably not cited as
much as you deserve. Many of you who are not cited at all deserve citation but must settle for
this apologetic acknowledgment. I have heard your talks at meetings, exchanged ideas at your
posters or in the halls, and even read your papers, but have forgotten that you were the source
of those ideas. Even more sadly, many of you have done important work and produced
important ideas that should appear in this text but do not, because I am unaware of them.
There are forlorn piles of books, reports, and reprints on the table behind my back as I write
this that I really wanted to read before completing this book, but could not. So, if you feel
that I have not given your work the attention it deserves, you are probably right.

Parts of this book draw upon material in Ecological Risk Assessment for Contaminated
Sites. Thanks to Rebecca Efroymson, Brad Sample, and Dan Jones who were coauthors of
that book.
My 7 years with the US Environmental Protection Agency have improved this book by
giving me a deeper understanding of the role of risk assessment in environmental regulation.
Thanks to all of my agency colleagues. Particular thanks to Susan Cormier and Susan Norton
who have been wonderful friends, inspiring collaborators, and guardians against sloppy
thinking.
Finally, deep thanks to Linda who, after decades of marriage, has learned to tolerate my
long hours in my study and even helped with the final rush to submit the manuscript.

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ß 2006 by Taylor & Francis Group, LLC.


Authors
Glenn W. Suter II is science advisor in the US
Environmental Protection Agency’s National
Center for Environmental Assessment, Cincinnati, and was formerly a senior research staff
member in the Environmental Sciences Division, Oak Ridge National Laboratory, United
States. He has a PhD in ecology from the
University of California, Davis, and 30 years
of professional experience including 25 years in
ecological risk assessment. He is the principal
author of two texts in the field of ecological risk
assessment, editor of two other books, and
author of more than 100 open literature publications. He is associate editor for ecological
risk of Human and Ecological Risk Assessment,

and reviews editor for the Society for Environmental Toxicology and Chemistry (SETAC).
He has served on the International Institute
of Applied Systems Analysis Task Force on
Risk and Policy Analysis, the Board of Directors of SETAC, an expert panel for the
Council on Environmental Quality, and the editorial boards of Environmental Toxicology
and Chemistry, Environmental Health Perspectives, and Ecological Indicators. He is
the recipient of numerous awards and honors; most notably, he is an elected fellow of
the American Association for the Advancement of Science and he received SETAC’s
Global Founder’s Award, its highest award for career achievement, and the EPA’s Level 1
Scientific and Technical AchievementAward.
His research experience includes development
and application of methods for ecological risk
assessment and ecological epidemiology, development of soil microcosm and fish toxicity
tests, and environmental monitoring. His
workis currently focused on the development
of methods for determining the causes of
biological impairments.
Susan M. Cormier is a senior science advisor in
the U.S. Environmental Protection Agency’s
National Risk Management Research Laboratory. Dr. Cormier received her BA in Zoology
from the University of New Hampshire, her
MA in biology from the University of South
Florida, and her PhD in Biology from Clark
University.

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Donald Mackay (BSc, PhD (Glasgow)) is
director of the Canadian Environmental

Modelling Centre at Trent University, Peterborough, Ontario, Canada. He graduated in chemical engineering from the university of Glasgow.
After working in the petrochemical industry he
joined the University of Toronto, where he is
now Professor Emeritus in the Department of
Chemical Engineering and Applied Chemistry.
He has been director of the Canadian Environmental Modelling Centre of Trent University
Ontario since 1995. His primary research interest is the development, application, validation,
and dissemination of mass-balance models describing the fate of chemicals in the environment
in general, and in a variety of specific environments. These models include descriptions of
bioaccumulation in a variety of organisms,
water-quality models of contaminant fate in lakes, rivers, sewage-treatment plants, and in
soils and vegetation. He has developed a series of multimedia mass-balance models employing
the fugacity concept that are widely used for assessment of chemical fate in national regions in
the global environment. A particular interest is the
transport of persistent organic chemicals to cold
climates such as the Canadian Arctic and their
accumulation and migration in arctic ecosystems.
Susan B. Norton is a senior ecologist in the U.S.
Environmental Protection Agency’s National
Center for Environmental Assessment. Since
joining EPA in 1988, Dr. Norton has developed
methods and guidance to better use ecological
knowledge to inform environmental decisions.
She was an author of many agency guidance
documents including the 2000 Stressor Identification Guidance document, the 1998 Guidelines
for Ecological Risk Assessment, the 1993 Wildlife Exposure Factors Handbook, and the 1992
Framework for Ecological Risk Assessment. She
has published numerous articles on ecological
assessment and edited the book Ecological Assessment of Aquatic Resources: Linking Science to Decision-Making. She is currently enthusiastic about making methods and information for causal analysis more available via the World
Wide Web at www.epa.gov=caddis. Dr. Norton received her BS in plant science from Penn

State, her MS in natural resources from Cornell University, and her PhD in environmental
biology from George Mason University.
Neil Mackay (BSc (Waterloo), DPhil (York)) is a senior research scientist for environmental
modelling with DuPont (UK) Limited. As a member of the DuPont Crop Protection Global
Modelling Team he is active in strategic development and regulatory exposure and risk
assessment activities. Previous work experience includes employment as a consultant to

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both industry and government bodies, primarily
in Europe. He was a participant in the European
Commission Health and Consumer Protection
Directorate General and the FOCUS Risk Assessment Working Group and is a member of
the UK government expert advisory panel
on veterinary medicines. Particular interests include aquatic risk assessment and use of spatial
tools (GIS and remote sensing methods) to
evaluate risks at various scales (field, catchment
and regional scales) and assessment of long
range transport potential for persistent organic
pollutants (POPs).
Lawrence W. Barnthouse is the president of
LWB Environmental Services, Inc. and adjunct
associate professor of zoology at Miami University. He was formerly a senior research staff
member and group leader in the Environmental
Sciences Division at Oak Ridge National
Laboratory. In 1981 he became co-principal
investigator (with Glenn Suter) on EPA’s first
research project on ecological risk assessment.
Since that time, he has been active in the development and application of ecological risk

assessment methods for EPA, other federal
agencies, state agencies, and private industry.
He has chaired workshops on ecological risk
assessment for the National Academy of Sciences and the Society of Environmental Toxicology and Chemistry, and served on the peer
review panels for the EPA’s Framework for
Ecological Risk Assessment and the Guidelines
for Ecological Risk Assessment. He continues
to support the development of improved
methods for ecological risk assessment as the
Hazard=Risk Assessment Editor of Environmental Toxicology and Chemistry and a Founding
Editorial Board Member of Integrated Environmental Assessment and Management.
Steven M. Bartell is a principal with E2 Consulting Engineers, Inc. He is also an adjunct
faculty member in the Department of Ecology and Evolutionary Biology at the University
of Tennessee, Knoxville. His education includes a PhD in oceanography and limnology
(University of Wisconsin 1978), an MS in botany (University of Wisconsin 1973), and a BA
in biology (Lawrence University 1971). Dr. Bartell’s areas of expertise include systems
ecology, ecological modeling, ecological risk analysis, risk-based decision analysis, vulnerability analysis, numerical sensitivity and uncertainty analysis, environmental chemistry, and
environmental toxicology. He works with a variety of public and private sector clients
in diverse projects in ecological risk assessment, environmental analysis, and more recently

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in ecological planning and restoration in the context of adaptive environmental management and
ecological sustainability. Bartell
has authored more than 100 peerreviewed publications. He is a senior contributing author on several
books including Ecological Modeling in Risk Assessment (2001),
Ecological Risk Assessment Decision-Support System: A Conceptual
Design (1998), Risk Assessment and
Management Handbook for Environmental, Health, and Safety Professionals (1996), and Ecological

Risk Estimation (1992). He currently serves on the editorial boards
of Aquatic Toxicology and Chemosphere having served previously on the editorial boards of Human and Ecological Risk
Assessment and Ecological Applications. Bartell served for 11 years on the USEPA Science
Advisory Board, mainly on the Environmental Processes and Effects Committee and review
committees.

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Contributors
Lawrence W. Barnthouse
LWB Environmental Services, Inc.
Hamilton, Ohio

Neil Mackay
Cambridge Environmental Associates
Cambridge, United Kingdom

Steven M. Bartell
E2 Consulting Engineers, Inc.
Maryville, Tennessee

Susan B. Norton
US Environmental Protection Agency
Washington, DC

Susan M. Cormier
US Environmental Protection Agency
Cincinnatti, Ohio

Glenn W. Suter II
US Environmental Protection Agency
Cincinnati, Ohio

Donald Mackay
Canadian Environmental Modelling Centre
Trent University
Petersborough, Ontario, Canada

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ß 2006 by Taylor & Francis Group, LLC.


Table of Contents
Part I

Introduction to Ecological Risk Assessment

Chapter 1 Defining the Field
1.1
Predictive vs. Retrospective Risk Assessment
1.2
Risks, Benefits, and Costs
1.3
Decisions to Be Supported
1.3.1 Prioritization of Hazards
1.3.2 Comparison of Alternative Actions
1.3.3 Permitting Releases

1.3.3.1 Chemicals
1.3.3.2 Effluents and Wastes
1.3.3.3 New Organisms
1.3.3.4 Items in International Trade
1.3.4 Limiting Loading
1.3.5 Remediation and Restoration
1.3.6 Permitting and Managing Land Uses
1.3.7 Species Management
1.3.8 Setting Damages
1.4
Sociopolitical Purposes of Risk Assessment
1.5
Cast of Characters
1.5.1 Assessors
1.5.2 Risk Managers
1.5.3 Stakeholders
Chapter 2 Other Types of Assessments
2.1
Monitoring Status and Trends
2.2
Setting Standards
2.3
Life Cycle Assessment
2.4
Prohibitions
2.5
Technology-Based Rules
2.6
Best Practices, Rules, or Guidance
2.7

Precautionary Principle
2.8
Adaptive Management
2.9
Analogy
2.10 Ecosystem Management
2.11 Health Risk Assessment
2.12 Environmental Impact Assessment
2.13 Summary
Chapter 3 Ecological Risk Assessment Frameworks
3.1 Basic US EPA Framework
3.2 Alternative Frameworks
3.2.1 WHO-Integrated Framework
3.2.2 Multiple Activities

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3.3
3.4

3.5
3.6

3.2.3 Ecological Epidemiology
3.2.4 Causal Chain Framework
Extended Frameworks
Iterative Assessment
3.4.1 Screening vs. Definitive Assessments
3.4.2 Baseline vs. Alternatives Assessments

3.4.3 Iterative Assessment as Adaptive Management
Problem-Specific Frameworks
Conclusions

Chapter 4 Ecological Epidemiology and Causal Analysis
4.1 Biological Surveys
4.2 Biological Assessment
4.3 Causal Analysis
4.3.1 Identifying Candidate Causes
4.3.1.1 What is a Cause?
4.3.1.2 Developing the List
4.3.1.3 Developing Maps and Conceptual Models
4.3.2 Analyzing the Evidence
4.3.2.1 Evidence of Co-occurrence
4.3.2.2 Evidence of Sufficiency
4.3.2.3 Evidence of Temporality
4.3.2.4 Evidence from Manipulation
4.3.2.5 Evidence of Coherence
4.3.3 Characterizing Causes
4.3.3.1 Elimination
4.3.3.2 Diagnostic Protocols and Keys
4.3.3.3 Koch’s Postulates
4.3.3.4 Strength-of-Evidence Analysis
4.3.4 Iteration of Causal Analysis
4.4 Identifying Sources and Management Alternatives
4.5 Risk Assessment in Ecoepidemiology
4.6 Summary
Chapter 5 Variability, Uncertainty, and Probability
5.1 Sources of Unpredictability
5.1.1 Variability

5.1.2 Uncertainty
5.1.3 Variability Uncertainty Dichotomy
5.1.4 Combined Variability and Uncertainty
5.1.5 Error
5.1.6 Ignorance and Confusion
5.1.7 Summary of Sources
5.2 What is Probability?
5.2.1 Types of Probability: Frequency vs. Belief
5.2.1.1 Frequency
5.2.1.2 Belief
5.2.2 Types of Probability: Categorical vs. Conditional

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5.3

5.4

5.5

5.6

5.7
5.8

Ways to Analyze Probabilities
5.3.1 Frequentist Statistics
5.3.2 Bayesian Statistics
5.3.3 Resampling Statistics

5.3.4 Other Approaches
Why Use Probabilistic Analyses?
5.4.1 Desire to Ensure Safety
5.4.2 Desire to Avoid Excessive Conservatism
5.4.3 Desire to Acknowledge and Present Uncertainty
5.4.4 Need to Estimate a Probabilistic Endpoint
5.4.5 Planning Sampling and Testing
5.4.6 Comparing Hypotheses and Associated Models
5.4.7 Aiding Decision Making
5.4.8 Summary of Reasons
Techniques for Analysis of Variability and Uncertainty
5.5.1 Uncertainty Factors
5.5.2 Confidence Intervals
5.5.3 Data Distributions
5.5.4 Statistical Modeling
5.5.5 Monte Carlo Analysis and Uncertainty Propagation
5.5.6 Nested Monte Carlo Analysis
5.5.7 Sensitivity Analysis
5.5.8 Listing and Qualitative Evaluation
Probability in the Risk Assessment Process
5.6.1 Defining Exposure Distributions
5.6.2 Defining Effects Distributions
5.6.3 Estimating Risk Distributions
Parameters to Treat as Uncertain
Summary

Chapter 6 Dimensions, Scales, and Levels of Organization
6.1 Levels of Organization
6.2 Spatial and Temporal Scales
6.3 Regional Scale

6.4 Dimensions
6.4.1 Abundance or Intensity of the Agent
6.4.2 Temporal Duration
6.4.3 Space
6.4.4 Proportion Affected
6.4.5 Severity of the Effects
6.4.6 Type of Effect
6.4.7 What to do with Multiple Dimensions?
Chapter 7 Modes and Mechanisms of Action
7.1 Chemical Modes and Mechanisms
7.2 Testing for Mechanisms
7.3 Nonchemical Modes and Mechanisms
Chapter 8 Mixed and Multiple Agents
8.1 Chemical Mixtures

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8.1.1
8.1.2

8.2

Methods Based on Whole Mixtures
Methods Based on Tests of Components
8.1.2.1 Simple Similar Action and Concentration Addition
8.1.2.2 Independent Action and Response Addition
8.1.2.3 Interactive Action
8.1.2.4 Multiple Chemicals and Multiple Species
8.1.3 Integration of Complex Chemical Mixtures

Multiple and Diverse Agents
8.2.1 Categorize and Combine Agents
8.2.2 Determine Spatial and Temporal Overlap
8.2.3 Define Effects and Mode of Action
8.2.4 Screen Effects
8.2.5 Simple Additive Effects
8.2.6 Additive Exposures
8.2.7 Mechanistic Models of Combined Effects
8.2.8 Integration of Complex Sets of Agents and Activities

Chapter 9 Quality Assurance
9.1 Data Quality
9.1.1 Primary Data
9.1.2 Secondary Data
9.1.3 Defaults and Assumptions
9.1.4 Representing Data Quality
9.1.5 Data Management
9.2 Model Quality
9.3 Quality of Probabilistic Analyses
9.4 Assessment Quality
9.4.1 Process Quality
9.4.2 Peer Review of the Assessment
9.4.3 Replication of Assessments
9.5 Summary
Part II

Planning and Problem Formulation

Chapter 10

Impetus and Mandate

Chapter 11

Goals and Objectives

Chapter 12

Management Options

Chapter 13 Agents and Sources
13.1 Emissions
13.2 Activities and Programs
13.3 Sources of Causes
13.4 Properties of the Agent
13.5 Sources of Indirect Exposure and Effects
13.6 Screening Sources and Agents

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Chapter 14

Environmental Description

Chapter 15

Exposure Scenarios

Chapter 16 Assessment Endpoints

16.1
Assessment Endpoints and Levels of Organization
16.2
Generic Assessment Endpoints
16.2.1 Generic Endpoints Based on Policy Judgments
16.2.2 Functionally Defined Generic Endpoints
16.2.3 Applying Generic Endpoints
16.3
Making Generic Assessment Endpoints Specific
16.4
Endpoints Based on Objectives Hierarchies
Chapter 17 Conceptual Models
17.1
Uses of Conceptual Models
17.2
Forms of Conceptual Models
17.3
Creating Conceptual Models
17.4
Linkage to Other Conceptual Models
Chapter 18 Analysis Plans
18.1
Choosing Measures of Exposure, Effects,
and Environmental Conditions
18.2
Reference Sites and Reference Information
18.2.1 Information Concerning the Precontamination or
Predisturbance State
18.2.2 Model-Derived Information
18.2.3 Information Concerning Other Sites

18.2.4 Information Concerning a Regional Reference
18.2.5 Gradients as Reference
18.2.6 Positive Reference Information
18.2.7 Goals as an Alternative to Reference
Part III

Analysis of Exposure

Chapter 19 Source Identification and Characterization
19.1
Sources and the Environment
19.2
Unknown Sources
19.3
Summary
Chapter 20 Sampling, Analysis, and Assays
20.1
Sampling and Chemical Analysis of Media
20.2
Sampling and Sample Preparation
20.3
Encountered Data
20.4
Screening Analyses
20.5
Analysis of Cofactors
20.6
Water
20.7
Sediment

20.8
Soil

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20.9
20.10
20.11
20.12
20.13

Biota and Biomarkers
Bioassays
Biosurveys
Sampling, Analysis, and Probabilities
Conclusions

Chapter 21 Mathematical Models of Chemical Transport and Fate
21.1
Objectives
21.2
Basic Modeling Concepts
21.2.1 Emissions or Loadings
21.2.2 Point and Nonpoint Sources
21.2.3 Steady-State and Non-Steady-State Sources
21.2.4 Importance of Scale
21.3
Formulating Mass Balance Models
21.3.1 Defining Compartments

21.3.2 Reaction Rates
21.3.3 Transport Rates
21.3.4 Emissions
21.3.5 Solutions to the Mass Balance Equation
21.3.6 Complexity, Validity, and Confidence Limits
21.4
Illustration of a Simple Mass Balance Model
21.4.1 The System Being Modeled
21.4.2 Concentration Calculation
21.4.2.1 Chemical Input Rate
21.4.2.2 Partitioning between Water, Particles, and Fish
21.4.2.3 Outflow in Water
21.4.2.4 Outflow in Particles
21.4.2.5 Reaction
21.4.2.6 Deposition to Sediment
21.4.2.7 Evaporation
21.4.2.8 Combined Loss Processes
21.4.3 Fugacity Calculation
21.4.4 Discussion
21.5
Chemicals of Concern and Models Simulating their Behavior
21.5.1 General Multimedia Models
21.5.1.1 Level I
21.5.1.2 Level II
21.5.1.3 Level III
21.5.1.4 Level IV
21.5.1.5 Fugacity Models
21.5.1.6 CalTOX Model
21.5.1.7 Simplebox Model
21.5.1.8 Regional, Continental, and Global-Scale Models

21.5.2 Models Specific to Environmental Media
21.5.2.1 Plume Models in General
21.5.2.2 Atmospheric Models
21.5.2.3 Aquatic Models
21.5.2.4 Soil Models
21.5.2.5 Fish Uptake and Food Chain Models
21.5.2.6 Miscellaneous Models

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21.5.3

21.6

Models Specific to Chemical Classes
21.5.3.1 Agricultural Pesticides
21.5.3.2 Veterinary Medicines
21.5.3.3 Biocides
21.5.3.4 Metals
Concluding Thoughts on Selecting and Applying Models

Chapter 22 Exposure to Chemicals and Other Agents
22.1 Exposure Models
22.2 Exposure to Chemicals in Surface Water
22.3 Exposure to Chemicals in Sediment
22.4 Exposure to Contaminants in Soil
22.4.1 Chemical Analyses to Estimate Exposure
22.4.1.1 Partial Chemical Extraction and Normalization
22.4.1.2 Input Form of the Chemical

24.4.1.3 Chemical Interactions
24.4.1.4 Nonaqueous Phase Liquids
22.4.2 Soil Depth Profile
22.5 Exposure of Terrestrial Plants
22.5.1 Rooting Depth
22.5.2 Rhizosphere
22.5.3 Wetland Plant Exposures
22.5.4 Soil Properties and Exposure of Plants
22.5.5 Plant Interspecies Differences
22.5.6 Plant Exposure in Air
22.6 Exposure of Soil Invertebrates
22.6.1 Depth of Exposure and Ingested Material
22.6.2 Soil Properties and Chemical Interactions
22.7 Exposure of Soil Microbial Communities
22.8 Exposure of Wildlife
22.8.1 Exposure Models Based on External Measures
22.8.1.1 Dermal Exposure
22.8.1.2 Inhalation Exposure
22.8.1.3 Oral Exposure
22.8.1.4 Spatial Issues in Wildlife Exposure
22.8.1.5 Temporal Issues in Wildlife Exposure
22.8.1.6 Exposure Modifying Factors
22.8.2 Parameters for Estimation of Exposure
22.8.2.1 Body Weight
22.8.2.2 Food and Water Consumption Rates
22.8.2.3 Inhalation Rates
22.8.2.4 Soil and Sediment Consumption
22.8.2.5 Home Range and Territory Size
22.9 Uptake Models
22.9.1 Aquatic Organism Uptake

22.9.1.1 Neutral Organics
22.9.1.2 Ionizing Organic Chemicals
22.9.1.3 Inorganic and Organometalic Chemicals
22.9.1.4 Aquatic Plants
22.9.1.5 Aquatic Toxicokinetics

ß 2006 by Taylor & Francis Group, LLC.


22.9.2
22.9.3

22.10
22.11
22.12
22.13
22.14

Benthic Invertebrate Uptake
Terrestrial Plant Uptake
22.9.3.1 Soil Uptake
22.9.3.2 Empirical Models of Inorganic Chemicals
22.9.3.3 Empirical Models for Organic Chemicals
22.9.3.4 Surface Contamination
22.9.3.5 Plant Tissue Type
22.9.3.6 Mechanistic Models
22.9.4 Earthworm Uptake
22.9.5 Terrestrial Arthropod Uptake
22.9.6 Terrestrial Vertebrate Uptake
Exposure to Petroleum and other Chemical Mixtures

Exposure to Natural Extreme Events
Exposure to Organisms
Probability and Exposure Models
Presenting the Exposure Characterization

Part IV

Analysis of Effects

Chapter 23 Exposure–Response Relationships
23.1
Approaches to Exposure–Response
23.1.1 Mechanistic Models
23.1.2 Regression Models
23.1.3 Statistical Significance
23.1.4 Interpolation
23.1.5 Effect Level and Confidence
23.2
Issues in Exposure–Response
23.2.1 Thresholds and Benchmarks
23.2.2 Time as Exposure and Response
23.2.3 Combined Concentration and Duration
23.2.4 Nonmonotonic Relationships
23.2.5 Categorical Variables
23.2.6 Exposure–Response from Field Data
23.2.7 Residue–Response Relationships
23.3
Toxicodynamics—Mechanistic Internal Exposure–Response
23.3.1 Toxicodynamics of Metals on Gills
23.4

Indirect Effects
Chapter 24 Testing
24.1
Testing Issues
24.2
Chemical or Material Tests
24.2.1 Aquatic Tests
24.2.2 Sediment Tests
24.2.3 Soil Tests
24.2.4 Oral and Other Wildlife Exposures
24.3
Microcosms and Mesocosms
24.4
Effluent Tests
24.5
Media Tests
24.5.1 Contaminated Water Tests
24.5.2 Contaminated Sediment Tests

ß 2006 by Taylor & Francis Group, LLC.


24.6

24.7
24.8
24.9

24.5.3 Contaminated Soil Tests
24.5.4 Ambient Media Tests with Wildlife

Field Tests
24.6.1 Aquatic Field Tests
24.6.2 Field Tests of Plants and Soil Organisms
24.6.3 Wildlife Field Tests
Testing Organisms
Testing Other Nonchemical Agents
Summary of Testing

Chapter 25 Biological Surveys
25.1 Aquatic Biological Surveys
25.1.1 Periphyton
25.1.2 Plankton
25.1.3 Fish
25.1.4 Benthic Invertebrates
25.2 Terrestrial Biological Surveys
25.2.1 Soil Biological Surveys
25.2.2 Wildlife Surveys
25.2.3 Terrestrial Plant Surveys
25.3 Physiological, Histological, and Morphological Effects
25.4 Uncertainties in Biological Surveys
25.5 Summary
Chapter 26 Organism-Level Extrapolation Models
26.1 Structure–Activity Relationships
26.1.1 Chemical Domains for SARs
26.1.2 Approaches for SARs
26.1.3 State of SARs
26.2 Effects Extrapolation Approaches
26.2.1 Classification and Selection
26.2.2 Factors
26.2.3 Species Sensitivity Distributions

26.2.4 Regression Models
26.2.5 Temporal Extrapolation of Exposure–Response Models
26.2.6 Factors Derived from Statistical Models
26.2.7 Allometric Scaling
26.2.8 Toxicokinetic Modeling for Extrapolation
26.2.9 Multiple and Combined Approaches
26.3 Extrapolations for Particular Biotas
26.3.1 Aquatic Biota
26.3.2 Benthic Invertebrates
26.3.3 Wildlife
26.3.4 Soil Invertebrates and Plants
26.3.5 Soil Processes
26.3.6 Water Chemistry
26.3.7 Soil Properties
26.3.8 Laboratory to Field
26.4 Summary

ß 2006 by Taylor & Francis Group, LLC.