United States Office of Science Policy


Environmental Protection Office of Research and Development December 2000


Agency Washington, DC 20460 www.epa.gov


EPA 100-B-00-002 

Science Policy Council


HANDBOOK

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

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. 
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

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

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

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-1


POLICY FOR RISK CHARACTERIZATION .......................... Page A-1


APPENDIX B ......................................................... Page B-1


WAQUOIT BAY CASE STUDY .................................... Page B-1


APPENDIX C ......................................................... Page C-1


GENERIC KETONE CASE STUDY ................................. Page C-1


APPENDIX D ......................................................... Page D-1


MITEC CASE STUDY ............................................ Page D-1


APPENDIX E ......................................................... Page E-1


MIDLOTHIAN CASE STUDY ...................................... Page E-1


APPENDIX F .......................................................... Page F-1


References Concerning Risk Characterization .......................... Page F-1


References of EPA Risk Assessment Guidelines ........................ Page F-2

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 

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 

"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 

(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. 
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

Risk Characterization Handbook Page ix 

Science Policy Council 

W. Michael McCabe, OA, Chair Norine Noonan, ORD, Vice-Chair


Donald Barnes, OA Robert Brenner, OAR


Tudor Davies, OW Steven Galson, OPPTS


Sylvia Lowrance, OECA Albert McGartland, OPEI


William Muszynski, Region 2 Michael Ryan, OCFO


Michael Shapiro, OSWER Elaine Stanley, OEI


Ramona Trovato, OCHP


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 
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 
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 Effective characterization depends on 

depends on transparency, clarity, consistency Transparency, Clarity, Consistency and 

and reasonableness (TCCR). TCCR is the Reasonableness (TCCR) 

key to a successful risk characterization. 

This Handbook is divided into two parts: 

1. Risk Characterization Guide 

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. 
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 

CHAPTER 3 CHAPTER 4 

P

R

O

D

U

C

TS 

� ..... ��

• Risk Characterization 

including 

Integrated 

Analysis 

� .... ��

• Summaries 

�

• Communication 

Pieces 

A

U

DIE

N

CE 

• Peer 

Reviewers 

• Risk 

Assessors 

• Risk 

Managers 

• Public 

P

E

ER 

R

E

VIEW 

• These parts 

can be 

candidates 

for peer 

review 

• Pieces can be 

candidates for 

peer review 

• Usually a 

major work 

product for 

peer review 

activities. 

CHAPTER 2 

��

• Planning and 

Scoping 

• Conceptual 

Model 

• Analysis 

Plan 

• Risk 

Managers 

• Risk 

Assessors 

RISK 

ASSESSMENT 

GUIDELINES * 

� ....... ��

• Hazard 

Identification 

• Dose Response 

Assessment 

• Exposure 

Assessment 

• Risk Assessors 

� dialog 

• Risk Managers 

* 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. 
Risk Characterization Handbook Page 3 

U.S. Environmental Protection Agency 

RISK CHARACTERIZATION GUIDE 

Risk Characterization Handbook Page 5 

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.” 
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 
Risk Characterization Handbook Page 7 

assessment process are needed to ensure that risk assessors understand the needs of decisionmakers 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. 
Page 8 Risk Characterization Handbook 

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. 
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)). 
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 useful for 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 
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 Risk characterization is not only about makes clear that science doesn’t tell us science -- it is also about making clear that certain things and that science policy science doesn’t tell us certain things and choices must be made. It explains why the that policy choices must be made. 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	
Page 12 Risk Characterization Handbook 

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. 
Risk Characterization Handbook Page 13 

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 or regulation 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. 
Page 14 Risk Characterization Handbook 

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). 

The risk characterization is an 

intrinsic part of the risk assessment. Peer review is critical to ensure the scientific 

Generally, the entire risk assessment, soundness of a 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!). 
Risk Characterization Handbook Page 15 

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 public 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 wellcharacterized. 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 
Page 16 Risk Characterization Handbook 

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 
Risk Characterization Handbook Page 17 

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 
Page 18 Risk Characterization Handbook 

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-ofthe 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 
Risk Characterization Handbook 

1.4 Overview Presentation of TCCR Principles 

Page 19 

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 � Describe assessment approach, 

assessment process. assumptions, extrapolations and use of 

models 

� Describe plausible alternative 

assumptions 

� Identify data gaps 

� Distinguish science from policy 

� Describe uncertainty 

� Describe relative strength of assessment 

Clarity The assessment itself 

is free from obscure 

language and is easy to 

understand. 

� Employ brevity 

� Use plain English 

� Avoid technical terms 

� Use simple tables, graphics, and equations 

Consistency The conclusions of the 

risk assessment are 

characterized in 

harmony with other 

EPA actions. 

� Follow statutes 

� Follow Agency guidance 

� Use Agency information systems 

� Place assessment in context with similar 

risks 

� Define level of effort 

� Use review by peers 

Reasonableness The risk assessment is 

based on sound 

judgment. 

� Use review by peers 

� Use best available scientific information 

� Use good judgment 

� Use plausible alternatives 
Page 20 Risk Characterization Handbook 

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 
Risk Characterization Handbook Page 21 

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 a RfC 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 
Page 22 Risk Characterization Handbook 

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 

l)
 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 
Risk Characterization Handbook Page 23 

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 
Page 24 Risk Characterization Handbook 

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 Risk characterization communicates the 

identification, dose-response, key strengths and weaknesses of the 

and exposure assessment, assessment through a conscious and 

using a combination of deliberate effort to bring all the important 

qualitative information, considerations about risk into an 

quantitative information, and integrated picture.


information about	

uncertainties	

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 
Risk Characterization Handbook Page 25 

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. 
Page 26 Risk Characterization Handbook 

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. 
Risk Characterization Handbook Page 27 

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. 

2.2 Planning and Scoping 

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. 

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. 
Page 28 Risk Characterization Handbook 

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) 
Risk Characterization Handbook Page 29 

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. 
Page 30 Risk Characterization Handbook 

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. 
Risk Characterization Handbook Page 31 

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, policy makers, 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 sitespecific 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 
Page 32 Risk Characterization Handbook 

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 the NRC (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 may be developed 

in evaluating circumstances for chemical manufacture as with the 

premanufacturing notice program for new chemicals under the Toxic Substances 

Control Act (TSCA). 
Risk Characterization Handbook Page 33 

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. 

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 There is only a single technical 

characterization must be written with enough detailed characterization of risk as a final 

technical information so that another expert (e.g., product of the risk assessment. 

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 
Page 36 Risk Characterization Handbook 

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) 

l) 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. 
Risk Characterization Handbook Page 37 

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, stateof-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 Discussions about how the likely risk from 

or site compares to similar risks. Two types this stressor, agent or site compares to 

of comparisons should be considered. The others regulated by EPA can provide a 

first is to compare this risk assessment with valuable tool to risk managers. 
Page 38 Risk Characterization Handbook 

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. 
Risk Characterization Handbook Page 39 

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. 
Page 40 Risk Characterization Handbook 

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 may be 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 
Risk Characterization Handbook Page 41 

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. 
Page 42 Risk Characterization Handbook 

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 The goal of Risk Characterization is not to 

limited and who are not risk experts, is to repeat the entire assessment, just the key


convey that small subset of key findings and findings and conclusions.


strengths and limitations that really makes a


difference in the assessment outcome.


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. 
Risk Characterization Handbook Page 43 

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. 
Page 44 Risk Characterization Handbook 

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. 
Risk Characterization Handbook Page 45 

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. 
Page 46 Risk Characterization Handbook 

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 
Risk Characterization Handbook Page 47 

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)	 Federal Register Notices – includes decisions, For Your Information (FYI) 

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 
Page 48 Risk Characterization Handbook 

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 
Risk Characterization Handbook Page 49 

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 
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. 
Risk Characterization Handbook Page 51 

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. 
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 
Risk Characterization Handbook Page 53 

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. 
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. 
Risk Characterization Handbook Page 55 

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 

ensuring that a risk characterization is written for Risk characterizations must be 

each risk assessment and that a risk assessment/risk placed in writing. 

characterization record is maintained. 

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 
Page 56 Risk Characterization Handbook 

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, 
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-C98-1148). 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. 

Risk Characterization Handbook Page 59 

SUBJECT INDEX 

This is an alphabetical listing of subjects from the Handbook and the pertinent page numbers 

where they are found. 

- A -	 Elements of risk characterization (35, 

Accountability (20) 49) 

Administrative issues (55) Executive summary (46, 49) 

Alternatives (43) Exposure assessment (10) 

Analysis (10) - F -

Analysis plan (29) Fact sheets (47) 

Assistant Administrators (20, 22) Factors (51) 

Assumptions (11, 39) Federal Register notices (47) 

Audiences (47) Format and length (49) 

- B - - H -

Bias (41) Hazard identification (10) 

Branch Chiefs (22) History (5) 

Briefing packages (46) Human health risk assessment (10, 

Bright line (36) 11) 

Budget (56) - I -

Bullet list (46) Implementation (8) 

- C - Information (24) 

Chemical-specific risk assessment	 Informing Decision Makers (51) 

(20) - J -

Children (38) Justify (24)


Clarity (16) - K -


Communication (25) Key findings (11)


Conceptual model (29) Key information (37)


Consistency (17) - L -


Context (37, 49) Legal considerations (56)


Criteria (15) - M -


- D -	 Major conclusions (42, 50) 

Decision makers (22) Manager (11) 

Decision-making factors (51) - N -

Division Directors (22) NRC paradigm (10) 

Dose-response assessment (10) Number (13) 

- E - - O -

Ecological risk assessment (10, 11) Office Director (22) 
Page 60 Risk Characterization Handbook 

Office responsibility (25) 

- P -

Peer review (14, 57) 

People's roles (20) - U -

Planning and scoping (27) 

Policy choices (40) - V -

Press releases (47) 

Principles (14) 

Problem formulation (10) 

Public Relations notices (47) 

- Q -

Quantitative risk (13) 

- R -

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) 

- S -

Science Policy Council (SPC) (26) 

Sensitive populations (38) 

Site-specific risk assessment (21) 

Speeches and talks (47) 

Strengths and weaknesses (41) 

- T -

TCCR (1, 7, 8) 

Transparency (13, 15) 

Typology (31) 

“Technical” risk characterization 

(46) 

Uncertainty (24, 40) 

Variability (24, 40) 

Visual presentation (47) 
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


Risk Characterization Handbook Page A-1 

APPENDIX A 

U.S. Environmental Protection Agency 

POLICY FOR RISK CHARACTERIZATION 

March 1995 
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 peer review 

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. 
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. 
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. 
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 
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 
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 

Risk Characterization Handbook Page B-1 

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. 
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-11


1.3.4 Analysis ........................................... Page B-11


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-18


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

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 1a. Conceptual model of the Waquoit Bay watershed ecological risk


assessment. This portion shows land use activities and stressors ..... Page B-22


Figure 1b. 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

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 
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 overloading—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. 
Page B-6 Risk Characterization Handbook 

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: 
Risk Characterization Handbook Page B-7 

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. 
Page B-8 Risk Characterization Handbook 

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. 
Risk Characterization Handbook 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 

2 Prevent to xic levels of co ntamination in water, sedim ents, and bio ta 

3 Restore and maintain self-sustaining native fish populations and their habitat 

Estuarine 4 Reestablish viable eelgrass beds and associated aquatic communities in the 

Bay 
Page B-10 Risk Characterization Handbook 

5 Reestablish a self-sustaining scallo p popu lation in the B ay that can sup port a 

viable sport fishery 

6 Protect shellfish beds from bacterial contamination that results in closure 

7 Reduce or eliminate nu isance mac roalgal gro wth 

Freshwater 8 Prevent eutrophication of rivers and ponds 

9 Maintain diversity of native biotic communities 

10 Maintain d iversity of water-d epende nt 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 a measurable 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 ecosystem. 

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 
Risk Characterization Handbook Page B-11 

1.3.3 Conceptual Model 

Devised by the ecological risk assessment team with input from stakeholders, the general 

watershed conceptual model (Figure 1a 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 1a 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). 
Page B-12 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 

Migratory 

Fish 

Freshwater 

Biota 

Wetland 

Habitat 

Toxic 

Chemica ls 

1 1 1 

Altered Flow 3 2 2 

Resuspended 

Particulates 

1 1 1 

Nutrients 1 1 1 

Physical 

Alteration 

1 1 1 

Harvest 

Pressure 

2 1 0 0 0 2 2 0 

Assessment Endpoints 

Pond 

Troph ic 

Status 

Eelgrass 

Habitat 

Estuarine 

Invertebrates 

Estuarine 

Fish 

Barrier 

Beaches 

0 0 1 1 0 

0 0 0 1 0 

0 1 1 1 0 

3 3 2 2 0 

0 2 1 1 2 

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 interrelated because eelgrass meadows provide habitat to both estuarine fish and invertebrate species. 

Therefore, protecting eelgrass will protect fish and invertebrate species. 
Risk Characterization Handbook Page B-13 

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 
Page B-14 Risk Characterization Handbook 

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 nitrogenloading values. 
Risk Characterization Handbook Page B-15 

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 Percent to Watershed Percent to Estuary 

Atmospheric deposition 56 30 

Septic system 27 48 

Fertilizers 14 15 

Upper ponds 2 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. 
Page B-16 Risk Characterization Handbook 

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 influence 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 assessment, the models can be updated. 
Risk Characterization Handbook Page B-17 

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 
Page B-18 Risk Characterization Handbook 

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 available 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. 
Risk Characterization Handbook Page B-19 

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. 
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. 
Risk Characterization Handbook Page B-21 

Figure 1a. Conceptual model of the Waquoit Bay watershed ecological risk assessment. This 

portion shows land use activities and stressors. 
Page B-22 Risk Characterization Handbook 

THIS PAGE INTENTIONALLY LEFT BLANK 
Risk Characterization Handbook Page B-23 

Figure 1b. 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. 
Page B-24 Risk Characterization Handbook 

THIS PAGE INTENTIONALLY LEFT BLANK 
Risk Characterization Handbook Page B-25 

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. 
Page B-26
 Risk Characterization Handbook 

Figure 3. Changes in nitrogen loading alter the relative contribution of primary producers 

to total production in shallow estuaries (Valiela et al., 1997). 
Risk Characterization Handbook Page B-27 

Figure 4. Hypothetical response of eelgrass to increases in nitrogen load. 
Page B-28 Risk Characterization Handbook 

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. 
Risk Characterization Handbook Page C-1 

APPENDIX C 

GENERIC KETONE CASE STUDY 
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-11


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-11


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

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 
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. 
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. 
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 
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 
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, 
Risk Characterization Handbook 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 Type of Day Modeled 

Estimated Ambient Air 

Concentration (ppm) 

A 

Highest Concentration Day 4.8 

50th Highest Concentration Day 1.9 

Average Day 0.5 

B 

Highest Concentration Day 2.3 

50th Highest Concentration Day 1.3 

Average Day 0.3 
Page C-10 Risk Characterization Handbook 

C 

Highest Concentration Day 2.0 

50th Highest Concentration Day 1.2 

Average Day 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... 

Air Concentrations Would 

Increase By a Factor of... 

Over 24 hours/day, but only on weekd ays 1.5 

Over 24 hours/day every day, but only 6 months/year 2 

Over 365 days, but only one 8-hour shift per day 3 

Over 24 hours/day every day, but only 1 month/year 12 

Over 24 hours/day every day, but only 1 week/year 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 
Risk Characterization Handbook Page C-11 

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 μg/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 

Estimated Surface Water 

Concentration (μg/L) 

Acute Potential Dose Rate 

(mg/kg/day) 

1 47 0.0014 

2 9 0.00028 

3 4.4 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 
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 effects 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 
Risk Characterization Handbook 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 carcinogenicity 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 Type of Day Modeled MOE 

A 

Highest Concentration Day 209 

530 

1,944 

430 

785 

3,710 

510 

833 

4,082 

B 

C 

50th Highest Concentration Day 

Average Day 

Highest Concentration Day 

50th Highest Concentration Day 

Average Day 

Highest Concentration Day 

50th Highest Concentration Day 

Average Day 

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. 
Page C-14 Risk Characterization Handbook 

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. 

1 [ppm X (molecular weight/24.5) X rodent ventilation rate (m3

/day)]/ rodent body weight = mg/kg/day. For the rat, this becomes: 

[1,000 ppm X (100/24.5) X 0.14 m3

/day]/ 0.124 kg = 4,608 mg/kg/day. For the mouse, this becomes: [1,000 ppm X (100/24.5) X 0.04 m3/day]/ 

0.025 kg = 6,531 mg/kg/day. 
Risk Characterization Handbook 

Table 5. MOEs for Drinking Water Consumption 

Page C-15 

Facility MOE 

(using rat NOAEL) 

MOE 

(using mouse NOAEL) 

1 3.3 x 106 4.6 x 106 

2 1.6 x 107 2.3 x 107 

3 3.3 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 
Page C-16 Risk Characterization Handbook 

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. 
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 wellabsorbed 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 
Page C-18 Risk Characterization Handbook 

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 may be 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 
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-Dawley rats 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-1 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, 
Page C-20 Risk Characterization Handbook 

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 treatmentrelated. 

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 
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 concentrations, 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 
Page C-22 Risk Characterization Handbook 

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. 
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 

Duration of releases:


Release height:


Inner stack diameter:


Exit gas temperature:


Exit gas velocity:


Distance to fence line:


Site layout:


Generic ketone half life:


Other modeling options:


FUGITIVE (AREA) PARAMETERS 

Duration of releases:


Release height:


Exit gas temperature:


Area source size:


Exit gas velocity:


Distance to fence line:


Site layout:


Generic ketone half life:


Other modeling options:


ASSUMPTIONS 

24 hours


10 meters


0.01 meters


293o

K


0.01 meters/sec


100 meters


flat, rural


164,160 seconds (1.9 days)


default


ASSUMPTIONS 

24 hours


3 meters


293o

K


10m by 10m


0.01 meters/sec


100 meters


flat, rural


164,160 seconds (1.9 days)


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. 
Page C-24 Risk Characterization Handbook 

Table 1. Estimated Ambient Air Concentrations of Generic Ketone For Three Facilities 

Facility Type of Day Modeled 

Estimated Ambient Air 

Concentrat ion (ppm) 

A 

Highest Concentration Day 4.8 

50th Highest Concentration Day 1.9 

Average Day 0.5 

B 

Highest Concentration Day 2.3 

50th Highest Concentration Day 1.3 

Average Day 0.3 

C 

Highest Concentration Day 2.0 

50th Highest Concentration Day 1.2 

Average Day 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... 

Air Concentrations Would 

Increase By a Factor of... 

Over 24 hours/day, but only on weekd ays 1.5 

Over 24 hours/day every day, but only 6 months/year 2 
Risk Characterization Handbook Page C-25 

Over 365 days, but only one 8-hour shift per day 3 

Over 24 hours/day every day, but only 1 month/year 12 

Over 24 hours/day every day, but only 1 week/year 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 
Page C-26 Risk Characterization Handbook 

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 = C x IR x CF1 

BW 

where: 

C = surface water concentration (μg/l)


IR = water intake rate (l/day)


CF1 = conversion factor from μg 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 μg to mg (1.0e-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 μg/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 

Estimated Surface Water 

Concentration (μg/L)1 

Acute Potential Dose Rate 

(mg/kg/day)1 

1 47 0.0014 

2 9 0.00028 
Risk Characterization Handbook Page C-27 

3 4.4 0.00014 

1 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 a factor 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 ISCST3, 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. 

Risk Characterization Handbook Page D-1 

APPENDIX D 

MITEC CASE STUDY 
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

Risk Characterization Handbook


Tables


Page D-3 

Table 1. Estimated cancer risk from selected commodities ...................... Page D-16


Table 2. Comparison of Linear and Non-Linear Model Options .................. Page D-17

Page D-4 Risk Characterization Handbook 

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”for 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. 
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 1X 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 

(PDP); field trials; and processing studies. OPP conducted the dietary risk analysis using the 

Dietary Exposure Evaluation Model (DEEMTM), 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 
Page D-6 Risk Characterization Handbook 

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 Q1* 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 
Risk Characterization Handbook Page D-7 

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”for 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 (IPM) 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 
Page D-8 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 (PDP), field trials, and processing studies. OPP conducted the dietary risk analysis 

using the Dietary Exposure Evaluation Model (DEEMTM), 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 1X..) 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). 

CARC


Acronyms 

Cancer Assessment Review 

Committee 

DEEMTM 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) 

PDP USDA’s Pesticide Data Program 

PHED Pesticide Handlers Exposure 

Database 

DWLOC Drinking Water Level of 

Comparison 
Risk Characterization Handbook Page D-9 

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 1X 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 
Page D-10 Risk Characterization Handbook 

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 NO AEL rab bit oral dev elopmen tal 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/da y 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. 
Risk Characterization Handbook Page D-11 

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 a non-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 model 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 Q1

*

, is 1.71 x 10�1 (mg/kg/day)�1 for males; 

the Q1

*

 is in human equivalents. The Q1

*

 is based on male rat fatal jejunum sarcoma and is 

estimated using the Time-to-Tumor Multistage Model and a body weight3/4 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 Q1

*3 represents the slope of the 95% upper bound of the dose-response curve 

for jejunum sarcomas. Cancer risk estimates based on the Q1

*

 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 Q1

*

 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 Q1

*

 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 of ten. 

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. 
Page D-12 Risk Characterization Handbook 

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 Q1 . 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. 
Risk Characterization Handbook Page D-13 

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, HIARC 

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


Apples


Infant Apple Sauce


Raisins


Peaches


Infant Peaches


% Detects 

31% 

52% 

99% 

30% 

40% 

Detects/Total Samples 

62/200 

103/200 

197/200 

44/146 

79/199 

3 More detailed information regarding the basis for the dietary and occupational exposure assessments is available in the OPP 

Internal Review Document for Mitec (May 1997) and the supporting reviews. This includes information on the range of concentrations 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. 
Page D-14 Risk Characterization Handbook 

OPP used food consumption data from the USDA’s 1989-1992 survey to estimate dietary 

exposure. Data from the USDA 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. 
Risk Characterization Handbook Page D-15 

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. 
Page D-16 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 = Q1 x Anticipated Residue Contribution (ARC) 

where Q1

*

 = 1.71 X 10�1

 (mg/kg/day) �1

 based on jejunum sa rcoma in m ale 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 Cancer Risk Estimate Comments 

Apples, total 9.1 x 10�6 Major contributor to total 

risk, high use, common Fresh 6.1 X 10-6 

Cooked/Canned 2.4 X 10-6 

children’s food items 

Juice 6.0 X 10-5 

Peaches, total 2.5 X 10-6 Major contributor to total risk 

Grapes, total 1 X 10-6 Major contributor to total risk 

common children’s food item 

Wine/sherry 4.4 x 10�7 None 
Risk Characterization Handbook Page D-17 

Raisins 2.5 x 10�7 Common children’s food 

item 

The refined total dietary cancer risk for Mitec in the U.S. population was 1.6 x10-5. OPP 

has very high confidence in this estimate because it is based on actual residue data, the latest 

USDA food consumption data, a Q1* 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�6 

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/Q1 * 

Quantal 

Multistage/Q1* 

UNIT RISK 

ESTIMATE 

0.171 

TOTAL 

DIETARY 

RISK 

ESTIMATE 

GROUP 

SUPPORTING 

USE OF 

MODEL 

1.6 x 10-5 USEPA 

0.032 2.9 x 10-6 BigCorp 
Page D-18 Risk Characterization Handbook 

Time-to-Tumor 

Multista ge 

LED10 

0.160 1.5 x 10-5 USEPA, 1996 

Proposed Cancer 

Guidelines 

NON-LINEAR 

tumors expected 

only above a 

critical dose 

Margin of 

Exposure 

(MOE) 

NOAEL = 4 

mg/kg/day 

MOE>40,000 

(not of concern) 

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-toroute 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 Q1

*

 value were calculated as follows: 

* Extra cancer risk = Q1 x LADD 

* where Q1 = 1.71 x 10�1

 (mg/kg/day) �1 based on jejunum sa rcoma in m ale rats (oral b ioassay) 

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. HIARC 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 
Risk Characterization Handbook Page D-19 

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 

(Q1

*

 and ED10). The Q1* is the 95th percent confidence limit of the dose-response curve, which is 

the default Agency policy. The actual cancer potency may be considerably less than estimated 

using this value. OPP derived the Q1

*

 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-toroute 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 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 

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. 
Page D-20 Risk Characterization Handbook 

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 Q1

*

, 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 
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 10-4 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 1X 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. 
Page D-22 Risk Characterization Handbook 

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. 
Risk Characterization Handbook
 Page E-1 

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 
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

Risk Characterization Handbook Page E-3 

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 area 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 
Page E-4 Risk Characterization Handbook 

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 of fish 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 of fish 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 
Risk Characterization Handbook Page E-5 

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. 
Page E-6 Risk Characterization Handbook 

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 facilityspecific 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 
Risk Characterization Handbook Page E-7 

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 x10-6; 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 of ten 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 the HQ or HI equals or exceeds one, there may be concern 
Page E-8 Risk Characterization Handbook 

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 
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 ISCSTDFT (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, 

B1, C1) 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 sitespecific 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 A1 and subsistence farmer A1, resident B1, 

and resident C1 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 A1, B1, and C1 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. 

5

 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 exam ple, residentia l locations typica lly correspo nd to locatio ns of houses o r similar residen tialtype structures. Farms were estimated based on the presence of livestock or barn type structures in the area of 

interest. 
Page E-10 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 B1 

who eats fish from SCS Lakes 9 and10. 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 nonfasting 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 

Scen ario 

Theoretical 

Risks 

Point A1 

Adult Resident 7 x 10-6 

Child Resident 3 x 10-6 
Risk Characterization Handbook Page E-11 

Scen ario 

Theoretical 

Risks 

Subsistence Fisher SCS 

Lakes 

9 and 10 

9 x 10-5 

Joe 

Pool 

Lake 

3 x 10-5 

Subsistence Farmer 5 x 10-5 

Point B1 

Adult Resident 3 x 10-5 

Child Resident 1 x 10-5 

Subsistence Fisher SCS 

Lakes 

9 and 10 

1 x 10-4 

Joe 

Pool 

Lake 

5 x 10-5 

Subsistence Farmer 4 x 10-5 

Point C1 

Adult Resident 4 x 10-5 

Child Resident 2 x 10-5 

Subsistence Fisher SCS 

Lakes 

9 and 10 

1 x 10-4 

Joe 

Pool 

Lake 

6 x 10-5 

Subsistence Farmer 6 x 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. 
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 of fish, 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 of fish 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 x10-6, 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 
Risk Characterization Handbook Page E-13 

c)	 The potential for adverse health effects in humans as extrapolated from animal 

bioassays 

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 companyreported 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 DioxinLike 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. 
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 (IRIS). 
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 
Page E-16 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 C1 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), TXI has 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 may be 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 Modeled Soil 

Concentration 

(mg/kg) 

Measured6 

(mg/kg) 

Local Background 

(mg/kg) 

U.S. Background 

(mg/kg) 

Antimony 6.3 <3 <MDL <1 - 8.8 

Cadmium 11 - 50 < 0.095 - 3.6 <MDL-0.5 0.01 - 7 

Mercury 0.38 <1.0 <MDL <0.01 - 4.6 

6 Measu red values o btained fro m TN RCC’s re cent Critical Evaluation of the Potential Impact of Emissions 

from M idlothian Industries: A Summ ary Rep ort, and CSC’s Analytical Results - Off-Site Investigation, Chaparral 

Steel, Midlothian, Texas. 
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 Unit Combined 

Deposition 

(g/m2-yr) per 1 g/sec 

Unit Air 

Concentration 

(μg/m3

) per 1 g/sec 

CSC Fugitives 30.8 18 

CSC Baghouse A 0.320 0.37 

CSC Baghouse B 0.080 0.06 

CSC Baghouse C 0.078 0.063 

NTCC 0.005 0.006 

TXI 0.012 0.013 

Holnam 0.001 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 

Chaparral NTCC TXI Holnam 

Estimated 

Representative 

(g/sec) 

Estimated 

Representative 

(g/sec) 

Estimated 

Representative 

(g/sec) 

Estimated 

Representative 

(g/sec) 

Antimony 2.97 x 10-2 9.09 x 10-5 1.60 x 10 -4 NA 

Arsenic 1.89 -4 1.07 -5 2.13 -4 9.00 -5 x 10 x 10 x 10 x 10
Page E-18 Risk Characterization Handbook 

Chaparral NTCC TXI Holnam 

Constituent Barium s NA 2.65 -5 4.03 8.82 -4 

Beryllium NA 1.77 -6 2.08 -4 2.00 -5 

Cadmium 3.02 -3 5.18 -4 6.50 -4 NA 

Chromium VI 3.78 -4 2.65 -5 9.80 1.11 -5 

(total) 

Lead 5.85 -2 4.17 -3 1.43 8.00 -5 

Mercury 1.06 -5 4.67 -4 3.01 -4 2.52 -4 

Nickel 7.68 -3 2.78 -5 3.01 -4 3.78 -4 

Silver NA 8.96 -5 5.33 -5 NA 

Thallium NA 1.26 -5 5.04 -4 2.00 -5 

Zinc 5.96 -1 5.43 -6 2.69 -3 8.82 -4 

x 10 x 10-3 x 10

x 10 x 10 x 10

x 10 x 10 x 10

x 10 x 10 x 10-9 x 10

x 10 x 10 x 10-2 x 10

x 10 x 10 x 10 x 10

x 10 x 10 x 10 x 10

x 10 x 10

x 10 x 10 x 10

x 10 x 10 x 10 x 10

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 TXI’s 

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. 
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: Lake Michie 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. 

Hites, 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. 
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 ISD, 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 “D1" 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. 
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 D.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. 
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 

lb/hr but incorrectly adjusted data to gram/sec). 

Excerpt from a BIF test report entitled Semivolatile/PAH Data, 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. 
Risk Characterization Handbook Page E-23 

Pages II-1 through II-12 of a risk assessment protocol prepared by NTCC. 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 Protocol for 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 concentrations 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. 
Page E-24 Risk Characterization Handbook 

TNRCC air Permit for TXI - Emission Sources - Maximum Allowable Emission Rates. Permit 

Number 1360A. June 6, 1994. 
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Risk Characterization Handbook Page F-1 

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. 
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-B00-001, 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. 
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. 
Risk Characterization Handbook 

NOTES AND COMMENTS