United States
Environmental Protection
Agency
Office of Science Policy
Office of Research and Development
Washington, DC 20460
EPA100-B-00-002
December 2000
www.epa.gov
&EPA Science Policy Council
HANDBOOK
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EPA 100-B-00-002
December 2000
U.S. Environmental Protection Agency
RISK CHARACTERIZATION
HANDBOOK
Prepared for the U.S. Environmental Protection Agency
by members of the Risk Characterization Implementation Core
Team, a group of EPA's Science Policy Council
Principal Authors
John R. Fowle III, Ph.D. Kerry L. Dearfield, Ph.D.
Science Advisory Board Office of Science Policy
Office of the Administrator Office of Research and
Development
Science Policy Council
U.S. Environmental Protection Agency
Washington, DC 20460
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Page ii Risk Characterization Handbook
DISCLAIMER
This document has been reviewed in accordance with U.S. Environmental Protection
Agency policy and approved for publication and distribution. Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.
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Risk Characterization Handbook Page iii
TABLE OF CONTENTS
FOREWORD Page vii
ACKNOWLEDGMENTS Page x
OVERVIEW OF THIS RISK CHARACTERIZATION HANDBOOK Page 1
Outline of the Basic Structure of the Risk Characterization Guide Page 2
RISK CHARACTERIZATION GUIDE Page 3
1. INTRODUCTION TO RISK CHARACTERIZATION Page 5
1.1 Overview Page 5
1.2 Understanding Risk Characterization Page 10
1.2.1 What is Risk Characterization? Page 10
1.2.2 Are Risk Characterizations Written As Part of Ecological Risk
Assessments Different from Those Written As Part of Human
Health Risk Assessments? Page 11
1.2.3 Are Risk Assessment and Risk Characterization the Same? Page 13
1.2.4 Are Risk Characterization and Risk Communication the Same? . Page 13
1.2.5 What is the Value of Risk Characterization in the Regulation
Development Process? Page 13
1.2.6 What Role does Risk Characterization have in Regulatory
Negotiations? Page 14
1.2.7 Do Risk Characterizations Need Peer Review? Page 14
1.3 Risk Characterization Principles Page 14
1.3.1 What are Criteria for Transparency? Page 15
1.3.2 What are Criteria for Clarity? Page 16
1.3.3 What are Criteria for Consistency? Page 17
1.3.4 What are Criteria for Reasonableness? Page 18
1.4 Overview Presentation of TCCR Principles Page 19
1.5 The Roles of People and Organizations in Risk Characterization Page 20
1.5.1 Who is Ultimately Accountable for Risk Characterization? Page 20
1.5.2 Who Are the Agency Staff Involved in Risk Characterization? .. Page 20
1.5.3 What Are My Responsibilities as a Risk Assessor? Page 20
1.5.4 What Are My Responsibilities as a Risk Manager? Page 22
1.5.5 What Does the Risk Characterization Policy Tell
Risk Assessors? Page 24
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Page iv Risk Characterization Handbook
1.5.6 How Will Risk Characterization Help the Risk Assessor? Page 24
1.5.7 How Will Risk Characterization Help the Risk Manager? Page 24
1.5.8 Which Office/Region or Other Agency is Responsible for
Writing the Risk Characterization? Page 25
1.5.9 What is the Responsibility of Organizations that Submit
Risk Assessments to EPA? Page 25
1.5.8 What is the Role of the Science Policy Council (SPC)? Page 26
2. PREPARING FOR A RISK ASSESSMENT AND ITS RISK CHARACTERIZATION -
PLANNING AND SCOPING Page 27
2.1 Overview Page 27
2.2 Planning and Scoping Page 27
2.2.1 What Should You Discuss During Planning and Scoping? Page 28
2.2.2 Should the Planning and Scoping Discussion Focus on What
the Risk Assessment Results Should Be? Page 29
2.2.3 What are Possible Products Emerging from Planning
and Scoping? Page 29
2.2.4 What Are the Benefits of Planning and Scoping? Page 30
2.2.5 Who Does Planning and Scoping? Page 31
2.2.6 When Does the Risk Assessor/Risk Manager Dialog End? Page 31
2.3 Typology for Risk Characterization Page 31
3. ELEMENTS OF A RISK CHARACTERIZATION Page 35
3.1 Overview Page 35
3.2 Elements of a Risk Characterization Page 35
3.2.1 Can a "Bright Line" or Number be the Risk Characterization? . . . Page 36
3.2.2 What Key Information Needs to Be Identified During the Risk
Assessment Process to Prepare for Risk Characterization? Page 37
3.2.3 How Do I Put the Risks Estimated in this Assessment into
a Context with Other Similar Risks? Page 37
3.2.4 How Do I Address Sensitive Populations, Ecosystems
and Species? Page 38
3.2.5 What are Scientific Assumptions and How Do I Address
Them? Page 39
3.2.6 What Are Policy Choices and How Do I Address Them? Page 40
3.2.7 How Do I Address Variability? Page 40
3.2.8 How Do I Address Uncertainty? Page 40
3.2.9 How Do I Address Bias and Perspective? Page 41
3.2.10 How do I Address Strengths and Weaknesses? Page 41
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Risk Characterization Handbook Page v
3.2.11 What Are the Major Conclusions to Carry Forward? Page 42
3.2.12 How Do I Describe the Alternatives Considered? Page 43
3.2.13 How Do I Address Research Needs? Page 43
3.3 Should Decisions be Delayed Until Research is Completed? Page 44
4. RISK CHARACTERIZATION-RELATED PRODUCTS Page 45
4.1 Overview Page 45
4.2 Products of Risk Characterization Page 45
4.2.1 What is the Technical Risk Characterization? Page 46
4.2.2 What are Risk Characterization Products I Can Prepare for Risk
Managers? Page 46
4.2.3 What are Risk Characterization Products I Can Prepare for Other
Audiences, Like the Public? Page 47
4.3 Audiences for Risk Characterization Products Page 47
4.3.1 Who Are the Audiences for Risk Characterization Products? .... Page 47
4.3.2 Can I Use a Single Risk Characterization Product for All
Audiences? Page 48
4.3.3 How Much Technical Detail is Needed for Different
Audiences? Page 48
4.3.4 How Do I Ensure that the Irreducible Set of Risk Characterization
Information is Carried Forward in All Risk Characterization
Products? Page 49
4.4 Risk Characterization Format and Length Page 49
4.4.1 Is There a Standard Format for a Risk Characterization? Page 49
4.4.2 What is an Appropriate Length for a Risk Characterization? .... Page 50
5. INFORMING DECISION MAKERS Page 51
5.1 Overview Page 51
5.2 Science in Decision Making Page 51
5.2.1 Is the Risk Assessment the Single Driving Force Behind
Decision Making? Page 51
5.3 Decision-Making Factors Page 51
5.3.1 What Are the Major Factors that Affect Decision Making? Page 51
5.4 Characterization of Non-Science Factors Page 54
5.4.1 Are the Economic and Other Non-Risk Assessments Subject to
Characterization? Page 54
5.4.2 Can the Principles of TCCR Apply to Characterizations of the
Other Factors? Page 54
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Page vi Risk Characterization Handbook
6. ADMINISTRATIVE ISSUES Page 55
6.1 Overview Page 55
6.2 Risk Characterization Record Page 55
6.2.1 What is the Risk Characterization Record? Page 55
6.2.2 How Can the Risk Characterization Record Improve the Risk
Characterization Process? Page 55
6.2.3 Where Should the Risk Characterization Record be Kept and
For How Long? Page 56
6.3 Budget Planning Page 56
6.4 Legal Considerations Page 56
6.4.1 Are There Legal Ramifications from the Risk Characterization
Policy? Page 56
6.4.2 Is Legal Advice Needed? Page 56
6.5 Peer Review of Risk Characterization Handbook Page 57
SUBJECT INDEX Page 59
COMMONLY USED ACRONYMS Page 61
APPENDIX A Page A-l
POLICY FOR RISK CHARACTERIZATION Page A-l
APPENDIX B Page B-l
WAQUOIT BAY CASE STUDY Page B-l
APPENDIX C Page C-l
GENERIC KETONE CASE STUDY Page C-l
APPENDIX D Page D-l
MITEC CASE STUDY Page D-l
APPENDIX E Page E-l
MIDLOTHIAN CASE STUDY Page E-l
APPENDIX F Page F-l
References Concerning Risk Characterization Page F-l
References of EPA Risk Assessment Guidelines Page F-2
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Risk Characterization Handbook Page vii
FOREWORD
This Handbook was prepared by the Science Policy Council (SPC) for EPA staff and
managers and others as a guide to Risk Characterization. It implements EPA's March 1995 Risk
Characterization Policy which improved on the foundation of the February 1992 Agency-wide
policy for risk characterization. Both the 1992 and 1995 documents point out that "... scientific
uncertainty is a fact of life (and) ... a balanced discussion of reliable conclusions and related
uncertainties enhances, rather than detracts, from the overall credibility of each assessment...".
Both also note that while the role of science to inform but not make decisions is widely
recognized in EPA, and in the larger risk assessment and regulatory community, these
communities often use the risk assessment number as the stated reason for decisions, not always
clearly highlighting the legal, economic, social and other non-scientific issues that also go into
the decision.
From the start it was recognized that implementation of this policy would require a
culture change at EPA and that achieving an Agency-wide culture change would not be effective
if imposed from the top down. Thus, every effort was made to engage career EPA employees,
including risk assessors, risk managers and senior decision-makers across the Agency to help
implement the policy. The effort was monumental, directly involving several hundred Agency
employees in all Offices and Regions. A Risk Characterization Implementation Team was
established with members from each Region and Program Office, including the Office of General
Counsel, to guide and direct the initial efforts to implement the policy.
During the dialog that led to the decision to prepare a single guidance document, the SPC
heard from the Programs and Regions about the need for tools and case studies to make the
guidance understandable and assure
consistent implementation. This Handbook
"If I send a man to buy a horse for me, I
expect him to tell me that horse's points —
not how many hairs he has in his tail."
Abraham Lincoln
provides a single, centralized body of risk
characterization implementation guidance for
Agency risk assessors and risk managers to
help make the risk characterization process
transparent and the risk characterization
products clear, consistent and reasonable
(TCCR). TCCR became the underlying principle for a good risk characterization. The elements
of a risk characterization (among them, for example, key findings, policy choices, uncertainty
and variability) describe in a straight-forward fashion the critical points that a good risk
characterization should contain to make it valuable in any Agency risk assessment.
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Page viii Risk Characterization Handbook
This Handbook has two parts. The first is the Risk Characterization guidance itself. The
second part comprises the Appendices which contain the Risk Characterization Policy, the risk
characterization case studies and references.
As mentioned earlier, hundreds of people from across the Agency were instrumental in
the preparation of this Handbook, guided by the SPC and its Risk Characterization Team. They
were essential in bringing this effort to fruition. In addition, I want to give a special
acknowledgment to the principal authors, Jack Fowle and Kerry Dearfield — their hard work and
persistence made this Handbook a reality. I also want to recognize the thoughtful and helpful
input that the recently retired Executive Director of the Science Policy Council, Dr. Dorothy
Patton, provided. The Agency is indebted to her for her guidance, patience and support.
It is with great pleasure that I present the Risk Characterization Handbook.
Norine E. Noonan, Ph.D.
Assistant Administrator
Office of Research and Development
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Risk Characterization Handbook
Page ix
Science Policy Council
W. Michael McCabe, OA, Chair
Donald Barnes, OA
Tudor Davies, OW
Sylvia Lowrance, OECA
William Muszynski, Region 2
Michael Shapiro, OSWER
Ramona Trovato, OCHP
Norine Noonan, ORD, Vice-Chair
Robert Brenner, OAR
Steven Galson, OPPTS
Albert McGartland, OPEI
Michael Ryan, OCFO
Elaine Stanley, OEI
Science Policy Council Steering Committee
Donald Barnes, OA
Reginald Cheatham, OEI
William Farland, ORD
Penelope Fenner-Crisp, OPPTS
Jerri-Anne Garl, Region 5
Roland Hemmett, Region 2
Carl Mazza, OAR
Jennifer Orme-Zavaleta, ORD
Larry Reed, OSWER
Rosemarie Russo, Region 4
Mary Ellen Weber, OPPTS
William Wood, ORD
Michael Brody, OCFO
Patricia Cirone, Region 10
Michael Feldman, OCFO
Michael Firestone, OCHP
Peter Grevatt, OSWER
Kate Mahaffey, OPPTS
James Nelson, OGC
Peter Preuss, ORD
Joseph Reinert, OPEI
Vanessa Vu, ORD
Jeanette Wiltse, OW
Science Policy Council Staff
Edward Bender
Kerry Dearfield
James Rowe
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Page x Risk Characterization Handbook
ACKNOWLEDGMENTS
Many people have worked on the risk characterization implementation effort that
ultimately resulted in this Handbook, including the Risk Characterization Implementation Core
Team and several hundred EPA employees from the Agency's Offices and Regions. They are
too numerous to mention here, but we would like to specifically acknowledge Don Barnes, David
Bennett, Carol Braverman, Maggie Breville, Penny Fenner-Crisp, Jim Kariya, Barnes Johnson,
Mary McCarthy-O'Reilly, Edward Ohanian, Dorothy Patton, Peter Preuss, Margaret Stasikowski,
and Jeanette Wiltse.
Other individuals were instrumental in creating the case studies:
Waquoit Bay
a) Jennifer Orme-Zavaleta
b) Suzanne Marcy
c) William van der Schalie
Generic Ketone
a) Jennifer Seed
b) Vanessa Vu
Mitec
a) Debbie McCall
b) Christina Scheltema
Midlothian
a) Gerald Carney
b) Jeffrey Yurk
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Risk Characterization Handbook Page 1
U.S. Environmental Protection Agency
OVERVIEW OF THIS RISK CHARACTERIZATION
HANDBOOK
The Risk Characterization Handbook is created as a single, centralized body of risk
characterization implementation guidance for Agency risk assessors and risk managers. The
Risk Characterization Policy calls for a transparent process and products that are clear,
consistent and reasonable. All risk
assessments have a risk characterization
product, but effective characterization
depends on transparency, clarity, consistency
and reasonableness (TCCR). TCCR is the
key to a successful risk characterization.
This Handbook is divided into two parts:
1. Risk Characterization Guide
Effective characterization depends on
Transparency, Clarity, Consistency and
Reasonableness (TCCR)
The Risk Characterization Guide is designed to provide risk assessors, risk managers, and
other decision-makers an understanding of the goals and principles of risk characterization, the
importance of planning and scoping for a risk assessment, the essential elements to address in a
risk characterization, the factors that are considered in decision making by risk managers, and the
forms the risk characterization takes for different audiences. A discussion of the various
administrative details regarding risk characterization completes the guide.
The following page provides an outline and a table describing the basic structure of the
risk characterization guide.
2. Appendices
The Appendices contain the Risk Characterization Policy and case studies. The case
studies contain examples of risk characterizations from risk assessments that apply the principles
described in the Risk Characterization Guide. A list of references is also provided for your use.
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Page 2
Risk Characterization Handbook
Outline of the Basic Structure of the Risk Characterization Guide
Chapter 1 provides all audiences with an introduction to risk characterization in general,
including details of TCCR.
Chapters 2-4 describes a continuous process from planning and scoping to final
products from the risk characterization. The table below shows this basic flow of work
and where the risk assessment guidelines fit into this continuum.
Chapter 5 briefly discusses for all audiences the role of science and risk assessment in
the decision-making process.
Chapter 6 describes for Agency risk assessors and risk managers their essential roles and
activities.
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• Planning and
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• Conceptual
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• Analysis
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•Risk
Managers
•Risk
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• These parts
can be
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for peer
review
RISK
ASSESSMENT
GUIDELINES*
^> ^>^>
• Hazard
Identification
• Dose Response
Assessment
• Exposure
Assessment
• Risk Assessors
t dialog
• Risk Managers
• Pieces can be
candidates for
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CHAPTER 3
^> ^>^>
• Risk Charac-
terization
including
Integrated
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• Peer
Reviewers
•Risk
Assessors
• Usually a
major work
product for
peer review
CHAPTER 4
^> ^>^>
• Summaries
•Risk
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^>
• Communi-
cation
Pieces
• Public
* The Risk Assessment Guidelines are not covered by this Handbook. They are mentioned in this table because they
are part of the overall risk assessment process at EPA.
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Risk Characterization Handbook Page 3
U.S. Environmental Protection Agency
RISK CHARACTERIZATION GUIDE
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1. INTRODUCTION TO RISK CHARACTERIZATION
1.1 Overview
To help inform its decision making, the United States Environmental Protection Agency
(U.S. EPA) evaluates environmental risks through an assessment process that involves a
substantial body of scientific data and analysis with much judgment and uncertainty. EPA has
published guidelines to steer the Agency's evaluation of the risks from exposure to
environmental agents (see references for EPA Risk Assessment Guidelines at the end of this
document). These evaluations culminate in a characterization of the risks. Our understanding of
risk characterization has evolved over many years.
The first major reference to risk characterization is found in the 1983 National Academy
of Sciences' (NAS') National Research Council (NRC) publication Risk Assessment in the
Federal Government: Managing the Process (commonly referred to as the "Red Book"). Risk
characterization is defined as
"... the process of estimating the incidence of a health effect under the various conditions
of human exposure described in exposure assessment. It is performed by combining the
exposure and dose-response assessments. The summary effects of the uncertainties in the
preceding steps are described in this step."
In this definition, ways to make the risk assessment process transparent are not fully developed or
apparent.
The following year, in 1984, EPA published Risk Assessment and Management:
Framework for Decision-Making where risk characterization is described as the place where
"... finally we estimate the risk associated with the particular exposures in the situation
being considered for regulation. While the final calculations themselves are straight
forward (exposure times potency, or unit risk) the way in which the information is
presented is important. The final assessment should display all relevant information
pertaining to the decision at hand, including such factors as the nature and weight of
evidence for each step of the process, the estimated uncertainty of the component parts,
the distribution of risk across various sectors of the population, the assumptions contained
within the estimates and so forth."
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Page 6 Risk Characterization Handbook
While arriving at the risk assessment number is stressed, more emphasis is placed on making the
risk assessment process transparent, on a fuller description of the strengths and weaknesses of the
assessment, and on providing plausible alternatives within the assessment.
Concerns over adequately characterizing risk to maintain the public's perception of and
confidence in EPA's risk assessments led former Deputy Administrator Henry Habicht to issue
an Agency-wide policy for risk characterization on February 26, 1992. He noted that
"... scientific uncertainty is a fact of life (and) ... a balanced discussion of reliable
conclusions and related uncertainties enhances, rather than detracts, from the overall
credibility of each assessment ..."
In its 1992 publication "Improving Risk Characterization" the American Industrial Health
Council (AIHC) recommended ways to improve risk characterization. AIHC recommended the
following steps:
a) Identify potential users of risk characterization at the beginning of the risk
assessment process
b) Identify the types of decisions that need to be made early in the process
c) Make the content of the assessment relevant to the diversity of potential decisions
by including in the technical content of the risk characterization wherever
possible, several dimensions and estimates of risk
d) Ensure periodic two-way communication between assessors and users during the
risk assessment process
e) Conduct future research and systematic study"... on the effectiveness of risk
characterization messages and approaches, on ways of improving 'risk literacy' of
users of assessments, on the process of integration of technical information about
risk with information on other social values, so that social dimensions of risk are
recognized as legitimate parts of the risk management decision and are accounted
for in the risk characterization."
In this definition, the focus of risk characterization shifted from an emphasis on the purely
technical aspect of combining exposure and dose-response information to arrive at a risk
assessment number to the importance of the social aspects of risk assessment. Conversations
between risk assessors and users of risk assessment from the beginning and throughout the risk
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Risk Characterization Handbook Page 7
assessment process are needed to ensure that risk assessors understand the needs of decision-
makers to communicate the results of the risk assessment to those who are affected by the risk
management decision.
In 1994 in Science and Judgment, the NAS returned the focus to the original concept of
risk characterization. The NAS defined it as
"... the integration of information from the first three steps of the risk assessment process,
as defined in the 1983 NAS 'Redbook', to develop a qualitative estimate of the likelihood
that any of the hazards associated with the agent of concern will be realized in exposed
people. This is the step in which risk assessment results are expressed. Risk
Characterization should also include a full discussion of the uncertainties associated with
the estimates of risk."
Administrator Carol Browner reaffirmed the central role of risk characterization for the
Agency on March 21,1995 when she issued the Agency-wide Risk Characterization Policy
(found in Appendix A). The Policy calls for all risk assessments performed at EPA to include a
risk characterization to ensure that the risk assessment process is transparent and that the risk
assessments are clear, reasonable and consistent with other risk assessments of similar scope
prepared by programs across the Agency. Effective risk characterization is achieved through
transparency in the risk assessment process and clarity, consistency, and reasonableness of the
risk assessment product (TCCR).
In their 1996 report Understanding Risk, the NAS extended their definition of risk
characterization. The NAS defined it as
"... a synthesis and summary of information about a potentially hazardous situation that
addresses the needs and interests of decision makers and of interested and affected
parties. Risk characterization is a prelude to decision making and depends on an iterative,
analytic-deliberative process." They go on to refer to risk characterization as "the process
of organizing, evaluating and communicating information about the nature, strength of
evidence and the likelihood of adverse health or ecological effects from particular
exposures."
Here the NAS places equal emphasis on fully characterizing the scope, uncertainties, limitations,
and strengths of the assessment and on the social dimensions of interacting with decision makers
and other users of the assessment in an iterative, analytic-deliberative process. The purpose of
this process is to ensure that the assessment will be useful for the purposes for which it is
intended and that it will be understandable.
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The Presidential Commission on Risk Assessment and Risk Management (CRARM) was
created by the Clean Air Act Amendments of 1990 and formed in 1994. Its Congressional
mandate was to develop more scientific use of risk-based methods and specifically to provide
guidance on how to deal with residual emissions from Section 112 hazardous air pollutants after
technology-based controls have been placed on stationary sources of air pollutants. In 1997, the
Commission published its report in two volumes (CRARM, 1997a; CRARM, 1997b) and also
wrote about the importance of risk characterization to better understand and quantify risks as
well as to evaluate strategies to reduce human and ecological risks. They noted that
"risk characterization is the primary vehicle for communicating health risk assessment
findings. Many risk characterizations have relied primarily on mathematical estimates of
risk to communicate risk assessment findings, often conveying an unwarranted sense of
precision while failing to convey the range of scientific opinion. They are particularly
difficult for audiences unfamiliar with risk assessment to comprehend. Effective risk
management is impeded without effectively communicating information about who is at
risk, how they might be affected, what the severity and reversibility of adverse effects
might be, how confident the risk assessors are in their predictions and other qualitative
information that is critical to decision-making."
EPA's risk characterization efforts build on its own 1995 Risk Characterization Policy,
NAS, President's Commission, AIHC and others' concepts as well as on the Agency's
understanding that risk assessments provide important information about the nature, magnitude
and likelihood of possible environmental risks to inform decisions. By August 1995, EPA
Program Offices and Regions drafted Risk Characterization Implementation Plans to guide the
development of risk characterizations done in each Office/Region. Over the next two years, a
series of colloquia for risk assessors and roundtables for risk managers was held to test these
draft Implementation Plans against case studies, and to work out just what it takes to adequately
characterize risk. Over 200 EPA employees participated in these events, sharing their office's
culture and their own experiences and perspectives about risk characterization with other EPA
staff whose offices' cultures and whose personal experiences and perspectives were often
different.
The Agency recognized that a culture change is needed at EPA if the Agency is to
successfully implement the Risk Characterization Policy which describes a philosophy of
transparency, clarity, consistency, and reasonableness or TCCR as coined in the first
colloquium. The TCCR philosophy needs to be practiced in the everyday work of EPA as the
different products (e.g., reports, briefings etc.) flowing from Agency risk assessments are
developed to translate risk assessment findings for managers and the public.
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Risk Characterization Handbook Page 9
Risk characterization at EPA assumes different levels of complexity depending on the
nature of the risk assessment being characterized. The level of information contained in each
risk characterization varies according to the type of assessment for which the characterization is
written and the audience for which the characterization is intended. The goal of risk
characterization is to clearly communicate the key findings and their strengths and limitations so
its use in decision making can be put into context with the other information critical to evaluating
options for rules, regulations and negotiated agreements (e.g., economics, social values, public
perception, policies, etc.). EPA's concept of risk characterization has evolved since March 1995
to build on the experience of Agency risk assessors and managers and on the AIHC, President's
Commission, and the NAS Understanding Risk definitions. Risk characterization at EPA is
considered to be a conscious and deliberate process to bring all important considerations about
risk, both the likelihood of the risk but also the strengths and limitations of the assessment and a
description of how others have assessed the risk into an integrated picture. As an integrated
picture, the risk characterization focuses on how those components interact.
It should be noted that most of the emphasis in the discussion about risk characterization
generally focused on human health risk assessments. It is well recognized that the general
principles for risk assessment and risk characterization apply equally to ecological risk
assessments. Efforts at EPA culminated in the publication of risk assessment guidelines for
ecological risk assessment. Included in these guidelines is a discussion on risk characterization
for ecological risk assessments. This Handbook also builds on this effort.
Based on the experiences of those attending the meetings and using these various
documents to help characterize risk across the Agency since 1995, a single Agency-wide
document was determined to be needed. The Risk Characterization Handbook in general
supersedes the original Guidance and its associated "Elements Document" issued with the Risk
Characterization Policy. However, some of the more technical aspects of the original Guidance
which are not covered specifically in this Handbook (e.g., Section III - Exposure Assessment and
Risk Descriptors in the 1995 Guidance) are still appropriate. Furthermore, the Handbook
coalesces the ideas and directions found in the draft Implementation Plans and also supersedes
those plans. However, Agency offices and regions may wish to prepare tailored guidance that
meets their individual needs to supplement and remain consistent with the information in this
Handbook (e.g., Risk Assessment Guidance for Superfund: Volume I- Human Health
Evaluation Manual (RAGS/HHEM)).
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Page 10 Risk Characterization Handbook
1.2 Understanding Risk Characterization
1.2.1 What is Risk Characterization?
Risk characterization is an integral component of the risk assessment process for both
ecological and health risks, i.e., it is the final, integrative step of risk assessment. As defined in
the Risk Characterization Policy (Appendix A), the risk characterization integrates information
from the preceding components of the risk assessment and synthesizes an overall conclusion
about risk that is complete, informative, and usefiilfor decision makers. In essence, a risk
characterization conveys the risk assessor's judgment as to the nature and existence of (or lack
of) human health or ecological risks.
For health risk assessment, the NAS describes a four step paradigm (NRC, 1983). For
each step, the relevant and scientifically reliable information is evaluated. In addition, the related
uncertainties and science policy choices are described.
a) Hazard Identification — the determination of whether a particular chemical is or is
not causally linked to particular health effects
b) Dose-Response Assessment — the determination of the relation between the
magnitude of exposure and the probability of occurrence of the health effects in
question
c) Exposure Assessment — the determination of the extent of human exposure before
or after application of regulatory controls
d) Risk Characterization — the description of the nature and often the magnitude of
human risk, including attendant uncertainty
In 1998, EPA published risk assessment guidelines for ecological risk assessment
(USEPA, 1998), calling for:
a) Problem Formulation — the evaluation of goals, selection of assessment
endpoints, preparation of the conceptual model, and development of an analysis
plan
b) Analysis — the evaluation of exposure to stressors and identification of the
relationship between stressor levels and ecological effects
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Risk Characterization Handbook Page 11
c) Risk Characterization — the estimation of ecological risks, discussion of overall
degree of confidence in the risk estimates, citation of evidence supporting risk
estimates, and interpretation of the adversity of ecological risks
In addition, both the health and ecological risk assessment paradigms suggest to risk
assessors that in order to write an overall risk characterization, each risk assessment section
needs to have its own individual characterization. For human health risk, separate
characterizations accompany the hazard identification, dose-response assessment and exposure
assessment sections. For ecological risk, separate characterizations accompany the analysis plan,
the stressor-response profile and the exposure profile. These separate, component
characterizations carry forward the key findings, assumptions, strengths and limitations, etc. for
each section and provide a fundamental set of information used in an integrative analysis that
must be conveyed in the final overall risk characterization.
The overall risk characterization lets the manager, and others, know why EPA assessed
the risk the way it did in terms of the available data and its analysis, uncertainties, alternative
analyses, and the choices made. A good risk characterization will restate the scope of the
assessment, express results clearly, articulate major assumptions and uncertainties, identify
reasonable alternative interpretations, and separate scientific conclusions from policy judgments.
The Risk Characterization Policy calls for the explanation of the choices made to be highly
visible.
Importantly, remember that risk
characterization is not just about science. It Rigk characterization is not only about
makes clear that science doesn't tell us sdence __ h fe flfetf abouf making dear fhat
certain things and that science policy
choices must be made. It explains why the
risk assessment result is the way it is given
all the choices made during the course of
the risk assessment process. And when
others have also assessed the agent in a biologically plausible fashion, even if their assessment
does not agree with EPA's assessment, it makes clear that EPA has assessed the agent this way
but that others have assessed it differently.
1.2.2 Are Risk Characterizations Written As Part of Ecological Risk Assessments
Different from Those Written As Part of Human Health Risk Assessments?
In practice, the goals of ecological health and human health risk assessments are
essentially the same. While there are some differences in the specific activities between the two
science doesn 't tell us certain things and
that policy choices must be made.
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types of assessment (see specific appropriate EPA published guidelines), they generally approach
an overall risk assessment and its associated risk characterization similarly.
a) Human health assessment adopts the problem formulation stage concept from
ecological risk assessment and incorporates it into planning and scoping activities.
Note that planning and scoping is not a specifically named step in the original
1983 NAS paradigm. However, planning and scoping are increasingly
incorporated into the front end of human health risk assessment (e.g., see NRC,
1996; USEPA, 1997). Ecological risk assessment already incorporates a planning
phase as well at the front end of its assessment process (USEPA, 1998).
Ultimately, the efforts of these activities produce, in both types of assessments, a
conceptual model that identifies the receptor issues/contaminants of concern and
the potential exposure pathways for the assessment to concentrate upon. Chapter
2 provides more detail of the planning and scoping activities.
b) The analysis phase, where both exposure assessment and effects assessment or
dose response analyses are conducted under ecological risk assessment, is similar
to the dose response and exposure assessments conducted under human health risk
assessment. While human health risk assessments focus on the risks to
individuals and populations/subpopulations, ecological risk assessments may
focus on individuals (for rare and endangered species), populations, communities,
or ecosystems, depending on decisions made in the planning and scoping/problem
formulation activities. The many risk assessment guidelines issued by the EPA
provide much detail into the analyses needed in the assessment (references for
these guidelines are found in Appendix F after the Handbook references).
c) Risk characterization is an integral part of the ecological risk assessment
framework and is the final step in the human health risk assessment paradigm.
For example, in ecological risk assessment, it is routine under risk
characterization to address the ecological significance of the risks by asking the
question "So what?" That is, if this risk exists as estimated, will it make a
difference or be observed above the other dynamic factors operating in the
environment? Similarly, the significance of human health risks relative to other
similar hazards and activities is considered in its risk characterization. Chapter 3
provides more detail of the elements of a risk characterization.
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1.2.3 Are Risk Assessment and Risk Characterization the Same?
No, they're not the same. Risk assessment is a process comprised of several steps (see
section 1.2.1 above for detail). Risk characterization is the culminating step of the risk
assessment process. Risk characterization communicates the key findings and the strengths and
weaknesses of the assessment through a conscious and deliberate transparent effort to bring all
the important considerations about risk into an integrated analysis by being clear, consistent and
reasonable. Remember though, unless you actually characterize the assessment, the risk
assessment is not complete — risk characterization is an integral component of every risk
assessment. As an example, just giving the quantitative risk estimate ("the number") is not a risk
characterization.
1.2.4 Are Risk Characterization and Risk Communication the Same?
Risk characterization is an integral part of a risk assessment that summarizes the key
findings and the strengths and weaknesses for risk managers and others. While it provides
information that may be used to inform the public, risk characterization is not synonymous with
risk communication. Risk communication emphasizes the process of exchanging information
and opinion with the public, including individuals, groups, and other institutions, about levels of
health or environmental risks. Risk communication is used for such things as information and
education, behavior change and protective action, disaster warnings and emergency information,
joint problem solving and conflict resolution. While the final risk assessment documentation
(including the risk characterization) can be used to communicate with the public, the risk
communication process is probably better served by separate documentation designed for
particular audiences (Chapter 4 discusses this further).
1.2.5 What is the Value of Risk Characterization in the Regulation Development
Process?
The risk characterization section of risk assessments that support rulemaking actions is an
important, fundamental step informing the policy setting process. Risk characterization plus peer
review provide a mechanism to help the Agency achieve scientific credibility. The risk
characterization criteria of TCCR are essential, because new rules, and the work products
supporting them, must often withstand intense scrutiny by the general public and the stakeholders
affected by EPA's decisions. Although no rule orregulation itself is subject to the Risk
Characterization Policy, the risk assessments that help inform the rules and regulations are
subject to the Policy, and they should include risk characterization prior to use in any rule.
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1.2.6 What Role does Risk Characterization have in Regulatory Negotiations?
Regulatory negotiations are not risk assessments; however, to ensure final decisions are
based on sound and credible science, any risk assessments used during the regulatory negotiation
need to be properly characterized before the negotiation is completed.
1.2.7 Do Risk Characterizations Need Peer Review?
The principle underlying the Peer Review Policy is that all major scientific and/or
technical work products used in Agency decision making will be peer reviewed. Any risk
assessment can be a candidate for peer review. Use the criteria in the Peer Review Handbook to
determine which assessments need to be peer reviewed (USEPA, 2000).
Peer review is critical to ensure the scientific
soundness of a risk assessment.
The risk characterization is an
intrinsic part of the risk assessment.
Generally, the entire risk assessment,
with its risk characterization section, is
the candidate for peer review. In some
instances, the risk characterization piece itself may be a candidate for peer review. In
performance of the peer review, you need to make sure that the TCCR criteria (see section 1.3
below for detailed discussion) are addressed in addition to the validity and credibility of the risk
assessment itself.
1.3 Risk Characterization Principles
The Risk Characterization Policy states that "A risk characterization should be prepared
in a manner that is clear, transparent, reasonable, and consistent with other risk characterizations
of similar scope prepared across programs in the Agency." Risk characterization is therefore
judged by the extent to which it achieves the principles of Transparency, Clarity, Consistency,
and Reasonableness (TCCR).
While the Policy calls for TCCR in the risk characterization, the principles of TCCR need
to be fully applied throughout every aspect of the risk assessment process. By applying TCCR
principles from the planning and scoping stages, through the actual risk assessment, and then to
all the communication and documentation of the risk assessment, the whole process will benefit
and help better ensure success of all assessment efforts and products (including the risk
characterization!).
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Criteria are needed to fully implement the TCCR principles and to evaluate success.
Because risk characterization, as called for in the Policy, clarifies EPA's way of doing business,
risk assessors need some criteria to know what is asked of them as they prepare risk
characterizations, risk managers need some criteria to know what to look for as they read risk
characterizations, and the pub lie needs some criteria to help them judge EPA's success in
characterizing risk.
The sections below describe the criteria for TCCR. Before launching each risk
assessment, the criteria should be kept in mind to help ensure that the risk assessment is well-
characterized. After the assessment is complete, the criteria can be used to measure how well the
assessment was characterized.
1.3.1 What are Criteria for Transparency?
Transparency provides explicitness in the risk assessment process. It ensures that any
reader understands all the steps, logic, key assumptions, limitations, and decisions in the risk
assessment, and comprehends the supporting rationale that lead to the outcome. Transparency
achieves full disclosure in terms of:
a) the assessment approach employed
b) the use of assumptions and their impact on the assessment
c) the use of extrapolations and their impact on the assessment
d) the use of models vs. measurements and their impact on the assessment
e) plausible alternatives and the choices made among those alternatives
f) the impacts of one choice vs. another on the assessment
g) significant data gaps and their implications for the assessment
h) the scientific conclusions identified separately from default assumptions and
policy calls
i) the major risk conclusions and the assessor's confidence and uncertainties in them
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j) the relative strength of each risk assessment component and its impact on the
overall assessment (e.g., the case for the agent posing a hazard is strong, but the
overall assessment of risk is weak because the case for exposure is weak)
Transparency is the principal value from among the four
TCCR values, because, when followed, it leads to clarity,
consistency and reasonableness.
In many cases this will be a qualitative discussion and/or an acknowledgment that the
assessor doesn't know the impact on the assessment due to uncertainty. For example, if there are
no measurements for a given input to a risk assessment and a model or assumption is used and
there is little information on the accuracy of the particular model or assumption for the particular
type of application, then you may not be able to say anything meaningful about the impact on the
assessment of using a model, other than to acknowledge the uncertainty inherent in using this
model or assumption. Similarly, a complex risk assessment may have many assumptions
imbedded in the analysis (all of which should be disclosed). However, the only way to know the
impact of alternative choices in the model might require running the model many different ways
and this might not be possible given resources (dollars and time). However, to the extent feasible
within the resources and time available you should address the points noted above.
1.3.2 What are Criteria for Clarity?
Clarity refers to the risk assessment product(s). Making the product clear makes the
assessment free from obscurity and easy to understand by all readers inside and outside of the
risk assessment process. Clarity is achieved by:
a) brevity
b) avoiding jargon
c) using plain language so it's understandable to EPA risk managers and the
informed lay person
d) avoiding the use of technical terms and, if used, by defining those terms
e) describing any quantitative estimations of risk clearly
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f) using understandable tables and graphics to present the technical data
g) using clear and appropriate equations to efficiently display mathematical
relationships (complex equations should be footnoted or referred to in the
technical risk assessment)
1.3.3 What are Criteria for Consistency?
Consistency provides a context for the reader and refers to the presentation of the material
in the risk assessment. For example, are the conclusions of the risk assessment characterized in
harmony with relevant policy, procedural guidance, and scientific rationales and if not, why the
conclusions differ. Also, does the assessment follow precedent with other EPA actions or why
not. However, consistency should not encourage blindly following the guidance for risk
assessment and characterization at the expense of stifling innovation. Consistency is achieved
by:
a) following statutory requirements and program precedents (e.g., guidance,
guidelines, etc.)
b) following appropriate Agency-wide assessment guidelines
c) using Agency-wide information, where appropriate, from systems such as the
Integrated Risk Information System (IRIS)
d) putting the risk assessment in context with other similar risk assessments
1) how does it compare to other EPA assessments of similar agents or sites
2) how does it compare to others done by the scientific and regulatory
community (e.g., other federal and state agencies, by other countries
and/or by various interest groups; note: a reasonable search for similar
assessments is expected)
i) how do the conclusions drawn by others differ from EPA's
assessment
ii) what are the strengths and limitations compared to EPA's
assessment
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e) defining and explaining the purpose of the risk assessment (e.g. regulatory
purpose, or policy analysis, or priority setting, etc.)
f) defining the level of effort (e.g. quick screen, extensive characterization) put into
the assessment and the reason(s) why this level of effort was selected
g) following established Agency peer review procedures
1.3.4 What are Criteria for Reasonableness?
Reasonableness refers to the findings of the risk assessment in the context of the state-of-
the science, the default assumptions and the science policy choices made in the risk assessment.
It demonstrates that the risk assessment process followed an acceptable, overt logic path and
retained common sense in applying relevant guidance. The assessment is based on sound
judgment. Reasonableness is achieved when:
a) the risk characterization is determined to be sound by the scientific community,
EPA risk managers, and the lay public, because the components of the risk
characterization are well integrated into an overall conclusion of risk which is
complete, informative, well balanced and useful for decision making
b) the characterization is based on the best available scientific information
c) the policy judgments required to carry out the risk analyses use common sense
given the statutory requirements and Agency guidance
d) the assessment uses generally accepted scientific knowledge
e) appropriate plausible alternative estimates of risk under various candidate risk
management alternatives are identified and explained
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1.4 Overview Presentation of TCCR Principles
The following table presents an encapsulated overarching presentation of the TCCR
principles and their criteria for a good risk characterization. It is meant to serve as a stand alone
summary one-page guide for the use of TCCR throughout the risk assessment process.
Principle
Definition
Criteria for a Good Risk Characterization
Transparency
Explicitness in the risk
assessment process.
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1.5 The Roles of People and Organizations in Risk Characterization
1.5.1 Who is Ultimately Accountable for Risk Characterization?
Under the March 21, 1995 Risk Characterization Policy, the Administrator designated the
Assistant Administrators, Associate Administrators, Regional Administrators (AAs and RAs),
the General Counsel, and the Inspector General to be accountable for implementing the Policy in
their respective organizations. In her memo to Senior Agency Management (Appendix A), the
Administrator noted that:
"These core values of transparency, clarity, consistency, and reasonableness need to guide
each of us in our day-to-day work; from the toxicologist reviewing the individual cancer
study, to the exposure and risk assessors, to the risk manager, and through to the ultimate
decision maker. I recognize that issuing this memo will not by itself result in any change.
You need to believe in the importance of this change and convey your beliefs to your
managers and staff through your words and actions in order for the change to occur. You
also need to play an integral role in developing the implementing policies and procedures
for your programs."
While the above persons are ultimately accountable for ensuring health and ecological
risk assessments from their organizations have proper risk characterizations, it is recognized
much of the responsibility to ensure that the risk assessments include risk characterizations that
are done well according to the principles of TCCR is delegated to their Risk Managers.
1.5.2 Who Are the Agency Staff Involved in Risk Characterization?
The principal Agency staff are risk assessors and risk managers. Risk assessors are the
scientific and technical staff who actually perform the various components of the risk
assessment.
1.5.3 What Are My Responsibilities as a Risk Assessor?
People who perform the risk assessment, in whole or in part, are the risk assessors. Risk
assessors rely heavily on the risk assessment guidelines to help guide the risk assessment and
address science policy issues and scientific uncertainties specific to the endpoint in each
guideline. You may fall into either of two major groupings of risk assessors, or both:
a) Risk assessors that develop chemical- or stressor-specific risk assessments
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b) Risk assessors that generate site- or medium-specific risk assessments - these
assessors usually rely on existing databases and site- or media-specific exposure
information (e.g., IRIS, HEAST, OPP database, Exposure Factors Handbook)
Regardless of which group you are in, your major responsibility as a risk assessor is to
communicate your key risk findings and conclusions and your confidence in them in the risk
characterization section of your assessment. Your basic job is to write the risk assessment with
the technical risk characterization (see section 4.2.1).
Your specific responsibilities are to:
a) Explain what is the risk, what individuals, populations or systems are affected and
by what route of exposure
b) Describe your level of comfort with the conclusions and what degree of certainty
you place in them
1) Summarize and identify the key pieces of information critical to your
evaluation
2) Let your manager know whether the key data used for the assessment are
considered experimental, state-of-the art or generally accepted scientific
knowledge
c) Describe quantitative risk estimates in plain English; the use of tables and
graphics may be helpful as a supplement
d) Describe the uncertainties inherent in the risk assessment and the default positions
used to address these uncertainties or gaps in the assessment
e) Refer the reader to an Agency risk assessment guideline or other easily obtainable
reference that explains terminology (e.g., how aRfC was developed)
f) Put this risk assessment into a context with other similar risks that are available to
you and describe how the risk estimated for this stressor, agent or site compares to
others regulated by EPA
g) Describe how the strengths and weaknesses of EPA's assessment compare with
other assessments prepared by EPA in the past
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h) Describe the rationale and bases for the conclusions drawn by those outside EPA
about this agent, stressor or site
1) If their conclusions differ from yours, let the manager know whether theirs
is a reasonable alternative
2) Can their conclusions reasonably be derived from the data set
3) Inform the manager of the strengths and weaknesses of their evaluations
compared to yours
i) If you have developed specific assessments for one or more risk management
alternatives, let the risk manager know what changes in risk would occur under
these various candidate risk management alternatives
j) Highlight areas in the assessment which might be overlooked or misinterpreted by
the risk manager
k) Keep the decision maker informed of the status of your risk assessment and risk
characterization
1) Organize, conduct, and complete the risk characterization following Agency
procedures
m) Archive the risk characterization record in a manner consistent with your
organization's archiving procedures
1.5.4 What Are My Responsibilities as a Risk Manager?
Risk managers are generally the decision makers in their organization. The AA/RA is the
ultimate decision maker for his/her organization and is accountable for both the risk
characterization process and products in his/her office. The AA/RA may designate Office
Directors, Division Directors, and/or Branch Chiefs (or other appropriate level line-managers) as
the front-line decision makers. Generally, the decision makers commit the resources needed to
ensure a proper risk assessment which includes a complete risk characterization.
As a risk manager, you are responsible for ensuring that risk assessments, containing risk
characterizations, are properly performed and documented. You are also responsible for ensuring
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that the key information from each risk characterization is honestly and clearly elevated up the
management chain and communicated to senior management. As a decision maker, you integrate
the risk characterization with other considerations specified in applicable statutes, Agency and
office policies, executive orders, and other factors (e.g., see Chapter 5) to make and justify
regulatory decisions.
Your specific responsibilities are:
a) Promote a culture supportive of preparing risk characterizations and ensure that
all risk assessment work products produced by or submitted to your organization
are well characterized
b) Provide advice, guidance, and support for the preparation, conduct, and
completion of a full risk characterization for each assessment
c) Play a major role in determining the scope of the risk assessment
d) Ensure that sufficient funds are designated in the office's budget request to
conduct a risk characterization for each risk assessment
e) Establish a realistic risk assessment schedule that includes risk characterization
f) Designate the stage(s) of product development where risk characterization is
appropriate
g) Ensure that the characterizations prepared by individual risk assessors for their
portion of each risk assessment document are integrated into a complete risk
characterization for each risk assessment
h) Provide proper risk assessment training for your staff including how to write risk
assessments and their characterizations
i) Establish systems to maintain records of the risk assessments, including risk
characterizations, prepared by risk assessors under your supervision
j) Ensure that the key points from the risk characterization are carried forward in all
deliberations or considerations for decision making
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1.5.5 What Does the Risk Characterization Policy Tell Risk Assessors?
The policy tells risk assessors to include the following in the risk characterization:
a) Carry forward the key
information from hazard
identification, dose-response,
and exposure assessment,
using a combination of
qualitative information,
quantitative information, and
information about
uncertainties
Risk characterization communicates the
key strengths and weaknesses of the
assessment through a conscious and
deliberate effort to bring all the important
considerations about risk into an
integrated picture.
b) Discuss uncertainty and variability appropriate for the level of analysis
c) Present risk conclusions and information regarding the strengths and limitations of
the assessment at the level appropriate for the risk assessment (e.g., if it is a
screening assessment the risk characterization portion of the risk assessment
should be brief)
1.5.6 How Will Risk Characterization Help the Risk Assessor?
Risk characterization makes the whole risk assessment story clearer and easier to
communicate. If you properly characterize risk, your risk assessment is easier to explain, justify,
and defend.
1.5.7 How Will Risk Characterization Help the Risk Manager?
Risk characterization allows you to understand and better communicate risk assessment
findings. You can better convey information up the management decision-making chain and to
the public. Transparency is a powerful tool. You can use it to ensure clarity, consistency and
reasonableness to achieve a better-informed decision.
Risk managers have made the following comments about risk characterization:
a) Being transparent helps me make better-informed decisions
1) It brings out the usually unseen parts of the assessment
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2) When I require transparency, I can incorporate clarity, consistency and
reasonableness to achieve a better-informed decision
3) Helps me understand the scientific basis of my decisions
4) Helps me build trust and credibility with staff, public and stakeholders
b) Communication helps and it has two parts
1) When I ask questions, getting to TCCR is facilitated
2) I need to ask early and to check progress often
1.5.8 Which Office/Region or Other Agency is Responsible for Writing the Risk
Characterization?
The organization preparing the risk assessment is normally responsible for preparing the
risk characterization. If more than one Agency office or region or other agencies are involved,
each is responsible for characterizing that component of the assessment they prepared. The
responsibility for preparing the overall risk characterization is usually accepted by the office
making the decision, but this can be negotiated.
1.5.9 What is the Responsibility of Organizations that Submit Risk Assessments to
EPA?
Just as the Agency is expected to follow its own guidance for characterizing risk in every
risk assessment, the Agency expects that any risk assessment done by any organization for EPA
consideration and possible use will include a proper risk characterization that is transparent,
clear, consistent and reasonable and addresses the risk characterization elements. The Agency
reserves the right to determine the acceptability of the submitted risk assessment and its
characterization and will evaluate each submission in line with the guidance in this Handbook.
If the submitting party has questions about any aspect of the risk assessment, it may want
to contact the agency office or region that is associated with and ultimate recipient of the
assessment. Care should be taken to make it clear that while the Agency is glad to comment on
questions presented about the assessment and risk characterization, it will not provide any
approval or commitments prior to its evaluation of the actual final submission.
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1.5.8 What is the Role of the Science Policy Council (SPC)?
The Science Policy Council (SPC) will consult with each Program Office and each
Region as they implement risk characterization. The SPC will also periodically evaluate the
Agency's experience with risk characterization and as necessary will provide supplemental
guidance or when appropriate, revise this Handbook. The implementation of the Risk
Characterization Policy is the responsibility of management within each Office or Region.
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2. PREPARING FOR A RISK ASSESSMENT AND ITS RISK
CHARACTERIZATION - PLANNING AND SCOPING
2.1 Overview
The risk characterization is the summarizing step of the risk assessment. However, the
participants in the colloquia and roundtables noted that the risk characterization principles of
TCCR and the elements of risk characterization (described in Chapter 3) offer powerful tools to
help plan and scope a risk assessment before it is begun. Therefore, these principles should be
considered by risk assessors, risk managers
and others as they begin each new
assessment. Planning and scoping is an
important first step to ensure that each risk
assessment has a clear purpose, has a
defined scope, and is well thought out.
These provide a sound foundation for
judging the success of the risk assessment
and for an effective risk characterization.
If you begin the overall risk assessment
process with planning and scoping, you set
a sound foundation for a good risk
characterization at its end.
2.2 Planning and Scoping
Based on EPA's experience with the four-step NAS risk assessment paradigm (NAS,
1983), it has become clear that the additional step of planning and scoping is needed at the front
end of the risk assessment process. This will help ensure that a risk assessment is well done and
is well characterized. In 1997, the Agency issued preliminary planning and scoping guidance in
the context of cumulative risk (USEPA, 1997). A more developed Planning and Scoping Guide
is currently being written under the auspices of the Agency's Science Policy Council. This Guide
should be referred to when published for greater detail on planning and scoping, particularly as to
cumulative risk assessment and stakeholder involvement.
Planning and scoping can be viewed as a lens that defines the purpose and scope of a risk
assessment and focuses the issues involved in performing the assessment. The risk
characterization portion of the risk assessment, in turn, is a second lens that focuses the
conclusions of the risk assessment into a coherent picture for applying and communicating the
assessment. At the end of the risk assessment, a comparison of the risk assessment, including the
risk characterization, with the goals and objectives defined during planning and scoping can
provide a useful measure of success.
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2.2.1 What Should You Discuss During Planning and Scoping?
Planning and scoping provides the opportunity for the risk manager(s), the risk
assessor(s), and other members of the "team" to define what is expected to be covered in the risk
assessment and to explain the purposes for which the risk assessment information will be used.
During the planning and scoping phase of the risk assessment process risk assessors and risk
managers should engage in a dialog to identify:
a) Motivating need for the risk assessment (regulatory requirements? public
concern? scientific findings? other factors?)
b) Management goals, issues, and policies needing to be addressed
c) Context of the risk
d) Scope and coverage of the effort
e) Current knowledge
f) What and where are the available data
g) An agreement about how to conduct the assessment including identifying:
1) Resources available to do the assessment
2) Participants in the process
3) Plans for coordinating across offices, with other agencies and with
stakeholders
4) Schedule (e.g., milestones) and time frame
h) Plans for how the results will be communicated to senior managers and to the
public
i) Information needs/data for other members of the "team" to conduct their analyses
(e.g., economic, social, or legal analyses)
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Another discussion during the planning and scoping process concerns the identification of
key data gaps and thoughts about how to fill the information needs. For example, can you fill the
information needs in the near-term using existing data, in the mid-term by conducting tests with
currently available test methods to provide data on the agent(s) of interest, and over the long-term
to develop better, more realistic understandings of exposure and effects and to construct more
realistic test methods to evaluate agents of concern? In keeping with TCCR, care must be taken
not to set the risk assessment up for failure by delaying environmental decisions until more
research is done. Planning and scoping discussions about filling information/data gaps should
include:
a) Do you have enough data to perform the risk assessment despite having certain
information gaps
b) When will the results be available
c) Will the results likely make a real difference in the assessment
d) To what extent will a policy call have to be made when data are unavailable or are
not certain
2.2.2 Should the Planning and Scoping Discussion Focus on What the Risk
Assessment Results Should Be?
No! While Agency risk managers should meet often with their risk assessors and other
team members to discuss the need for, and the context of, the risk assessment, the discussions
should definitely not touch upon what the risk assessment result(s) should be. The purpose of
these discussions is to ensure that the needs for the assessment are well understood by those
conducting it, that the assessment is properly scoped, and that the results will be timely and
useful for the intended purpose.
2.2.3 What are Possible Products Emerging from Planning and Scoping?
Products that can emerge from the planning and scoping process are the conceptual model
with its associated narrative and the analysis plan. The conceptual model is a visual presentation
relating sources and releases of possible contaminants or the level of ambient concentrations to
exposure of people and ecosystems which result in potential adverse effects to human health or
ecology. The narrative explains the rationale for the nature of the conceptual model developed.
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The analysis plan is the final stage of planning and scoping and is a bridge to the risk
assessment. The analysis plan is the implementation strategy for performing the risk assessment
and addressing the Agency's needs. It documents the agreements made during the planning and
scoping process and provides details on how the risk assessment will proceed. This provides
transparency to the whole process. In addition, the analysis plan provides measures against
which the final risk assessment and its risk characterization can be evaluated. As the risk
assessment proceeds, the analysis plan may need to be revisited and refined to ensure that the
risk assessment still meets the Agency's needs.
In general, conceptual models and analysis plans are candidates for peer review. Peer
review early in the risk assessment process can provide additional insights, corrections to
assumptions, and directions on proper ways to proceed during the risk assessment (see Section
1.2.7). These are valuable additions to the Agency's way of conducting business.
2.2.4 What Are the Benefits of Planning and Scoping?
The planning and scoping process helps risk assessors understand how their risk
assessment and its characterization fit into the overall environmental decision-making process.
Preliminary information on the various inputs to decision-making, the possible roles and
participation of stakeholders, and how the analyses will be peer reviewed are considered at the
planning and scoping stage. Management concerns about funding, human resources, timing etc.
are also discussed. This is important information to the risk assessor.
Planning and scoping promotes:
a) Initial planning to save time and resources, and buy-in by stakeholders or
interested parties by setting realistic expectations
b) Better-informed decisions, and the prospect of less controversy (e.g., fewer court
cases, criticism)
c) Participation by those from many disciplines (e.g., economists, lawyers) to help in
the process thereby ensuring that each risk assessment and characterization is
useful for the intended audience(s), and is of the scope and degree of complexity
needed to inform the decision at hand in conjunction with other analyses, for
instance, economics.
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2.2.5 Who Does Planning and Scoping?
The planning and scoping process involves relevant risk managers, risk assessors and
other members of the "team" working on the decision that needs to be made. The other members
include the economists, lawyers, engineers, policymakers, etc. working on the issue at hand. To
ensure that risk assessment meets the Agency's needs, and that those who will use the results are
fully informed, the communication within the team begun during the planning and scoping phase
should continue throughout the risk assessment process until the final risk characterization is
communicated to the decision maker(s) and beyond in certain cases (e.g. litigation support).
Stakeholders (interested and affected parties) may participate during the planning and
scoping process depending upon the nature of the problem, their interest, and ability to
contribute. Affected parties can share their points of view about the risk and how it should be
managed. Their input is particularly helpful in determining what should be included in the
assessment, how they might be affected or exposed to the risk, and what additional data or
exposure scenarios should be developed. Early in the planning and scoping of the risk
assessment, decisions need to be made about who the stakeholders are and how they will
participate.
2.2.6 When Does the Risk Assessor/Risk Manager Dialog End?
Risk assessors work with risk managers and others as a team. Ongoing dialog before and
during the assessment is essential for its successful completion. Generally, once the risk
management decision is made, the ongoing dialog usually ends. However, since emphasis on
evaluating the effectiveness of the risk management action and decision has become part of the
Agency's way of doing business (due to the Government Performance Results Act (GPRA)),
there will probably be an occasional need for the risk assessors and risk managers to discuss the
assessment after the risk management decision is made.
2.3 Typology for Risk Characterization
As the Policy states, EPA conducts many types of risk assessments. Assessments involve
various levels of complexity to support the wide range of decisions that have an impact on
human and environmental health. These include screening-level assessments of new chemicals,
in-depth assessments of pollutants such as dioxin and environmental tobacco smoke, and site-
specific assessments for hazardous waste sites. An iterative approach to risk assessment,
beginning with screening techniques, may be used to determine if a more comprehensive
assessment is necessary. The degree to which confidence and uncertainty are addressed in a risk
characterization depends largely on the scope of the assessment. In general, the scope of the risk
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characterization should reflect the length, depth, and breadth of the corresponding risk
assessment. When special circumstances (e.g., lack of data, extremely complex situations,
resource limitations, statutory deadlines) preclude a full assessment, such circumstances need to
be explained and their impact on the risk assessment discussed in the risk characterization.
During the planning and scoping stages of the risk assessment process, discussions about
the level of effort and complexity of detail take place in regards to the upcoming risk assessment.
These discussions may be revisited once the assessment is underway. A decision typology
adapted from theNRC (NRC, 1996) is provided below to help you think about the possible
information needs for decision making and the effort needed to develop such information. While
this typology doesn't cover all possible circumstances, it provides an example range of effort
needed for risk assessments (including risk characterizations).
This typology, derived from the NRC (1996), should be borne in mind as the risk
assessment is planned, scoped and conducted to ensure that the risk characterization section of
the assessment is of the proper level of detail for the task at hand.
a) Unique, wide-impact decisions and risk characterizations. The risk
characterization informs single-time decisions that uniquely impact the health of
large numbers of people or large portions of the environment, sometimes over
long periods of time. Typically, they are controversial, with disparate
perspectives on the nature and extent of the risk and a spectrum of affected parties
and visible, interested stakeholders.
Those planning the risk assessment process will no doubt recognize and have the
support for extensive risk analyses with broad participation. But the nature of the
process will be particularly important in achieving a risk characterization that will
be useful in the decision-making process.
b) Routine, narrow-impact decisions and risk characterizations. Risk
characterizations of this type will be very similar to previous ones that have been
performed. Typically, the impact under review will involve a small geographical
area and few people. Examples of risk characterizations of this type are the
thousands of screening level site-specific risk characterizations performed
annually to support air permit decisions for small facilities. Other examples are
the screening level chemical use-specific characterizations that maybe developed
in evaluating circumstances for chemical manufacture as with the
premanufacturing notice program for new chemicals under the Toxic Substances
Control Act (TSCA).
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Significant unresolved issues may underlie individual risk characterizations of this
type. However, it will be neither practical nor desirable to debate the assumptions
and develop multiple descriptions for each risk characterization. The most
reasonable course is to make the process and characterization development
routine, but provide the opportunity for appeal. Also, there should be periodic
review of the routine procedures.
c) Repeated, wide-impact decisions and risk characterizations. Risk
characterizations of this type have wide impact; that is, they support decisions that
can have an impact on large numbers of people or large geographical areas.
However, the characterizations developed are similar in structure to ones done
previously with respect to issues discussed and supporting risk assessments. Also,
in planning and scoping the assessment process, the issues are likely to be similar
to those previously raised.
Therefore, some aspects can be made routine, although certain other aspects may
need special attention so that they meet the unique needs of the particular decision
at hand. Also, questions should be raised at the start to attempt to uncover issues
important to the decision that would not be anticipated on the basis of other
similar risk characterization exercises. An example of this type of
characterization would be one performed in support of the siting of a large waste
incineration facility.
d) Generic hazard and dose-response decisions and risk characterizations. Risk
characterizations of this type are one step removed from the characterization of a
particular chemical use or site-specific risk. In fact, they typically support the
routine risk characterizations described above. Since they fall outside specific
decisions at hand, it is sometimes difficult to appreciate the full range of issues.
Indeed, it may be a challenge to construct a risk assessment or characterization
development and review process with adequate participation, absent a particular
decision context.
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There is only a single technical
characterization of risk as a final
product of the risk assessment.
Risk Characterization Handbook Page 35
3. ELEMENTS OF A RISK CHARACTERIZATION
3.1 Overview
Risk characterization does not stand alone. It is one of the four steps in risk assessment.
It is very important that risk characterization be done well because it is the final component of
the risk assessment process. There is only a single
technical characterization of risk as a final product of
the assessment (see section 4.2.1). This technical
characterization must be written with enough detailed
technical information so that another expert (e.g.,
other risk assessors, peer reviewers) can reasonably
reconstruct what was done in the assessment,
including being able to identify the assumptions made during the assessment. Since the risk
characterization is a part of the risk assessment itself, keep in mind that the goal of the risk
characterization is not to repeat the entire assessment, just to identify the key elements from the
risk assessment that really make a difference in its outcome.
The actual elements that go into an assessment are addressed in the many risk assessment
guidelines and program-specific guidance documents that are issued by the EPA. You need to
refer to the guidelines while conducting a risk assessment (see reference list at end of this
Handbook for these guidelines). Those materials that guide you through the risk assessment will
not be reiterated here. This Handbook provides guidance for the risk characterization part of the
risk assessment.
This chapter presents many of the elements you need to consider when drafting the risk
characterization part of your assessment. You should not use a checklist approach here. Instead,
you should consider the elements presented below while writing your risk characterization.
Whether every element is actually written into the characterization or not is dependent upon the
purpose of the risk assessment and the detail necessary to adequately characterize it.
3.2 Elements of a Risk Characterization
By the time you have completed your assessment, you should have identified the universe
of policy choices, management decisions, and uncertainties, as well as the conclusions of your
risk assessment. The point of risk characterization is not to repeat the entire risk assessment, but
rather to describe the key findings and other elements (i.e., not all the issues and conclusions,
only the key information) from each step of the human health or ecological assessment paradigm.
Because key findings differ for each assessment, it is not possible to define exactly what they are
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generically. Professional judgment is necessary to define them. You will want to alert the risk
manager to the major elements that affect the characterization:
a) Key information (section 3.2.2)
b) Context (section 3.2.3)
c) Sensitive Subpopulations (section 3.2.4)
d) Scientific Assumptions (section 3.2.5)
e) Policy Choices (section 3.2.6)
f) Variability (section 3.2.7)
g) Uncertainty (section 3.2.8)
h) Bias and Perspective (section 3.2.9)
i) Strengths and Weaknesses (section 3.2.10)
j) Key Conclusions (section 3.2.11)
k) Alternatives Considered (section 3.2.12)
1) Research Needs (section 3.2.13)
3.2.1 Can a "Bright Line" or Number be the Risk Characterization?
No! Whatever the form the risk characterization takes, don't just give the "number." The
goal is to give an understandable, rich description of the findings and the strengths and
weaknesses of the assessment, i.e., avoid the single "bright line" presentation. Every risk
characterization has a fundamental, irreducible set of information consisting of the key findings
that must be conveyed to every audience to adequately characterize the risk; again, it is more than
just a number.
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3.2.2 What Key Information Needs to Be Identified During the Risk Assessment
Process to Prepare for Risk Characterization?
When you prepare a risk characterization, you need to think about what is the information
to present in the risk characterization. The following provides some considerations to help you
capture the key information from the risk assessment to carry forward into the risk
characterization. For each stage of the assessment for human health or ecological risks, the
assessor identifies:
a) The studies available and how robust they are (e.g., have the findings been
repeated in an independent lab)
b) The major risk estimates calculated, the assumptions and the extrapolations made
during the estimated risk calculation, and the residual uncertainties and their
impact on the range of plausible risk estimates. Your description of the risk
estimate should indicate what you are assessing (e.g., individual, population,
ecosystem) and include such things as the high end and central tendency
estimates.
c) Use of defaults, policy choices and any risk management decisions made (e.g.,
refer the reader to an Agency risk assessment guidance, guideline, or other easily
obtainable reference source that explains the meaning of terminology)
d) Whether the key data used for the assessment are considered experimental, state-
of-the art or generally accepted scientific knowledge
e) The meaning of quantitative data in an easily understandable form — the use of
tables and graphics may be helpful
f) Variability (see section 3.2.7)
3.2.3 How Do I Put the Risks Estimated in this Assessment into a Context with
Other Similar Risks?
It is important for the risk manager to
know how the estimated risk from this agent
or site compares to similar risks. Two types
of comparisons should be considered. The
first is to compare this risk assessment with
Discussions about how the likely risk from
this stressor, agent or site compares to
others regulated by EPA can provide a
valuable tool to risk managers.
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previous Agency decisions to provide a feel for the comfort level, weight of evidence, and likely
problems the Agency will have with this assessment when comparing it to past Agency
assessments. The second is to provide a sense of how generally the assessment is accepted by the
scientific and regulatory community at large by comparing the results of EPA's assessment on
this agent or site with available assessments made on the same agent or site by other federal and
state agencies, by other countries and/or by various interest groups.
a) Comparisons to Agency assessments
1) Let the risk manager know what other risk assessments have been
performed on this agent or site or similar agents and sites
2) Describe how the strengths and weaknesses of EPA's assessment compare
with other assessments prepared by EPA in the past
b) Comparisons to assessments done by others
1) Describe the rationale and bases for the conclusions drawn by others about
this agent if they differ from EPA's assessment
2) If their assessment differs from EPA's, is it a reasonable alternative (i.e.,
can their conclusions reasonably be derived from the data set)
3) What are the strengths and weaknesses of their evaluations compared to
EPA's assessment
3.2.4 How Do I Address Sensitive Populations, Ecosystems and Species?
In its risk assessments and risk characterizations, the EPA attempts to identify the
universe of people that may be affected, including sensitive populations (e.g., children, ethnic
groups, gender, age, nutritional status, other genetic predisposition), ecosystems or ecological
entities (e.g., endangered species), and those that are highly exposed (e.g., human, wildlife, etc.).
In the planning and scoping phase of the risk assessment process, the potential for exposures or
for unique adverse effects to sensitive populations should be noted. Any sensitive populations
that are identified should be evaluated in the risk assessment, and the assessment should contain
an appropriate characterization It may not be necessary or possible to do a quantitative risk
assessment on each one. For instance, where there are many sensitive population groups for a
given pollutant, it may be sufficient to estimate risks for the most sensitive group and as long as
they are protected, other groups may be protected adequately.
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While all sensitive populations need to be considered, Executive Order 13045 entitled
"Protection of Children from Environmental Health Risks and Safety Risks" (April, 1997), and
the Administrator's "Policy on Evaluating Health Risks to Children" (October, 1995),
specifically require that EPA risk assessments, risk characterizations, and environmental and
public health standards characterize health risks to infants and children as appropriate.
The following points are illustrative of the information that can be valuable in the
assessment and characterization of children's risk As risk assessors conduct their risk
assessment, they should consider these factors about children's risks in their risk
characterization. The first two points to consider should be part of the fundamental, irreducible
set of information carried forward in the risk characterization:
a) Have the potential hazards to children been adequately characterized?
b) Have the exposures to children been adequately characterized?
In addition, the Agency has issued specific guidance for rule writers about how to address
children's risk pursuant to Executive Order 13045. This is found in the "EPA Rule Writer's
Guide to Executive Order 13045" issued as interim final guidance in April 1998 (USEPA, 1998).
3.2.5 What are Scientific Assumptions and How Do I Address Them?
Because we only have a limited amount of information from laboratory, human, and field
studies, it is necessary to predict the effects that will occur after exposures to environmental
pollutants. For some pollutants data are available from certain stages of development but not
others. Or perhaps the study was conducted in one sex only or in a certain ethnic population or
one whose diet is much different from that in the U.S. In such cases, it is necessary to describe
the variation and unpredictability of responses to toxicant exposure at different developmental
stages, to the other sex or another population, as well as other complexities (e.g., the possibility
of delayed response).
At EPA, various risk assessment guidelines have been written to ensure a scientifically
defensible and consistent approach to risk assessment. When you write the risk characterization
portion of your assessment, indicate whether or not you followed the guidelines and describe the
key assumptions you made during your assessment and the impact they have on the assessment
outcome. For example, if the endpoint of concern is ovarian cancer, it makes no difference and
is not worth noting that males were not studied for ovarian cancer. However, in other cases, for
example, if the cancer risk from carcinogenicity from drinking water contaminated by arsenic is
being considered, the effect of diet on the disease outcome should be stressed.
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3.2.6 What Are Policy Choices and How Do I Address Them?
In years past, different EPA offices sometimes had different policies about how to assess
risk (e.g., different uncertainty factors or different levels of regulatory concern). While the
development of the various risk assessment guidelines and the establishment of the Science
Policy Council have helped to eliminate such discrepancies, possibilities for policy choices
affecting risk assessment outcomes still exist in EPA (i.e., different laws and their implementing
regulations may still dictate divergent policies). Also, there maybe important differences
between EPA's risk assessment policy choices and those of other agencies. To the extent you are
aware of such information be sure to describe it in the risk characterization portion of your
assessment and to let your manager know of the impact the alternative policy choices have on the
outcome of your assessment.
3.2.7 How Do I Address Variability?
The risk assessor should strive to distinguish between variability and uncertainty to the
extent possible (see 3.2.8 for a discussion of uncertainty). Variability arises from true
heterogeneity in characteristics such as dose-response differences within a population, or
differences in contaminant levels in the environment. The values of some variables used in an
assessment change with time and space, or across the population whose exposure is being
estimated. Assessments should address the resulting variability in doses received by members of
the target population. Individual exposure, dose, and risk can vary widely in a large population.
Central tendency and high end individual risk descriptors capture the variability in exposure,
lifestyles, and other factors that lead to a distribution of risk across a population (e.g., see
Guidelines for Exposure Assessment; referenced in Appendix F).
3.2.8 How Do I Address Uncertainty?
Uncertainty represents lack of knowledge about factors such as adverse effects or
contaminant levels which may be reduced with additional study. Generally, risk assessments
carry several categories of uncertainty, and each merits consideration. Measurement uncertainty
refers to the usual error that accompanies scientific measurements — standard statistical
techniques can often be used to express measurement uncertainty. An amount of uncertainty is
often inherent in environmental sampling, and assessments should address these uncertainties.
There are likewise uncertainties associated with the use of scientific models, e.g.,dose-response
models, models of environmental fate and transport.
Evaluation of model uncertainty considers the scientific basis for the model and available
empirical validation. A different kind of uncertainty stems from data gaps; that is, estimates or
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assumptions used in the assessment. Often, the data gap is broad, such as the absence of
information on the effects of exposure to a chemical on humans or on the biological mechanism
of action of an agent. The risk assessor should include a statement of confidence that reflects the
degree to which the risk assessor believes that the estimates or assumptions adequately fill the
data gap. For some common and important data gaps, Agency or program-specific risk
assessment guidance provides default assumptions or values. Risk assessors should carefully
consider all available data before deciding to rely on default assumptions. If defaults are used,
the risk assessment should reference the Agency guidance that explains the default assumptions
or values.
While it is generally preferred that quantitative uncertainty analyses are used in each risk
characterization, there is no single recognized guidance that currently exists on how to conduct
an uncertainty analysis. Nonetheless, risk assessors should perform an uncertainty analysis.
Even if the results are arrived at subjectively, they will still be of great value to a risk manager.
The uncertainty analysis should, in theory, address all aspects of human health and ecological
risk assessments, including hazard identification, dose-response assessment, and exposure
assessment. Uncertainty analysis should not be restricted to discussions of precision and
accuracy, but should include such issues as data gaps and models.
Identify those scientific uncertainties that if reduced (e.g., about whether or not we know
if the agent causes cancer, about whether or not we know what happens at low doses, that we
know the exposure only occurs in certain specific locations) or the policy choices and
management decisions that if changed would make a real impact on the risk assessment.
3.2.9 How Do I Address Bias and Perspective?
There is an understood, inherent, EPA bias that in the light of uncertainty and default
choices the Agency will decide in the direction of more public health protection than in the
direction of less protection. However, it is not always clear where such bias enters into EPA risk
assessments. To the extent it may make a difference in the outcome of your assessment,
highlight the relevant areas so the impact will not be overlooked or misinterpreted by the risk
manager.
3.2.10 How do I Address Strengths and Weaknesses?
Identify major imbalances among the components of the assessment. For example, the
case for the stressor or agent posing a hazard may be strong, while the overall assessment of risk
is weak because there are no data about whether there is exposure to the stressor or agent.
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3.2.11 What Are the Major Conclusions to Carry Forward?
Each component of the risk assessment (e.g., hazard identification, exposure assessment,
etc.) contains its own summary "mini-characterization." When integrated, these identify the
fundamental, irreducible set of key points that must be communicated to characterize adequately
the corresponding section of that risk assessment. Because every risk assessment has many
uncertainties, and involves many
assumptions, the challenge in characterizing
risk for decision makers, whose time is
limited and who are not risk experts, is to
convey that small subset of key findings and
strengths and limitations that really makes a
difference in the assessment outcome.
The goal of Risk Characterization is not to
repeat the entire assessment, just the key
findings and conclusions.
a) Bring out those key strengths and weaknesses in plain English consistent with
TCCR
b) Provide a brief bottom line statement about the risks, including your confidence in
any estimate(s) of risk and in your conclusions
c) Help the reader clearly grasp what is known about the nature, likelihood and
magnitude of any risk
The idea is to relay to the risk manager in frank and open terms the scope, strengths, and
limitations of the assessment. An example of possible strengths of an assessment would be that
the overall weight of evidence of the data indicates that the quality and quantity of data
supporting the hazard and/or exposure is high. There might also be general consensus within the
scientific community on certain points used to build the hazard/exposure case.
If you know of information that would yield changes in the risk estimates under various
candidate risk management alternatives, let the manager know. For instance, if a feasibility study
has been performed that evaluates the risk associated with different treatment technologies or
remedial alternatives, discuss the range of possible outcomes and the implications of each.
It is important to remember that while you are conducting your risk assessment you need
to think about what the key points are that you want to present in the risk characterization portion
of the assessment
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3.2.12 How Do I Describe the Alternatives Considered?
As you prepare the risk characterization section of your risk assessment you should ask
yourself what are the qualitative characteristics of the hazard (e.g., voluntary vs. involuntary,
technological vs. natural, etc.)? You should also comment on findings, if any, from studies of
risk perception that relate to this hazard or similar hazards and let the risk manager know:
a) What are the alternatives to this hazard? How do the hazards compare?
b) How does this risk compare to other risks?
1) How does this risk compare to other risks in this regulatory program, or
other similar risks that the EPA has made decisions about?
2) Where appropriate, can this risk be compared with past Agency decisions,
decisions by other federal or state agencies, or if appropriate, to common
risks with which people may be familiar?
You should describe the limitations of making these comparisons, and comment on
significant community concerns which influence public perception of risk, if known.
You should also comment on other risk assessments that have been done in similar
situations (e.g., specific chemical, similar site) by EPA, other federal agencies, or other
organizations. Are there significantly different conclusions that merit discussion? Is there other
information that would be useful to the risk manager or the public in this situation that has not
been described above?
3.2.13 How Do I Address Research Needs?
While many data needs and methodology gaps are identified when assessing risk, only
the key ones that really make a difference in the risk assessment outcome are highlighted in
the risk characterization portion of the risk assessment. A systematic capturing of such needs
identified during risk characterization may provide an effective way to identify high priority
scientific support needs and a mechanism to reduce the tension within EPA between the need for
immediate technical support for today's regulations and the need to improve test methods and
risk assessment models to more realistically estimate risk from environmental exposures.
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3.3 Should Decisions be Delayed Until Research is Completed?
Unless the research need is so compelling as to its critical use in the risk assessment, a
decision should not be delayed unduly to fulfill the need. Research is never certain and it often
raises additional questions. The main benefit of risk characterization is that it provides context
for available information for use in decision making and for strengthening the scientific
underpinnings of the Agency's decisions.
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4. RISK CHARACTERIZATION-RELATED PRODUCTS
4.1 Overview
The portion of the risk assessment referred to as risk characterization is the final
summarizing product of the risk assessment process (elements discussed in Chapter 3). This is
referred to as the "technical" risk characterization. Once this is written, it can be used as the
basis for subsequent communication instruments or products for audiences beyond the technical
users of the characterization. The communication of the risk characterization will take different
written and oral forms to meet the needs of the intended audiences (e.g., risk managers, the
public). Thus, the communication of risk requires different products for different audiences at
different times. In other words, it is probably not realistic to expect one product to serve diverse
audiences equally.
The level of information contained in each product will vary according to the detail of
the risk assessment which is being characterized by this product. In addition, it will often vary in
format or detail in order to effectively communicate with the intended audience. Use good
judgment and common sense.
Remember, risk characterization is not synonymous with risk communication. While the
final risk assessment document (including the technical risk characterization) is available to all
audiences, the risk communication process may be better served by separate products designed
for particular audiences. This chapter deals with these separate "risk characterization" products
and their audiences.
4.2 Products of Risk Characterization
Because there is more than one audience for each assessment, there will probably be more
than one risk characterization product written or spoken about the risk assessment. There are
many risk assessments that vary in length and degree of detail. Therefore, each risk
characterization is as simple or complex as the assessment from which it derives and the
audience for which it is prepared. The subsequent products derived from the risk
characterization will be similarly simple or complex. The purpose of a risk characterization is
full disclosure, but that does not mean that you have to be wordy.
Further, each office and region produces different types of risk assessments, often
producing more than one type at any given time. The differences are due to the requirements of
enabling legislation, the types of decisions to be made, the culture of the office, and to other
factors.
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4.2.1 What is the Technical Risk Characterization?
The "technical" risk characterization is the integrating and concluding product of the risk
assessment. It is the risk characterization referred to in the risk assessment paradigm and is
usually within the domain of risk assessors to assemble and write. It is written with enough
detailed technical information so that another expert can understand the steps taken to conduct
the assessment and identify the assumptions made during the assessment. The risk
characterization is able to undergo peer review. TCCR applies to the risk characterization and it
fully addresses the elements discussed in Chapter 3. Example technical risk characterizations
(case studies) are found in the appendices.
4.2.2 What are Risk Characterization Products I Can Prepare for Risk Managers?
The usual products prepared from the risk characterization for risk managers are generally
in the form of a summary. Summaries can take various forms and you need to decide which
form is the most appropriate for the particular risk manager involved and the needs of that risk
manager. In general, risk managers do not need the depth of technical detail found in the
technical risk characterization They want the key issues and conclusions clearly highlighted in
the summary. If risk managers want to read and understand the technical details, they can refer
to the technical risk characterization or the full risk assessment.
Summary products can include:
a) Executive summary style product - at most a few pages with some technical detail
for audiences with some technical knowledge, e.g., first line managers (this
executive summary may sometimes be the executive summary of the technical
risk characterization itself depending on the audience)
b) Bulleted list highlighting the key issues and conclusions culled from the technical
risk characterization - probably 1-2 pages with little or no technical detail for
audience with little or no technical knowledge, e.g., higher lever managers,
decision makers
c) Briefing packages
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4.2.3 What are Risk Characterization Products I Can Prepare for Other
Audiences, Like the Public?
The products prepared from the risk characterization for other audiences besides risk
assessors and risk managers can come in many forms. Generally, these are communication
pieces with little or no technical detail, but still carry forward the key issues and conclusions
more in a lay person's context than a technical context. The public is most thought of as the
main audience in this regard.
Among the many forms these communication products may take are:
a) Fact sheets - more prose-like product that describes key issues and conclusions
for non-technical audience, e.g., interested public
b) Press releases - another prose-like product that describes key issues and
conclusions for mostly non-technical audience, e.g., affected and/or interested
public
c) Slide shows - visual presentation (perhaps accompanied by audio presentation) of
key issues and their context for mostly non-technical audience, e.g., affected
public
d) Federa 1 Regi ster N otice s - inc ludes decis ions, For Yo ur Info rmati on (FY I)
material
e) Public Relations (PR) Notices
f) Decision Documents - includes Reregistration Eligibility Decisions (REDs),
Record of Decisions (RODs)
g) Speeches and Talks
4.3 Audiences for Risk Characterization Products
4.3.1 Who Are the Audiences for Risk Characterization Products?
While not specifically defined, they run the gamut from risk assessors through line
managers to the decision makers, the Administrator (the ultimate decision maker), peer
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reviewers, the scientific community, and the general public. The risk characterization product
needs to be tailored to each of these specific audiences in terms of depth and detail.
Furthermore, since the work of EPA should be conducted as if in a fishbowl
(transparency), the total number of audiences can be potentially limitless and can include most
anyone. This will probably present a challenge to the writers of these risk characterization
products, but one that needs to be met nonetheless. As these audiences are identified, additional
products are tailored to their needs in terms of depth and detail.
4.3.2 Can I Use a Single Risk Characterization Product for All Audiences?
Generally, no. The technical risk characterization itself is consistent with the level of
detail and complexity of the assessment conducted. However, as you characterize the assessment
for various less technically oriented audiences, the subsequent products need to be tailored to
those audiences. Technical science has become increasingly more precise, detailed, and
specialized over the years. It is not easy for non-technical people to fully comprehend the details
and nuances of the scientific data It has even become increasingly difficult for scientists
themselves to fully understand the meaning of data in scientific disciplines outside their own
expertise. Therefore, the products you write from the technical risk characterization need to be
tailored to the particular audience you need to communicate with.
4.3.3 How Much Technical Detail is Needed for Different Audiences?
This will depend on the audience. Generally, the use of technical terms should be
minimized to help maintain clarity in a product. However, products prepared from risk
characterizations use the appropriate amount of technical detail as required by each audience.
For the technical risk characterization, full technical detail is expected. After all, this is the
expert's integration of the scientific data. But even here, extensive use of technical detail and
equations should be kept as minimal as practically possible. If great detail is needed, for instance
with many equations, this material might be better suited in an appendix for other experts to
examine in detail if they wish or for a peer review. Remember, enough technical detail is needed
for a fellow expert (e.g., peer reviewer) to reconstruct the thinking behind the risk assessment.
For other audiences, a great deal less technical detail is appropriate. While the use of
technical terms should be avoided to help maintain clarity in any product, products prepared from
risk characterizations can present information with different amounts of technical detail as
required by each audience (see section 4.2 above). For example, first-level risk managers may be
technically competent, but have little time to review details. For this audience, a good approach
would be to provide a short executive summary with the technical information included in an
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appendix or reference the risk assessment itself (which would probably accompany the summary
for first-level managers). Higher level managers and/or policy-makers are likely to have less
technical expertise than first-level managers, so technical terms and equations appropriately may
be removed from risk characterization products intended for this audience. For senior Agency
officials, it may be appropriate to provide an abstracted risk characterization product of one page
or less with little or no technical detail. For non-technical audiences, and especially when you
communicate the characterization to the general public, write and speak in plain English (clarity!)
- again, practically little or no technical detail is necessary. Note, however, synopsis and
simplification do not mean simplistic products.
4.3.4 How Do I Ensure that the Irreducible Set of Risk Characterization
Information is Carried Forward in All Risk Characterization Products?
Risk characterization is an integrating process that can lead to a range of products that
might be written at different times by different people for different audiences. To ensure that the
key messages are carried forward, peer review is an important component of the risk
characterization portion of the risk assessment process, because it helps ensure the scientific
integrity of the risk characterization, especially as it is distilled and simplified. At these points in
time, there is a need to ensure that the key points are faithfully passed on and interpreted. Formal
peer review may not be practical for small quick risk assessments, or as the risk characterization
products are turned into briefings. However, each office needs to have procedures in place to
ensure that as this is done, the major points of the characterization are faithfully captured.
4.4 Risk Characterization Format and Length
4.4.1 Is There a Standard Format for a Risk Characterization?
Not really. While most technical risk characterizations will look similar, a set format is
not required for any particular characterization. Based on experiences from the colloquia and
roundtables, a general flow for a format is suggested:
a) Executive Summary — begin with a concise, brief summary at the beginning of the
characterization
b) Context — briefly describe the context of the risk assessment, including planning
and scoping initiatives
c) Elements — the main body of the risk characterization addresses all, or as many as
possible, of the risk characterization elements outlined in Chapter 3
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Page 50 Risk Characterization Handbook
d) Final Conclusions — state succinctly the key final conclusions
4.4.2 What is an Appropriate Length for a Risk Characterization?
Common sense should be used. Each risk characterization should reflect the length,
depth, and breadth of the corresponding risk assessment and the audience for which it is
intended. The length of a risk characterization for a screening assessment, for example, will not
likely be very long due to little data or scientific knowledge. It will not probably change much
when adapted for different audiences since limited information is usually available, although the
language used may change in complexity. The length of a risk characterization for an
intermediate or comprehensive risk assessment with much more data and technical detail will be
correspondingly longer. Subsequent products from these risk characterizations will then likely
take on shorter lengths for non-technical audiences. Don't forget to always include that
irreducible set of key points that really makes a difference in the assessment outcome, no matter
what the length.
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5. INFORMING DECISION MAKERS
5.1 Overview
During the series of colloquia and roundtables with many Agency risk managers and risk
assessor to implement the Risk Characterization Policy, a primary question that arose was "What
is the role of science in the decision-making process for EPA?" Their major conclusion
determined that while science is important to inform risk managers, there are other factors that
also drive decision making. This small chapter provides a brief overview of how science is just
one of the factors considered for decision making. A full discussion of the decision-making
process is beyond the scope of this Handbook.
5.2 Science in Decision Making
5.2.1 Is the Risk Assessment the Single Driving Force Behind Decision Making?
While the scientific risk assessment has ostensibly been the primary factor and driving
force for most regulatory and risk management decisions, it is apparent that factors in addition to
scientific risk assessment (and economic analyses) play an important role in decision making.
This reality is recognized by outside parties as well (e.g., NAS (1994) and the
Presidential/Congressional Commission on Risk Assessment and Risk Management (1997)) that
many other factors are important in environmental decision making. The scientific risk
assessment and its peer review provide the sound scientific underpinnings for a decision.
However, it is only one of the many factors that a decision maker considers in arriving at a final
environmental decision.
5.3 Decision-Making Factors
5.3.1 What Are the Major Factors that Affect Decision Making?
Most risk management decisions are informed by a variety of factors in addition to
science (Figure 5.1). In addition to the scientific factors, decisions generally involve
consideration of many of these factors.
a) Scientific factors provide the basis for the risk assessment, including information
drawn from toxicology, chemistry, epidemiology, ecology, mathematics, etc.
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Page 52 Risk Characterization Handbook
b) Economic factors inform the manager on the cost of risks and the benefits of
reducing them, the costs of risk mitigation or remediation options and the
distributional effects
c) Laws and legal decisions are factors that define the basis for the Agency's risk
assessments, management decisions, and, in some instances, the schedule, level or
methods for risk reduction
d) Social factors, such as income level, ethnic background, community values, land
use, zoning, availability of health care, life style, and psychological condition of
the affected populations, may affect the susceptibility of an individual or a
definable group to risks from a particular stressor
e) Technological factors include the feasibility, impacts, and range of risk
management options
f) Political factors are based on the interactions among branches of the Federal
government, with other Federal, state, and local government entities, and even
with foreign governments; these may range from practices defined by Agency
policy and political administrations through inquiries from members of Congress,
special interest groups, or concerned citizens
g) Public values reflect the broad attitudes of society about environmental risks and
risk management
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Page 53
%%
•^
V "^>
Planning and Scoping
Analysis
Characterization
Synthesis
Legal Factors ^ (Decisioij^
*^^-^£^
Public Values
$~
13
°fy.
o
Figure 5.1 Risk Management Decision Framework. At least seven factors (represented by the
arrows) affect and inform risk management decisions. Each factor passes through four analytical
steps to integrate the information for a risk management decision.
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Page 54 Risk Characterization Handbook
5.4 Characterization of Non-Science Factors
5.4.1 Are the Economic and Other Non-Risk Assessments Subject to
Characterization?
The Risk Characterization Policy applies only to clarifying the risk assessment inputs to
the decision-making process. The goal of risk characterization is to openly communicate the full
range of scientific considerations surrounding a risk assessment. This overarching approach can
be applied to all assessments, including those of the other factors, in a general sense. A decision
maker who is informed by comprehensive information, analysis, and characterization, can more
easily weigh all factors to make the decision, and help the public better understand the basis for
his/her decision.
5.4.2 Can the Principles of TCCR Apply to Characterizations of the Other
Factors?
The principles of TCCR (transparency, clarity, consistency, and reasonableness) can be
readily adapted to economic assessments/characterizations and the other factors besides risk that
are characterized. It is probably desirable that the risk characterization principles apply not only
to the scientific factor, but to all the factors in the way they do business.
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6. ADMINISTRATIVE ISSUES
6.1 Overview
Risk characterization, as a component of risk assessment, is done by many people over
time. It is often iterative in nature. Thus, risk characterizations should be memorialized in
writing by the regions and offices as part of each risk assessment. If the risk assessment is done
piecemeal, each risk assessment section should be accompanied by a written risk characterization
for that section of the assessment. Each individual section risk characterizations can be stitched
together with the other sections' risk characterizations as they are completed later to prepare the
overall risk characterization of the risk assessment. Similarly, when sections of the risk
assessment are updated, the risk characterization for that section should be updated too, in
writing.
Decision makers are responsible for
,,, -11 , • >• • V*. f Risk characterizations must be
ensuring that a nsk charactenzation is written tor
each risk assessment and that a risk assessment/risk
characterization record is maintained.
placed in writing.
This chapter provides an overview of the roles and responsibilities of people and
organizations that write and use the risk characterization. Also, some administrative issues
concerning the written risk characterization are addressed such as record keeping, budget
planning, and legal considerations.
6.2 Risk Characterization Record
6.2.1 What is the Risk Characterization Record?
At its core, the risk characterization record is the written risk characterization. In
addition, the record should include the planning and scoping materials, a record of the risk
assessors/risk managers decisions, all parts of the risk assessment, including their individual
characterizations and the final risk characterization, with any updates. It needs to be maintained
in accordance with the organization's archiving procedures.
6.2.2 How Can the Risk Characterization Record Improve the Risk
Characterization Process?
A good risk characterization record allows future reference to the key findings and
strengths and weaknesses of the assessment. It can be studied by the risk manager to help better
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inform him/her about the facts in hand at that time. In addition, a good record helps ensure that
the Risk Characterization Policy is followed.
6.2.3 Where Should the Risk Characterization Record be Kept and For How
Long?
During the active conduct of the risk characterization, it is likely that each risk assessor
maintains the risk characterization record until his/her portion of the risk characterization is
completed. Establishment and maintenance of an archive where the risk characterization records
ultimately reside are an organization's responsibilities. The risk characterization record is part of
the risk assessment record.
6.3 Budget Planning
As soon as it is known in the planning and scoping process that a risk assessment will be
done, the resources needed to conduct the risk assessment and its characterization need to be
designated. It is the risk manager's/decision maker's responsibility to ensure that the necessary
resources are requested as part of the usual Agency budgetary processes. Risk characterization
needs to be considered as a normal part of doing business, just as peer review should be. Risk
assessment/risk characterization resource considerations should also be addressed in the analytic
blueprint for Agency rulemaking actions.
6.4 Legal Considerations
6.4.1 Are There Legal Ramifications from the Risk Characterization Policy?
The Risk Characterization Policy does not establish or affect legal rights or obligations.
Rather, it confirms the importance of risk characterization where appropriate, outlines relevant
principles, and identifies factors Agency staff should consider in implementing the Policy.
Except where provided otherwise by law, risk characterization is not a formal part of or
substitute for notice and comment on rulemaking or adjudicative procedures. EPA's decision to
characterize risk as part of the risk assessment in any particular case is wholly within the
Agency's discretion.
6.4.2 Is Legal Advice Needed?
With respect to risk characterization products, it is unlikely that legal advice will be
needed. However, as part of the risk characterization process, legal counsel, as appropriate,
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Risk Characterization Handbook Page 57
should be included in the "team" supporting the decision maker and work with risk assessors,
economists, and others, from planning and scoping through to the final decision.
6.5 Peer Review of Risk Characterization Handbook
A draft Risk Characterization Guide and associated case studies (i.e., Risk
Characterization Handbook) were peer reviewed by a group of experts outside of EPA. EPA
contracted Eastern Research Group, Inc. (ERG) to conduct the peer review (Contract No. 68-C-
98-1148). ERG selected the outside experts and held a workshop, open to the public, to conduct
the peer review. The workshop was held March 24-25, 1999 in Alexandria, Virginia. EPA used
the comments from this public peer review, comments received from reviewers inside the
Agency, and additional public comments to revise and finalize the Handbook into its current
form. A summary report containing peer review comments was issued on May 21, 1999 under
the auspices of the Office of Science Policy in the Office of Research and Development.
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Page 59
SUBJECT INDEX
This is an alphabetical listing of subjects from the Handbook and the pertinent page numbers
where they are found.
-A-
-B-
-C-
-D-
-E-
Accountability (20)
Administrative issues (55)
Alternatives (43)
Analysis (10)
Analysis plan (29)
Assistant Administrators (20, 22)
Assumptions (11, 39)
Audiences (47)
Bias(41)
Branch Chiefs (22)
Briefing packages (46)
Bright line (36)
Budget (56)
Bullet list (46)
Chemical-specific risk assessment
(20)
Children (38)
Clarity (16)
Communication (25)
Conceptual model (29)
Consistency (17)
Context (37, 49)
Criteria (15)
Decision makers (22)
Decision-making factors (51)
Division Directors (22)
Dose-response assessment (10)
Ecological risk assessment (10, 11)
-F-
-H-
-I-
-J-
-K-
-L-
-M-
-N-
-O-
Elements of risk characterization (35,
49)
Executive summary (46, 49)
Exposure assessment (10)
Fact sheets (47)
Factors (51)
Federal Register notices (47)
Format and length (49)
Hazard identification (10)
History (5)
Human health risk assessment (10,
11)
Implementation (8)
Information (24)
Informing Decision Makers (51)
Justify (24)
Key findings (11)
Key information (37)
Legal considerations (56)
Major conclusions (42, 50)
Manager (11)
NRC paradigm (10)
Number (13)
Office Director (22)
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Risk Characterization Handbook
-P-
-Q-
-R-
-S-
-T-
Office responsibility (25)
Peer review (14, 57)
People's roles (20)
Planning and scoping (27)
Policy choices (40)
Press releases (47)
Principles (14)
Problem formulation (10)
Public Relations notices (47)
Quantitative risk (13)
Reasonableness (18)
Regional Administrators (20, 22)
Regulation development (13)
Regulatory negotiations (14)
Research needs (43)
Risk assessor (20)
Risk assessor/risk manager dialog
(31)
Risk characterization (10)
Risk characterization criteria (14)
Risk Characterization Policy (7)
Risk characterization record (55)
Risk characterization-related
products (45)
Risk communication (13)
Risk estimates (37)
Risk manager (22)
Science Policy Council (SPC) (26)
Sensitive populations (38)
Site-specific risk assessment (21)
Speeches and talks (47)
Strengths and weaknesses (41)
TCCR(1,7, 8)
Transparency (13, 15)
-U-
-V-
Typology (31)
"Technical" risk characterization
(46)
Uncertainty (24, 40)
Variability (24, 40)
Visual presentation (47)
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Risk Characterization Handbook Page 61
COMMONLY USED ACRONYMS
AA Assistant Administrator
EPA Environmental Protection Agency
FYI For Your Information
GPRA Government Performance Results Act
IRIS Integrated Risk Information System
NAS National Academy of Sciences
NRC National Research Council
RA Regional Administrator
RED Reregistration Eligibility Decision
RfC Reference Concentration
ROD Record of Decision
TCCR Transparency, Clarity, Consistency and Reasonableness
TSCA Toxic Substances Control Act
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Risk Characterization Handbook Page A-l
APPENDIX A
U.S. Environmental Protection Agency
POLICY FOR RISK CHARACTERIZATION
March 1995
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Page A-2 Risk Characterization Handbook
Policy for Risk Characterization
INTRODUCTION
Many EPA policy decisions are based in part on the results of risk assessment, an analysis
of scientific information on existing and projected risks to human health and the environment.
As practiced at EPA, risk assessment makes use of many different kinds of scientific concepts
and data (e.g., exposure, toxicity, epidemiology, ecology), all of which are used to "characterize"
the expected risk associated with a particular agent or action in a particular environmental
context. Informed use of reliable scientific information from many different sources is a central
feature of the risk assessment process.
Reliable information may or may not be available for many aspects of a risk assessment.
Scientific uncertainty is a fact of life for the risk assessment process, and agency managers
almost always must make decisions using assessments that are not as definitive in all important
areas as would be desirable. They therefore need to understand the strengths and the limitations
of each assessment, and to communicate this information to all participants and the public.
This policy reaffirms the principles and guidance found in the Agency's 1992 policy
(Guidance on Risk Characterization for Risk Managers and Risk Assessors, February 26, 1992).
That guidance was based on EPA's risk assessment guidelines, which are products of peerreview
and public comment. The 1994 National Research Council (NRC) report, "Science and
Judgment in Risk Assessment," addressed the Agency's approach to risk assessment, including
the 1992 risk characterization policy. The NRC statement accompanying the report stated,"...
EPA's overall approach to assessing risks is fundamentally sound despite often-heard criticisms,
but the Agency must more clearly establish the scientific and policy basis for risk estimates and
better describe the uncertainties in its estimates of risk."
This policy statement and associated guidance for risk characterization is designed to
ensure that critical information from each stage of a risk assessment is used in forming
conclusions about risk and that this information is communicated from risk assessors to risk
managers (policy makers), from middle to upper management, and from the Agency to the
public. Additionally, the policy will provide a basis for greater clarity, transparency,
reasonableness, and consistency in risk assessments across Agency programs. While most of the
discussion and examples in this policy are drawn from health risk assessment, these values also
apply to ecological risk assessment. A parallel effort by the Risk Assessment Forum to develop
EPA ecological risk assessment guidelines will include guidance specific to ecological risk
characterization.
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Risk Characterization Handbook Page A-3
Policy Statement
Each risk assessment prepared in support of decision-making at EPA should include a
risk characterization that follows the principles and reflects the values outlined in this policy. A
risk characterization should be prepared in a manner that is clear, transparent, reasonable and
consistent with other risk characterizations of similar scope prepared across programs in the
Agency. Further, discussion of risk in all EPA reports, presentations, decision packages, and
other documents should be substantively consistent with the risk characterization. The nature of
the risk characterization will depend upon the information available, the regulatory application of
the risk information, and the resources (including time) available. In all cases, however, the
assessment should identify and discuss all the major issues associated with determining the
nature and extent of the risk and provide commentary on any constraints limiting fuller
exposition.
Key Aspects of Risk Characterization
Bridging risk assessment and risk management. As the interface between risk
assessment and risk management, risk characterizations should be clearly presented, and separate
from any risk management considerations. Risk management options should be developed using
the risk characterization and should be based on consideration of all relevant factors, scientific
and nonscientific.
Discussing confidence and uncertainties. Key scientific concepts, data and methods
(e.g., use of animal or human data for extrapolating from high to low doses, use of
pharmacokinetics data, exposure pathways, sampling methods, availability of chemical-specific
information, quality of data) should be discussed. To ensure transparency, risk characterizations
should include a statement of confidence in the assessment that identifies all major uncertainties
along with comment on their influence on the assessment, consistent with the Guidance on Risk
Characterization (attached). (Note added later: the Risk Characterization Handbook replaces the
Guidance on Risk Characterization)
Presenting several types of risk information. Information should be presented on the
range of exposures derived from exposure scenarios and on the use of multiple risk descriptors
(e.g., central tendency, high end of individual risk, population risk, important subgroups, if
known) consistent with terminology in the Guidance on Risk Characterization, Agency risk
assessment guidelines, and program-specific guidance. In decision-making, risk managers
should use risk information appropriate to their program legislation.
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Page A-4 Risk Characterization Handbook
EPA conducts many types of risk assessments, including screening-level assessments of
new chemicals, in-depth assessments of pollutants such as dioxin and environmental tobacco
smoke, and site-specific assessments for hazardous waste sites. An iterative approach to risk
assessment, beginning with screening techniques, may be used to determine if a more
comprehensive assessment is necessary. The degree to which confidence and uncertainty are
addressed in a risk characterization depends largely on the scope of the assessment. In general,
the scope of the risk characterization should reflect the information presented in the risk
assessment and program-specific guidance. When special circumstances (e.g., lack of data,
extremely complex situations, resource limitations, statutory deadlines) preclude a full
assessment, such circumstances should be explained and their impact on the risk assessment
discussed.
Risk Characterization in Context
Risk assessment is based on a series of questions that the assessor asks about scientific
information that is relevant to human and/or environmental risk. Each question calls for analysis
and interpretation of the available studies, selection of the concepts and data that are most
scientifically reliable and most relevant to the problem at hand, and scientific conclusions
regarding the question presented. For example, health risk assessments involve the following
questions:
Hazard Identification — What is known about the capacity of an environmental agent for
causing cancer or other adverse health effects in humans, laboratory animals, or wildlife
species? What are the related uncertainties and science policy choices?
Dose-Response Assessment — What is known about the biological mechanisms and
dose-response relationships underlying any effects observed in the laboratory or
epidemiology studies providing data for the assessment? What are the related
uncertainties and science policy choices?
Exposure Assessment — What is known about the principal paths, patterns, and
magnitudes of human or wildlife exposure and numbers of persons or wildlife species
likely to be exposed? What are the related uncertainties and science policy choices?
Corresponding principles and questions for ecological risk assessment are being discussed as part
of the effort to develop ecological risk guidelines.
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Risk Characterization Handbook Page A-5
Risk characterization is the summarizing step of risk assessment. The risk
characterization integrates information from the preceding components of the risk assessment
and synthesizes an overall conclusion about risk that is complete, informative and useful for
decision makers.
Risk characterizations should clearly highlight both the confidence and the uncertainty
associated with the risk assessment. For example, numerical risk estimates should always be
accompanied by descriptive information carefully selected to ensure an objective and balanced
characterization of risk in risk assessment reports and regulatory documents. In essence, a risk
characterization conveys the assessor's judgment as to the nature and existence of (or lack of)
human health or ecological risks. Even though a risk characterization describes limitations in an
assessment, a balanced discussion of reasonable conclusions and related uncertainties enhances,
rather than detracts, from the overall credibility of each assessment.
"Risk characterization" is not synonymous with "risk communication." This risk
characterization policy addresses the interface between risk assessment and risk management.
Risk communication, in contrast, emphasizes the process of exchanging information and opinion
with the public - including individuals, groups, and other institutions. The development of a risk
assessment may involve risk communication. For example, in the case of site-specific
assessments for hazardous waste sites, discussions with the public may influence the exposure
pathways included in the risk assessment. While the final risk assessment document (including
the risk characterization) is available to the public, the risk communication process may be better
served by separate risk information documents designed for particular audiences.
Promoting Clarity, Comparability and Consistency
There are several reasons that the Agency should strive for greater clarity, consistency
and comparability in risk assessments. One reason is to minimize confusion. For example, many
people have not understood that a risk estimate of one in a million for an "average" individual is
not comparable to another one in a million risk estimate for the "most exposed individual." Use
of such apparently similar estimates without further explanation leads to misunderstandings
about the relative significance of risks and the protectiveness of risk reduction actions.
EPA's Exposure Assessment Guidelines provide standard descriptors of exposure and
risk. Use of these terms in all Agency risk assessments will promote consistency and
comparability. Use of several descriptors, rather than a single descriptor, will enable EPA to
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Page A-6 Risk Characterization Handbook
present a fuller picture of risk that corresponds to the range of different exposure conditions
encountered by various individuals and populations exposed to most environmental chemicals.
Legal Effect
This policy statement and associated guidance on risk characterization do not establish or
affect legal rights or obligations. Rather, they confirm the importance of risk characterization as
a component of risk assessment, outline relevant principles, and identify factors Agency staff
should consider in implementing the policy.
The policy and associated guidance do not stand alone; nor do they establish a binding
norm that is finally determinative of the issues addressed. Except where otherwise provided by
law, the Agency's decision on conducting a risk assessment in any particular case is within the
Agency's discretion. Variations in the application of the policy and associated guidance,
therefore, are not a legitimate basis for delaying or complicating action on Agency decisions.
Applicability
Except where otherwise provided by law and subject to the limitations on the policy's
legal effect discussed above, this policy applies to risk assessments prepared by EPA and to risk
assessments prepared by others that are used in support of EPA decisions.
EPA will consider the principles in this policy in evaluating assessments submitted to
EPA to complement or challenge Agency assessments. Adherence to this Agency-wide policy
will improve understanding of Agency risk assessments, lead to more informed decisions, and
heighten the credibility of both assessments and decisions.
Implementation
Assistant Administrators and Regional Administrators are responsible for implementation
of this policy within their organizational units. The Science Policy Council (SPC) is organizing
Agency-wide implementation activities. Its responsibilities include promoting consistent
interpretation, assessing Agency-wide progress, working with external groups on risk
characterization issues and methods, and developing recommendations for revisions of the policy
and guidance, as necessary.
Each Program and Regional office will develop office-specific policies and procedures
for risk characterization that are consistent with this policy and the associated guidance. Each
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Risk Characterization Handbook Page A-7
Program and Regional office will designate a risk manager or risk assessor as the office
representative to the Agency-wide Implementation Team, which will coordinate development of
office-specific policies and procedures and other implementation activities. The SPC will also
designate a small cross-Agency Advisory Group that will serve as the liaison between the SPC
and the Implementation Team.
In ensuring coordination and consistency among EPA offices, the Implementation Team
will take into account statutory and court deadlines, resource implications, and existing Agency
and program-specific guidance on risk assessment. The group will work closely with staff
throughout Headquarters and Regional offices to promote development of risk characterizations
that present a full and complete picture of risk that meets the needs of the risk managers.
/s/
APPROVED: DATE: MAR 21 1995
Carol M. Browner, Administrator
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Risk Characterization Handbook Page B-l
APPENDIX B
WAQUOIT BAY CASE STUDY
The Waquoit Bay case study is not a complete risk characterization. It is an example of
the beginning of the ecological risk assessment process that includes a problem formulation
summary and a proposed risk characterization based on the planning and scoping for this risk
assessment.
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Page B-2 Risk Characterization Handbook
Contents
EXECUTIVE SUMMARY Page B-4
1. CONTEXT Page B-6
1.1 The Watershed Page B-7
1.2 The Watershed Case Study Team Page B-8
1.3 Problem Formulation Page B-9
1.3.1 Planning and Selection of Management Goals and Objectives .. Page B-9
1.3.2 Assessment Endpoints Page B-10
1.3.3 Conceptual Model Page B-l 1
1.3.4 Analysis Page B-l 1
2. RISK PARADIGM Page B-14
2.1 Measures of Exposure Page B-14
2.1.1 Estimating Nitrogen Load from Watershed and
Subwatersheds Page B-14
2.1.2 Validating the Nitrogen-Loading Model Page B-15
2.2 Measures of Effects of Nitrogen on Eelgrass Page B-16
2.3 Calculations and Uncertainties Page B-17
2.3.1 Risk Elements Page B-17
2.3.2 Integrating Nitrogen Exposure with Eelgrass Response Page B-17
2.3.3 Predicting Eelgrass Recovery Under Different Nitrogen-
Loading Scenarios Page B-l8
2.3.4 Additional Effects of Other Stressors on Eelgrass Page B-18
3. CONCLUSIONS Page B-19
4. RECOMMENDATIONS REGARDING DATA GAPS Page B-19
4.1 Other Stressors Affect Valued Resources Page B-19
5. LITERATURE CITATIONS Page B-20
Tables
Table 1. The Waquoit Bay Watershed Management Goal, Interpreted
as 10 Management Objectives Page B-9
Table 2. Impact Matrix for the Waquoit Bay Watershed Page B-12
Table 3. Stressor Rankings Based on Overall Effects on All Assessment Endpoints . . Page B-12
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Risk Characterization Handbook Page B-3
Table 4. Estimates of Percent Nitrogen Loading from Atmosphere, Fertilizer,
and Wastewater to Waquoit Bay Page B-15
Figures
Figure la. Conceptual model of the Waquoit Bay watershed ecological risk
assessment. This portion shows land use activities and stressors Page B-22
Figure Ib. Conceptual model of the Waquoit Bay watershed ecological risk
assessment. This portion shows how stressors may interact with
the ecological system to cause effects on valued resources Page B-24
Figure 2. Differences in arrival time of nitrogen between the static and
dynamic nitrogen loading models Page B-25
Figure 3. Changes in nitrogen loading alter the relative contribution of primary
producers to total production in shallow estuaries Page B-26
Figure 4. Hypothetical response of eelgrass to increases in nitrogen load Page B-27
Figure 5. Hypothetical relationship between the probable extent of eelgrass
habitat and nitrogen loading under high and low uncertainty Page B-28
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Page B-4 Risk Characterization Handbook
Waquoit Bay Watershed Ecological Risk Assessment:
Problem Formulation Summary and Proposed Risk Characterization
EXECUTIVE SUMMARY
Context
EPA sponsored the Waquoit Bay ecological risk assessment to evaluate the impact of
stressors introduced by human activities and to provide resource managers with viable options to
protect the Bay.
Waquoit Bay is a small estuary on the south coast of Cape Cod, Massachusetts. Its
watershed covers approximately 53 square kilometers (21 square miles) of freshwater streams
and ponds, salt ponds and marshes, pine and oak forests, barrier beaches, and open estuarine
waters. Waquoit Bay is in the fastest growing county in the state, and as the human population
grows, so does pressure on the valuable natural resources that have attracted people to the area.
This document presents only the problem formulation for the risk assessment, along with
summary information and a proposed plan for estimating risk.
Problem Formulation
Local resource managers identified a goal to reestablish and maintain water quality and
habitat conditions in Waquoit Bay and associated wetlands, rivers and ponds. Based on this goal,
a risk assessment team identified 10 management objectives that they believed were required to
achieve the goal. They then presented the objectives to the risk managers for their consideration
and approval.
The risk assessment team conducted a comparative risk analysis to help set priorities to
determine which stressors, assessment endpoints, and relationships should be examined further.
Stakeholders in the state helped identify the assessment endpoints, which include both an entity
(e.g., eelgrass) and a measurable attribute (e.g., distribution). These endpoints provide direction
for the assessment as well as a basis for the development of questions, predictions, models, and
analyses. After the team selected a focus for the assessment, it determined appropriate exposure
and effects measures and models and described the approaches to characterizing risks.
The comparative risk analysis identified nitrogen loading as a primary stressor in
estuarine habitats of the Waquoit watershed; submerged aquatic vegetation, specifically eelgrass
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Risk Characterization Handbook Page B-5
(Zostera marina) habitat was identified as the most important assessment endpoint. Numerous
studies have shown that eelgrass meadows provide a very good habitat for many commercially
and recreationally important fish and shellfish. Therefore, protecting eelgrass protects fish and
invertebrate species.
Eelgrass requires a lot of light to grow. In Waquoit Bay, increased phytoplankton
(microscopic one-celled organisms) and seaweed populations, fueled by the addition of nitrogen
from coastal development, have decreased the amount of light penetrating the water. In 1951,
eelgrass meadows covered most of Waquoit Bay and its adjoining coastal ponds and rivers.
Today, eelgrass is absent from the Bay and has declined significantly in the adjoining tributaries
and ponds. Species dependent on eelgrass, particularly scallops, have likewise decreased.
Although it has been known that nitrogen loading contributes to the loss of submerged
aquatic vegetation, predictive relationships between nitrogen sources and loading and biological
response have not been developed for estuaries, such as Waquoit Bay. Because of these findings
and due to the constraints of limited data to assess other endpoints, the risk assessment focused
on the risk to eelgrass habitat from nitrogen loading from the adjacent watershed.
Risk Paradigm
The analysis plan involved estimating the loading of nitrogen to the watershed/estuary
(measures of exposure), and evaluating how a given load of nitrogen directly or indirectly
impacts eelgrass habitat (measures of effects).
Exposure
The team used a nitrogen-loading model to estimate the amount of nitrogen that arrives at
the edge of the estuary. This model showed that of the three major contributors to nitrogen over-
loading—atmospheric deposition, septic systems, and fertilizer use—septic systems are the
largest source of nitrogen to the estuary. The team verified the model predictions against actual
measurements of nitrogen in groundwater about to enter the estuary. The team also found that
model predictions of nitrogen coming from wastewater agreed with stable isotopic ratios of
nitrogen in groundwater.
Effect
Increases in nitrogen change the composition of primary plant producers, such as
eelgrass, seaweed, and phytoplankton, in receiving waters. The team used the estuarine
simulation model to predict the response of different plant producers to increasing nitrogen loads.
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The stressor-response relationship was defined by plotting nitrogen-loading rates provided by the
static and dynamic loading models against measures of ecological effect. The deleterious effect
of excess nitrogen on eelgrass in shallow coastal bays is primarily an indirect one; nitrogen
stimulates the rapid growth of phytoplankton and seaweed. Therefore, analyzing the effects of
nitrogen on eelgrass first requires estimating its effects on algae growth and other intermediates.
Calculations and Uncertainties
The risk assessment team will estimate the risk by integrating the output from the
nitrogen-loading models with the predictions of the ecological response model. With knowledge
of the location of houses and of groundwater travel times, it will be possible to estimate how
much nitrogen can be removed under different management scenarios and how much longer the
rest of the nitrogen will remain in the aquifer traveling to the Bay. However, that information
alone will not be sufficient to predict the time when water quality conditions can support
eelgrass. The contribution of benthic processes and sediment conditions also must be
considered. These parameters increase the uncertainty surrounding the ability to estimate time to
recovery.
If nitrogen were reduced and eelgrass were to reestablish itself or be replanted, other
stressors, such as dredging activities, dock construction over eelgrass beds, and propeller scour
from passing boats, may become important. As funding permits, relationships among other
stressors and valued resources will be evaluated.
4. CONTEXT
This document includes summary information from the planning and problem
formulation report produced for the Waquoit Bay ecological risk assessment case study and a
description of the planned risk characterization component of the risk assessment.
EPA sponsored the Waquoit Bay watershed ecological risk assessment to evaluate the
danger to valued water resources from stressors caused by human activities, and to provide
resource managers with viable options to protect the resources. A qualitative risk analysis
identified nitrogen loading as a primary stressor in estuarine habitats of the watershed and
eelgrass habitat as the most important assessment endpoint. Because of these findings and due to
constraints of limited data to assess other endpoints, the risk assessment focused on the risk to
eelgrass habitat from nitrogen loading from the adjacent watershed.
The goal of the Waquoit Bay ecological risk assessment is to provide managers with
answers to key questions:
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a) What are the sources of nutrients and their relative contributions?
b) What will be the effects of different degrees of nutrient reduction?
1.1 The Watershed
Waquoit Bay is a small estuary on the south coast of Cape Cod, Massachusetts. Its
watershed covers about 53 square kilometers (21 square miles) of freshwater streams and ponds,
salt ponds and marshes, pine and oak forests, barrier beaches, and open estuarine waters. The
land and water are home, spawning ground, and nursery for plant and animal life including
piping plovers, least terns (endangered birds), the sandplain gerardia (an endangered plant),
alewife, winter flounder, blue crab, scallops and clams, and other fish species that migrate
through the estuary. Initially valued for hunting, farming, and fishing, Waquoit Bay now
primarily provides aesthetic and recreational opportunities, demands that have generated
residential development and business for local marine-dependent industries.
Cape Cod's economic viability is largely dependent on tourists who are drawn to the
sandy beaches, seafood restaurants, boating opportunities, and water recreation areas. Thus the
economy on Cape Cod and the environment on Cape Cod are mutually inter-dependent. The
once rural surroundings have become increasingly suburbanized as bedroom and retirement
communities have sprung up. Barnstable County, where the Waquoit Bay watershed is located,
is the fastest growing county in Massachusetts. As the population grows, so does pressure on the
valuable natural resources that have attracted people to the area.
Living in bottom sediments of shallow embayments of the northwestern Atlantic is a
flowering plant known as eelgrass (Zostera marina). Numerous studies have shown that
submerged aquatic vegetation, such as eelgrass meadows provide a very good habitat for many
commercially and recreationally important fish and shellfish. Eelgrass needs a lot of light to
grow. In Waquoit Bay, increased phytoplankton (microscopic one-celled organisms) and
seaweed populations, fueled by the addition of nitrogen from coastal development, have
decreased the amount of light penetrating the water. In 1951, eelgrass meadows covered most of
Waquoit Bay proper and its adjoining coastal ponds and rivers. Today, eelgrass is absent from
the Bay proper and has declined significantly in the adjoining tributaries and ponds. Species
dependent on eelgrass, particularly scallops, have likewise decreased. In 1987, 1988, and 1990,
fish kills occurred in Waquoit Bay, and the northern beach was covered with thousands of dead
winter flounder, shrimp, blue crabs, and other estuarine species.
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In Ashumet and Johns Ponds, blooms of phytoplankton have changed the color of the
water and depleted oxygen levels in the bottom waters of the pond. Fish kills occurred in
Ashumet Pond in 1985 and 1986.
The Massachusetts Military Reservation, a Superfund site within the watershed of
Waquoit Bay, is the source of several plumes of toxic chemicals that threaten drinking water
supplies.
As with many coastal areas where marine recreation is important, the number of boats
and request for permits to build docks have increased in the Waquoit Bay area. Resuspended
sediments from boating activities, toxic chemicals from pressure treated wood in docks, propeller
scarring from boat motors, and shading of eelgrass beds from docks are all potential sources of
stress to valuable marine resources.
Concern about the effects of development on Cape Cod have led to several initiatives.
Among these have been the creation of a regional planning agency, the Cape Cod Commission,
that has authority over developments of regional impact; the work of the Association for the
Preservation of Cape Cod, which has contributed to the protection of the Cape's drinking water
supply, among other issues; the efforts of the Waquoit Bay Land Margin Ecosystem Research
Project, a multi-institutional, interdisciplinary program that has contributed to our knowledge of
the problem of nitrogen overloading; the designation of a U.S. Fish and Wildlife Refuge in parts
of the Waquoit Bay watershed, which will remove many areas from development; the
designation of the Waquoit Bay area as an Area of Critical Environmental Concern, a
Massachusetts designation that provides for special scrutiny to any alterations that might impact
natural resources; and the designation of the Waquoit Bay National Estuarine Research Reserve
that also serves to protect the resources of the Bay and its adjacent lands.
1.2 The Watershed Case Study Team
The EPA-sponsored ecological risk assessment underway in the Waquoit Bay watershed
builds on the above efforts by creating a mechanism to integrate the results of various research
and planning efforts into management options for local coastal decision-makers. The Waquoit
Bay watershed was selected as one of several EPA-sponsored ecological risk assessment case
studies because of interest by local, state, and federal organizations in the watershed, the type of
watershed (estuarine), the diversity of stressors (e.g., nutrients, toxic chemicals, obstructions,
altered flow), a substantial existing database, and willingness by the Waquoit Bay National
Estuarine Research Reserve (WBNERR) and EPA Region 1 to lead the risk assessment team.
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Page B-9
The prior activities and current and planned work of the risk assessment are described in
the following sections that emphasize the major elements of planning and problem formulation
(management goal development, selecting assessment endpoints, preparing a conceptual model,
and producing an analysis plan) and a proposed risk estimation.
1.3 Problem Formulation
1.3.1 Planning and Selection of Management Goals and Objectives
The management goal was developed through a multistep planning process initiated and
completed by the team. The process included a public meeting to initiate the process, evaluation
of goals by interested organizations in the watershed, and a meeting of members of these
organizations to review and approve the management goal and team-derived objectives. The
management goal is a qualitative statement that captures essential interests expressed by different
management organizations and the public in the Waquoit Bay watershed. The goal developed for
the Waquoit Bay watershed risk assessment through community involvement is:
Reestablish and maintain water quality and habitat conditions in Waquoit Bay and
associated wetlands, freshwater rivers, and ponds to (1) support diverse, self-sustaining
commercial, recreational, and native fish and shellfish populations and (2) reverse
ongoing degradation of ecological resources in the watershed.
In order for the management goal to support an ecological risk assessment, the risk assessment
team evaluated the goal and interpreted it as 10 management objectives believed to be required to
achieve the goal (see Table 1). The objectives were intended to state explicitly the management
results implied in the general goal statement. By performing this kind of evaluation, the team
provided feedback to the managers on the ecological characteristics of the goal, developed a
systematic process for identifying assessment endpoints that could be directly linked to the
management goal, and provided a way to measure achievement of the goal for risk managers.
Table 1. The Waquoit Bay Watershed Management Goal, Interpreted as 10 Management
Objectives.
Affected Area
Number
Component Management Objective
Estuarine and
Freshwater
1
Reduce or eliminate hyp oxic or ano xic events
Prevent toxic levels of contamination in water, sediments, and biota
Restore and maintain self-sustaining native fish populations and their habitat
Estuarine
Reestablish viable eelgrass beds and associated aquatic communities in the
Bay
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Risk Characterization Handbook
Freshwater
5
6
7
8
9
10
Reestablish a self-sustaining scallop population in the Bay that can support a
viable sport fishery
Protect shellfish beds from bacterial contamination that results in closure
Reduce or eliminate nuisance macroalgal growth
Prevent eutrophication of rivers and ponds
Maintain diversity of native biotic communities
Maintain diversity of water-dependent wildlife
Table 1 is partitioned into three categories. The "Estuarine and Freshwater" category
includes three objectives that are common to both surface water types. Four objectives under the
"Estuarine" category and three objectives under the "Freshwater" category are unique to those
waters. The 10 objectives are stated as goals for specific aspects of exposure, stressors, and
valued ecological resources. Assessment endpoints were selected and justified based on these
objectives. Although risk managers developed the goal, the specific management objectives
were generated by the team based on available information on watershed resources. The
objectives were then provided to the risk managers for their consideration and approval.
1.3.2 Assessment Endpoints
Following the assessment of available information for the watershed, the team selected
eight assessment endpoints that directly link management goals to measurable ecological values
in the watershed. Assessment endpoints are measurable attributes of valued resources identified
by the stakeholders that represent ecologically important components of the ecosystems.
Assessment endpoints include both an entity (e.g., eelgrass) and ameasurable attribute (e.g.,
distribution), and they provide direction for the assessment as well as a basis for the development
of questions, predictions, models, and analyses. The first seven endpoints (below) that the team
selected represent ecological concerns about estuarine and freshwater components of the eco-
system.
1) Estuarine eelgrass habitat abundance and distribution
2) Resident and juvenile nursery estuarine finfish species diversity and abundance
3) Estuarine benthic invertebrate diversity, abundance, and distribution
4) Migratory (stream) fish reproduction
5) Freshwater stream assemblages, diversity, and abundance
6) Freshwater pond trophic status
7) Wetlands habitat
8) Barrier beach habitat
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1.3.3 Conceptual Model
Devised by the ecological risk assessment team with input from stakeholders, the general
watershed conceptual model (Figure la and b) is a broad representation of relationships among
human activities in the watershed (sources), the stressors believed to occur as a result of those
sources, and ecological effects likely to occur in each of the assessment endpoints. The pathways
from sources of stressors to valued resources are actually risk hypotheses that can be analyzed
during the ecological risk assessment process.
Because eelgrass is the foundation for the estuarine community and because its presence
indicates good water quality, it was targeted as a high priority assessment endpoint in this
ecological risk assessment (Figure la and b).
1.3.4 Analysis
Problem formulation concludes with the development of an analysis plan. For the
Waquoit Bay ecological risk assessment, the risk assessment team first conducted a comparative
risk analysis to help prioritize which stressors, assessment endpoints, and relationships should be
examined further. Once a focus for the assessment was selected, the team determined
appropriate exposure and effects measures and models and described the approaches to
characterizing risks.
Comparative Risk Analysis
To help focus the risk assessment, the risk assessment team ranked stressors in terms of
their potential risk to all resources in the watershed using a "fuzzy set" decision analysis method
based on best professional judgment (Harris et al., 1994). The analysis ranked the stressors in
order of greatest overall contribution of risk to the endpoints, based on an ordinal effect of a
stressor on that endpoint, ranging from no effect to severe effect. For example, in Table 2, the
effect of nutrients on eelgrass habitat is assigned a 3 (severe indirect effect), but the effect of
physical alteration on eelgrass habitat is considered a 1 (slight effect).
The results of the comparative analysis ranked nutrients as the primary stressor in the
watershed followed by physical alteration of habitat, flow alteration, harvest pressure,
resuspended particulates, and toxic chemicals (Tables 2, 3).
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Risk Characterization Handbook
Table 2. Impact Matrix for the Waquoit Bay Watershed. Each cell represents the estimated
effect of a stressor on an endpoint, on an ordinal scale from 0 (no effect) to 3 (severe effect).
Stressors
Toxic
Chemicals
Altered Flow
Resuspended
Participates
Nutrients
Physical
Alteration
Harvest
Pressure
Assessment Endpoints
Migratory
Fish
1
3
1
1
1
2
Fresh-
water
Biota
1
2
1
1
1
1
Wetland
Habitat
1
2
1
1
1
0
Pond
Trophic
Status
0
0
0
3
0
0
Eelgrass
Habitat
0
0
1
3
2
0
Estuarine
Inverte-
brates
1
0
1
2
1
2
Estuarine
Fish
1
1
1
2
1
2
Barrier
Beaches
0
0
0
0
2
0
Table 3. Stressor Rankings Based on Overall Effects on All Assessment Endpoints.
Stressors
Nutrients
Physical Alteration of Habitat
Altered Flow
Toxic Chemicals
Harvest Pressure
Resuspended Particulates
Unweighted
1
2
3
4
5
6
Weighted for
Persistence
1
2
3
4
5
6
Weighted for
Persistence and
Interaction
1
2
3
4
5
6
The comparative analysis established that nutrients affected three assessment endpoints in
the estuarine system to different degrees: eelgrass habitat (severe effect), estuarine invertebrates
(moderate effect), and estuarine fish (moderate effect). These assessment endpoints are inter-
related because eelgrass meadows provide habitat to both estuarine fish and invertebrate species.
Therefore, protecting eelgrass will protect fish and invertebrate species.
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The comparative analysis ranked other stressors to eelgrass in addition to nutrients:
resuspended particulates (minor effect) and physical alteration of habitat (moderate effect). The
team concluded that these stressors were not as important for reasons discussed below.
Although rivers enter Waquoit Bay, they do not carry a sediment load because rivers on
Cape Cod are fed by groundwater and are really drains for the aquifer. The particle size and
composition of the Cape's sandy glacial soils are such that any suspended particles sediment out,
and the sandy soils quickly absorb precipitation so there is very little surface runoff.
The resuspended particles in waters of Waquoit Bay are organic matter from decaying
algae, plants, and other estuarine organisms. Studies of particle settling following passage of
boats whose motors disrupt the bottom show that the particles very quickly settle out. Although
there are many boats on the Bay and adjacent tributaries and ponds on weekends. Little boat
traffic occurs during weekdays. Docks and marinas, where heavy boat use is expected, comprise
only a very small part of the surface area of the Waquoit Bay estuarine complex.
Physical alteration of habitat due to activities, such as shellfish harvesting, motor boat
operation, and construction of docks can fragment or eliminate eelgrass habitat. The number,
frequency, and placement of these activities are such that deleterious effects would be restricted
to a small area of the overall estuarine complex.
Focus of Analysis Plan
The team concluded that reducing nutrient loads to restore water quality to conditions that
would support eelgrass growth was the most important stressor-endpoint relationship to evaluate
and that less critical stressors, such as resuspended particulates and physical alteration of habitat,
would be important to monitor and assess once water quality was improved via reducing the
nutrient load.
Therefore, the risk assessment team decided to focus on one stressor (nitrogen) and one
assessment endpoint (eelgrass) based on the results of the comparative analysis and also on
limitations of data and funding. Many other valued resources in the estuarine waters utilize
eelgrass beds. For example, juvenile scallops attach to eelgrass blades, reducing their risk from
predators. Winter flounder spawn in eelgrass meadows. The team believed that focusing on
eelgrass distribution would encompass risks to other valued resources.
Although it has been known for some time that nitrogen loading contributes to estuarine
eutrophication and loss of submerged aquatic vegetation in Waquoit Bay and other estuaries of
Cape Cod, predictive relationships between nitrogen sources and loading and the biological
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response of the estuary have not been developed for estuaries, such as Waquoit Bay. The
objective of this analysis is to develop a link between modeled estimates of nitrogen loading and
predicted ecological effects in the estuary.
The analysis plan to evaluate risk from nitrogen loading to eelgrass habitat involves (1)
estimating the loading of nitrogen to the watershed and estuary (measures of exposure), and (2)
evaluating how a given load of nitrogen directly or indirectly impacts eelgrass habitat (measures
of effects). These analyses are performed on subwatersheds and their adjacent estuaries that have
experienced different degrees of development resulting in different amounts of nitrogen entering
the estuaries. Information about past and present land use is employed to forecast future changes
in the estuary in response to future loads of nitrogen.
2. RISK PARADIGM
2.1 Measures of Exposure
2.1.1 Estimating Nitrogen Load from Watershed and Subwatersheds
The hypothesis underlying this part of the analysis is that development on coastal
watersheds increases the amount of nitrogen entering coastal waters. On Cape Cod, the number
of houses has been positively related to the median amount of nitrate measured in groundwater
(Persky, 1986). Nitrogen in groundwater eventually travels to receiving waters of the Waquoit
Bay estuarine complex.
The analysis relies on a nitrogen-loading model to estimate the amount of nitrogen that
arrives at the edge of the estuary (Valiela et al., 1997). The model sums all nutrient loads,
subtracts losses during transport, and yields a value for nitrogen arriving at the edge of the
estuary (or salt marsh). The nitrogen-loading model includes more than 50 input terms (e.g.,
number of houses, area in agriculture, amount of nitrogen fertilizer applied to lawns, per capita
contribution of nitrogen to septic systems, percent loss of nitrogen in septic systems, percent loss
of fertilizer nitrogen).
Many of the parameters in the nitrogen-loading calculation are very uncertain. For
example, the amount of nitrogen lost in septic systems on sandy soils like those on Cape Cod
ranges from 10-90% (Valiela et al., 1997). Estimates of the contribution of dry deposition and of
dissolved organic nitrogen to the total amount of atmospheric nitrogen are also highly uncertain
due to limited sampling and analyses. Estimates of uncertainty surrounding model inputs and
outputs have been calculated (Collins et al. submitted) and will be applied to the final nitrogen-
loading values.
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Because groundwater travels approximately 100 meters per year in the watershed, there is
a lag between the time of development and the time that nitrogen arrives at the estuary. The
nitrogen-loading model can be run in dynamic mode to determine the actual load of nitrogen
arriving at the estuary at any given time (Figure 2). The nitrogen-loading model can also be run
in static or dynamic mode using historic land use information to hindcast nitrogen loading and
under a variety of future build-out scenarios to predict future loading and effects.
Within the Waquoit Bay watershed are several subwatersheds that can, in turn, be divided
into recharge areas. The load of nitrogen can be estimated for the entire watershed or its
component parts.
The nitrogen-loading model shows that atmospheric deposition, septic systems, and
fertilizer use are the three major contributors to nitrogen overloading (Table 4). Although more
nitrogen is delivered to the watershed from the atmosphere, much of that nitrogen is taken up by
vegetation, soils, and the aquifer during travel to the estuary. Septic systems are the largest
source of nitrogen to the estuary (Valiela et al., 1997). The relative contribution of these three
sources are important to local coastal decision-makers since the source of most of the
atmospheric nitrogen is far outside the watershed.
Table 4. Estimates of Percent Nitrogen Loading from Atmosphere, Fertilizer, and
Wastewater to Waquoit Bay.
Source
Atmospheric deposition
Septic system
Fertilizers
Upper ponds
Percent to Watershed
56
27
14
2
Percent to Estuary
30
48
15
8
2.1.2 Validating the Nitrogen-Loading Model
Modeled predictions of the load of nitrogen to the edge of the estuary were validated in
two ways. First the model predictions were verified against actual measurements of nitrogen in
groundwater about to enter estuaries. As with model predictions, there is uncertainty associated
with the groundwater measures. Second, model predictions of wastewater nitrogen were
compared to stable isotopic ratios of nitrogen in groundwater. The predictions of nitrogen
coming from wastewater agreed with the values derived from stable isotopes.
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The nitrogen-loading model predicts a concentration of nitrogen arriving at the edge of a
salt marsh (if present) or at the edge of the water, but a correction is necessary to estimate the
amount of nitrogen actually available to primary producers in the water. A biological process
(denitrification) that occurs within salt marshes can reduce the amount of nitrogen that finally
enters the Bay. Salt marsh areas and data on denitrification in Waquoit Bay sediments are used
to estimate the potential interception of land-derived nitrogen. These terms are applied as
correction terms to the model predictions. Water column nutrient and salinity data from different
estuarine reaches are used to estimate losses or gains of nitrogen in excess of dilution during
down-estuary transport.
The validated estimates of nitrogen from the watershed minus losses in marshes and
sediments and during travel down the river yield an amount of nitrogen available to the primary
producers in the estuary(ies).
2.2 Measures of Effects of Nitrogen on Eelgrass
As is shown in the conceptual model (Figure 1), the deleterious effect of excess nitrogen
on eelgrass, which requires a lot of light, in shallow coastal bays is primarily an indirect one.
Phytoplankton shade the water column, and seaweed grow over, shade, and displace the eelgrass.
Therefore, to analyze effects of nitrogen on eelgrass requires first estimating the effects on algae
growth and other intermediates. To these are added physical and temporal factors of the
estuarine system that affect nutrient availability and other aspects of plant growth.
The analysis utilizes an estuarine model to simulate the effects of nitrogen inputs, water
residence time, mixing in the water, and seasonal changes in light and temperature on the system
metabolism of phytoplankton, seaweed, and eelgrass. The model compares responses (especially
eelgrass decline) to different nitrogen-loading rates across a variety of subestuaries. The influ-
ence of any one subestuary on another, or on the whole Waquoit Bay system, is assessed. Model
output is validated with data from estuaries not used in development of the model.
Increases in nitrogen change the mix of primary producers (plants such as eelgrass,
seaweed, and phytoplankton) in receiving waters. The estuarine simulation model predicts the
response of different producers to increasing nitrogen loads (Figure 3).
The nitrogen-loading model and estuarine system model can be performed under a variety
of nitrogen-loading scenarios (e.g., build-out) in an attempt to hindcast and forecast loading and
response. As new information becomes available during the analysis phase of the risk assess-
ment, the models can be updated.
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2.3 Calculations and Uncertainties
No risk calculations are available at this time. Research in Waquoit Bay and elsewhere
suggests that development in coastal watersheds increases the amount of nitrogen entering
coastal watersheds and their adjacent waters. On Cape Cod, the nitrate concentration in
groundwater is higher below developed landscapes than below naturally vegetated areas (Persky
1986). The nitrogen in groundwater travels to coastal bays where it fertilizes vegetation.
Research shows that once in coastal bays nitrogen is rapidly taken up by some species of algae
(phytoplankton and seaweed) increasing their growth rates. These algae shade the water column
so less light reaches the bottom.
Thus, increased loads of nitrogen from coastal development leads to overgrowth of
opportunistic species of algae that alter the functioning of the estuarine system. These alterations
include changes in water chemistry (e.g., dissolved oxygen concentration), habitat loss, and
abundance of some species.
2.3.1 Risk Elements
To define the stressor-response relationship, nitrogen-loading rates provided by the static
and dynamic loading models will be plotted against measures of ecological effects. Achieving
low nitrogen loading to Waquoit Bay will require nitrogen source control, as well as a sufficient
time lag to allow nitrogen currently in the groundwater to be flushed out. The travel times of
groundwater vary across the watershed, thus, nitrogen loading to the estuary is not a function of
land use at any one point in time. The two sets of models and their estimated uncertainties can
be used to predict the effects of different nutrient management scenarios for Waquoit Bay using
information about the groundwater travel time, location of houses in the watershed, time to
remove different percentages of nitrogen, and the time required for the remaining nitrogen to
travel to the estuary.
Septic systems and fertilizers are two local sources of nitrogen, but atmospheric
deposition can originate hundreds of miles from the Waquoit Bay watershed. Viable options to
reduce nitrogen to the extent necessary to improve water quality will depend on the relative
contributions of different nitrogen sources, the amount of nitrogen that needs to be eliminated,
and the uncertainty surrounding that estimate.
2.3.2 Integrating Nitrogen Exposure with Eelgrass Response
Risk characterization will include integration of the output from the nitrogen-loading
models with the predictions of the ecological response model (see Section 2.1 for description of
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individual models). The response of eelgrass to effects of increased nitrogen can be depicted as
in Figure 4.
2.3.3 Predicting Eelgrass Recovery Under Different Nitrogen-Loading Scenarios
Ecosystems are highly complex and variable systems that can and do change over time in
species composition, distribution, and abundance. Scientists working in the waters of Waquoit
Bay agree that nitrogen overloading is the major stressor on eelgrass and that decreasing the load
of nitrogen to the Bay may result in water quality conditions that could support eelgrass, but there
is no certainty that eelgrass will reestablish itself or maintain itself if replanted.
Predicting changes in water quality over time that may result from a decrease in nitrogen
loading requires incorporating the travel time of nitrogen in groundwater. With knowledge of the
location of houses and groundwater travel times, it is possible to estimate how much nitrogen
will be removed under different management scenarios and how much longer the rest of the
nitrogen will remain in the aquifer traveling to the Bay. But that information alone is not
sufficient to predict the time when water quality conditions would support eelgrass. The
contribution of benthic processes and sediment conditions also must be factored into predictions.
These parameters increase the uncertainty surrounding the ability to estimate time for recovery.
Output for Examining Model Results and Attendant Management Options
A target load of nitrogen that will lead to water quality conditions that support eelgrass
can be identified for specific subembayments or the whole system. Figure 5 illustrates how such
a relationship might be portrayed. The probability that eelgrass might cover 10% or less of avail-
able habitat is plotted against nitrogen-loading levels to the estuary. If the uncertainty levels in
these estimates are high, a curve with a shallow slope results. If uncertainty is low, a closer
relationship between eelgrass cover and nitrogen loading exists, and the slope of the curve will
be steep. For a 25% probability that eelgrass habitat will be 10% or less of available habitat (or a
75% chance of recovery), required nitrogen loading would be estimated to be much lower under
conditions of high uncertainty.
2.3.4 Additional Effects of Other Stressors on Eelgrass
If nitrogen were reduced and eelgrass reestablishes itself or is replanted, other stressors
may become important. For example, remaining small stands of eelgrass may be further
impacted by natural events (e.g., in 1991, Hurricane Bob overwashed a spit on Washburn Island,
burying an eelgrass bed on the inside of Eel Pond). Building docks over eelgrass beds, dredging
activities, propeller scour from passing boats, and mooring scars all stress eelgrass.
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3. CONCLUSIONS
This document represents only a problem formulation at this time. A more complete
ecological risk assessment is forthcoming. For further information on the characterization of
risk, see Section 2.3 of this document.
4. RECOMMENDATIONS REGARDING DATA GAPS
4.1 Other Stressors Affect Valued Resources
As funding permits, relationships among other stressors and valued resources will be
evaluated.
Physical Alteration of Habitat. The loss of barrier beaches due to insufficient sand
transport cannot be addressed in this assessment. Wetlands are an important habitat in the
watershed. To date little work has been done on wetlands loss, but as results become available,
they will be incorporated into the final risk assessment document if possible.
Altered Flow. The sandy soils of the Waquoit Bay watershed hold copious amounts of
water. Future development could affect the quality of groundwater, which has been degraded
due to development, and the number of possible well sites. Other potential problems include loss
of wetlands function and habitats for trout and alewife spawning due to changes in flow. It is
hoped that as more research is conducted, these issues can be addressed.
Toxic Chemicals. A large contingent of scientists and policy-makers are evaluating the
problem of toxic plumes emanating from the Superfund site. These stressors may affect the
quality of Johns and Ashumet ponds, as well as freshwater and saltwater bodies downgradient.
As results become available, the risk assessment team will include their findings in the final
Waquoit Bay Ecological Risk Assessment product if possible.
Harvest pressure. Harvesting of fish mainly occurs offshore and is beyond the scope of
this assessment. Increased stress on valuable finfish populations comes from degraded estuarine
habitats where many offshore fish spawn.
Resuspended Particulates. There is concern that boating, dredging, and shell-fishing
activities may resuspend sediments causing harm to valued resources. These issues are under
study at Waquoit Bay by the National Estuarine Research Reserve Research Coordinator, Dr.
Richard Crawford. Pertinent results will again be added to the risk assessment document if
possible.
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Page B-20 Risk Characterization Handbook
5. LITERATURE CITATIONS
Collins, G., J. Kremer, and I. Valiela. submitted. Assessing uncertainty in estimates of nitrogen
loading to estuaries.
Harris, H. J., R. B. Wenger, V. A. Harris, and D. S. Devault. 1994. A method for assessing
environmental risk: a case study of Green Bay, Lake Michigan, USA. Environmental
Management 18(2):295-306.
Persky, J. H. 1986. The relation of ground-water quality to housing density, Cape Cod,
Massachusetts. Water Resources Investigation Report 86-4093. U.S Geological Survey.
Marlborough, MA.
Valiela, I., G. Collins, J. Kremer, K. Lajtha, M. Geist, B. Seely, J. Brawley, and C. H. Sham.
1997. Nitrogen loading from coastal watersheds to receiving estuaries: new method and
application. Ecological Applications 7(2):358-380.
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Risk Characterization Handbook
Page B-21
Waquoit Bay Watershed
Conceptual Model
Fertilizer
A pplic atio n
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Figure la. Conceptual model of the Waquoit Bay watershed ecological risk assessment. This
portion shows land use activities and stressors.
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Page B-22 Risk Characterization Handbook
THIS PAGE INTENTIONALLY LEFT BLANK
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Risk Characterization Handbook
Page B-23
CS
Trout &
Herring
Pond
Community
Wetland
Habitat
E stuarine
Invertebrates
E stuaiine
Fish
B airier
Beaches
Figure Ib. Conceptual model of the Waqyiut Bay watershed ecological risk assessment. This shows
how stressors may interact with the ecological system to cause effects on valued resources.
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Page B-24 Risk Characterization Handbook
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Page B-25
6000 T
1
1850 1860 1870 1880 1890 19001910 1920 19301940 1950 1960 1970 1980 19902000 2010 2020 2030 2040 2050
Year
Figure 2. Differences in arrival time of nitrogen between the static and dynamic nitrogen loading models. An example from the Jehu
Pond subwatershed of the Waquoit Bay watershed.
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Page B-26
Risk Characterization Handbook
100
100
200
300
400
500
Figure 3. Changes in nitrogen loading alter the relative contribution of primary producers
to total production in shallow estuaries (Valiela et al., 1997).
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Risk Characterization Handbook
Page B-27
I-H
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Page B-28
Risk Characterization Handbook
a ts ioo%-
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Figure 5. Hypothetical relationship between the probable extent of eelgrass habitat and nitrogen
loading under high and low uncertainty (J. Gerritsen, Pers. Com.). See text for explanation.
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Risk Characterization Handbook Page C-l
APPENDIX C
GENERIC KETONE CASE STUDY
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Page C-2 Risk Characterization Handbook
Contents
EXECUTIVE SUMMARY Page C-3
1. CONTEXT Page C-6
1.1 Toxic Release Inventory Page C-6
1.2 Scope and Purpose of Generic Ketone Assessment Page C-7
2. RISK PARADIGM Page C-7
2.1 Hazard Identification Page C-7
2.2 Exposure Assessment Page C-8
2.2.1 Estimates of Ambient Air Concentrations Page C-9
2.2.2 Estimates of Surface Water Concentrations and Drinking Water
Consumption Page C-10
2.3 Dose-Response, Calculations, and Uncertainties Page C-ll
2.3.1 MOE Calculations for Ambient Air Concentrations at
the Fence Line Page C-12
2.3.2 MOE Calculations for Releases to Surface Water Page C-14
3. CONCLUSIONS Page C-15
4. RECOMMENDATIONS REGARDING DATA GAPS Page C-15
5. LITERATURE CITATIONS Page C-16
APPENDIX A
HAZARD AND EXPOSURE ASSESSMENTS OF GENERIC KETONE . . . Page C-17
Tables
Table 1. Estimated Ambient Air Concentrations of Generic Ketone
For Three Facilities Page C-9
Table 2. Estimated Ambient Air Concentrations of Generic Ketone — Impact
of Pattern of Release Page C-10
Table 3. Acute Exposures Resulting From Surface Water Releases Page C-ll
Table 4. MOEs for the Average to Worst Case Day of the Year Page C-13
Table 5. MOEs for Drinking Water Consumption Page C-15
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Risk Characterization Handbook Page C-3
Risk Characterization of Generic Ketone
EXECUTIVE SUMMARY
Context
EPA received a petition to remove generic ketone from the Toxic Release Inventory
(TRI). Outside parties may petition EPA to list chemicals that are not currently on the TRI or to
delist chemicals from the TRI. Originally, EPA had included generic ketone on the TRI due to
concerns about developmental toxicity, neurotoxicity, hepatic toxicity, and renal toxicity. The
petitioner stated that new information indicates that the toxicity profile for generic ketone does
not meet the criteria for listing on the TRI. In addition, the petitioner stated that the exposure
estimates for facilities with the highest reported releases do not support a concern for risk to
human health.
The purpose of EPA's screening level risk assessment of generic ketone was to assist
EPA senior managers in addressing the delisting petition. EPA has 180 days to respond to a
petition and generally conducts a screening level risk assessment, which is not peer reviewed due
to the tight timeline. Risk assessors reviewed all available epidemiology and animal toxicology
studies of generic ketone to determine whether they met the criteria for listing the chemical on
the TRI. Potential ecological effects were not addressed since they had not been the basis of the
original listing of generic ketone and no new information is available that would impact the
original assessment.
Risk Paradigm
Exposure
EPA considers two scenarios when assessing human exposure to a chemical that is listed
on the TRI: (1) ambient air concentration at the fence line of a particular facility, and (2) the
concentration in the surface water that feeds into a drinking water facility. Facilities must report
only total annual emissions based on actual measurements or estimates of the emissions. As a
result, risk assessors had to estimate daily air and water concentrations of generic ketone from a
single estimate of the total amount released during the year by each facility. To do this in
accordance with EPA's Office of Pollution Prevention and Toxics' policy, they chose a default
value of 24 hours per day, 365 days per year to estimate ambient air concentrations and surface
water concentrations. The greatest source of uncertainty in estimating these concentrations
pertains to the assumption that generic ketone is released continuously over the year.
Risk assessors used the Industrial Source Complex Short Term model to estimate ambient
air concentrations of generic ketone at the fence line of three facilities with the highest releases to
air (stack and fugitive) in 1994. Meteorological information based on each facility's zip code
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Page C-4 Risk Characterization Handbook
was the only site-specific data available to the modelers. All other parameters represented
default values, which for the most part were based on conservative assumptions. If releases were
to occur over shorter durations than those based on continuous release over the year (the default),
the estimated ambient air concentrations, which ranged from 0.25 to 4.8 ppm, could increase up
to a factor of 52.
Risk assessors derived estimates of generic ketone in drinking water using the ReachScan
model. Because the primary human health concern is potential developmental toxicity, the
modelers estimated drinking water consumption rates on a daily basis (referred to as the acute
potential dose rate) from surface water concentrations at three facilities with the highest releases
to water. If releases of generic ketone were to occur over shorter periods than those estimated
using the default of continuous exposure over the year, the estimated surface water
concentrations, which ranged from 4.4 to 47 ppb, could increase up to a factor of 37.
Effect
Only the developmental toxicological studies provided sufficient evidence that generic
ketone can be reasonably anticipated to cause serious or irreversible health effects. Also,
developmental effects represented the only endpoint that was consistent with the criteria for
listing a chemical on the TRI. Extensive uncertainty exists about other types of potential health
effects (neurological, hepatic, renal, reproductive, and cancer) that were not considered because
the data are lacking or do not support a concern that is consistent with the criteria for TRI listing.
Inhalation prenatal developmental toxicity was observed in mice and rats, but maternal
toxicity was not observed in either species. Mice exposed to generic ketone exhibited an
increased incidence of dead fetuses, reductions in fetal body weight, and delayed ossification. In
rats, exposure to generic ketone was associated with reduced fetal body weight and delayed
ossification. For both species, the Lowest Observed Adverse Effect Level was 3,000 ppm and
the No Observed Adverse Effect Level (NOAEL) was 1,000 ppm. There were no oral
developmental toxicity data available for generic ketone. According to the EPA guidelines for
developmental toxicity risk assessment (1991), evidence of developmental toxicity in a single
animal study is sufficient to assume a potential hazard to humans.
Calculations and Uncertainties
Risk assessors used a margin of exposure (MOE) approach to describe the potential for
developmental toxicity associated with exposure to generic ketone. The MOE is calculated as
the ratio of the NOAEL for developmental toxicity to the estimated exposure level. Risk
assessors applied two uncertainty factors to the calculation, each with a value of 10 in accordance
with Agency policy: one for consideration of intraspecies variation and another for interspecies
variation.
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Risk Characterization Handbook Page C-5
Overall, the risk assessment supports a low concern for potential developmental effects
resulting from releases of generic ketone to surface water or air (stack or fugitive). The MOE
estimates for drinking water exposure ranged from 106 to 107. Because these MOEs are so large,
there is a high level of confidence that no appreciable concern exists due to releases to surface
water. Although uncertainties associated with the duration of release of generic ketone to water
could result in an increase in the surface water concentration by a factor of 37, the estimate
would have to increase by a factor of 1,000 to change the MOE enough to influence the level of
concern.
The MOE estimates for air exposure at the fenceline are greater than 100 at all three
facilities, which according to Agency policy indicates a low level of concern for developmental
toxicity resulting from exposure to generic ketone. However, there are substantial uncertainties
associated with the pattern and duration of release of generic ketone to ambient air that could
result in an increase in the ambient air concentration estimate by a factor of 52. Such an increase
would raise the level of concern for developmental toxicity. Given the uncertainties, the policy
to view a MOE of 100 as a "bright line" may not be sufficiently conservative in this case since
the uncertainty associated with the exposure assessment for ambient air concentrations may be
higher than the MOE value of 100.
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Page C-6 Risk Characterization Handbook
1. CONTEXT
1.1 Toxic Release Inventory
Under the reporting requirements of Section 313 of the Emergency Planning and
Community Right-To-Know Act of 1986 (EPCRA), facilities that use greater than 10,000 pounds
or that manufacture or process greater than 25,000 pounds of any chemical on the Toxic Release
Inventory (TRI) are required to report their total annual emissions to EPA and the states. The
criteria that EPA uses to determine whether a chemical should be on the TRI include
consideration of both human health and ecological effects as follows:
a) The chemical is known to cause or can reasonably be anticipated to cause
significant adverse acute human health effects at concentration levels that are
reasonably likely to exist beyond facility site boundaries as a result of continuous,
or frequently recurring, releases;
b) The chemical is known to cause or can reasonably be anticipated to cause in
humans cancer or teratogenic effects, or serious or irreversible effects including
reproductive dysfunctions, neurological disorders, heritable gene mutations, or
other chronic health effects.
c) The chemical is known to cause or can reasonably be anticipated to cause, because
of its toxicity, its toxicity and persistence in the environment, or its toxicity and
tendency to bioaccumulate in the environment, a significant adverse effect on the
environment.
In accordance with Agency science policy, traditionally cancer and heritable gene
mutations have been viewed as non-threshold effects, whereas non-cancer effects have been
viewed as threshold effects. Accordingly, the analyses required to include a chemical on the TRI
differ for heritable gene mutations and cancer versus non-cancer effects. Hazard information that
provides evidence that the chemical causes or can be reasonably anticipated to cause heritable
gene mutations or cancer in humans is sufficient for a chemical to be included on the TRI. In
contrast, for non-cancer effects, the hazard data must first be evaluated and determined to be
sufficient to provide evidence that the chemical can reasonably be anticipated to pose a hazard to
humans. If the hazard case is determined to be strong enough, then a risk assessment is
subsequently conducted to demonstrate that under the specific exposure conditions, the chemical
can be reasonably anticipated to cause the effect in humans.
It is possible for outside parties to petition EPA to list chemicals that are not currently
included on the TRI or to delist chemicals from the TRI. When a petition is submitted, the
Agency has 180 days to respond. Given this timeline, the Agency conducts a screening level
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Risk Characterization Handbook Page C-7
hazard, and, if necessary, a risk assessment of the chemical in question. An external peer review
is not conducted for these assessments due to the tight timeline.
1.2 Scope and Purpose of Generic Ketone Assessment
EPA recently received a petition to remove a chemical, referred to in this assessment as
generic ketone, from the TRI. Originally, EPA had included generic ketone on the TRI due to
concerns for developmental toxicity, neurotoxicity, hepatic toxicity, and renal toxicity. The
petitioner stated that new information indicates that the toxicity profile for generic ketone does
not meet the criteria for listing on the TRI and that the exposure estimates for facilities with the
highest reported releases do not support a concern for risk to human health.
The purpose of the screening level risk assessment of generic ketone is to assist EPA
senior managers in addressing the delisting petition. All available epidemiology and animal
toxicology studies of generic ketone were reviewed to determine whether they met the above
EPCRA criteria for listing. Potential ecological effects were not addressed since they had not
been the basis for the original listing of generic ketone and no new information is available that
would impact the original assessment. Agency risk assessment guidelines were followed. This
document constitutes the risk characterization for the risk assessment. The hazard and exposure
portions of the risk assessment are provided in Appendix A.
Two exposure scenarios are considered when assessing human exposure to a chemical
that is listed on the TRI. The first scenario is the ambient air concentration at the fence line of a
facility, and the second is the concentration in the surface water that feeds into a drinking water
facility. Risk assessors used the Industrial Source Complex Short Term model to derive
estimates of the ambient air concentrations of generic ketone at the fence line of specific
facilities. Estimates of generic ketone in drinking water were derived using the ReachScan
model. Agency exposure guidelines were followed for the exposure assessment.
2. RISK PARADIGM
The risk characterization for generic ketone is presented below. It was concluded from
the risk assessment that there is low concern for human health effects resulting from exposure to
ambient air concentrations of generic ketone at the fence line or from surface water releases of
generic ketone.
2.1 Hazard Identification
EPA evaluated the epidemiology and animal toxicology studies to determine the overall
toxicological profile of generic ketone and to determine whether sufficient evidence exists to
demonstrate that generic ketone can cause or reasonably be anticipated to cause severe or
irreversible health effects in humans. In general, there are very limited data available concerning
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Page C-8 Risk Characterization Handbook
the potential toxicity of generic ketone. Generic ketone is an eye and respiratory irritant in
humans at concentrations of 100-500 ppm, but it has not been associated with significant
neurobehavioral effects.
In animal studies, generic ketone has low acute toxicity by the oral, dermal, and
inhalation routes. For example, in acute oral toxicity studies, the LD50 in rats, mice, and guinea
pigs, ranges from 1.9 - 4.6 g/kg. A dermal LD50 in the rabbit of > 16 g/kg has been reported. In
acute inhalation toxicity studies in rats, the LC50 ranges from 2,000 to greater than 4,000 ppm.
Subchronic animal studies have provided equivocal evidence of neurotoxicity, hepatic
toxicity, and renal toxicity. However, chronic studies were not available, so it was not possible
to support or refute the findings from the short-term studies. Similarly, there are no data
available regarding the potential reproductive toxicity or carcinogenicity of generic ketone. The
results of mutagenic assays indicate that generic ketone has little mutagenic activity.
Inhalation prenatal developmental toxicity studies have been conducted in rats and mice.
Developmental toxicity was observed in mice and rats, but maternal toxicity was not observed in
either species. In mice, exposure to generic ketone was associated with an increased incidence of
dead fetuses, reductions in fetal body weight, and delayed ossification. In rats, exposure to
generic ketone was associated with reduced fetal body weight and delayed ossification. For both
species, the LOAEL was 3,000 ppm and the NOAEL was 1,000 ppm.
The only toxicological studies that provide sufficient evidence that generic ketone can be
reasonably anticipated to cause serious or irreversible health effects are the developmental
toxicity studies. According to EPA guidelines for developmental toxicity risk assessment (1991),
evidence of developmental toxicity in a single animal study is sufficient to assume a potential
hazard to humans. Since this is a non-cancer endpoint, it is necessary to conduct a risk
assessment to determine whether there is a potential hazard to humans as specified under EPCRA
313.
There are several sources of uncertainty associated with the hazard assessment. The
major uncertainty is due to the paucity of human health effects and toxicological information on
generic ketone. Sufficient evidence exists to support a potential concern for developmental
effects. However, there is a great deal of uncertainty regarding the potential for other health
effects due to a lack of information.
2.2 Exposure Assessment
A summary of the exposure assessments for ambient air and drinking water
concentrations is provided below (see Appendix A for details). For human health effects, two
exposure scenarios are considered when assessing the exposure to a chemical that is listed on the
TRI. The first scenario is the ambient air concentration at the fence line of a particular facility,
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Page C-9
and the second is the concentration in the surface water that feeds into a drinking water facility.
Facilities that meet the reporting requirements of EPCRA 313 must report to EPA the total
annual emissions of the chemical listed on the TRI. The information is supplied simply as the
total annual emission and may be based on actual measurements of the emissions or on estimates
of the emissions. No information is provided regarding the pattern of the emissions throughout
the year. Therefore, for this exposure assessment it was necessary to estimate daily air
concentrations and water concentrations of generic ketone from a single estimate of the total
amount released during the year by each facility.
Releases reported for generic ketone during 1994 were retrieved from the Toxic Release
Inventory System (TRIS) data base. According to TRIS, more than 25,500,000 pounds of
generic ketone were released in 1994 from 1,031 sources nationwide. Of this amount, 27 percent
was from fugitive or nonpoint source emissions and 72 percent originated from stack or point
source emissions to the atmosphere. In addition, lesser amounts of generic ketone (less than 1
percent) were released to surface waters, underground injection of wastes, and the land.
2.2.1 Estimates of Ambient Air Concentrations
The Industrial Source Complex Short Term (ISCST3) model was used to derive estimates
of the ambient air concentration of generic ketone at the fence line. For this assessment,
modeling was conducted for the three facilities that reported the highest releases of generic
ketone in 1994 to air (stack and fugitive). The ISCST3 model was used to calculate estimates of
the ambient air concentration for three scenarios, the single worst day (highest concentration) of
the year, the 50th worst day of the year, and the average day. Each of these estimates for the
three facilities is shown in Table 1.
Table 1. Estimated Ambient Air Concentrations of Generic Ketone For Three Facilities
Facility
A
B
Type of Day Modeled
Highest Concentration Day
50th Highest Concentration Day
Average Day
Highest Concentration Day
50th Highest Concentration Day
Average Day
Estimated Ambient Air
Concentration (ppm)
4.8
1.9
0.5
2.3
1.3
0.3
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Risk Characterization Handbook
c
Highest Concentration Day
50th Highest Concentration Day
Average Day
2.0
1.2
0.25
There are many uncertainties associated with the estimates shown in Table 1. The impact
of different assumptions regarding the pattern of releases of generic ketone on the estimates of
the ambient air concentration is shown in Table 2. As noted above, the only site-specific
information available was some meteorological information based on the zip code of the facility.
All other parameters used in the model were default values, which for the most part are based on
conservative assumptions. The largest source of uncertainty is associated with the pattern and
duration of the release of generic ketone. The values shown in Table 1 were derived based on the
assumption that releases of generic ketone take place continuously over 365 days per year. This
assumption is necessary since the only site-specific data available are a single estimate of total
annual release; therefore the actual number of days when releases occur is unknown. However, if
releases actually occur over shorter periods, the model would estimate higher ambient air
concentrations.
Table 2. Estimated Ambient Air Concentrations of Generic Ketone — Impact of Pattern of
Release
If Releases Occurred...
Over 24 hours/ day, but only on weekdays
Over 24 hours/day every day, but only 6 months/year
Over 365 days, but only one 8-hour shift per day
Over 24 hours/day every day, but only 1 month/year
Over 24 hours/day every day, but only 1 week/year
Air Concentrations Would
Increase By a Factor of...
1.5
2
3
12
52
2.2.2 Estimates of Surface Water Concentrations and Drinking Water
Consumption
The ReachScan model was used to derive estimates of the surface water concentration of
generic ketone resulting from reported releases to surface water. The potential exposure of the
population to releases of generic ketone to surface water is through consumption of drinking
water. Drinking water consumption can be calculated on a daily basis or as a lifetime average.
The former estimate is generally referred to as the acute potential dose rate (APDR), and the
latter is generally referred to as the lifetime average daily dose (LADD). The APDR is
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Page C-ll
calculated when the toxic effect of a chemical is thought to be the result of a short-term acute
exposure, whereas the LADD is calculated when the toxic effect is thought to be the result of
long-term chronic exposure. For generic ketone, the primary concern is for potential
developmental toxicity. A central assumption in developmental toxicity risk assessment is that
developmental effects can result from a single exposure to the chemical (EPA 1991). Therefore,
for this assessment, it is most appropriate to use estimates of the APDR.
The three facilities with the highest annual releases to surface water were modeled by
ReachScan for this assessment. The estimated surface water concentrations and the associated
drinking water APDRs are presented in Table 3. The generic ketone concentrations in the water
range from 4.4 to 47 ug/L at the three highest drinking water utilities. The drinking water
APDRs range from 1.4 x 10'4 to 1.4 x 10'3 mg/kg/day.
Table 3. Acute Exposures Resulting From Surface Water Releases
Facility
1
2
3
Estimated Surface Water
Concentration (ug/L)
47
9
4.4
Acute Potential Dose Rate
(mg/kg/day)
0.0014
0.00028
0.00014
There are several sources of uncertainty associated with the estimates of surface water
concentration and the resultant estimates of APDR. The greatest source of uncertainty pertains to
the assumption that generic ketone is released continuously over 365 days per year. However, if
releases actually occur over shorter periods, the model would estimate higher surface water
concentrations. For example, if the releases occurred over 10 days per year the value calculated
for the surface water concentration would increase by a factor of 37. The value would increase
by a factor of 12 or 1.5 if releases occurred over 30 days per year or 250 days per year,
respectively. The resultant APDRs would increase by the same amount.
2.3 Dose-Response, Calculations, and Uncertainties
This assessment focuses on the potential risk of developmental toxicity associated with
exposure to generic ketone. Developmental effects are considered in the analysis because they
represent the only endpoint for which the hazard data were consistent with the criteria specified
by EPCRA 313. Other types of health effects are not considered either because the available data
do not support a concern that is consistent with the criteria, or the data are lacking.
A margin of exposure (MOE) approach is used in this assessment to describe the potential
for developmental toxicity associated with exposure to generic ketone. The MOE is calculated
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Page C-12 Risk Characterization Handbook
as the ratio of the NOAEL for developmental toxicity to the estimated exposure level. The MOE
does not provide an estimate of population risk; it simply describes the relative distance between
the exposure level and the NOAEL. The value of the MOE that is associated with a concern for
toxic effects is generally expressed as the product of the applicable uncertainty and modifying
factors. Uncertainty factors that the Agency considers for non-cancer effects are described in
IRIS (1998). For consideration of developmental toxicity, the applicable uncertainty factors are
described in the developmental toxicity risk assessment guidelines (EPA 1991). These include
two uncertainty factors, one for consideration of intraspecies variation and another for
interspecies variation. In accordance with Agency science policy, each of these uncertainty
factors is given a value of 10. Thus, for developmental effects, an MOE greater than 100 would
generally indicate a low level of concern, whereas a value less than 100 is judged to be of
concern.
As described previously, inhalation developmental toxicity studies of generic ketone have
been conducted in mice and rats. No maternal toxicity was noted in either study. Similar
developmental eifects were noted in both species, and included reduced fetal body weight,
delayed ossification, and increased fetal death (mice only). For both species, the LOAEL was
3,000 ppm and the NOAEL was 1,000 ppm. In accordance with Agency science policy regarding
developmental toxicity studies, the LOAEL's and NOAEL's were not duration-adjusted (EPA
1991). In addition, human equivalent concentrations were not calculated since a blood:air
partition coefficient was not available for generic ketone. Although the RfC guidance (EPA
1994) suggests that a default value of 1 can be used in the absence of a blood:air partition
coefficient, this results in a less conservative risk assessment. In such cases, it is OPPT policy to
use the more conservative approach. Therefore, for this assessment the NOAEL of 1,000 ppm
was used in the derivation of the MOE. Separate analyses were conducted for the two exposure
scenarios. Each is presented below.
2.3.1 MOE Calculations for Ambient Air Concentrations at the Fence Line
To determine the MOEs for exposure at the fence line of the three facilities with the
highest releases of generic ketone, the NOAEL of 1,000 ppm was divided by the estimated
ambient air concentrations (Table 1). MOEs were calculated for three exposure scenarios at each
facility: the day with the highest ambient air concentration of generic ketone, the 50th highest day
of the year, and the average day of the year. These values are shown below in Table 4. The
MOEs are greater than 100 under all three exposure conditions at each facility, which in
accordance with Agency science policy would indicate a low level of concern for developmental
toxicity resulting from exposure to generic ketone at the fence line.
There are several sources of uncertainty associated with the hazard/dose response
assessment and the exposure assessment that impact the specific MOEs. The hazard assessment
was conducted in accordance with the criteria used to assess whether a chemical should be on the
TRI. Thus, the hazard data were assessed within a framework of whether the data are sufficient
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Page C-13
to determine with reasonable certainty that serious or irreversible effects are likely to occur in
humans. There was some equivocal evidence of neurotoxicity, hepatic toxicity, and renal
toxicity from short-term animal studies; however, chronic toxicity studies were not available so it
was not possible to provide evidence to support or refute the findings from the short-term studies.
Similarly, there were no data available regarding the potential reproductive toxicity or carcino-
genicity of generic ketone. Thus, while the toxicologic data for effects other than developmental
effects were not strong enough for the purposes of EPCRA, there is uncertainty regarding the
potential for other types of effects resulting from exposure to generic ketone.
Table 4. MOEs for the Average to Worst Case Day of the Year
Facility
A
B
C
Type of Day Modeled
Highest Concentration Day
50th Highest Concentration Day
Average Day
Highest Concentration Day
50th Highest Concentration Day
Average Day
Highest Concentration Day
50th Highest Concentration Day
Average Day
MOE
209
530
1,944
430
785
3,710
510
833
4,082
A second source of uncertainty in the hazard/dose-response assessment is the use of a
NOAEL from a rodent study in the calculation of the MOE. The Agency has developed guidance
for dosimetric conversions of animal inhalation concentrations to human equivalent
concentrations. Unfortunately, for a compound such as generic ketone, such conversions require
knowledge of the blood:air partition coefficient. This was not available for generic ketone, and
therefore derivation of a human equivalent concentration was not feasible. The impact of this on
the MOE is not known.
There are also many uncertainties associated with the exposure assessment. As noted
previously, the only available information on actual releases of generic ketone are total annual
releases from the facilities. Therefore, ambient air concentrations are derived through the use of
the ISCST3 model. This model requires the input of various parameters, and in the absence of
site-specific information, default values are used. The only site-specific information that was
available in this case was some meteorological data obtained using the zip codes of the facilities.
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For the default values, the largest source of uncertainty exists for the number of hours per day
and number of days per year that generic ketone was actually released from each facility. In
accordance with OPPT policy, a default value of 24 hours per day, 365 days per year was used to
calculate the ambient air concentrations. These estimates can increase up to a factor of 52 when
releases are estimated over shorter durations (Table 2).
If it were assumed that releases occurred only 8 hours per day (one work shift), 365 days
per year, the estimates of ambient air concentrations would increase by a factor of 3. This would
result in estimates ranging from 14.4 ppm (facility A, highest concentration day) to 0.75 ppm
(facility C, average day). The resulting MOEs would then range from 70 (facility A, highest
concentration day) to 1,333 (facility C, average day). This would not change the level of concern
for facilities B or C but would indicate a higher level of concern for facility A for the worst case
day. If it was assumed that generic ketone was released 24 hours per day, but only for 1 week per
year the estimates of ambient air concentrations would increase by a factor of 52. The estimates
would then range from 13 ppm (facility C, average day) to 250 ppm (facility A, highest
concentration day). Increasing the ambient air concentrations by a factor of 52 would result in
MOEs ranging from 4 (facility A, highest concentration day) to 77 (facility C, average day). In
accordance with Agency policy, MOEs in this range would suggest that there is a relatively high
concern for potential developmental effects.
2.3.2 MOE Calculations for Releases to Surface Water
The potential exposure of the population to releases of generic ketone to surface water
would be through consumption of drinking water. Ideally, a NOAEL from an oral study would
be used for the derivation of MOEs in this exposure since this is the route of concern. However,
there are no oral developmental toxicity data available for generic ketone. Therefore, to
determine the MOEs for exposure from drinking water, it was necessary to assume that the
inhalation developmental toxicity data were relevant for oral exposures (EPA 1991).
Accordingly, the NOAEL of 1,000 ppm was converted to units of mg/kg/day.1
MOEs were then derived by dividing the NOAEL in mg/kg/day by the estimated acute
potential dose rate (APDR) (shown in Table 3); these are presented in Table 5. The APDR
estimates resulting from surface water releases for the top three discharging facilities range from
2.8 x 10"5 - 1.4 x 10"3 mg/kg/day. Using the rat NOAEL, the MOE values for these estimates
range from 3.3 x 107 - 3.3 x 107. Using the mouse NOAEL, the MOE values for these estimates
range from 2.3 x 107- 4.6 x 106.
[ppm X (molecular weight/24.5) X rodent ventilation rate (mVday)]/ rodent body weight = mg/kg/day. For the rat, this becomes:
[1,000 ppm X (100/24.5)X 0.14 nf/day]/ 0.124 kg = 4,608 mg/kg/day. For the mouse, this becomes: [1,000ppm X (100/24.5) X0.04 mVday]/
0.025 kg = 6,531 mg/kg/day.
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Page C-15
Table 5. MOEs for Drinking Water Consumption
Facility
1
2
3
MOE
(using rat NOAEL)
3.3 xlO6
1.6 xlO7
3.3 xlO7
MOE
(using mouse NOAEL)
4.6 xlO6
2.3 x 107
4.6 x 107
There are uncertainties associated with the assessment that could influence the calculated
MOEs. The largest source of uncertainty in the exposure assessment is the default value used for
the number of hours per day and number of days per year that generic ketone was actually
released from the facilities. A default value of 24 hours per day, 365 days per year was used to
calculate the surface water concentrations. These estimates can increase up to a factor of 37
when releases are estimated over shorter durations. However, because the MOEs that are
calculated for drinking water are so large, increasing the APDR by a factor of 37 would not alter
the level of concern; the ADPR would have to increase by close to a factor of 1,000 to have any
appreciable effect on the level of concern for developmental effects. Therefore, even though
there is a great deal of uncertainty associated with the drinking water exposure, the MOE is so
large that there is a high level of confidence that there is no appreciable concern for
developmental effects resulting from exposure to generic ketone released to surface water.
3.
CONCLUSIONS
Overall, the assessment supports a low concern for potential developmental effects
resulting from releases of generic ketone to air (stack or fugitive) or surface water. There are
substantial uncertainties associated with the exposure assessments that could result in increases
in the estimates of ambient air concentrations by a factor of 52 and increase estimates of surface
water concentrations by a factor of 37. Such an increase would not affect the level of concern for
releases to surface water since these estimates would have to increase by a factor of 1,000 to
change the MOE enough to effect the level of concern. Increasing the estimates of the ambient
air concentration by a factor of 52 may increase the level of concern for developmental toxicity.
Given these uncertainties, it may be prudent to point out that the policy to view a MOE of 100 as
a "bright line" may not be sufficiently conservative in this case since the uncertainty associated
with the exposure assessment for ambient air concentrations may be higher than the MOE value
of 100.
4.
RECOMMENDATIONS REGARDING DATA GAPS
Several uncertainties that have been highlighted in this assessment could be reduced with
additional information. With respect to the toxicological data base, there was equivocal evidence
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of neurotoxicity, hepatic toxicity, and renal toxicity from the subchronic studies. If chronic
studies were conducted, it would be possible to support or refute these findings. With respect to
the exposure data base, there are substantial uncertainties associated with the pattern and duration
of the releases of generic ketone to air. These uncertainties could be reduced through the
development of accurate release information.
5. LITERATURE CITATIONS
EPA. 1991. Guidelines for developmental toxicity risk assessment. U.S. Environmental
Protection Agency. Federal Register 56(234): 63798-63826.
EPA. 1994. Methods for derivation of inhalation reference concentrations and application of
inhalation dosimetry. U.S. Environmental Protection Agency. EPA/600/8-90/066F.
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Risk Characterization Handbook Page C-17
APPENDIX A
HAZARD AND EXPOSURE ASSESSMENTS OF GENERIC KETONE
1. HAZARD SUMMARY
1.1 Absorption and Metabolism
Absorption and metabolism studies in animals suggest that generic ketone is well-
absorbed from the lung, gastrointestinal tract, and skin; well distributed; and rapidly metabolized.
Although no metabolism studies have been conducted in humans, short-term exposure to generic
ketone is associated with eye and respiratory irritation and clinical signs of reversible central
nervous system (CNS) effects. This finding is consistent with the animal studies that
demonstrate that generic ketone is rapidly absorbed.
1.2 Acute Toxicity
Available data indicate that generic ketone is associated with low toxicity in humans and
animals following acute exposures. In humans, short-term inhalation exposures of up to 30
minutes each day to concentrations as high as 500 ppm produced irritation of the eyes and upper
and lower respiratory system—effects characteristic of solvent exposure. In some studies,
reversible CNS and irritant effects were seen after 8-hour exposures to 100 ppm, while in other
studies, 100 ppm produced no effects (additional studies are described in Section 1.8 of this
appendix).
In acute inhalation toxicity studies, rats were able to tolerate concentrations of 2,000 -
4,000 ppm for periods up to 6 hours, while concentrations > 20,000 ppm produced death in all
animals within an hour. The estimated 4- and 6-hour LC50 in rats were 3,000 and > 4,000 ppm,
respectively. Although no mortality was reported in mice exposed to concentrations as high as
900 ppm generic ketone, a decrease in the duration of immobility in a behavioral despair
swimming test and a reduction in the respiratory rate were observed. In acute oral toxicity tests,
the LD50 ranged from 1,900 - 3,000 mg/kg in the mouse and 3,000 - 4,600 mg/kg in the rat. The
dermal LD50 in rabbits has been reported as being greater than 16 g/kg.
1.3 Mutagenicity
In general, generic ketone does not appear to be associated with genotoxicity in vitro or in
vivo. Generic ketone is not a gene mutagen in Salmonella typhimurium strains TA98, TA100,
TA1535, and TA1538 either with or without metabolic activation. It is weakly positive in
L5178Y TK+/" mouse lymphoma cells in vitro without, but not with activation. It is not a
chromosome mutagen in vitro in Chinese hamster ovary (CHO) and rat RL4 cells, nor does it
induce micronuclei in vivo in the mouse micronucleus assay by the intraperitoneal injection
route. Generic ketone does not induce DNA effects in the Saccharomyces cerevisiae
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homozygosis and recombination assay, and it is equivocal in the unscheduled DNA synthesis
(UDS) assay in rat hepatocytes in vitro. It induces morphological cell transformation in BALB/c
3T3 cells in culture without and possibly with metabolic activation.
1.4 Carcinogenicity
There are no human or animal carcinogenicity data on generic ketone.
1.5 Systemic Toxicity from Repeated Doses
Only one epidemiological worker study and a follow-up study are available on the
potential effects of generic ketone in humans. However, no information was provided
concerning the exposure of the individuals, and potential confounders were not accounted for.
As a result, no definitive conclusions could be made.
Limited animal data are available regarding the potential systemic toxicity of generic
ketone. A 90-day inhalation toxicity study in rats and mice has been conducted. In that study, 14
male and 14 female Fischer 344 rats and B6C3F1 mice per group were exposed to 0; 50; 250;
and 1,000 ppm generic ketone by vapor inhalation 6 hr/day, 5 days/week for 14 weeks.
Parameters assessed for toxicity included clinical observations, body and organ weight data,
water consumption, urinalysis, serum chemistry, hematology, gross pathology, and histology. No
treatment-related effects were noted in the mouse study. In the rat study there was evidence of
hepatic toxicity as demonstrated by a dose-related increase in serum cholesterol levels in male
rats exposed to 250 and 1,000 ppm (23% and 35% higher than controls, respectively). In
addition, there was evidence of renal toxicity; statistically significant dose-related increases in
urine glucose excretion occurred in male rats (55%, 37%, and 23% for the 1,000; 250; and 50
ppm levels, respectively) and in female rats at 1,000 ppm (28% above control values). In
addition, increases in total urinary protein were observed. The authors of the study suggested
that the urinary glucose and protein excretion maybe due to functional impairment of normal
reabsorption in the renal proximal convoluted tubules. Increases in renal hyaline droplets were
also noted in mid- and high-dose male rats. Although the presence of hyaline droplets in the
renal proximal tubules may be considered male-rat specific and could explain the functional
impairment of glucose and protein absorption in the kidney tubules, increased urinary glucose
was observed at the high dose in both sexes. Significant alterations in other parameters of renal
function did not occur.
Another group of investigators conducted a 90-day inhalation toxicity study in dogs, rats,
and monkeys. They exposed 8 beagle dogs, 100 Wistar rats, and 2 monkeys continuously for 90
days under space cabin conditions (reduced atmospheric pressure) to 100 ppm generic ketone.
Dogs and monkeys did not appear to have any toxic responses to the exposure. Special staining
of dog kidney sections did not reveal treatment-related effects. Since only 2 monkeys were used
per group, the etiology of the chronic inflammation of the kidney in one of the exposed monkeys
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Risk Characterization Handbook Page C-19
is uncertain. Renal toxicity was clearly present in the rats as demonstrated by hyaline droplet
nephrosis. The lesions developed within two weeks of exposure and were reversible after 90
days of exposure.
In addition, a subchronic oral toxicity study in rats has been conducted. In that study,
four groups of an unspecified number of Sprague-Dawleyrats were given 0; 50; 250; and 1,000
mg/kg/day generic ketone by oral gavage daily for 90 days. Doses of 250 mg/kg/day produced
increased kidney weights and urinary ketones in both sexes and epithelial cells in males. There
were no treatment-related effects at 50 mg/kg/day.
In summary, the major target organs in both the 90-day rat subchronic inhalation and oral
toxicity studies were the liver and kidney. Oral gavage doses produced more severe reactions as
demonstrated by the changes in clinical chemistry parameters indicative of hepatic toxicity,
urinalyses, and histopathological changes in the male rat kidney. The main effects in the
inhalation study appeared to be due to functional changes in the liver and kidney, increased liver
weight, increased serum cholesterol, and impaired renal absorption of protein and glucose in
male rats. However, the elevations in serum chemistry parameters were slight and the liver and
kidney effects in the inhalation study were considered to be relatively minor with no major signs
of histopathological lesions with the exception of increases in renal hyaline droplets in mid- and
high-dose males.
1.6 Developmental Toxicity
Inhalation prenatal toxicity studies have been conducted in rats and mice. In that study,
30 pregnant CD-I mice and 35 pregnant Fischer 344 rats per group were exposed to 0; 300;
1,000; and 3,000 ppm generic ketone by vapor inhalation 6 hr/day on gestation days (GD) 6-15.
In mice, there was no evidence of maternal toxicity. There was evidence of developmental
toxicity as demonstrated by an increased incidence of dead fetuses; reductions in fetal body
weights per litter; and delayed ossification, which was observed at the high dose of 3,000 ppm.
No effects were noted at 1,000 or 300 ppm.
In rats, there was no evidence of maternal toxicity. Exposure to 3,000 ppm resulted in a
reduction in fetal body weight per litter and delayed skeletal ossification. Additionally, at 300
ppm but not at 1,000 ppm, there was evidence of reduced fetal body weights per litter and an
increase in delayed ossification. The authors of the study reported that historical control data
from their laboratory for Fischer 344 rats indicate an inverse relationship between litter size and
fetal body weight. They offered this as an explanation for the decreases in fetal body weight
observed at the low dose group of 300 ppm. Fetal body weight per litter was examined by dose
and by litter size and evaluated statistically. Their analysis indicated that fetal body weights
differed significantly from controls for both small and large litters at 3,000 ppm, indicating a
treatment-related effect. Conversely, fetal body weights at the 1,000 ppm dose group were
comparable to controls for both large and small litters. At 300 ppm, fetal body weights for small,
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but not large, litters were significantly reduced compared to controls. The authors contend that
the significant reduction in fetal body weight per litter seen in small litters at 300 ppm was
actually an artifact of exceptionally heavy fetuses in two small litters in the control group and
therefore not treatment-related. Furthermore, the authors argued that since the control group
overall had more smaller litters than the 300 ppm group, the evidence of minimal delayed
ossification at 300 ppm was consistent with larger litter sizes, concomitant lower fetal body
weights, and reductions in ossification. Thus, these effects are not considered to be treatment-
related.
In conclusion, adverse developmental effects were noted in the mouse and rat studies;
maternal toxicity was not observed in either species. For both species, the NOAEL for maternal
toxicity was 3,000 ppm; the LOAEL for developmental toxicity was 3,000 ppm and the NOAEL
was 1,000 ppm.
1.7 Reproductive Toxicity
No reproductive/fertility studies have been conducted with generic ketone. The only
information available is from the 90 day inhalation toxicity study in mice and rats described
above. In that study, organ weight and histological data in high-dose rats and mice were
comparable to controls for the ovaries, uterus, oviducts, vagina, cervix, testis, epididymis,
prostate, and seminal vesicles. However, this is not sufficient information to characterize the
potential for reproductive toxicity of generic ketone.
1.8 Neurotoxicity
Several human studies have examined the neurotoxicity of generic ketone. Although the
data are limited to studies with small numbers of subjects, the results are fairly consistent. One
group of investigators tested neurobehavioral performance following a 4-hour exposure to 100
ppm generic ketone. Five different psychomotor tests, chemical measurements, and reports of
sensory and irritant effects were measured. No marked neurobehavioral effects were reported,
but sensory and irritant effects (i.e., odor, headache, nausea, throat irritation, tearing) were
reported by 20-30% of the subjects exposed to generic ketone. In another study, 8 subjects were
exposed to 50 ppm generic ketone for shorter exposure periods. There were no significant
effects on simple reaction time or mental arithmetic tasks. However, irritation of the nose,
throat, headache, and vertigo were reported by up to a third of the subjects (based on a
questionnaire). Subjects reported an increase in the degree of irritative and CNS symptoms for
exposures of 24 ppm and 48 ppm, as compared to 2.4 ppm. Similar results were also reported for
2-hour exposures to 2.4 and 48 ppm generic ketone where subjects reported fatigue and irritation
to airways, but no reduction of reaction time or performance on arithmetic tests.
Numerous studies have been conducted in animals to assess the neurotoxic potential of
generic ketone. Generally have found no evidence of permanent impairment of neurological
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Risk Characterization Handbook Page C-21
function. For example, histological examination of the nervous system including the brain,
spinal cord, and peripheral nerves, was unremarkable, and no clinical signs of neurotoxicity were
observed in rats or mice exposed to doses as high as 1,000 ppm generic ketone by vapor
inhalation for 90 days.
A 90-day inhalation study of schedule-controlled operant behavior (SCOB) in rats has
also been conducted. In this study, male rats were subjected to exposures of 0; 250; 750; and
1,500 ppm generic ketone for 6 hr/day. The results showed that rats exposed to 1,500 ppm
exhibited reduced activity and sialorrhea (excessive salivation) following one hour of exposure.
This effect was transient, and did not persist after ten weeks of exposure. The same effect was
seen in animals exposed to 750 ppm, following 2 hours of exposure, but was only seen during
weeks 1 through 8. No effects were seen during exposure to 250 ppm. No significant behavioral
effects were detected following exposure at any of the doses tested, using the schedule-controlled
operant behavior test. These data indicate that generic ketone may cause transient neurologic
effects.
In summary, the available human data are consistent with data previously summarized.
Exposure to generic ketone is associated with eye and respiratory irritation at high concen-
trations, but no human or animal data demonstrate an association between exposure to generic
ketone and serious and irreversible neurological effects.
1.9 Hazard Characterization
Human studies have reported irritation of the eyes and mucous membranes as well as
symptoms, such as headache, nausea, and vertigo (effects characteristic of solvent exposure) due
to inhalation of generic ketone at concentrations ranging from 100 to 500 ppm. However, no
significant neurobehavioral effects have been reported at these concentrations.
In animal studies, generic ketone has low acute toxicity by the oral, dermal, and
inhalation routes. For example, in acute oral toxicity studies, the LD50 in rats, mice, and guinea
pigs ranges from 1.9- 4.6 g/kg. A dermal LD50 in the rabbit of > 16 g/kg has been reported. In
acute inhalation toxicity studies in rats, the LC50 ranges from 2,000 to greater than 4,000 ppm.
The results of mutagenic assays indicate that generic ketone has little mutagenic activity.
There is neither human nor animal data on the potential carcinogenicity of generic ketone.
Subchronic inhalation studies in rats, mice, dogs, and monkeys exposed to concentrations
ranging from 50-2,000 ppm generic ketone indicate liver and kidney toxicity. However, in the
absence of appropriate chronic data, the data were considered inadequate to support a concern for
serious or irreversible effects. Neurotoxicity studies in rats on generic ketone indicate that
transient CNS depression can occur at high exposure levels. However, there is no evidence to
support a concern for serious or irreversible neurological effects. No conclusions regarding the
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potential for reproductive toxicity can be made since no reproductive/fertility studies on generic
ketone have been conducted.
Inhalation developmental toxicity studies in rats and mice demonstrate that generic
ketone is not associated with maternal toxicity. Developmental toxicity was observed in mice
and rats. In mice, exposure to generic ketone was associated with an increased incidence of dead
fetuses, reductions in fetal body weight, and delayed ossification. In rats, exposure to generic
ketone was associated with reduced fetal body weight and delayed ossification. For both species,
the LOAEL was 3,000 ppm and the NOAEL was 1,000 ppm. According to EPA guidelines for
developmental toxicity risk assessment (1991), evidence of developmental toxicity in a single
animal study is sufficient to assume a potential hazard to humans.
2. EXPOSURE SUMMARY
For human health effects, two exposure scenarios are considered when assessing
exposure to a chemical that is listed on the TRI. The first scenario is the ambient air
concentration at the fence line of a particular facility, and the second is the concentration in the
surface water that feeds into a drinking water facility. As noted previously, facilities that meet
the reporting requirements of EPCRA 313 must report the total annual emissions of the chemical
listed on the TRI to EPA. The information is supplied simply as the total annual emission and
may be based on actual measurements of the emissions or on estimates of the emissions. No
information is provided regarding the pattern of the emissions throughout the year. Therefore,
for this exposure assessment it was necessary to estimate daily air concentrations and water
concentrations of generic ketone from a single estimate of the total amount released during the
year by each facility.
Releases reported for generic ketone during 1994 were retrieved from the Toxic Release
Inventory System (TRIS) data base. According to TRIS, more than 25,500,000 pounds of
generic ketone were released in 1994 from 1,031 sources nationwide. Of this amount, 27 percent
was from fugitive or nonpoint source emissions and 72 percent originated from stack or point
source emissions to the atmosphere. In addition, lesser amounts of generic ketone (less than 1
percent) were released to surface waters, underground injection of wastes, and the land.
The Industrial Source Complex Short Term (ISCST3) model was used to derive estimates
of the ambient air concentration of generic ketone at the fence line. For this assessment,
modeling was conducted for the three facilities that reported the highest releases of generic
ketone in 1994 to air (stack and fugitive). The ReachScan model was used to derive estimates of
the surface water concentration of generic ketone. This information was then used to calculate
general population exposures resulting from surface water releases to drinking water sources. A
description of the ISCST3 and the ReachScan models is provided below.
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Risk Characterization Handbook Page C-23
2.1 Modeling Ambient Air Concentrations of Generic Ketone
The ISCST3 model was used to estimate short-term ambient air concentrations. The
model requires the input of certain information, such as pollutant emission rate; stack height (for
point sources); release height (for area sources); stack gas temperature; stack diameter; stack gas
exit velocity; location of the point of emission with respect to surrounding topography and the
character of that topography, a detailed description of all structures in the vicinity of the stack in
question; and similar information from other significant sources in the vicinity of the subject
source stack height. Ideally, the input for these parameters would be based on site-specific data.
However, in the absence of site-specific information generic default values are used.
For generic ketone, the only site-specific information available was some meteorological
data. By using the zip code or the latitude and longitude of the release site, the ISCST3 model
can access meteorological data (e.g., wind speed and direction) from the nearest weather station.
If several stations are nearby, the user selects the one that he or she believes adequately portrays
the release site. The following generic parameters were used for the three facilities:
STACK PARAMETERS ASSUMPTIONS
Duration of releases: 24 hours
Release height 10 meters
Inner stack diameter: 0.01 meters
Exit gas temperature: 293°K
Exi t gas vel oci ty: 0.01 meters/sec
Distance to fence line: 100 meters
Site layout: flat, rural
Generic ketone half life: 164,160 seconds (1.9 days)
Other modeling options: default
FUGITIVE (AREA) PARAMETERS ASSUMPTIONS
Duration of releases: 24 hours
Release height 3 meters
Exit gas temperature: 293°K
Area source size: 10m by 10m
Exit gas velocity: 0.01 meters/sec
Distance to fence line: 100 meters
Site layout: flat, rural
Generic ketone half life: 164,160 seconds (1.9 days)
Other modeling options: default
The ISCST3 model was used to calculate estimates of the ambient air concentration for
three scenarios, the single worst day (highest concentration) of the year, the 50th worst day of the
year and the average day. Each of these estimates for the three facilities is shown in Table 1.
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Risk Characterization Handbook
Table 1. Estimated Ambient Air Concentrations of Generic Ketone For Three Facilities
Facility
A
B
C
Type of Day Modeled
Highest Concentration Day
50th Highest Concentration Day
Average Day
Highest Concentration Day
50th Highest Concentration Day
Average Day
Highest Concentration Day
50th Highest Concentration Day
Average Day
Estimated Ambient Air
Concentration (ppm)
4.8
1.9
0.5
2.3
1.3
0.3
2.0
1.2
0.25
There are many uncertainties associated with the estimates shown in Table 1. As noted
above, the only site-specific information available was some meteorological information based
on the zip code of the facility. All other parameters used in the model were default values, which
for the most part are based on conservative assumptions. The largest source of uncertainty is
associated with the pattern and duration of the release of generic ketone. It is necessary to use an
assumption since the only site-specific data available are a single estimate of total annual release;
therefore the actual number of days where releases occur is unknown. The values shown in
Table 1 were derived based on the assumption that releases of generic ketone take place
continuously over 365 days per year. However, if releases actually occur over shorter periods,
the model would estimate higher ambient air concentrations. The impact of different
assumptions regarding the pattern of releases of generic ketone on the estimates of the ambient
air concentration is shown in Table 2.
Table 2. Estimated Ambient Air Concentrations of Generic Ketone — Impact of Pattern of
Release
If Releases Occurred...
Over 24 hours/ day, but only on weekdays
Over 24 hours/day every day, but only 6 months/year
Air Concentrations Would
Increase By a Factor of...
1.5
2
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Risk Characterization Handbook Page C-25
Over 365 days, but only one 8-hour shift per day
Over 24 hours/day every day, but only 1 month/year
Over 24 hours/day every day, but only 1 week/year
3
12
52
2.2 Modeling of Surface Water Concentration of Generic Ketone
The ReachScan model was used to estimate the surface water concentrations resulting
from reported annual releases of generic ketone to surface water. ReachScan is a simple dilution
model used to estimate steady-state chemical concentration in surface water bodies (mainly river
reaches) due to a continuous loading from a single discharging facility. Several default
parameters are used for the modeling including:
Duration of releases: Constant over 365 days per year
Distance of search: 200 km
Direction of search: Downstream
Type of search: Search for utilities
Flow type: Harmonic mean
The model provides stream concentration estimates at the reach where the releasing
facility is located and at the reach where the drinking water utilities are located. In addition to
the default assumptions listed above, it was also assumed that generic ketone was not removed
in-stream (e.g., volatilization) or at the drinking water facility. Thus, the estimate of the stream
concentration at the drinking water utility is assumed to be the same as the concentration in the
drinking water.
As noted above, the greatest source of uncertainty pertains to the assumption that generic
ketone is released continuously over 365 days per year. However, if releases actually occur over
shorter periods, the model would estimate higher surface water concentrations. For example, if
the releases occurred over 10 days per year, the value calculated for the surface water
concentration would increase by a factor of 37. The value would increase by a factor of 12 or 1.5
if releases occurred over 30 days per year or 250 days per year, respectively.
2.3 Estimation of Acute Potential Dose Rates Via Drinking Water Consumption
The potential exposure of the population to releases of generic ketone to surface water
would be through consumption of drinking water. Drinking water consumption can be calculated
on a daily basis or it can be calculated as a lifetime average. The former estimate is generally
referred to as the acute potential dose rate (APDR) and the later is generally referred to as the
lifetime average daily dose (LADD). The APDR is calculated when the toxic effect of a
chemical is thought to be the result of a short-term acute exposure, whereas the LADD is
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calculated when the toxic effect is thought to be the result of long-term chronic exposure. For
generic ketone, the primary concern is for potential developmental toxicity. A central
assumption that is used in developmental toxicity risk assessments is that developmental effects
can result from a single exposure to the chemical. Therefore, for this assessment, it is most
appropriate to use estimates of the APDR.
In accordance with Agency guidelines for exposure assessment, the APDR was calculated
using the following equation:
APDR = CxIRxCFl
BW
where:
C = surface water concentration (ug/1)
IR = water intake rate (I/day)
CF1 = conversion factor from ug to mg (0.001)
BW = body weight (kg)
The following assumptions were made:
C = Calculated using a simple dilution water model executed in ReachScan.
The concentration in the water varies from facility to facility. Used the
highest stream concentration estimated by ReachScan and assumed no
removal
IR = 2 L/day, this value represents the high-end value for water consumption
CF = Conversion from ug to mg (1 .Oe"3)
BW = 65 kg, this value represents adult females
The three facilities with the highest annual releases to surface water were modeled by
ReachScan for this assessment. The estimated surface water concentrations and the associated
drinking water APDRs are presented in Table 3. The concentration in the water ranged from 4.4
to 47 ug/L at the three highest drinking water utilities. The drinking water APDRs range from
1.4 x 10'4 to 1.4 x 10'3 mg/kg/day.
Table 3. Acute Exposures Resulting From Surface Water Releases
Facility
1
2
Estimated Surface Water
Concentration (ug/L)1
47
9
Acute Potential Dose Rate
(mg/kg/day)1
0.0014
0.00028
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4.4
0.00014
Assumes that the amount reported released to water in 1994 was released over 365 days/year.
If the number of release days were changed to 10, 30, or 250, the resulting surface water concentrations and APDR would
increase by afactor of 37, 12 and 1.5, respectively.
2.4 Exposure Characterization
Ninety-nine percent of generic ketone released to the environment is through stack (point)
and fugitive (area) emissions into the atmosphere. The remaining one percent of releases go to
surface waters, landfill, and deep well injections. For this assessment, ambient air concentrations
and surface water concentrations were estimated for the three facilities with the highest releases
of generic ketone. These values were estimated through the use of two models, the KCST3, and
ReachScan models.
In the absence of site-specific information, each model requires the use of various default
assumptions which introduce uncertainties into the analysis. The greatest uncertainty is due to
the assumption regarding the number of days during the year that the facility releases generic
ketone. This assumption arises because of the fact that facilities only report total annual releases
and do not provide information on the pattern of the releases. For this assessment, it was
assumed that the air and water releases of generic ketone occurred evenly over 365 days per year.
However, the values calculated could be substantially higher if releases occurred for less than 24
hours per day (such as only during a 8 hour work shift) or occurred for less than 365 days per
year.
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APPENDIX D
MITEC CASE STUDY
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Page D-2 Risk Characterization Handbook
Contents
EXECUTIVE SUMMARY Page D-4
1. CONTEXT Page D-6
1.1 Background Page D-6
1.2 Planning and Scoping Page D-7
2. RISK PARADIGM Page D-9
2.1 Hazard Identification and Dose Response Page D-9
2.1.1 Noncancer Page D-9
Systemic Toxicity Page D-9
Acute Toxicity Page D-9
Route-to-Route Extrapolation Page D-10
2.1.2 Cancer Page D-10
EPA's 1996 Cancer Risk Guidelines Page D-10
EPA's Proposed Cancer Risk Guidelines Page D-12
2.1.3 FQPA Considerations Page D-12
2.2 Exposure Assessment Page D-13
2.2.1 Dietary Exposure (Food) Page D-13
2.2.2 Dietary Exposure (Drinking Water) Page D-14
2.2.3 Occupational and Residential Exposures Page D-15
2.3 Risk Calculations Page D-15
2.3.1 Occupational Noncancer Risks for Mixers/Loaders
and Applicators Page D-15
2.3.2 Dietary (Food and Water) Risk Page D-16
2.3.3 Risk to Children Page D-17
2.3.4 Occupational and Residential Cancer Risks Page D-18
2.4 Strengths and Uncertainties Page D-18
2.4.1 Hazard Identification and Dose Response Page D-18
2.4.2 Dietary Exposure Estimates Page D-19
2.4.3 Occupational and Residential Exposure Estimates Page D-20
2.4.4 BigCorp's Risk Assessment Page D-20
3. CONCLUSIONS Page D-20
4. RECOMMENDATIONS REGARDING DATA GAPS Page D-21
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Risk Characterization Handbook Page D-3
Tables
Table 1. Estimated cancer risk from selected commodities Page D-16
Table 2. Comparison of Linear and Non-Linear Model Options Page D-17
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MITEC RISK CHARACTERIZATION
EXECUTIVE SUMMARY
Context
EPA's Office of Pesticide Programs (OPP) initiated the human health risk assessment of
Mitec under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) reregistration
process. Mitec is a miticide registered for agricultural use on field, fruit, nut, and vegetable
crops. The preliminary risk assessment for Mitec showed potential "unreasonable adverse
effects," according to FIFRA criteria. Therefore, OPP scientists and regulatory staff were faced
with the task of determining what risk-mitigation measures might be needed. To accomplish
this, the OPP Mitec team entered into risk mitigation discussions with the registrant, BigCorp.
Just as these discussions were about to begin, another EPA office (outside the Pesticide Program)
released DRAFT cancer risk assessment guidelines. These draft guidelines introduced some
science policy changes which significantly impacted the Mitec risk assessment. These science
policy changes are discussed in the case study.
Also during the reregistration process for Mitec, new pesticide legislation was introduced.
On August 3, 1996, the Food Quality Protection Act of 1996 (FQPA) was signed into law. This
Act amends the existing pesticide legislation, FIFRA and FFDCA is some important ways.
FQPA requires EPA to make a safety finding of a "reasonable certainty of no harm'Tor every
pesticide. FQPA further requires that EPA consider special sensitivity of infants and children to
pesticides, as well as the aggregate exposure of the public to pesticide residues from all sources
(such as food, water, and residential use), and the cumulative effect of pesticides with other
pesticides which share a common mechanism of toxicity. For the Agency to proceed with the
reregistration of Mitec, the risk assessment had to be revised to address the criteria mandated by
FQPA.
Risk Paradigm
Hazard Identification and Dose Response Assessment
The OPP Hazard Identification Assessment Review Committee (HIARC) reviewed the
entire toxicological database to identify appropriate toxicological endpoints to assess the dietary
and occupational risks.
HIARC selected the endpoint of decreased maternal body weight gain from a rabbit
developmental toxicity study to analyze risks from short- and intermediate-term exposures to
agricultural workers. The No Observed Adverse Effect Level (NOAEL) for the rabbit
developmental study was 6 mg/kg/day this value was used in the occupational risk assessment.
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Risk Characterization Handbook Page D-5
The HIARC also recommended further evaluation of the Mitec database for
carcinogenicity potential by the OPP Cancer Assessment Review Committee (CARC) because
the chronic rodent studies for Mitec showed carcinogenic activity. CARC reviewed the
carcinogenicity of Mitec on two different occasions. At the first CARC, Mitec was classified as
a Group B2 carcinogen according to EPA's 1986 Guidelines for Carcinogen Risk Assessment as
a Group B2 carcinogen. The classification was based on two rat bioassays that showed
undifferentiated jejunal sarcoma, a malignant and extremely rare tumor type. The second CARC
was convened to evaluate Mitec's carcinogenicity in light of the proposed revisions to the
Carcinogen Risk Assessment Guidelines. Based on the direction of the proposed revisions to the
Guidelines, the CARC recommended evaluating cancer risk of Mitec using two methods.
The Food Quality Safety Act factor for the protection of infants and children was reduced
to IX based on the: (1) completeness of the toxicology database; (2) lack of evidence of
increased susceptibility following pre- and post-natal exposures; and (3) the use of adequate data
(actuals and surrogate) to satisfactorily assess dietary and non-dietary exposures.
Exposure Assessment
During the planning and scoping phase, OPP identified dietary and occupational exposure
as the primary exposure pathways for Mitec. FQPA requires EPA to aggregate exposure from
food, water, and residential exposure. Since Mitec is not likely to reach groundwater and surface
water under most environmental conditions and there are no residual risks associated with Mitec
use, only the dietary risk from food was included in the aggregate risk assessment. Occupational
exposure is not assessed under FQPA, and is not included in the aggregate risk assessment.
OPP estimated potential dietary exposures from BigCorp's market basket survey, which
provided actual residue monitoring data at the point of food distribution to grocery stores;
monitoring data from the U.S. Department of Agriculture's (USDA's) Pesticide Data Program
(POP); field trials; and processing studies. OPP conducted the dietary risk analysis using the
Dietary Exposure Evaluation Model (DEEM™), which estimates the percent of the acute and
chronic population adjusted dose (PAD) contributed through the diet. OPP also used food
consumption data from the 1989-1992 USDA CSFII survey to determine dietary food
consumption patterns of commodities containing Mitec residues. OPP used information
primarily from the Pesticide Handlers Exposure Database (PHED) to estimate potential
exposures to mixers, loaders, and applicators as well as private growers and aerial applicators
who use typical Mitec products.
Risk Characterization
Noncancer risks (Margin of Exposures, MOEs) were of low concern based upon limited
exposure and minimal systemic toxicity. MOEs ranged from 33 to 30,000 for total exposure.
Although mixer/loaders and applicators of Mitec on almonds and walnuts have systemic toxicity
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MOEs less than 100, their exposure is likely to be of short duration. The severity of effect and
route-to-route extrapolation further lessen OPP's concern. Uncertainty associated with the
systemic toxicity endpoint has mainly to do with route-to-route extrapolation from oral gavage to
dermal routes. Mixer/loaders and applicators are exposed to Mitec primarily by the dermal route
and to a minor extent by inhalation. The method OPP used to estimate a dermal absorption
factor of 6% has not been validated with pharmacokinetic studies.
Confidence in the basis for a dietary cancer risk and for exposure is high. The total
dietary risk from all published agricultural uses of Mitec is 1.6 x 10"5 with exposure to children
from apples, peaches, and grapes (2.5 x 10"7 to 9.1 x 10"6) resulting in the major source of risk
concern. Occupational cancer risks (skin exposure) ranged from 10"7 to 10"4 with high risks
estimated for wettable powders on grapes (open and closed cabs) and commercial mixer/loaders
(open mix system). Occupational cancer risks in the range of 10"4 to 10"6 are acceptable based
upon the OPP Cancer Worker Risk Policy. OPP derived the Qj* using the time-to-tumor
statistical model, which HIARC and CARC believe is the most scientifically appropriate model
for this case. Alternate (lower) cancer risks estimated by the registrant are not considered as
scientifically valid since they do not account for time-to-tumor information.
The evidence for carcinogenicity and the evidence for systemic toxicity (decreased body
weight gain) is strong. Rare and fatal tumors observed in two rat bioassays confirmed
carcinogenicity. Three different species exhibited decreased body weight gain within a similar
dose range.
OPP has high confidence in the dietary risk estimates. Two reliable sources of residue
data (the market basket survey and USDA's PDP) are in close agreement, and OPP used the food
consumption data from the 1989-1992 USDA CSFII survey, which is the latest survey available.
OPP has low overall confidence in many of the occupational exposure scenarios due to a
low number of replicates or poor data quality. Therefore, the occupational exposure estimates
should be considered preliminary.
1. CONTEXT
1.1 Background
EPA's Office of Pesticide Programs (OPP) initiated the human health risk assessment of
Mitec under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) reregistration
process. The 1988 Amendments to FIFRA requires EPA to reregister all pesticides first
registered before November 1, 1984. Reregistration involves a thorough review of the scientific
database underlying a pesticide's registration. The purpose of EPA's reregistration process under
FIFRA was to reassess the potential hazards and risks arising from the currently registered uses
of the pesticide according to modern standards; to determine whether the data requirements for
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the pesticide have been satisfied and whether there is a need for additional data on health and
environmental effects; and to determine whether the pesticide meets the "no unreasonable
adverse effects" criteria of FIFRA. Because the risk assessment for Mitec showed potential
"unreasonable adverse effects," OPP scientists and regulatory staff were faced with the task of
determining what risk-mitigation measures may be needed. Therefore, the OPP Mitec team
entered into risk mitigation discussions with the registrant, BigCorp. Just as the risk mitigation
negotiations were about to begin, another EPA office (outside the Pesticide Program) released
DRAFT Cancer Risk Assessment Guidelines for the Agency. These draft guidelines introduced
some science policy changes that significantly impacted the Mitec risk assessment; these policy
changes are discussed in the case study.
New pesticide legislation was introduced during the reregistration process for Mitec. On
August 3, 1996, the Food Quality Protection Act of 1996 (FQPA) was signed into law, amending
the existing pesticide legislation, FIFRA and FFDCA.. FQPA established a new regulatory
standard, requiring EPA to make a safety finding of a "reasonable certainty of no harm'Tor every
pesticide. To make this finding, FQPA requires EPA to consider certain criteria: (1) special
sensitivity of infants and children to pesticides, (2) the aggregate exposure of the public to
pesticide residues from all sources (such as food, water, and residential use), and (3) the
cumulative effect of pesticides with other pesticides which share a common mechanism of
toxicity. For OPP to proceed with the reregistration of Mitec, the risk assessment had to be
revised to address the criteria mandated by FQPA.
Mitec is a miticide used on field, fruit, nut, and vegetable crops. Apples, grapes, oranges,
peaches, almonds, walnuts, cotton, field corn, and mint comprise 80% of Mitec use in the United
States. There are no residential (non-occupational) uses of Mitec. The most widely used Mitec
products are the wettable powder and emulsifiable concentrate. BigCorp is the sole manufacturer
and owner of Mitec, which is one of the last remaining miticides on the market. One of its major
benefits is that it can be used in Integrated Pest Management (PM) programs because it does not
kill beneficial mites. There are few registered alternative miticides, but none of them spares
beneficial mites.
1.2 Planning and Scoping
In planning the risk assessment, OPP considered how risk managers might use the risk
assessment and focused on two options: (1) if the risks were unsafe, risk managers could adopt
risk mitigation measures on any or all uses of Mitec to ensure conformance with the Agency's
dietary and worker exposure standards for acceptable risk; and (2) if the risks were already within
acceptable risk standards, risk managers could choose to take little or no action. OPP could then
proceed with reregistration of Mitec.
During the planning and scoping phase, OPP identified dietary and occupational
(mixer/loader, applicator, growers, commercial applicators) risks as the primary risks. Dietary
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Risk Characterization Handbook
risk to children was of particular concern based on their food consumption patterns. OPP also
used food consumption data from the 1989-1992 USDA Food Consumption Survey to determine
dietary food consumption patterns of commodities containing Mitec residues. As the case study
will demonstrate, commodities containing the highest residues of Mitec were also foods
comprising a large part of a typical child's diet preliminary estimates show that exposure to
fresh fruit commodities comprise between 75 and 89% of the total dietary exposure of Mitec to
adults, infants (non-nursing) less than one year of age, and children one to six years of age. For
infants, exposure to processed fruit commodities contributes more than 82% of their total dietary
exposure to fruits. However, despite the concern for children's exposure to Mitec on the basis of
food consumption patterns, OPP does not have any evidence that children show any special
sensitivity to Mitec.
OPP estimated potential exposures in the diet with data from BigCorp's market basket
survey, monitoring data from the U.S. Department of Agriculture's (USDA's) Pesticide Data
Program (POP), field trials, and processing studies. OPP conducted the dietary risk analysis
using the Dietary Exposure Evaluation Model (DEEM™), which estimates the percent of the
acute and chronic population adjusted dose (PAD) consumed by each population group. (The
PAD reflects the acute or chronic Reference Dose (RfD) for a chemical that has been adjusted to
account for the FQPA safety factor, which, for Mitec, was IX..) OPP also used the DEEM
model to estimate cancer risk for the total US population. OPP used food consumption data
from the 1989-1992 USDA Food Consumption survey to estimate dietary exposure to Mitec.
OPP used information primarily from
the Pesticide Handlers Exposure Database
(PHED) to estimate potential exposures to
mixers, loaders, and applicators as well as
private growers and aerial applicators using
typical Mitec products.
The OPP Hazard Identification
Assessment Review Committee (HIARC)
reviewed the entire toxicological database and
appropriate endpoints characterized for the
dietary and occupational risks. The
Committee's function was to validate the
toxicity conclusions and choose appropriate
endpoints for risk assessment. The HIARC
recommended further evaluation of the
database for Mitec carcinogenicity potential
by the OPP Cancer Assessment Review
Committee (CARC).
Acronyms
CARC Cancer Assessment Review
Committee
DEEM™ Dietary Exposure Evaluation
Model
FQPA Food Quality Protection Act
HIARC Hazard Identification
Assessment Review Committee
MOE Margin of Exposure
OPP EPA's Office of Pesticide
Programs
PAD Population Adjusted Dose (RfD
adjusted for FQPA factor)
POP USDA's Pesticide Data Program
PHED Pesticide Handlers Exposure
Database
DWLOC Drinking Water Level of
Comparison
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Although the Food Quality Protection Act was passed during the risk assessment process
for Mitec, OPP determined that FQPA would not considerably change the risk assessment. The
FQPA factor for the protection of infants and children was reduced to IX for Mitec. In addition,
no aggregate risk assessment was necessary because there is no residential exposure and water
exposure is negligible. Further, Mitec is not believed to share a common mechanism of action
with any other pesticides, so a cumulative risk assessment is not necessary.
2. RISK PARADIGM
This section summarizes the key information from the human health risk assessment on
Mitec.
2.1 Hazard Identification and Dose Response
The HIARC reviewed the toxicological database for Mitec and determined that while
cancer and systemic toxicity (i.e., decreased body weight gain) are the critical endpoints for risk
assessment, workers may also experience acute, severe dermatitis due to Mitec's corrosive
properties (see Section 2.1.1, Acute Toxicity).
2.1.1 Noncancer
Systemic Toxicity
HIARC evaluated the toxicological database for Mitec and selected an appropriate
endpoint for assessing the noncancer risks associated with short (1-7 days) and intermediate (1
week-several months) term exposure to agricultural workers. Toxicity studies of relatively short
duration were reviewed since most workers are only exposed to Mitec for a few days to a few
weeks per year. The endpoint HIARC selected for short- and intermediate-term occupational
exposures is decreased maternal body weight gain from a rabbit developmental toxicity study.
The No Observed Adverse Effect Level (NOAEL) is 6 mg/kg/day. This NOAEL is supported by
another rabbit developmental study and rat and dog chronic feeding studies with NOAELs in the
range of 6-8 mg/kg/day.
Acute Toxicity
HIARC evaluated animal studies for effects related to acute toxicity, irritation, and
dermal sensitization. The Committee also considered developmental toxicity data because
developmental effects can result from a single exposure to a chemical. Mitec has low acute
toxicity with most LD50 values >5 g/kg. Mitec is a reported skin and eye irritant in animals, and
there are reports of severe dermatitis in farm workers reentering fields treated with Mitec in
California. Further evaluation of this issue is underway (see Section 4.0, data gaps). HIARC
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determined that the weight-of-evidence, including the developmental toxicity data, is insufficient
to support an acute risk assessment.
Route-to-Route Extrapolation
The most appropriate toxicological studies for a human health risk assessment are by the
oral route. However, because dermal contact is the primary exposure route for mixer/loader and
applicator exposure (inhalation is expected to be a minor pathway and therefore a minor
contributor to risk), OPP estimated an absorption factor for route-to-route extrapolation. There
was no adequate dermal absorption study. OPP did this by comparing the NOAEL from a rabbit
21-day dermal toxicity study to the NOAEL for reduced maternal body weight gain from the oral
rabbit developmental toxicity study. The systemic dermal absorption factor is estimated as
follows:
% dermal absorption ~ systemic NOAEL rabbit oral developmental tox study x 100
systemic NOAEL rabbit 21-day dermal tox study
The rabbit 21-day dermal toxicity study on Mitec showed hematologic changes at the
high dose of 100 mg/kg/day, but the investigators attributed this effect to secondary inflammation
resulting from dermal irritation. Other signs of systemic toxicity, such as decreased body weight
gain, were not observed at this dose. Therefore, 100 mg/kg/day was considered to be the
NOAEL for the rabbit 21-day dermal toxicity study. The 6% dermal absorption factor was
calculated as follows:
% dermal absorption ~ 6 mg/kg/day X 100 = 6%
100 mg/kg/day
HIARC concluded that the 6% dermal absorption factor is not likely to underestimate the
risk.
2.1.2 Cancer
EPA's 1996 Cancer Risk Guidelines
Mitec is classified according to the EPA's 1986 Guidelines for Carcinogen Risk
Assessment as a Group B2 carcinogen. OPP's risk assessors and OPP's CARC2 based this
classification on two rat bioassays that showed undifferentiated jejunal sarcoma, a malignant and
extremely rare tumor type. In the first bioassay, OPP was concerned that the stabilizer, propylene
oxide, a known carcinogen and mutagen could have influenced the results. However, tumors
were confirmed with the second bioassay that used an epoxidized soybean oil stabilizer.
1 This is a standard internal peer review conducted within OPP. The conclusions of the CARC have not been evaluated by an
external peer review body, which normally is the OPP Scientific Advisory Panel.
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Evidence for the induction of gene mutations in cultured mammalian cells and chromosome
breaking ability in exposed mice contributed to the weight-of-evidence for carcinogenicity.
BigCorp proposed that Mitec is carcinogenic via anon-linear mechanism, where cell
proliferation in the small intestine (jejunum) is followed by tumor formation. BigCorp submitted
a short-term cell proliferation study to support their claim. HIARC and CARC reviewed these
data and found that they are not sufficient to support the mechanistic claim. BigCorp is planning
to conduct an additional 65-week cell proliferation study, and HIARC and CARC have provided
BigCorp with comments on the protocol for this study.
No data, other than the cell proliferation data, submitted to OPP addressed a possible
mode of action for Mitec tumor induction. HIARC and CARC determined that a low-dose
extrapolation model for projected human exposures is the most appropriate mo del to use due to
the lack of a plausible mode of action other than mutagenic activity, the rarity of the tumor type,
the malignancy, and no evidence that the tumor induction is not relevant to humans.
The cancer mode of action has important risk assessment implications. If Mitec is
carcinogenic by a non-linear mode of action and tumors are only found above a certain critical
dose, then the Agency would use a non-linear model to evaluate human health risk, and risk
numbers probably would be significantly lower (see Section 2.3.1).
CARC determined that the data from the first rat bioassay are adequate for dose-response
quantification. The Mitec unit risk for cancer, called Q!*, is 1.71 x 10 ! (mg/kg/dayT1 for males;
the Q]* is in human equivalents. The Q!* is based on male rat fatal jejunum sarcoma and is
estimated using the Time-to-Tumor Multistage Model and a body weight374 interspecies scaling
factor (the quantification did not include interim sacrificed animals). OPP used a time-to-tumor
model fatal tumor analysis to account for dose related mortality and the high incidence of fatal
sarcomas. The use of this extrapolation model assumes a linear dose-response relationship at
lower doses. The Q^3 represents the slope of the 95% upper bound of the dose-response curve
for jejunum sarcomas. Cancer risk estimates based on the Q]* are an estimate of the upper-bound
risk as per Agency policy, the true value of the cancer risk is unknown.
BigCorp calculated a separate Q!* of 3.2 x 10 2 (mg/kg/day)-1 using the Quantal
Multistage Model, a slightly different statistical model than the one EPA used. The Quantal
Multistage Model does not account for differential mortality and represents the geometric mean
of the Q]* values for males and females from the same tumor data set. HIARC believes that this
statistical model is inappropriate because it is necessary to account for differences in mortality
noted between dose groups since death was from malignant, fatal tumors. The cancer risk
estimates using the Time-to-Tumor Multistage Model versus the Quantal Multistage Model
differ by a factor often.
2 This upper-bound estimate of risk is generally thought to cover the range of human variability and EPA considers it to be
inherently conservative of public health and may also overestimate the risk.
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EPA's Proposed Cancer Risk Guidelines
Based on the direction of the proposed revisions to the Carcinogen Risk Assessment
Guidelines, the CARC has evaluated risk using another linear extrapolation method. CARC has
calculated an LED10 (lower bound of the 10% effective dose or ED10) for Mitec using the time to
tumor model. The LED10 is used as the point of departure from the observed data to draw a
straight line to the origin for a low-dose extrapolation. The unit risk based on this line is very
close to the Q]*. Thus, use of the LED10 does not significantly impact the cancer quantification or
the projected risk estimates. The LED10 versus ED10 is the current Agency consensus for the
point of departure stemming from the proposed Guidelines.
BigCorp submitted their own LED10 for Mitec (not presented). However, the company
used the Quantal Multistage Model to fit the data, which CARC believes is inappropriate for the
reason stated above.
2.1.3 FQPA Considerations
To comply with FQPA, OPP evaluated Mitec to determine whether infants and children
showed any special sensitivity to Mitec, to determine the aggregate exposure of the public to
Mitec residues from all sources (such as food, water, and residential use), and to determine the
cumulative effect of Mitec and other pesticides which share a common mechanism of toxicity.
The FQPA Safety Factor Committee (1999) evaluated the Mitec to determine if an FQPA
Safety Factor was warranted. The Committee concluded that Mitec does not indicate an
increased susceptibility to infants and children. This is based on the pre-natal developmental
toxicity studies in rats and rabbits that provided no indication of increased susceptibility of rat or
rabbit fetuses to in utero exposure to Mitec.
OPP evaluated the potential exposure pathways for Mitec to determine aggregate
exposure from all residue sources. The office concluded that Mitec had very little potential to
contaminate drinking water. Mitec has no residential uses, so residential exposure is not
anticipated. Therefore, aggregate exposure for Mitec only included dietary exposure from
residues in food. OPP conducted an analysis to determine if Mitec was either structurally similar
or showed similar toxicological effects to any other pesticide. The Office concluded that Mitec
is did not share a common mechanism of action with any other currently registered pesticides, so
a cumulative risk assessment is not necessary.
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2.2 Exposure Assessment4
2.2.1 Dietary Exposure (Food)
FIFRA requires submission of residue chemistry data to support all food-use pesticides.
A typical data set includes studies on (1) the nature of the pesticide residue in plants and animals;
(2) the magnitude of the residue in treated crops, processed food and feed, and livestock
commodities, such as meat, milk, and eggs; (3) reduction of residue during food processing; (4)
analytical methods for detecting the residue(s); and (5) chemical identity. These data are used to
determine the residue(s) of concern, establish tolerance levels for enforcement, and estimate
"anticipated" residues of the pesticide in foods on a national level.
OPP calculated the anticipated residues for Mitec to provide a realistic picture of
pesticide residues in foods and subsequent dietary exposure. The data used in this assessment
were based on actual monitoring data at the point of distribution, i.e., market basket survey data
and subsequent monitoring data from USDA's Pesticide Data Program (PDP). Market basket
and/or PDP data were used for most commodities, particularly those that contributed a large
portion of total dietary exposure.
Initially, BigCorp conducted a market basket survey for major food crops treated with
Mitec. The market basket survey measured residues collected at the supermarket. Later, the
USDA PDP collected residue data at regional food distribution centers explicitly for the dietary
risk assessment. The USDA PDP data confirmed the results of the registrant's market basket
survey. Anticipated residues are typically based on data from field trials, processing studies,
FDA, USDA monitoring data, and market basket data, when available. Therefore, FflARC
considered the residue data listed below for Mitec to be a realistic measure of actual residues on
food. HIARC believes the exposure risks based on these data are not overestimated. Listed
below are the commodities showing the highest number of detects from the market basket
survey:
Commodities % Detects Detects/Total Samples
Apples 31% 62/200
Infant Apple Sauce 52% 103/200
Raisins 99% 197/200
Peaches 30% 44/146
Infant Peaches 40% 79/199
3 More detailed information regarding the basis for the dietary and occupational exposure assessments isavaikble in the OPP
Internal Review Document for Mitec (May 1997) and the supporting reviews. This includes information on the range of concen-
trations of Mitec noted in the detects in the commodity samples; use parameters for mixer/loaders and applicators of Mitec; and
unit exposure estimates for dermal, hand, total dermal and inhalation exposures for these workers based on the PHED database.
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OPP used food consumption data from the USDA's 1989-1992 survey to estimate dietary
exposure. Data from the USD A are translated into food forms, which are the individual
components of various foods. OPP calculated dietary exposure for Mitec by combining
information on residues for various foods with food consumption patterns from the USDA
survey to derive an average lifetime exposure estimate for Mitec.
OPP has extremely high confidence in the anticipated residue values used in the dietary
risk assessment because they represent typical residues found in national supermarkets for the
commodities tested, and OPP's and BigCorp's residue values are consistent.
2.2.2 Dietary Exposure (Drinking Water)
Drinking water exposure to pesticides can occur through groundwater and surface water
contamination. EPA considers both acute (one day) and chronic (lifetime) drinking water risks
and uses either modeling or actual monitoring data, if available, to estimate those risks. EPA
determines the maximum allowable contribution of treated water allowed in the diet in a two step
process that involves evaluating how much of the overall risk is contributed by food and
determining a drinking water level of comparison (DWLOC). The Agency uses the DWLOC as
a surrogate to capture risk associated with exposure from pesticides in drinking water. The
DWLOC is the maximum concentration in drinking water which, when considered together with
dietary and residential exposure, does not exceed a level of concern.
OPP based the estimates of Mitec concentrations in groundwater on the SCI-GROW
model, which is a screening tool that provides a high-end estimate under "worst-case" conditions.
OPP based the estimates of Mitec concentrations in surface water on the PRZM-EXAMS model,
which is also a screening tool. Both of the models represent an upper-bound value in units of
parts per billion.
EPA's Pesticides in Groundwater Database reports no detections in 3,341 samples that
have been submitted to date for Mitec. This is consistent with the results of the laboratory and
field dissipation studies, which showed no downward mobility of Mitec in soil.
Because Mitec is not likely to reach groundwater and surface water under most
environmental conditions, and there are no residential risks associated with Mitec use, only the
dietary risk from food is considered for the purpose of calculating the DWLOC . The DWLOC
was then compared with the results of the SCI-GROW and PRZM-EXAMS models. The
modeled concentrations of Mitec in surface and groundwater did not exceed the DWLOC .
Therefore, drinking water risk below OPP's level of concern.
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2.2.3 Occupational and Residential Exposures
Exposure estimates for mixer/loaders and applicators are estimated from the uses of
Mitec on grapes, almonds, apples, peaches, oranges, walnuts, corn, and cotton because these
crops represent high-volume uses of Mitec. The application methods evaluated in the analysis
are the major agricultural methods used on the selected commodities, and they include airblast
(for fruit and nut crops) and ground boom and aerial application for field crops (corn and cotton).
OPP identified the tasks that could lead to occupational exposure to Mitec using the generic
worker monitoring data available in the Pesticide Handlers Exposure Database (PHED) and
usage data for Mitec in OPP's possession. PHED is used in lieu of adequate chemical-specific
monitoring data. PHED may also be used in conjunction with adequate chemical-specific data to
obtain a larger sample pool of monitoring replicates. Although BigCorp submitted worker
exposure monitoring studies for Mitec, these studies were all of poor quality. They did not meet
basic guideline requirements under subdivision U of the Pesticide Assessment Guidelines. No
residential (non-occupational) uses or exposures are associated with Mitec.
2.3 Risk Calculations
2.3.1 Occupational Noncancer Risks for Mixers/Loaders and Applicators
For noncancer effects, OPP calculates margins of exposure (MOEs) as a measure of how
close the estimated exposures come to a no-effect level in an animal study. For Mitec, OPP
calculated MOEs for systemic toxicity (decreased weight gain) based on a NOAEL of 6
mg/kg/day for maternal toxicity from a rabbit developmental toxicity study. This effect was also
noted in other oral studies in other species. OPP reported MOEs for mixer/loaders and
applicators using maximum application rates designated on the label. OPP reported MOEs
separately for inhalation and dermal exposure. Absorption through inhalation is assumed to be
100%, and 6% absorption is assumed for dermal exposure.
MOEs are calculated using the following equation:
MOE = NOAEL (mg/kg/day)
exposure (mg/kg/day) x % absorption
MOEs for Mitec ranged from 33 to 30,000 for total exposure. Uses with low MOEs
(<100) for mixers/loaders or applicators included almonds and walnuts. Mixer/loaders using
Mitec in a wettable powder formulation had MOEs (for total exposure) of 75 for almonds and 58
for walnuts. Growers (mixer/loader/applicators) had low MOEs (<100) for almonds and walnuts
under the following exposure scenarios: wettable powder/open cab and wettable powder/closed
cab. Label restrictions would preclude Mitec application by airblast in open cabs at the
maximum rates for almonds and walnuts; this is the scenario that would otherwise be associated
with MOEs of <50 for growers.
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Risk Characterization Handbook
HIARC has low overall concern for the noncancer risk based on the best available
exposure data, despite MOEs of less than 100. Mixer/loaders and applicators have systemic
toxicity MOEs less than 100 with two crops: almonds and walnuts. For these crops, Mitec
exposure is likely to be of short duration based on average farm size and average acreage treated
per day. HIARC does not support the Mitec systemic toxicity endpoint for short duration or
intermittent exposures. The severity of effect and route-to-route extrapolation further lessen
HIARC's concern for potential systemic effects from Mitec exposure following treatment of
almonds and walnuts.
2.3.2 Dietary (Food and Water) Risk
OPP estimated dietary cancer risks for Mitec using the low-dose extrapolation model.
Cancer risk estimates are given for typical Mitec application rates. Dietary risk from all
published uses is 1.6 x 10 5. This total dietary cancer risk is the accumulation of all cancer risks
calculated for each commodity using the following equation:
Extra cancer risk = Qj* x Anticipated Residue Contribution (ARC)
where Q/ =1.71X10' (mg/kg/day) ' based on jejunum sarcoma in male rats
and ARC is calculated for each commodity based on anticipated residues and food consumption
A few commodities appeared to drive the risk; namely, apples, peaches, and grapes. Table
1 below presents the dietary risk from these individual commodities. Table 2 presents a
comparison of total dietary risk from the linear and non-linear cancer risk models.
Table 1. Estimated cancer risk from selected commodities
Commodity
Apples, total
Fresh
Cooked/Canned
Juice
Peaches, total
Grapes, total
Wine/sherry
Cancer Risk Estimate
9.1 x 10 6
6.1X1Q-6
2.4 X1Q-6
6.0 X1Q-5
2.5 X1Q-6
1 X ID'6
4.4 xlO7
Comments
Major contributor to total
risk, high use, common
children's food items
Major contributor to total risk
Major contributor to total risk
common children's food item
None
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Page D-17
Raisins
2.5xl(T
Common children's food
item
The refined total dietary cancer risk for Mitec in the U.S. population was 1.6 xlO"5. OPP
has very high confidence in this estimate because it is based on actual residue data, the latest
USDA food consumption data, a Qj* based on a rare tumor type, and a scientifically defensible
dose-response extrapolation.
2.3.3 Risk to Children
Because high detects of Mitec residues are found in apples, raisins, and other commodities
consumed by children in large quantities, OPP was particularly concerned about potential risks to
children, the Agency does not have adequate methodology to address cancer risks to children at
this time. A crude assessment was performed to give OPP risk managers information about
potential cancer risks to children from short-term exposure to Mitec. As previously noted, OPP
does not have any evidence that children show any special sensitivity to Mitec, so OPP assumed
that Mitec would have the same cancer potency in children as it does in adults. OPP estimated
cancer risk to children from a single year's exposure to Mitec in the event that Mitec residues
remained in the food supply for up to a year. (Risk to children was estimated by this approach:
annual risk was calculated according to exposure for each subgroup; this risk was then divided by
70 years to estimate annual risk). These risk estimates were calculated using food consumption
values for nursing and non-nursing infants and children of various ages. Annual dietary risk for
each subgroup was amortized over a 70-year lifetime, which assumed that children's food
consumption patterns remained the same over a lifetime. A similar approach was used to
calculate dietary cancer risk to children from alar.
Children's cancer risk from 1-year's exposure to Mitec was estimated to be in the 10
range.
Table 2. Comparison of Linear and Non-Linear Model Options
LINEAR
RESPONSE AT
LOW DOSE
"one-hit" single
dose could
trigger sequence
of events
leading to cancer
MODEL
Time-to-Tumor
Multistage/Qj*
Quantal
Multistage/Qj*
UNIT RISK
ESTIMATE
0.171
0.032
TOTAL
DIETARY
RISK
ESTIMATE
1.6x ID'5
2.9 x ID'6
GROUP
SUPPORTING
USE OF
MODEL
USEPA
BigCorp
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Risk Characterization Handbook
NON-LINEAR
tumors expected
only above a
critical dose
Time-to-Tumor
Multistage
LED10
Margin of
Exposure
(MOE)
0.160
NOAEL = 4
mg/kg/day
1.5xlO-5
MOE>40,000
(not of concern)
USEPA, 1996
Proposed Cancer
Guidelines
BigCorp
2.3.4 Occupational and Residential Cancer Risks
There are no residential (non-occupational) exposures and therefore no residential risks
associated with the use of Mitec. However, risks via oral and dermal routes of exposure are
associated with occupational uses of Mitec, and an absorption factor was estimated for route-to-
route extrapolation for mixer/loader and applicator exposure scenarios (see Section 2.1.1).
Occupational cancer risks (skin exposure) ranged from one in ten million (10~7) to one in
ten thousand to (10~4) with the highest risks estimated for growers that use wettable powders on
grapes (open and closed cabs) and commercial mixer/loaders that support aerial sprayers (open
mix system). These risks are within the range of acceptable risks (of 10"4 to 10"6) set forth in
OPP's Cancer Worker Risk Policy. OPP calculated the occupational cancer risk estimates using
the Q]* value were calculated as follows:
Extra cancer risk = Qj* x LADD
where Q!* = 1.71 x 10 ' (mg/kg/day) ' based on jejunum sarcoma in male rats (oral bioassay)
and LADD = Lifetime average daily dose, worker exposure at typical application rate,
amortized over a 70-year lifetime (with a 35-year work life) and adjusted for 6%
dermal exposure.
2.4 Strengths and Uncertainties
The risk assessment for Mitec contains strengths and uncertainties based on the existing
toxicological and exposure data, data gaps, and gaps in scientific knowledge. The assessment
includes standard assumptions regarding: human body weight, work life, interspecies and
intraspecies uncertainty (safety) factors, and other exposure parameters; interspecies
extrapolation; and exposure prorated over a lifetime to estimate cancer risks. HI ARC made
additional assumptions regarding route-to-route extrapolation.
2.4.1 Hazard Identification and Dose Response
The existing evidence for the carcinogenicity endpoint is strong. The two rat bioassays
and the rare and fatal tumor type—undifferentiated sarcoma of the jejunum—confirmed
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carcinogenicity. CARC classified Mitec as a Group B2, probable human carcinogen. HIARC and
CARC have high confidence in the statistical model used for the cancer dose-response assessment
(Qj* and ED10). The Qj* is the 95th percent confidence limit of the dose-response curve, which is
the default Agency policy. The actual cancer potency maybe considerably less than estimated
using this value. OPP derived the Q!* using the time-to-tumor statistical model because it
incorporates the biological observations of dose-related mortality issues in the rodent bioassay.
HIARC and CARC believe this model is the most scientifically appropriate model for this
particular case. Although BigCorp proposed a potential non-linear mode of action, the database
does not support this argument. CALEPA and HEALTH CANADA agree with EPA's
interpretation of the data.
The evidence for the systemic toxicity endpoint (decreased weight gain) is also strong.
Three species—rat, rabbit, and dog—exhibited this effect within a similar dose range. For the
chronic rat and dog feeding studies and the rabbit developmental toxicity study (gavage), the
NOAEL was within the range of 4-6 mg/kg/day with Lowest Observed Adverse Effect Levels
(LOAELs) for all species based on decreased weight gain.
There is uncertainty regarding the relevance of the systemic toxicity endpoint to the
anticipated exposure scenarios for Mitec. HIARC believes this endpoint is not relevant to single
day, intermittent exposures. HIARC believes that repeated exposure would be required to
produce this effect at levels to which humans are exposed. Growers who apply Mitec at the rate
specified on the label would be exposed from 1 to 5 days per treatment and from 2 to 12 days per
season. Exposure duration is likely to vary with farm size and the severity of the pest problem.
Commercial applicators may be exposed throughout the treatment window for a particular crop
and pest.
An additional area of uncertainty pertaining to the systemic toxicity endpoint is route-to-
route extrapolation. Most of the toxicology data used to support the systemic endpoint are from
studies with oral gavage or dietary administration. Investigators used oral gavage in the rabbit
developmental study used for the risk assessment. However, mixer/loaders and applicators are
exposed to Mitec by the dermal and inhalation routes. There are likely to be significant
differences in absorption and pharmacokinetics between routes due to the bolus effect associated
with oral gavage, local irritation seen with dermal dosing, and other factors. Another issue for
consideration is severity of effect. Decreased weight gain is a relatively minor effect.
2.4.2 Dietary Exposure Estimates
OPP has extremely high confidence in these dietary risk estimates. Two highly re liable
sources of residue data (the market basket survey and USDA's POP) are in close agreement, and
OPP used the food consumption data from the 1989-1992 USDA CSFII survey, which is the latest
such survey available. OPP's analyses were based on a well designed market basket survey as
recommended by the 1993 NAS report on Pesticides in the Diets of Infants and Children.
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Overall, the Mitec case is one of the most refined dietary risk assessments ever performed in the
Agency.
2.4.3 Occupational and Residential Exposure Estimates
OPP has low overall confidence in many of the occupational exposure scenarios due to a
low number of replicates and/or poor data quality. There are no residential (non-occupational)
uses of Mitec.
The occupational exposure estimates should be considered preliminary for a number of
reasons. OPP limited the occupational exposure assessment to the major crops and application
methods. For many of the scenarios evaluated, PHED exposure estimates were based on data sets
with either low numbers of replicates and/or poor quality. Exposure scenarios with medium or
high confidence include open mixing for liquid formulations, airblast application with closed
cabs, and aerial spraying.
OPP based the exposure estimates for commercial applicators (for aerial spraying) on the
maximum number of acres that could be treated in a given day. No information was available on
the average acreage treated per year by commercial applicators. The best available information on
pest control practices indicates that Mitec may be used up to 3 months per growing season.
Therefore, to estimate cancer risk, the lifetime average daily dose for the cancer risk assessment
was estimated for two scenarios: application of Mitec either 1-3 days/year or 5 days/week for 3
months for corn and cotton. The first scenario is likely an underestimate of lifetime exposure, and
the second may be an overestimate.
2.4.4 BigCorp's Risk Assessment
In 1993, BigCorp submitted a dietary and occupational risk assessment that showed
dietary risk to the total U.S. population of 1.53 x 10 6 to 9.25 x 10 10 and occupational risks in the
range of mid 10 5 to 10 9. However, BigCorp made significantly different assumptions from those
the Agency used. BigCorp used a different Qj*, different residue values, and a different method of
dietary analysis (Tolerance Assessment System or TAS). In addition, BigCorp rebutted many of
the assumptions made in the current dietary risk assessment. However, OPP has discussed these
differences in assumptions at great length internally and EPA scientists believe that the available
data strongly support the Agency's position on the dietary cancer risks of Mitec.
3. CONCLUSIONS
The assessment of Mitec is the product of many choices in the assumptions used to
address the uncertainties. In all risk analyses there are a range of mixes of choices that can be
made. Of those that OPP considered reasonable for Mitec, occupational exposures give both the
largest and least estimates of risk to workers. Our judgement for the best mix of choices made in
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Risk Characterization Handbook Page D-21
this assessment of the estimated risk is for dietary cancer among children, which was a value
judgement based upon the risk estimates calculated, policy considerations for occupational risks
including its voluntary nature, and differences in data quality between dietary and worker
exposure data.
The total dietary risk from all published agricultural uses of Mitec is 1.6 x 10~5 with
exposure to children from apples, peaches, and grapes (2.5 x 10~7 to 9.1 x 10~6) resulting in the
major source of risk concern. Occupational cancer risks (skin exposure) ranged from 10~7 to 10~4
with high risks estimated for wettable powders on grapes (open and closed cabs) and commercial
mixer/loaders (open mix system). Occupational cancer risks in the range of 1CF4 to 10~6 are
acceptable based upon the OPP Cancer Worker Risk Policy.
Confidence in the basis for a dietary cancer risk and for exposure is high. Occupational
exposure estimates are considered preliminary. Alternate (lower) cancer risks estimated by the
registrant are not considered as scientifically valid since they do not account for time-to-tumor
information. Noncancer risks (Margin of Exposures, MOEs) were of low concern based upon
limited exposure and minimal systemic toxicity.
Although the Food Quality Protection Act was passed during the risk assessment process
for Mitec, FQPA did not considerably change the risk assessment. As stated previously, the
FQPA factor for the protection of infants and children was reduced to IX for Mitec. In addition,
no aggregate risk assessment was necessary because there is no residential exposure and water
exposure is negligible. Further, Mitec is not believed to share a common mechanism of action
with any other pesticides, so a cumulative risk assessment is not necessary.
4. RECOMMENDATIONS REGARDING DATA GAPS
4.1 BigCorp claims that Mitec is carcinogenic via a non-linear mechanism, where cell
proliferation in the small intestinal (jejunum) is followed by tumor formation. To
substantiate this claim, BigCorp is planning to conduct a 65-week cell proliferation
study. If a threshold dose, indicating a non-linear mechanism for tumor formation,
can be justified, the Agency is likely to consider using a different model that could
significantly modify concerns about the risk.
4.2 Pharmacokinetic data are needed to verify the assumption of 6% dermal absorption
as well as to validate the general use of ratios of oral and dermal NOAELs as a
scientifically acceptable method of estimating dermal penetration.
4.3 High quality occupational exposure data are needed for the major crops Mitec is
used on and application methods that agricultural workers use.
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4.4 Additional investigation of exposures experienced by workers reentering fields
treated with Mitec, including the adequacy of their protective equipment, is needed
based on concerns about Mitec's corrosive properties.
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Risk Characterization Handbook Page E-l
APPENDIX E
MIDLOTHIAN CASE STUDY
Multimedia Planning and Permitting Division
U.S. Environmental Protection Agency
Region 6
1445 Ross Avenue
Dallas, TX 75202
December 1998
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Page E-2 Risk Characterization Handbook
Contents
EXECUTIVE SUMMARY Page E-3
1. CONTEXT Page E-6
1.1 Scope and Purpose Page E-6
1.2 Characteristics of Study Area Page E-7
1.3 Context with Superfund Page E-7
2. RISK PARADIGM Page E-8
2.1 Exposure Assessment Page E-8
2.2 Hazard Identification, Dose-Response, and Risk Estimation Page E-10
2.3 Limitations and Uncertainties Page E-12
2.3.1 Emission Rates Page E-13
2.3.2 Exposure Parameter Uncertainty Page E-14
2.3.3 Limitations of ISCSTDFT Air Modeling Page E-15
2.3.4 Uncertainty Associated with Exposure Scenarios Page E-15
3. CONCLUSIONS Page E-15
4. RECOMMENDATIONS REGARDING DATA GAPS Page E-18
5. LITERATURE CITATIONS Page E-19
Map 1 Page E-25
Tables
Table 1. Overall Cancer Risk (Direct and Indirect) for All Carcinogenic Chemicals . . Page E-10
Table 2. Comparison of Modeled and Measured Concentrations Page E-16
Table 3. Comparison of Unit Deposition Rates and Air Concentrations at Point 3 ... Page E-17
Table 4. Comparison of Emission Rates Page E-17
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Midlothian Cumulative Risk Assessment Risk Characterization
EXECUTIVE SUMMARY
Context
EPA Region 6 prepared a risk assessment in support of the RCRA permitting process and
in response to citizens' concerns about the permitted burning of hazardous waste in a cement kiln
by Texas Industries (TXI) of Midlothian, Texas, which is approximately 30 miles south of the
Dallas-Ft. Worth metropolitan area. Because of the close proximity of a steel company and two
other cement manufacturing companies, Region 6 included emissions from all four industrial
facilities in the risk assessment. Chaparral Steel Corporation is 0.7 miles southwest of TXI, and
North Texas Cement Company and Holnam Cement Company are approximately 4 and 5 miles
northeast of TXI, respectively. From TXI, the study area extends 3 miles south, 3 miles east, 6
miles west, and 8 miles north to Joe Pool Lake, which supplies drinking water to the study area.
With the exception of the City of Midlothian (approximate population of 5,100), located
approximately 3 miles northeast of TXI, the land use of the study area is predominately
agricultural with some industrial development. The area is home to several small cattle
operations and rural residential developments. Many homes in the are a have gardens. In
addition to Joe Pool Lake, the area contains two privately owned lakes known as Soil
Conservation Service (SCS) Lakes 9 and 10.
Risk Paradigm
Exposure
The risk assessment presents an overview of screening level risk estimates for direct (i.e.,
drinking water consumption and inhalation) and indirect (i.e., food consumption) exposures
attributable to emissions from the three cement companies and the steel mill. Risk assessors
considered four types of exposed individuals: the subsistence farmer, adult resident, child
resident, and subsistence fisher as suggested in the draft Guidance for Performing Screening
Level Risk Analyses at Combustion Facilities Burning Hazardous Wastes (U.S. EPA, 1994).
Since overall risks for each pathway could vary according to which contaminant was deposited at
the highest rate at a particular location or was present at the highest ambient air location, the risk
assessors considered multiple receptor locations for each exposure scenario to ensure that the
maximum media concentrations of each pollutant were considered.
EPA evaluated the most current information available to estimate the probability of
potential impacts to human health, both directly via inhalation, incidental soil ingestion, and
drinking water (via surface water intakes), and indirectly via modeled deposition and uptake
through the food chain. Because the drinking water supplied to the area surrounding the facilities
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comes from one source—Joe Pool Lake—exposure via contaminated drinking water from this
source was considered under all of the scenarios.
The predominant sources of risk from the four industries were evaluated by comparing
the emission rates and the unit-combined deposition and air concentrations associated with each
facility. The indirect exposure air model used in this analysis is the only EPA-recommended air
dispersion and deposition model for addressing a variety of exposure pathways important for
chemicals that bioaccumulate and persist in the environment.
Effect and Risk Estimation
No cancer risk above regulatory levels of concern was identified. The most significant
theoretical cancer risk would result from the ingestion offish caught from SCS Lakes 9 & 10,
and arsenic contributes up to 80% of this risk.
Risk assessment results based on theoretical and conservative modeling indicate a
potential for non-cancer health effects from exposure to antimony in drinking water, and to
cadmium and mercury through the ingestion offish from SCS Lakes 9 & 10. However, actual
site data (for soil and water samples near residents and fishing areas) indicate that the models
over-predict media concentrations of the principle contaminants, antimony and cadmium, which
drive the potential for theoretical non-cancer health effects.
Region 6 found no basis for federal regulatory action in regards to potential mercury
risks. Borderline potential effects predicted in the risk assessment represent conservative
estimates of risk for this compound. Also, measured media concentrations of mercury are within
the range of U.S. background concentrations of mercury. In addition, the Texas Natural
Resources and Conservation Commission found in 1995 that concentrations of mercury in the
Midlothian area are equal to or lower than local and U.S. background levels.
The lack of good quality chemical-specific emission rates presents one of the largest
sources of uncertainty associated with this screening level risk assessment. Another significant
source of uncertainty overall is that the compound-specific allocation of emissions for the steel
mill is based on the assumption that baghouse and fugitive emissions contained concentrations of
contaminants similar to those found in steel mill baghouse dust. Another area of uncertainty
concerns the use of standard EPA default values in the analysis. These include inhalation and
consumption rates, body weight, and exposure duration and frequency, which are used in most
EPA risk assessments. Using a single-point estimate for these variables rather than exposure
parameter probability distributions ignores a variability that may influence the results by up to a
factor of two or three.
Taking the uncertainties into account, the conclusions of the screening level risk
assessment are that there are no cancer risks. Nor is there a potential for non-cancer health
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effects above regulatory levels of concern even though conservative, theoretical models estimate
exposures equal to or slightly above threshold levels for potential non-cancer effects. The
majority of the potential for theoretical non-cancer health effects associated with antimony and
cadmium results from the steel mill, not the cement manufacturing facilities. Theoretical
exposures of concern for antimony, cadmium, and mercury are in the "borderline" range (equal to
or barely over the threshold). Furthermore, Region 6 believes that using alternative approaches
or information would likely lower the estimated risks and therefore strengthen the conclusion.
Finally, actual measured concentrations of those contaminants that result in exposures above
threshold values appear to be present in media at concentrations less than modeled
concentrations.
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1. CONTEXT
1.1 Scope and Purpose
EPA Region 6 initiated a risk assessment in response to concerns expressed by the
citizens of Midlothian, Texas, over the proposed burning of hazardous waste at a cement kiln
owned by Texas Industries (TXI). TXI had applied to the Texas Natural Resources and
Conservation Commission for a RCRA permit to burn the hazardous wastes. Citizens primarily
were concerned with the cumulative health effects from air emissions from TXI, and the
emissions from two other cement kilns and a steel mill in the vicinity. In the course of the risk
assessment, citizens also requested that Region 6 consider risk to infants from dioxin, via the
breast milk pathway, and from a tire fire that occurred at a tire shredding facility in December
1995.
This risk characterization presents an overview of screening level risk estimates for direct
(i.e., drinking water consumption and inhalation) and indirect (i.e., food consumption) exposures
attributable to emissions from the three cement companies and steel mill. The risk screening
document, Midlothian Cumulative Risk Assessment, was written by risk assessors in Region 6's
Multimedia Planning and Permitting Division. Region 6 developed the estimates following the
procedures outlined in the EPA's draft Guidance for Performing Screening Level Risk Analyses
at Combustion Facilities Burning Hazardous Wastes (1994).
Risk assessors modeled emissions associated with the combustion sources using facility-
specific emission rates, stack characteristics, and representative receptor locations around the
facility. The types of receptors (exposed individuals) that were considered include an adult and
child resident, a subsistence farmer, and a subsistence fisher (see further discussion under Section
2.1).
The risk estimates presented in this risk characterization are limited by the uncertainties
inherent in the models used to estimate risk and in the data used in the models. Region 6
attempted to minimize uncertainties by:
a) evaluating and incorporating site-specific data collected by the Texas Natural
Resource Conservation Commission,
b) requesting actual air emission rates from each of the facilities,
c) estimating emission rates based on tests conducted at similar facilities when
specific rates were not provided, and
d) comparing the data provided for the facilities to data from other sources to
evaluate its overall reasonableness.
The final risk assessment report was submitted to the Texas Natural Resources and
Conservation Commission (TNRCC) to support their development of TXI's hazardous waste
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burning permit. Results of the report also were provided to concerned citizens groups, mayors
and industry representatives.
1.2 Characteristics of Study Area
Midlothian is located approximately 30 miles south of the Dallas-Ft. Worth metropolitan
area. The study area extends 8 miles north, 3 miles south, 3 miles east, and 6 miles west of TXI
(Map 1). Chaparral Steel Corporation (CSC) is 0.7 miles southwest of TXI, and North Texas
Cement Company (NTCC) and Holnam Cement Company are approximately 4 and 5 miles
northeast of TXI, respectively.
The study area is characterized by small hills and valleys with elevations ranging from
approximately 800 feet above mean sea level south of TXI to 500 feet above mean sea level at
Joe Pool Lake to the north. The predominant wind direction is from the south.
With the exception of the City of Midlothian (approximate population of 5,100), which is
located approximately 3 miles northeast of TXI, the land use of the study area is predominately
agricultural with some industrial development. The area is home to several small cattle
operations and rural residential developments. Gardens were observed at many homes in the area
during several site visits.
In addition to Joe Pool Lake (surface area approximately 7,600 acres), the area contains
two privately owned lakes known as Soil Conservation Service (SCS) Lakes 9 and 10 (combined
surface area of approximately 84 acres). SCS Lakes 9 & 10 are approximately 2 to 3 miles
northwest and north, respectively, of the CSC/TXI complex, and very near residential
developments.
1.3 Context with Superfund
In the Superfund program, EPA established a theoretical value of an excess acceptable
lifetime cancer risk that ranges from one in ten thousand to one in one million. This range may
be expressed as 1 x 10"4 to 1 x 10"6. For example, a risk of 1 x 10"6 means that 1 person out of
one million could develop cancer as a result of a lifetime exposure to emissions from the four
facilities studied in this risk assessment. In the Superfund program, EPA must consider the need
to conduct remedial action (cleanup) at a site if the theoretical risk exceeds 1 xlO"6; EPA usually
requires remedial action at locations where the calculated number of excess cancer risks is
greater than 1 x 10"4 (one excess cancer case in a population often thousand people could
potentially occur).
The level of concern for non-carcinogenic contaminants is determined by calculating a
Hazard Quotient (HQ) or Hazard Index (HI). An HI is the sum of the HQs for several chemicals
that affect the same target organ. If theHQ or HI equals or exceeds one, there maybe concern
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for potential exposure to site contaminants. EPA typically considers the need for remedial action
at locations where the HQ or HI values equal or are slightly greater than 1.0 for people who may
reasonably be expected to be exposed. EPA usually requires remedial action at locations where
HQ or HI values significantly exceed one.
2. RISK PARADIGM
2.1 Exposure Assessment
The four types of exposed individuals considered in this screening level risk assessment
are the subsistence farmer, the adult and child resident, and the subsistence fisher as suggested in
the draft Guidance for Performing Screening Level Risk Analyses at Combustion Facilities
Burning Hazardous Wastes (U.S. EPA, 1994). The individuals considered in each of the
exposure scenarios were assumed to be exposed to contaminants from the emission sources via
inhalation of particles and vapors, ingestion of above-ground vegetables, incidental ingestion of
soil, and consumption of drinking water. The exposed individuals differed primarily in their
consumption of certain foods. Specifically, only the subsistence farmer was assumed to consume
contaminated beef and milk, while only the subsistence fisher was assumed to consume
contaminated fish. Because the drinking water supplied to the area surrounding the facilities
comes from Joe Pool Lake, exposure via contaminated drinking water was considered under all
of the scenarios.
Although the difference in the amount of food consumed is the primary difference
between the types of exposed individuals, other differences exist. The ingestion rate of soil and
above-ground vegetables and the inhalation rate of air differ for children and the adults.
Exposure duration is another difference. The adult resident and fisher are assumed to be exposed
to the contaminants for 30 years, the subsistence farmer for 40 years, and the child exposed for 6
years.
The three water bodies considered in the risk analysis were selected based on information
collected during a visit to Midlothian. These water bodies—Joe Pool Lake, SCS Lake 9, and
SCS Lake 10—and their watersheds were those that were large enough to support fish and would
experience the highest impact from the facilities' emissions, due to their location. U.S. Geologic
Survey (USGS) topographic maps were used to delineate the watersheds associated with the
three water bodies and to estimate water body and watershed surface areas.
According to the Texas Department of Health, Joe Pool Lake is the City of Midlothian's
primary drinking water source, so it was used as such in the modeling efforts. The watershed of
SCS Lakes 9 & 10 is a subsection of the Joe Pool Lake watershed that includes Cottonwood
Creek and portions of the Newton Branch of Soap Creek. The assumption that the SCS Lakes
watersheds are sufficient to support subsistence fishing is conservative because it has not been
determined that they are able to support subsistence fishing. Furthermore, both lakes are
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Risk Characterization Handbook Page E-9
privately owned and SCS Lake 10 is on property with posted "No Trespassing" signs.
Nevertheless, Region 6 assumed that these water bodies could support subsistence activity based
on their size and their proximity to residential development.
Contaminants were assumed to be emitted from the four facilities 24 hours per day, 7
days per week, and 365 days per year. EPA's draft air dispersion model KCSTDFT (Industrial
Source Complex Sort-Term) was employed to estimate the transport of airborne contaminants to
the surrounding area. Soil was assumed to become contaminated by wet and dry deposition of
particles and vapors from the air. Above-ground vegetation for human and animal consumption
was assumed to become contaminated via deposition of particles on plants, transfer of vapor
phase contaminants to the vegetation, and uptake of soil and water contaminants through the
roots. Beef and milk were assumed to be contaminated via ingestion by cattle of contaminated
forage, silage, grain, and soil. Fish and the drinking water sources were assumed to be
contaminated by surface runoff and the deposition of particles directly onto the water body.
Map 1 shows the points of maximum air concentration (D, E, and F) and combined
deposition (A, B, and C) generated by the model based on estimated constituent-specific
emission rates. For each compound group, these points were typically located close to the
facility emitting the compound at the highest rate. Map 1 also shows the general locations (A1?
Bj C]) of the site-specific receptors to be evaluated in the study as suggested by the model.
Based on land use maps for the area, subsistence farming was not a reasonable use for location
C1? so risk to subsistence farmers was calculated at an agricultural area to the north represented
by point C3.
Rather than estimate theoretical worst-case risk, Region 6 identified (through site visits)
several potential residences and farms likely to be most impacted by the facilities5. Three site-
specific residents, subsistence fishers, and subsistence farmers were identified for use in the
modeling analysis (Table 1). Three of each type of exposed individual were considered to ensure
that the maximum concentrations of each pollutant were taken into account, because the overall
risks for each pathway can vary according to which contaminant is deposited the fastest or is
present at the highest ambient air location. Resident Al and subsistence farmer Al, resident Bl,
and resident Cl and subsistence farmer C3 are the exposed individuals located closest to the
points of maximum combined deposition A, B, and C, respectively. The exposed individuals
assumed to live at residence Al, Bl, and Cl included the adult and child resident and the
subsistence fisher. The difference between the adult resident and subsistence fisher was that the
fisher was additionally exposed through the consumption of contaminated fish.
It should be noted that these locations do not necessarily reflect actual residences and farms based on
interviews etc., but rather reflect a reasonably conservative analysis of activities as seen from driving in and about
the study area. For example, residential locations typically correspond to locations of houses or similar residential-
type structures. Farms were estimated based on the presence of livestock or barn type structures in the area of
interest.
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Risk Characterization Handbook
2.2 Hazard Identification, Dose-Response, and Risk Estimation
No cancer risk above regulatory levels of concern was identified. As shown in Map 1, the
most significant theoretical cancer risk, 1 x 10~4, would occur for a subsistence fisher at point Bl
who eats fish from SCS Lakes 9 andlO. Arsenic contributes up to 80% of this risk. Other
exposure scenarios that result in theoretical risk near regulatory levels of concern are subsistence
farming and subsistence fishing in Joe Pool Lake. A combination of organic contaminants,
including dioxin, BAP, and DEHP, drive the subsistence farming risk, while arsenic dominates
the subsistence fishing risk at Joe Pool Lake.
The conservative, theoretical modeling results indicate the potential for non-cancer health
effects. The modeled estimates of antimony and cadmium concentrations drive the potential for
non-cancer health effects. Actual soil and water samples collected near residents and fishing
areas, however, indicate that the models over-predict media concentrations of antimony and
cadmium.
Risk assessment results based on theoretical modeling show a potential for non-cancer
effects because some of the calculated HQs are greater than or equal to one. The HQ for
exposure to antimony in drinking water is estimated to be three for adults and six for children at
every receptor location. The HQ for the ingestion of cadmium in fish from SCS Lakes 9 and 10
equals one for the subsistence fisher; and the HQ for the ingestion of mercury in fish from both
the SCS lakes and Joe Pool Lake equals one for the subsistence fisher.
The chronic oral reference dose for antimony (0.0004 mg/kg/day) contains an uncertainty
of factor of 1,000. An uncertainty factor of 1,000 means that the critical amount of antimony
found in laboratory studies to cause potential non-cancer health effects was multiplied by 1,000
to account for uncertainties in the studies before the amount was used in this study to estimate
the potential for non-cancer health effects. Critical health effects from animal studies upon
which the reference dose is based include a decrease in median life span, a decrease in non-
fasting blood glucose levels, altered cholesterol levels, and a decrease in the mean heart weight
of males. Table 1 presents the overall results of the risk assessment process.
Table 1. Overall Cancer Risk (Direct and Indirect) for All Carcinogenic Chemicals
Associated with the Four Facilities
Scenario
Adult Resident
Child Resident
Theoretical
Risks
Point Al
7x 10'6
3x 10'6
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Risk Characterization Handbook
Page E-ll
Scenario
Subsistence Fisher
Subsistence Farmer
Adult Resident
Child Resident
Subsistence Fisher
Subsistence Farmer
Adult Resident
Child Resident
Subsistence Fisher
Subsistence Farmer
Theoretical
Risks
scs
Lakes
9 and 10
9x 10'5
Joe
Pool
Lake
3x 10'5
5x 10'5
Point Bl
3x 10'5
1 x 10'5
SCS
Lakes
9 and 10
1 x 10'4
Joe
Pool
Lake
5 x 10'5
4 x 10"5
Point Cl
4 x 10"5
2x 10'5
SCS
Lakes
9 and 10
1 x 10'4
Joe
Pool
Lake
6x 10'5
6x 10'5 (Point C3)
The chronic reference doses for cadmium (0.001 mg/kg/day for food and 0.0005
mg/kg/day for water) contain an uncertainty factor of 10. Critical human health effects attributed
to cadmium include anemia and pulmonary disease, edema, pneumonitis, possible effects on the
endocrine system, defects in sensory function, and bone damage.
Region 6 also considered risk to infants from dioxin via the breast milk pathway from a
tire fire that occurred at a Midlothian tire shredding facility in December 1995. To address the
risk via the breastmilk pathway, Region 6 used the draft screening guidance methodology to
estimate an infant's daily intake of dioxin if the mother were a resident, subsistence farmer, or
subsistence fisher. These estimated intakes were then compared to an infant's background
exposure to dioxin through ingestion of breast milk. Based on the modeled values, an infant's
estimated daily intake of dioxin is 0.01 pg/kg/day if the mother is a resident, 0.45 pg/kg/day if the
mother is a subsistence farmer, and 0.38 pg/kg/day if the mother is a subsistence fisher. All of
these intakes are less than 1% of the average daily dose (50 pg/kg/day) an infant would obtain
from background levels of dioxin in breast milk.
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Page E-12 Risk Characterization Handbook
Region 6 considered including the risk effects of the December tire fire in this
assessment, but was unable to complete the evaluation because of a lack of actual emission rates
of contaminants during the tire fire. Furthermore, there is uncertainty associated with using a
methodology based on long-term chronic exposures to estimate the effects from a short-term
event like a tire fire.
Finally, Region 6 conducted a qualitative analysis of the combined effects of windblown
cement kiln dust (CKD) and contaminant emissions. This analysis was conducted by comparing
"best estimates" of high-end baseline risks, listed in EPA's Report to Congress on Cement Kiln
Dust (U.S. EPA, 1993), to the maximum theoretical risk estimates discussed above. For
example, the most significant cancer risk identified in this risk characterization is 1 x 10~4 to a
subsistence fisher. Pathways contributing to this level of risk include ingestion offish, ingestion
of drinking water, incidental ingestion of soil, ingestion of vegetables, and inhalation. According
to the Report to Congress on Cement Kiln Dust, the "best estimate" of high-end baseline risk
from the ingestion offish contaminated with CKD is 4 x 10~6. Risk from ingestion of surface
water contaminated by CKD emissions are estimated at 1 x 10~8, and risk from the ingestion of
soil contaminated by CKD is estimated at 1 x 10~7. Risk from ingestion of vegetables is
estimated at 2 xlO"6, and risk from inhalation is estimated at 2 x 10~12. All of these risks added
together do not substantially affect the most risk estimate of 1 x 10~4. Thus, the uncertainty
associated with the failure to quantitatively assess risk from the emissions of cement kiln dust
does not appear to be significant
A quantitative analysis of the combined effects of windblown CKD and contaminant
emissions could not be performed because the exposure assumptions and fate and transport
methodologies used in the two studies contain some differences. However, the comparison does
provide a general feel for the overall contribution of CKD emissions to the theoretical risk
estimated for the area.
2.3 Limitations and Uncertainties
This section discusses the limitations and uncertainties associated with this screening
level cumulative risk assessment. The degree to which the uncertainty needs to be quantified and
the amount of uncertainty that is acceptable varies with the intent of the analysis. For a screening
level analysis such as this, a high degree of uncertainty is often acceptable, provided that
conservative assumptions are used to bias potential error toward protecting human health.
Uncertainty can be introduced into a health risk assessment at every step in the process.
Risk assessment is a complex process, requiring the integration of:
a) The release of pollutants into the environment
b) The fate and transport of pollutants in a variety of environments by processes that
are often poorly understood or too complex to quantify accurately
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Risk Characterization Handbook Page E-13
c) The potential for adverse health effects in humans as extrapolated from animal
bio ass ays
d) The probability of adverse effects in a human population that is highly variable
genetically, in age, in activity level, and in life style
While a more sophisticated risk assessment may substantially reduce the uncertainty in
both the assumptions and models utilized in this screening assessment, it is not possible to
eliminate all uncertainty.
Uncertainty of data used to estimate risk or potential health effects for emission rate data,
exposure parameters, air modeling, and exposure scenarios are described in the following
sections. The term "significant" uncertainty is defined here as an uncertainty that results in a
potential error in risk estimates which could raise or lower values above or below regulatory
levels of concern.
2.3.1 Emission Rates
The lack of good quality chemical-specific emission rates presented one of the largest
sources of uncertainty associated with this screening level assessment. For the cement
manufacturing companies, the majority of the emission rates were based on trial burn data from
NTCC. Because there were only limited data and limited information on the quality of the data
obtained during the trial burns (e.g., percent recovered) and on the representativeness of the
operating conditions during the trial burns, the representativeness of the emission rates could not
be fully evaluated. To address this source of uncertainty, the emission rates used in the analysis
were compared to available data sources (i.e., trial burn data, TNRCC data, and company-
reported data) to ensure that the selected emission rates were reasonable yet conservative enough
to allow for operational upsets and the uncertainty associated with the quality of the data. Region
6 is confident that the rates presented are as reasonable as can be provided given the availability
of accurate data. In fact, one of the outside reviewers noted that emission rates for dioxin were
consistent with EPA's experience in preparing the draft report Estimating Exposure to Dioxin-
Like Compounds (1994a).
Another significant source of uncertainty in the overall process is the compound-specific
allocation of emissions for CSC based on the assumption that baghouse and fugitive emissions
contained concentrations of contaminants similar to those found in steel mill baghouse dust. It is
unlikely that fugitive baghouse emissions to the atmosphere would contain contaminant
concentrations greater than those found in the baghouse dust. However, it is possible that the
fugitive emissions contain higher concentrations than those found in the baghouse dust since they
are emissions that have not yet been treated. The volume of fugitive emissions could be more or
less than assumed in this study because CSC's actual fugitive emissions have not been measured.
As a result, the uncertainty in the emission estimates for CSC are significant.
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Page E-14 Risk Characterization Handbook
One area of uncertainty that has been addressed since the review of the draft report by
outside experts is the uncertainty associated with assumed baghouse dust emissions profile. The
emissions allocation profile used to estimate emissions sets forth concentrations of contaminants
that are very similar to CSC's baghouse dust data, with the exception of antimony and hexavalent
chromium concentrations, which were not included in the profile. The actual amounts of
antimony and hexavalent chromium emitted by CSC are unknown. The lack of any method to
assess that accuracy of the antimony and hexavalent chromium emissions estimates is significant
because both of these contaminants contribute to the overall cancer risks and non-cancer effects
estimates. Antimony emissions were based solely on the baghouse dust profile contained in the
Detailed Summary of Information Collection Request Responses For Electric Arc Furnaces
(ICR). The ICR is based upon data from both stainless and non-stainless steel mill facilities;
however, CSC reportedly operates a non-stainless steel mill. Hexavalent chromium emissions
were estimated by assuming that the hexavalent chromium emissions constituted only two
percent of total chromium emissions. This assumption is based on a table included in the
Agency for Toxic Substances and Disease Registry's Toxicological Profile for Chromium.
2.3.2 Exposure Parameter Uncertainty
Another source of uncertainty involves the use of standard EPA default values in the
analysis. These include inhalation and consumption rates, body weight, and exposure duration
and frequency, which are used in most EPA risk assessments. These values often assume that the
exposed population is homogenous, when in fact variations exist among the population. Using a
single point estimate for these variables rather than exposure parameter probability distributions
ignores a variability that may influence the results by up to a factor of two or three.
Other data subject to uncertainty are estimates of the chemical concentration in the media
and locations of interest. For example, because no site-specific data of sufficient quality were
available, the Worth National Weather Station provided an approximation of the meteorological
conditions at the site. Different meteorologic conditions can influence the risk results by up to an
order of magnitude given the same facility characteristics and surrounding land uses.
Another area of uncertainty is the use of EPA-verified cancer slope factors, reference
doses, and reference concentrations. Single point estimates of these health benchmarks are used
throughout the analysis. These benchmarks have both uncertainty and variability associated with
them. However, the EPA has developed a process for setting verified health benchmark values to
be used in all EPA risk assessments. These benchmarks are derived to be conservative and
project upper bound risk estimates. With the exception of the dioxin and BaP toxicity
equivalency methodology, all health benchmarks used in this analysis are verified through the
EPA's work groups and are available on the EPA's Integrated Risk Information System (IRK).
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Risk Characterization Handbook Page E-15
2.3.3 Limitations of ISCSTDFT Air Modeling
ISCSTDFT, the indirect exposure air model used in this analysis, is EPA's current
method of addressing a variety of exposure pathways important for chemicals that bioaccumulate
and persist in the environment. ISCSTDFT was released as a draft and has not been widely
applied in the present form. Implementation of ISCSTDFT requires air dispersion modeling
results for wet and dry depositions and air concentrations of particles and vapors in a variety of
settings. ISCSTDFT is the only EPA-recommended air dispersion and deposition model
currently available to provide such estimates from combustion sources located in both complex
and non-complex terrains (U.S. EPA, 1994d).
2.3.4 Uncertainty Associated with Exposure Scenarios
The exposure scenarios included in this screening level assessment include an adult and
child resident, a subsistence fisher and a subsistence farmer. Although a distribution of the
characteristics (e.g., consumption rates) of each type of receptor are reasonably well
characterized, population distributions for the modeled behaviors and activities have not been
adequately studied. For example, little is known about the fraction of the general population that
consists of subsistence farmers and fishers. Without population distributions for these receptors,
the number of people likely to be exposed to contaminated media cannot be determined;
therefore, the appropriateness of the receptors cannot be evaluated from the standpoint of
population risk.
3. CONCLUSIONS
The conclusions of this conservative screening level risk assessment are:
1. Available site data show that there are no cancer risks; nor is there a potential for
non-cancer health effects above regulatory levels of concern even though
conservative, theoretical models estimate exposures equal to or slightly above
threshold levels for potential non-cancer effects.
2. CSC is the primary source of the theoretical exposures above threshold levels, not
the cement companies.
Region 6 arrived at the first conclusion for two reasons. First, they believe that the
models and exposure scenarios upon which the estimates of risks and potential non-cancer health
effects are thought to occur are conservative. The experts who reviewed the risk characterization
report concurred that the risk assessment is conservative. Because the risk assessment is
conservative, actual risks and exposures are likely to be less than the estimated risk and
exposures. Given this conservatism and the fact that the theoretical exposures of concern for
antimony, cadmium, and mercury are in the "borderline" range (equal to or barely over the
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Risk Characterization Handbook
threshold), Region 6 cannot currently justify the need for immediate regulatory action.
Furthermore, Region 6 believes that using alternative approaches or information would likely
lower the estimated risks and therefore strengthen the conclusion.
Second, actual measured concentrations of the contaminants that result in exposures
above threshold values appear to be present in media at concentrations less than modeled
concentrations. Assessment of measured concentrations of antimony (the contaminant with the
greatest exposure) in the Midlothian drinking water supply system results in a HQ of 0.05 rather
than the HQ of 3 based on modeling concentrations. Also, actual measured concentrations in soil
of antimony and cadmium for which exposures exceed threshold levels are less than modeled
concentrations in the area north of CSC (close to receptor points Cl and C3). The measured and
modeled concentrations are compared in Table 2 along with background concentrations. The fact
that the measured concentrations are approximately 60 times less than the modeled
concentrations is particularly interesting given that CSC has been operating since 1975 (20 years
to date), TXIhas been burning waste-derived fuel since 1987 (9 years to date), and the risk
assessment considers emissions for 30 years. Due to the linear relationship of deposition over
time, this implies that risk estimates maybe conservative by an order of magnitude for some
contaminants.
Region 6 currently can find no basis for federal regulatory action in response to a mercury
HQ of 1. There is no basis for action because of the conservatism and uncertainty associated
with the risk assessment method, and because the measured media concentrations of mercury are
within the range of U.S. background concentrations of mercury. Region 6 is currently unable to
judge the viability of estimated mercury exposures as with HQs greater than or equal to 1 due to
uncertainties in the method. In addition, TNRCC has stated in its Critical Evaluation of the
Potential Impact of Emissions from Midlothian Industries: A Summary Report (1995) that
concentrations of mercury in the Midlothian area are equal to or lower than local and U.S.
background levels.
Table 2. Comparison of Modeled and Measured Concentrations
Contaminant
Antimony
Cadmium
Mercury
Modeled Soil
Concentration
(mg/kg)
6.3
11-50
0.38
Measured6
(mg/kg)
<3
< 0.095 -3. 6
<1.0
Local Background
(mg/kg)
<1 -8.8
0.01 -7
<0.01 - 4.6
Measured values obtained from TNRCC's recent Critical Evaluation of the Potential Impact of Emissions
from Midlothian Industries: A Summ ary Report, and CSC's Analytical Results - Off-Site Investigation, Chaparral
Steel, Midlothian, Texas.
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Risk Characterization Handbook
Page E-17
Some citizens and organizations may still be concerned with emissions from the four
facilities despite the fact that the models and exposure scenarios used in this analysis are
conservative and Region 6 determined that actual cancer risks and non-cancer health effects are
below regulatory levels of concern. It may be of interest to local and state governments to
identify the predominant source(s) of theoretical risks from the four industries. The predominant
sources of risk from the four industries can be evaluated by comparing the emission rates and the
unit combined deposition and air concentrations associated with each facility. The unit
combined deposition rate and air concentrations associated with each emission source are
compared in Table 3 for point C3. Emission rates are compared in Table 4.
Table 3. Comparison of Unit Deposition Rates and Air Concentrations at Point 3
Facility
CSC Fugitives
CSC Baghouse A
CSC Baghouse B
CSC Baghouse C
NTCC
TXI
Holnam
Unit Combined
Deposition
(g/m2-yr) per 1 g/sec
30.8
0.320
0.080
0.078
0.005
0.012
0.001
Unit Air
Concentration
((ig/m3) per 1 g/sec
18
0.37
0.06
0.063
0.006
0.013
0.001
As noted in Table 3, the deposition rate of contaminants from CSC are at least an order of
magnitude greater than the contaminant deposition rate associated with the cement kilns. CSC's
fugitive emissions overwhelm all other deposition rates by two to three orders of magnitude
while Holnam's and NTCC's deposition rates at point C3 are almost negligible. TXI's deposition
rate at this location is greater than Holnam's and NTCC's, yet still significantly less than CSC's
deposition rates.
Table 4. Comparison of Emission Rates
Constituents
Antimony
Arsenic
Chaparral
Estimated
Representative
(g/sec)
2.97 x 102
1.89 xlO4
NTCC
Estimated
Representative
(g/sec)
9.09 x 10 5
1.07 xlO5
TXI
Estimated
Representative
(g/sec)
1.60 xlO4
2.13 xlO4
Holnam
Estimated
Representative
(g/sec)
NA
9.00 xlO5
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Page E-18
Risk Characterization Handbook
Baristttuents
Beryllium
Cadmium
Chromium VI
Lead
Mercury
Nickel
Silver
Thallium
Zinc
Chaparral
NA
NA
3.02 x 10 3
3.78 x 10 4
5.85 xlO2
1.06 xlO5
7.68 x 10 3
NA
NA
5.96 x 101
NTCC
2.65 x 10s
1.77 xlO6
5.18 x 104
2.65 xlO5
4.17 x 10 3
4.67 x 104
2.78 x 10 5
8.96 x 10 5
1.26 xlO5
5.43 x 10 6
TXI
4.03 x 10-3
2.08 xlO4
6.50 xlO4
9.80 x 10-9
1.43 xlO-2
3.01 xlO4
3.01 xlO4
5.33 xlO5
5.04 x 10 4
2.69 x 103
Holnam
8.82 x 10 4
2.00 x 10 5
NA
1.11 xlO5
(total)
8.00 x 10 5
2.52 x 10 4
3.78 x 10 4
NA
2.00 xlO5
8.82 xlO4
Likewise, the unit air concentrations associated with emissions from CSC are at least 100
times greater than those associated with NTCC and Holnam. The level of CSC's baghouse
emissions on contaminant air concentrations at this location is six times the level of TXI, the next
most significant source. The level of CSC's fugitive emissions is 1,000 times the level TXFs
emissions.
A comparison of the emission rates between the four facilities in Table 4 again shows that
CSC's emissions of antimony and cadmium dominate that of the other facilities. CSC's
estimated emissions of antimony are 186 times that of TXI and CSC's emissions of cadmium are
almost five times that of TXI.
Thus, it is clear that the majority of the potential for theoretical noncancer health effects
associated with antimony and cadmium result from CSC, not the cement manufacturing facilities.
4.
RECOMMENDATIONS REGARDING DATA GAPS
The data obtained for this screening level risk assessment were sufficient to meet the
objective of the study which was to assess the protectiveness to human health of permit operating
conditions. The study concluded that there are no cancer risks or non-cancer health effects above
regulatory levels of concern associated with permitted burning of hazardous waste at TXI. Thus,
there are no recommendations regarding data gaps to present
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Risk Characterization Handbook Page E-19
5. LITERATURE CITATIONS
General Information
4 USGS quadrangle maps (Cedar Hill, Britton, Venus, Midlothian).
Camp, Dresser, and McKee. 1989. Watershed Management Study: LakeMichie and Little River
Reservoir Watersheds. Prepared for the County of Durham, NC.
Document entitled Location of Known Commercial Animal Operations in the Midlothian Area.
Draft table entitled Emissions Estimates. This table was prepared by the TNRCC and describes
the rationale behind their selection of emission rates that are different from the rates
recommended by TNRCC permit engineers in memorandums dated March 20 and April
12, 1995 (see list of items for NTCC and TXI below).
Dravo Corporation. 1976. Managing and Disposing of Residues from Environmental Control
Facilities in the Steel Industry. Prepared for the U.S. EPA Office of Research and
Development. Contract Number R-803619.
Geological Survey Planimetric Map, Cleburne, Texas
Geological Survey Planimetric Map, Corsicana, Texas
Geological Survey Planimetric Map, Dallas, Texas
Geological Survey Planimetric Map, Ft. Worth, Texas
Geraghty, J.J, D.W. Miller, F. Van Der Leeden, and F.L. Troise. 1973. Water Atlas of the United
States. Water Information Center, Inc., NY.
Kites, R.A., and S.L. Simonich. 1994. Vegetation - Atmosphere Partitioning of Polycyclic
Aromatic Hydrocarbons. Env. Sci. Tech. Vol. 28 No.5.
Jindal, M. and D. Reinhold. 1991. Development of Particulate Scavenging Coefficients to Model
Wet Deposition from Industrial Combustion Sources. Paper 91-59.7. Annual Meeting -
Exhibition of Air and Waste Management Association, Vancouver, BC. June 16-21,
1991.
Memorandum, from U.S. EPA\ORD, to Addressees. January 20, 1995.
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Page E-20 Risk Characterization Handbook
PEI Associates, Inc. 1986. Air Quality Modeling Analysis of Municipal Waste Combustors.
Prepared for the U.S. Environmental Protection Agency, Monitoring and Data Analysis
Division, Research Triangle Park, NC.
Real Estate List (computer printout) for the Midlothian ISO, dated April 25, 1995. This report
was developed by the Ellis County Appraisal District and specifies property owners in the
area that have proven that their property is used for agricultural or ranching purposes.
Code "Dl" is a ranch and code "D3" is a farm.
Research Triangle Institute. 1993. Detailed Summary of Information Collection Request
Responses for Electric Arc Furnace (EAF) NESHAP. Prepared for U.S. EPA Office of
Air Quality Planning and Standards.
Texas Department of Health, Division of Milk and Dairy Products, Establishment Report dated
April 24, 1995.
TNRCC draft report section entitled Selection of Receptors for TXI dated April 4, 1995.
TNRCC, 1995. Critical Evaluation of the Potential Impact of Emissions from Midlothian
Industries: A Summary Report. Office of Air Quality/Toxicology and Risk Assessment
Section. Austin, TX.
U.S. EPA, 1989. Risk Assessment Guidance for Superfund. Office of Emergency and Remedial
Response. Washington, DC. EPA/540/1-89/002.
U.S. EPA. 1990. Exposure Factors Handbook. Office of Health and Environmental Assessment,
Exposure Assessment Group. Washington, D.C. March.
U.S. EPA. 1990a. Methodology for Assessing Health Risks Associated with Indirect Exposure to
Combustion Emissions. Interim Final. Office of health and Environmental
Assessment/Office of Research and Development. EPA/600/6-90/003.
U.S. EPA. 1993. "Report to Congress on Cement Kiln Dust." OSWER. EPA/530-R-94-001.
December.
U.S. EPA, 1994. Guidance for Performing Screening Level Risk Analysis at Combustion
Facilities Burning Hazardous Waste. Office of Emergency and Remedial Response/Office
of Solid Waste, Washington, DC.
U.S. EPA. 1994a. Estimating Exposure to Dioxin-like Compounds. Review Draft. Office of
Research and Development. Washington D.C. June. EPA/600/6-88/0055C.
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Risk Characterization Handbook Page E-21
U.S. EPA. 1994b. Mercury Study Report to Congress, Office of Air Quality Planning and
Standards and Office of Research and Development, Research Triangle Park, NC and
Washington, DC.
U.S. EPA. 1994d. User's Guide for the Industrial Source Complex Dispersion Models. Office of
Air Quality Planning and Standards, RTP, NC. Draft.
U.S. Department of Commerce. 1992. International Station Meteorological Climate Summary
CD ROM.
Van der Leeden, F., F.L. Troise, and O.K. Todd. 1990. The Water Encyclopedia. Lewis
Publishers, Chelsea, MI.
Chaparral Steel
Dispersion Modeling of Emissions from Large Section Mill Reheat Furnace (prepared by Forsite
Corporation for Chaparral Steel) dated November 1989.
Letter and enclosures from Chaparral Steel Company to Region 6 dated May 8, 1995, responding
to the Region's request for information about the emission of contaminants from
Chaparral's facility.
Unsolicited letter and enclosures from Chaparral Steel Company to Region 6 dated December 20,
1995. Enclosure entitled Ambient Monitoring Program contains concentrations of
contaminants in Chaparral's baghouse dust.
Unsolicited letter and enclosures from Chaparral Steel Company to Region 6 dated January 16,
1996. Enclosure entitled Analytical Results - Off-Site Investigation contains results of the
analysis of soil samples collected from the area immediately north of Chaparral Steel
Company.
New/Modified Source Technical Review (prepared by TNRCC) dated May 22, 1992.
TACB Mini Emissions Inventory Report (for Chaparral) from the Point Source Database dated
May 2, 1995.
Texas Natural Resource Conservation Commission (TNRCC) Air Permit dated February 22,
1994.
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Page E-22 Risk Characterization Handbook
Holnam Texas, L.P.
A letter from Holnam to TNRCC regarding the previous letter regarding dioxin emissions
submitted by its consultant Trinity. The letter corrects the emission rates identified in the
Trinity letter to account for sample dilution.
Letter from Holnam Texas, L.P. to Region 6 dated May 19, 1995, in response to Region 6's
request for information regarding emission rates.
Letter summarizing dioxin data from Trinity Consultants to TNRCC dated November 12, 1993.
Selected portions of Holnam's (known as BoxCrow Cement Co. at the time) application to amend
their air permit dated November 1992 prepared by Trinity Consultants.
TACB Mini Emissions Inventory Report (for Holnam) from the Point Source Database dated
May 2, 1995.
TNRCC Air Permit for Holnam - Maximum Allowable Emission Rates. Permit number 8996 and
PSD-TX-454M1. September 26, 1994.
TNRCC Air Permit for Holnam - Special Provisions. Permit number 8996 and PSD-TX-454M2.
April 26, 1994.
North Texas Cement Company (NTCC)
Appendix III. A., RCRA Part B Permit Application entitled General Engineering Report for
North Texas Cement Company.
Copies of Tables 21-24 summarizing results of dioxin testing conducted November 7-9, 1991.
Draft Table 2.2 dated May 2, 1995, entitled NTCC Emission Estimates Used in the Final Risk
Assessment. (This will eventually be used in TNRCC's risk assessment report. However,
be advised that Industry states that table contains an error with regard to emissions rates
for As, Be, Hg and Cr. TNRCC developed the emission rates based on permits limits in
Ib/hr but incorrectly adjusted data to gram/sec).
Excerpt from a BIF test report entitled Semivolatile/PAHData, June 1992 BIF Test. Excerpt
includes test data from Test 2, Runs 1-3. Analyses were conducted July 19, 1992.
Excerpt from the NTCC Trial Burn Report that provides information about contaminant
concentrations in NTCC's CKD.
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Risk Characterization Handbook Page E-23
Pages II-1 through 11-12 of a risk assessment protocol prepared byNTCC. This information was
provided to EPA during a meeting on May 8, 1995 with Bill Wilson of NTCC. The
emission rates identified in Table II-1 are the rates NTCC believes should be used to
support the risk assessment.
TACB Mini Emissions Inventory Report (for NTCC) from the Point Source Database dated May
2, 1995.
TNRCC memorandum dated March 20, 1995 from Michael Koenig to Lucy Fraiser regarding
emission estimates for TNRCC's NTCC risk assessment.
TNRCC's, 1995. North Texas Cement Company (NTCC) Modeling Approach to Risk Assessment
Screening Analysis, April 21, 1995.
Texas Industries, Inc. (TXI)
Copy of draft Table 2.2 dated May 2, 1995, entitled TXI Emission Estimates Used in the Final
Risk Assessment. (This table will eventually be used in TNRCC's risk assessment report.)
Copy of TNRCC's draft Texas Industries, Inc. (TXI) Modeling Approach to Risk Assessment
Screening Analysis dated April 24, 1995.
Copy of TXI's draft Pro tocolfor a Comprehensive Risk Assessment for the Texas Industries
Facility, Midlothian, Texas dated July 15, 1994.
Copy of draft memorandum from Paul DeCiutiis to Lucy Fraiser, dated April 12, 1995, regarding
emission estimates for TNRCC's TXI risk assessment.
Copy of selected portions of Part B Permit Application (Section 5.0 [contains modeling and stack
parameter/test data information]).
Copy of selected portions of Trial Burn Report (Volume 1, Chapter 1).
Copy of Adjacent Landowners Map identified as Figure I.G. 1. The source of this information is
unknown.
Excerpt from the TXI Trial Burn Report that provides information about contaminant concen-
trations in TXI's CKD.
Section 1 of Part B Permit Application. Contains facility background and land use information.
TNRCC Air Permit for TXI - Special Conditions. Permit Number 1360A. February 28, 1995.
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Page E-24 Risk Characterization Handbook
TNRCC air Permit forTXI - Emission Sources - Maximum Allowable Emission Rates. Permit
Number 1360A. June 6, 1994.
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MAPI:
Points of Maximum Combined Deposition and
Air Concentration
Points of Maximum
Combined Deposition
4 -AND 2, 6-DINITROTOLUENE
^-xHEXACHLOROBENZENE, PCNB,
PENTAC HLOROPHENOL,
THALIUM, AND BERYLLIUM
B FOR ALIXJTHER ORGANIC COMPOUNDS
C FOR ALL OTHEkxMETALS
Points of Maximum Air
Concentration
D TCDD2,4-AND2,6-DINITROTOLUENE
HEXACHLOROBENZENE, PCNB,
PENTACHLOROPHENOL,
THALIUM, AND BERYLLIUM
FOR ALL OTHER ORGANIC COMPOUNDS
F FOR ALL OTHER METALS
APPROXIMATE PROPERTY
BOUNDARIES
HYDROGRAPHY
LOCAL ROADS
HIGHWAYS
RAILROADS
FACILITY EMISSION POINTS
The point locations are approximate
Source: RTI
Region 6
CIS Support Group
ACS 12-06-99
19991206SR01
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Risk Characterization Handbook Page F-l
APPENDIX F
References Concerning Risk Characterization
American Industrial Health Council (AIHC) (1992) Improving Risk Characterization, American
Industrial Health Council, Washington, DC, 25 pages.
American Industrial Health Council (AIHC) (1995) Advances in Risk Characterization,
American Industrial Health Council, Washington, DC, 11 pages.
Browner, C. (1995) Risk Characterization Memorandum issued March 21, 1995 (Note: Found in
Appendix A of this Handbook).
Commission on Risk Assessment and Risk Management (CRARM) (1997) Framework for
Environmental Health Risk Management, Final Report Volume 1, Washington, DC.
Commission on Risk Assessment and Risk Management (CRARM) (1997) Risk Assessment and
Risk Management in Regulatory Decision-Making, Final Report Volume 2, Washington,
DC.
Habicht, F.H. (1992) Guidance on Risk Characterization for Risk Managers and Risk Assessment
Memorandum, Washington, DC.
National Research Council (NRC) (1983) Risk Assessment in the Federal Government:
Managing the Process, Washington, DC: National Academy Press, March 1983.
National Research Council (NRC) (1994) Science and Judgment in Risk Assessment,
Washington, DC: National Academy Press.
National Research Council (NRC) (1996) Understanding Risk: Informing Decisions in a
Democratic Society, eds. Paul C. Stern and Harvey V Fineberg, Washington, DC:
National Academy Press.
U.S. Environmental Protection Agency (USEPA) (1984) Risk Assessment and Management:
Framework for Decision Making, EPA 600/9-85-002, Washington, DC: U.S.
Environmental Protection Agency, December 1984.
U.S. Environmental Protection Agency (USEPA) (1997), Guidance on Cumulative Risk
Assessment. Part 1. Planning and Scoping, Science Policy Council, Washington, DC,
July 1997.
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Page F-2 Risk Characterization Handbook
U.S. Environmental Protection Agency (USEPA) (1998) Risk Assessment Guidance for
Superfund: Volume I — Human Health Evaluation Manual (RAGS/HHEM), Washington,
DC: U.S. Environmental Protection Agency, January 1998.
U.S. Environmental Protection Agency (USEPA) (1998)EPA 's Rule Writer's Guide to Executive
Order 13045: Guidance for Considering Risks to Children During the Establishment of
Public Health-Related Standard, Interim Final Guidance, Washington, DC.
U.S. Environmental Protection Agency (USEPA) (2000) Science Policy Council Handbook:
Peer Review, 2nd Edition, EPA 100-BOO-001, Washington, DC: U.S. Environmental
Protection Agency, December 2000.
References of EPA Risk Assessment Guidelines
Guidelines for Carcinogen Risk Assessment. Federal Register 51: 33992-34003, 24 September
1986; also EPA Publication No. EPA/600/8-87/045, August 1987.
Proposed Guidelines for Carcinogen Risk Assessment; Notice. Federal Register 61:
17960-18011,23 April 1996.
Guidelines for Mutagenicity Risk Assessment. Federal Register 51: 34006-34012, 24 September
1986; also EPA Publication No. EPA/600/8-87/045, August 1987.
Guidelines for the Health Risk Assessment of Chemical Mixtures. Federal Register 51:
34014-34025, 24 September 1986; also EPA Publication No. EPA/600/8-87/045, August
1987.
Guidelines for Developmental Toxicity Risk Assessment. Federal Register 56: 63798-63826, 5
December 1991.
Guidelines for Exposure Assessment. Federal Register 57: 22888-22938, 29 May 1992.
Guidelines for Reproductive Toxicity Risk Assessment; Notice. Federal Register 61:
56274-56322, 31 October 1996.
Assessment of Thyroid Follicular Cell Tumors. EPA Publication No. EPA/630/R-97/002, March
1998.
Guidelines for Ecological Risk Assessment. Federal Register 63: 26846-26924, 14 May 1998;
also EPA Publication No. EPA/630/R-95/002F, April 1998.
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Risk Characterization Handbook Page F-3
Guidelines for Neurotoxicity Risk Assessment; Notice. Federal Register 60: 26926-26954, 14
May 1998.
Guiding Principles for Monte Carlo Analysis (contains: Policy for Use of Probabilistic Analysis
in Risk Assessment at the U.S. Environmental Protection Agency). EPA Publication No.
EPA/630/R-97/001, March 1997.
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Risk Characterization Handbook
NOTES AND COMMENTS
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